Habitat creation for animals by teredinid bivalves in ... creation for animals by teredinid bivalves...

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Habitat creation for animals by teredinid bivalves in Indonesian

mangrove ecosystems

A thesis submitted in partial fulfilment of the requirements for the award of the

degree of Doctor of Philosophy of the University of Portsmouth

By

Ian Wyndom Hendy

Institute of Marine Sciences, School of Biological Sciences

University of Portsmouth

PO4 9LY

October 2012

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Abstract

A better understanding of the fundamental role large woody debris (LWD)

plays within mangrove ecosystems may provide further insights into important

ecological processes, such as wood degradation and biodiversity maintenance within

mangrove forests.Though the volume of fallen wood in mangrove forests can be

huge, little is known of the breakdown pathways and biodiversity maintenance of

LWD in mangrove ecosystems. The degree of mangrove fauna dependent upon

LWD and the need for such substratum in mangrove ecosystems may provide further

insights in to the important role of woody biomass in these otherwise globally

shrinking habitats due to forest harvesting.

The breakdown, recycling and flux of nutrients from LWD within mangrove

forests is maintained by biodegrading organisms in areas from terrestrial to marine

habitats. The tidal inundation sets limits on the wood degrading communities within

the mangrove forests of Sulawesi. This study presents details of the environmental

and biological association of biodegrading organisms within the forests in the

Wakatobi Marine Park (WMP), Sulawesi. Wood boring animals belonging to the

family Teredinidae are the dominant biodegraders of LWD in the mid- to low-

intertidal areas of the mangrove forests. Teredinid attack greatly reduces the volume

of LWD in the mid- to low intertidal areas of the forests. Within the forests, emersion

time was the greatest influence of the distribution of the biodegrading organisms

spanning from the supra-tidal down to the low intertidal.

The response of Rhizophora stylosa prop-roots to physical damage and the

activity of teredinids upon damaged prop-roots were investigated. With severe levels

of root damage, the level of teredinid activity increases, resulting in root death and

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detrital input. However, when the roots were exposed to a superficial and moderate

level of damage, an over-compensation of tissue re-growth was observed.

LWD in the intertidal zone is often tunnelled by teredinids. The tunnels are

blind-ending cylinders that taper to a small opening at the wood surface. However,

larger openings appear when wood is heavily tunnelled and the surface is broken

open. Teredinid death then leaves niches for cryptofauna. The greater the number of

teredinid tunnels within LWD, the more diversity was found. Animals of particular

interest were the dartfish, Parioglossus interruptus and the intertidal spider, Desis

martensi found in the vacant teredinid tunnels.

Desid spiders were abundant within the LWD and dartfish collected from

within teredinid-attacked LWD were smaller than dartfish populations not within

LWD. Desids and dartfish residing within the wood may benefit from the

significantly lower temperatures within teredinid-attacked detritus compared to

external air temperatures. Desis martensi has a life-history strategy centred on strong

parental care, with lots of energy invested in to its young. Vulnerable stages of

dartfish exploit the vacant teredinid tunnels. If it were not for the tunnels created by

the teredinids the unusual behaviour adopted by dartfish and spiders would not be

possible. Thus, many animals in mangrove forests of the WMP rely on LWD as a

predation refuge enhanced by the teredinid tunnels within the LWD. A variety of

different species were found inside teredinid attacked LWD, and the cryptic

behaviour of the fauna ranged from breeding to predator avoidance. These findings

indicate that in forests where wood is harvested, reduced availability of LWD will

result in reduced biodiversity.

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Acknowledgements

First and foremost, I wish express my sincere and total gratitude to Simon

Cragg, for seeing something in me which I believed I was not capable of. I thank

Simon for his tireless work ethic and professionalism. Thank you for your support,

encouragement and guidance.

I am very grateful towards Operation Wallacea for providing research

funding and providing the resources to make this project possible. I also want to give

my sincerest thanks to Amat and Kungdan – my wonderful mangrove posse who

worked with me with enthusiasm and passion, in long hard days when in the field. I

miss those guys. In addition, I also wish to give an extended very large Ian bear-hug

to several Hoga stalwarts – like Simon, you have been a role-model and inspiration

to me, Richard Barnes and Chris Todd.

To the dynamic and cheerful IMS team – it has been a pleasure to have been

a part of this institution for a number of years. The enthusiasm, passion and drive of

each and every one of you are infectious. In the early years, the support network

provided by Maureen and Ray and during the completion of my study Lucy, Graham,

Amaia, and Matt has been a constant source of encouragement, thank you.

I would also like to give a big thank you to Scott Armbruster, for his expert

opinions and rapid feed-back with various drafts of this thesis. My gratitude and

appreciation also goes out to David Jones (The Natural History Museum of London)

for identification of termites. J. Lawrence for his identification of coleopteran larvae,

and G. Jones and L. Ryvarden for their help towards identification of the

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basidiomycetes fruiting bodies. A big thank you goes out to Trevor Willis, for his

expert advice on using the PRIMER statistical package.

Furthermore, I would like to thank my very hard working American

colleagues who I have worked with on Hoga Island. Wayne, John and Theresa, each

of you have been a pleasure to work with. I have learnt so much with other scientific

disciplines – all of which is thanks to you guys. The seemingly hard endless hours

you all put in to your lab-work was a lesson in itself.

A special mention must go to Peter Chivers – another role model of mine.

Although you are gone and missed, you have never been forgotten - your

encouragement and belief in me during my A- levels and GCSEs when attending

Highbury College was such a boost. Also, very special thanks go out to Tricia

Farnham, my A- level biology teacher.

Combined with my collaborators and colleagues, to my family and friends –

your support and constant belief in me throughout has been amazing and a real

source of energy. Clare, thank you for putting up with me over the last year, you

have been a ray of sunlight. Mum, Matt thank you both for supporting me all the

way. To my boys at the gym, you must be the only bodybuilders who know what

teredinid bivalves are! Thank you all, for being so understanding and patient.

Grandpa, although you are no longer with us – this PhD is dedicated to you, I

miss you…

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List of contents

Chapter 1

General introduction

1.1 Overview 1

1.1.1 Indo-Pacific mangrove systems 2

1.1.2 Mangrove biomass and partitioning 6

1.1.3 Detrital input and breakdown pathways 8

1.1.4 Role of fallen mangrove wood 10

1.2 The Teredinidae (Mollusca: Bivalvia) 13

1.3 Study site, the Wakatobi Marine Park 15

1.4 Research aims and objectives 18

Chapter 2

MANGROVE FORESTS OF THE WMP, EAST SULAWESI, INDONESIA

2.1 Introduction 20

2.2 Materials and methods

2.2.1 Belt transects, tree identification, and measurements of emersion time

and salinity 22

2.2.2 Mangrove forest descriptions 23

2.2.3 Tree densities and species basal area 29

2.3 Data analysis 31

2.4 Results 32

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2.4.1 Mangrove area and botanical distributions 32

2.4.2 Environmental factors 34

2.4.3 Canopy-forming trees and forest characteristics 36

2.4.4 Tree species dominance – basal areas, biomass and tree densities

43

2.4.5 Site similarity and tree species diversity 55

2.5 Discussion 58

Chapter 3

INVESTIGATION OF WOOD BIODEGRADATION IN MANGROVE

ECOSYSTEMS

3.1 Introduction 66

3.2 Materials and methods 71

3.2.1 Measurement of wood-loss in panels 71

3.2.2 The measurement and collection of dead wood and arbitrary scale

classification and wood-loss from teredinid attack 72

3.2.3 Wood degrading organisms and environmental factors in the Galua and

Laulua mangrove forests 75


3.4 Results 77

3.4.1 Wood degradation within the landward, Sombano and seaward, Langira

forests 77

3.4.2 Sombano, Langira and Kal 1 panel analysis – wood loss 77

3.4.3 The biodegrading organisms found on LWD 78

3.4.4 The volume of LWD in mangrove forests 87

3.4.5 Wood-degrading organism distribution and environmental variables –

emersion, distance from the land and salinity 89

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3.4.6 The change between terrestrial and marine wood-degrading organisms

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3.4.7 Teredinid panel-fragmentation 96

3.5 Discussion 97

Chapter 4

THE EFFECT OF TEREDINID TUNNELLING ON MANGROVE PROP-

ROOTS

4.1 Introduction 110


4.2.1 Root scar experiment 115

4.2.2 Root biscuit analysis 116


4.4 Results 118

4.4.1 Root scar analysis upon live roots 118

4.4.2 Root biscuit analysis 123

4.4.3 Atypical growth of lignified tissues 125

4.5 Discussion 127

Chapter 5

HABITAT CREATION FOR ANIMALS BY TEREDINIDS



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5.2.1 Assessing the sediment macro-infauna, root epifauna and LWD cryptic

fauna 134

5.2.2 Assessing the effect of teredinid tunnelling on LWD in mangrove

forests 135

5.2.3 Recruitment and succession of animals to drilled wooden blocks

mimicking teredinid-attacked LWD 136


5.4 Results 138

5.4.1 Comparisons of animal diversity in different substrata 138

5.4.2 Biodiversity in teredinid tunnelled wood 142

5.4.3 Recruitment and succession of animals within drilled wooden blocks

mimicking teredinid tunnels 158

5.5 Discussion 166

Chapter 6

BIODIVERSITY MAINTENANCE BY VACANT TEREDINID TUNNELS



6.2.1 Field studies 175

6.2.2 Laboratory studies 177


6.3.1 Field studies 180

6.3.2 Laboratory studies 181

6.4 Results 182

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6.4.1 Temperature analysis 182

6.4.2 Parioglossus interruptus autecology analysis 185

6.4.3 Desis martensi autecology analysis 190

6.5 Discussion 193

Chapter 7

GENERAL DISCUSSION 202

Reference list 215

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Contribution of collaborators

Section Contributions of collaborators of work reported in this thesis Institution

3.1 Jason Williams prepared all arc G.I.S mangrove forest maps (Figure 3.1) Texas A&M University – Corpus

Christi

6.2.2 John Eme performed all thermal tolerance experiments for Parioglossus interruptus University of North Texas

6.2.2 Wayne Bennett and Theresa Dabruzzi designed the wind tunnel used for the wood cooling experiment University of West Florida

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Declaration

While registered as a candidate for a doctorate degree, I have not been registered

for any other research reward. The results and conclusions embodied in this thesis are

the work of the named candidate and have not been submitted for any other academic

post-graduate degree.

Ian Wyndom Hendy

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Chapter 1

GENERAL INTRODUCTION

1.1. Overview

Destruction and declines of ecologically important habitats continue; from the

global reduction of rain-forests (Foley et al., 2007) to the vast coral-bleaching events of

Caribbean reefs (McWilliams et al., 2005; Donner et al., 2007). Such ecosystems are

now reported as vulnerable and are a major cause of concern (Hughes, 1994; Laurence et

al., 2002). Moreover, the animals that depend upon the resources within those habitats

are also under threat (Laurence et al., 2002; Pandolfi et al., 2003). The knock-on effect

of the continued destruction will also magnify problems for ecosystems adjacent to the

impacted areas (Clausen and York, 2008). Eutrophication and increasing sedimentation

rates in freshwater systems and coastal-marine environments have been linked to forest

harvesting and farming (Nisbet, 2001; Brush, 2009). Thus, anthropogenic modifications

within natural habitats have been negatively linked to many ecological issues – from

declines of ecosystem resources to the reduction of ecosystem biodiversity. Indeed,

those issues also relate to the intertidal forest systems of tropical coastlines – mangrove

forests – which are also under threat (Duke et al., 2007).

This study is an investigation in to the ecology of mangrove forests of Sulawesi,

Indonesia. The study begins with detailed assessments and descriptions of different

mangrove forests, defined by their geomorphological setting such as land-locked and

forests connected with seagrass beds and coral reefs. Plant communities, their densities

and basal areas were recorded within each forest. Woody biomass was also studied, by

investigating the breakdown pathways of detritus from large trees to reveal how fallen

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wood is recycled and processed in areas of each mangrove forest that have different

biodegradation processes by organisms found in terrestrial to marine areas of the forests,

such as fungi, coleopteran larvae, termites and teredinids. In greater detail, wood-boring

molluscs were investigated. Teredinids are the primary focus of this study upon fallen

wood in the mid- to low- intertidal areas of mangrove forests. Fallen wood was split

apart and all fauna were identified to their lowest achievable taxonomic classification.

This study demonstrates that teredinid-attacked fallen wood in mangrove ecosystems

enhances the biodiversity of fauna. However, this study also demonstrates that sea level

rise and decreasing pH due to global warming may impact the degradation of LWD in

the mangrove forests of Sulawesi.

1.1.1. Indo-Pacific mangrove systems

This study was conducted in eight unusual mangrove forests from the Wakatobi

Marine Park (WMP), Tukang Besi Archipelago, Sulawesi, Indonesia. More than 17,000

Indonesian islands are carbonate in origin (Tomascik et al., 1997). Eastern Indonesia is

situated at the junction of three major tectonic plate regions. There are five major fault

zones, sutures that separate the tectonic plates. These sutures run along Molucca,

Sorong, Borneo, Sulawesi and the Banda Sea (Hall and Wilson, 2000). It is these major

fault regions that may give rise to the numerous fissured rocky islands that have coral-

rock intertidal zones. Most Indonesian mangrove forests are associated with muddy

fluvial deposits - sediments derived from rivers and streams. Nonetheless, some

mangrove forests have developed on calcareous coral-plateaus (Tomascik et al., 1997).

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Mangrove forests develop best where low wave energy and shelter enhance the

deposition of fine particles, which enables these salt-tolerant trees to establish roots and

grow (Alongi 2002). The retention of sediments within mangrove environments reduces

the turbidity of the surrounding ocean waters (Engelhart et al., 2007), which enhances

the photosynthetic ability of the zooxanthellae within coral colonies as turbid water

reduces sunlight penetration (Kleypas 1996). Mangroves are the only trees living at the

interface where the terrestrial environment meets the marine environment along tropical

coastal regions (Figure 1.1) (Sherman et al., 2003, Middleton and Mckee 2001).

Mangrove forests consist of groups of trees that form distinct zones occupying the

eulittoral and also dominating the supralittoral fringes (Woodroffe, 1982; Morton, 1983;

Tomascik et al., 1997). In Indonesia, zones of mangrove trees often include genera such

as Rhizophora and Sonneratia, commonly found at the low intertidal zone (Tomascik et

al., 1997; Giesen et al., 2006) and trees such as Avicennia, Xylocarpus, Bruguiera and

Excoecaria commonly found further in to the upper to high intertidal zone (Tomascik et

al., 1997; Giesen et al., 2006). Zonations of mangrove trees are controlled by

environmental factors such as hydrology, salinity, soil chemistry, nutrient availability,

predation, competition and also immersion time (Tomascik et al., 1997; McKee and

Faulkner, 2000; Pi et al., 2009). Mangrove zonation is also dependent upon substratum

type. Sonneratia alba frequently dominates sandy substrata whereas Avicennia marina

are commonly found on muddy areas (Giesen et al., 2006).

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Indonesia has the largest area of mangrove forests of any country, covering 45,

421 km2 (Spalding et al., 1997); almost one quarter of the World’s mangrove forests.

Such forests are important along Indonesian coastal areas as they play a vital role in the

ecological, economic and social development of coastal Indonesian communities

(Tomascik et al., 1997; Alongi, 2007). Indonesian mangrove forests also provide habitat

for many transient animals between adjacent ecosystems such as seagrass beds and coral

reefs (Sheaves, 2005). Many juvenile and vulnerable fish species enter the mangrove

forests at hightide – seeking the refuge of mangrove roots to avoid predation

(Laegdsgaard and Johnson, 2001). Those fish will then follow the ebbing tide to seek

refuge with adjacent reefs (Sheaves, 2005). Mangrove forests also support biodiversity

within adjacent coral reefs as they deliver organic nutrients to sessile reef-inhabitating

Figure 1.1, A Rhizophora-dominated Indonesian mangrove forest at low tide. When

flooded, seawater will immerse the exposed Rhizophora stylosa prop-roots that extend

up to 1.5 meters above the sediments.

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invertebrates (Granek et al., 2009). Thus, the connectivity between mangrove

ecosystems and coral reefs enhances the survival of the fauna from both habitats. Such

connectivity has rarely been studied in Indonesia even though the Indo-Pacific bioregion

is considered to be a biodiversity hotspot, containing the world’s richest diversity of

marine life (Roberts et al., 2002; Allen, 2008).

Indonesia is in the top ten percent of countries with ecosystems containing a high

level of marine animal diversity coupled with high animal endemism (Roberts et al.,

2002; Allen, 2008). When considering mangrove trees, Indonesia has 52 of the world’s

70 mangrove species (Giesen et al., 2006). Thus, mangrove forests have their center of

biodiversity richness located in the Indo-West-Pacific, where these forests have

important biological and physical functions (Tomascik et al., 1997; Kathiresan and

Bingham, 2001).

Environmental factors such as daily changes in water flow, anoxic sediments and

salinity make mangrove environments an unusual habitat for woody plants to become

established (Tomascik et al., 1997; Taylor et al., 2005). To combat daily tidal

inundation, anoxic sediments and salinity, mangrove trees have morphological (Figure

1.2) and physiological characteristics to enable those plants to thrive. These adaptations

include knee and prop roots, pneumatophores, viviparous seedlings, and xeromorphic

features of the leaves including thick cuticles, waxy coatings, and sunken stomata

(Clough, 1984; Tomascik et al., 1997; Alongi, 2002). Some of the features that

distinguish mangrove trees from terrestrial trees enhance their ability to thrive in hyper-

saline soils (Clough, 1984; Alongi, 2002).

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1.1.2. Mangrove biomass and partitioning

Indonesian mangrove forests are very productive. The biomass of these habitats

can rival or even surpass that of other marine ecosystems such as coral reefs (Alongi,

2007; Alongi, 2009). Mangrove forest biomass can vary greatly with latitude

(Komiyama et al., 2008), and within sites (Donato et al., 2011). Investigations into

whole-ecosystem carbon-storage and sequesteration within mangrove ecosystems found

that the majority of carbon is retained within the sediments (Figure 1.3) (Donato et al.,

2011).

Figure 1.2, Adaptations of Indo-Pacific mangrove trees. a, A complex tangle of Rhizophora

stylosa prop-roots, b, densely packed knee-roots belonging to the tree Bruguiera gymnorhiza, c,

large, corky lenticels - allowing for gas exchange on the trunk surface of B. cylindrica, d,

pneumatophores (breathing roots covered in small lenticels) belonging to the Xylocarpus

granatum tree and e, the fruiting structure (flower and propagule) of B. gymnorhiza.

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The partitioning of biomass for individual mangrove trees also varies (Ong et al.,

1995; Ong et al., 2004). The majority of biomass of mangrove trees remains in the trunk,

with estimates ranging from 60 – 74 % (Figure 1.4) (Ong et al., 1995; Ong et al., 2004).

A key component of litter in mangrove forests is wood, due to the large proportion of

trunk-biomass (Robertson, 1990). Biomass partitioning of mangrove trees among

conspecifics varies with tree size. Generally, more biomass is partitioned into the trunks

of trees with more than 25 cm circumference, than in smaller trees of the same species:

60 – 70 % compared with 15 – 20 % respectively (Ong et al., 2004). Thus, just a few

large trees can significantly contribute to the total above-ground biomass within a

mangrove forest (Ong et al., 1995).

Figure 1.3, The total carbon storage of Indonesian mangrove forests. The partitioning of

mangrove-derived carbon from the trees, fallen wood, roots and sediments. Data obtained from

Donato et al., (2011).

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1.1.3. Detrital Input and Breakdown Pathways

Mangrove forests are a sink for carbon (Bouillon et al., 2008; Donato et al.,

2011), and supports food webs (Figure 1.5) (Robertson and Daniel, 1989a; Feller, 2002;

Maria and Sridhar, 2003). The recycling of wood is much less well understood than that

of leaf litter (Kristensen et al., 2008), even though the majority of mangrove biomass is

wood (Robertson, 1990; Ong et al., 1995). However, wood has been shown to have a

similar carbon flux as leaf litter (Robertson and Daniel, 1989a). The flux of carbon from

wood in a Rhizophora-dominated Australian mangrove forest was estimated to be

Figure 1.4, The biomass partitioning of Rhizophora apiculata. From a 20-year old

Rhizophora-dominated mangrove forest in Malaysia, 74% of the total biomass is

allocated to the trunks of Rhizophora apiculata. The remaining 26 % of the biomass

is partitioned between the canopy and roots. Figure adapted from Ong et al., (1995).

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similar to that of leaves with 44g C m-2

y-1

compared with 62g C m-2

y-1

from the

consumption of leaves by crabs (Robertson and Daniel, 1989a).

Sesarmid crabs process mangrove leaf litter (Robertson and Daniel, 1989a;

Nordhaus and Wolff, 2007) and shrimps consume much of the mangrove-derived leaf

litter detritus (Ronnback et al., 2002; Kenyon et al., 2004). Fallen wood is processed by

fungi (Anandar and Sridhar, 2004), coleopteran larvae (Feller, 2002) and termites (Korb

and Lenz, 2004). Basidiomycetes are responsible for the initial breakdown of the

refractory components of wood in the high intertidal to supratidal areas within mangrove

forests (Anandar and Sridhar, 2004). Coleopteran larvae and termites break down wood

due to their mechanical processing and digestion within the upper to mid-intertidal zones

(Feller, 2002). However, in the seaward edges of mangrove forests the breakdown of

wood is due to the Teredinidae (Robertson and Daniel, 1989a; Robertson, 1990), and

limnoriid isopods, although limnoriids are not often found in Indonesian mangrove

forests and they only excavate superficial areas of the wood surface (Cragg and Hendy,

2010). The biodegradation processes of large woody debris (LWD) within mangrove

ecosystems are essential for nutrient sequestration within the sediments (Donato et al.,

2011). The retention of organic material within the sediments enhances mangrove

productivity (Sherman et al., 2003), and the recycling of wood in mangrove forests

provide nutrients for adjacent habitats such as seagrass beds and reefs (Granek et al.,

2009).

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1.1.4. Role of fallen mangrove wood

Mangrove forests provide an arena where mobile terrestrial animals exploit the

forest floor at low tide, arboreal animals thrive within the canopy, benthic animals and

pelagic animals utilise the forest at high tide (Cragg and Hendy, 2010). These animals

Figure 1.5, Woody detrital input and wood degrading organisms. a, a large fallen log in

a mangrove forest – serving as the primary base of an elaborate food web b, the fruiting

body of the fungus Pycnoporus sanguineus, a basidiomycete initiating saprophytic decay of

a large log in the high intertidal c, a cerambid beetle larvae found inside a fallen Excoecaria

agallocha tree and d, termites inside a log also in the high intertidal area of the mangrove

forest.

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range from a variety of invertebrates such as zooplankton, sponges, ascidians (Perry,

1988), crustaceans (Robertson, 1990), insects and molluscs (Coomans, 1969; Plaziat,

1984; Feller and Mathis, 1997), vertebrates including fish, amphibians, reptiles and birds

(Kathiresan and Bingham, 2001; Giesen et al., 2006). Similar to the zonation patterns of

the trees, distinct patterns of distribution can be observed with the mangrove fauna. Root

epifaunal distributions are influenced by various abiotic and biotic variables such as tidal

flow, salinity, food availability, temperature, competition and predation (Alongi, 2002).

The diversity of animals within the Indo-Pacific mangrove forests is similar to

that commonly found in tropical terrestrial forests and marine ecosystems such as the

giant centipede, Scolopendra, hunting spiders (Lycosidae) and moray eels Gymnothorax

richardsoni and octopus. Such animals are dependent upon fallen logs within the

mangrove environment which offer protection for particularly vulnerable animals

including juveniles (Figure 1.6). Large woody debris serves as a predation refuge for

many aquatic communities (Everett and Ruiz, 1993), therefore fallen wood is an

ecologically important resource for increasing biodiversity within mangrove habitats.

Mangrove forests also serve as a nursery refuge for many fish and crustaceans

(Kathiresan and Bingham, 2001; Nagelkerken et al., 2008). Juvenile fish depend upon

the complex root systems to avoid predation (MacDonald et al., 2009). The majority of

biodiversity is centred on the available hard substrata, as the sediments are generally

anoxic and therefore unsuitable for many animals (Prasad and Ramanathan, 2008).

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Mangrove ecosystems have a complex topography (Sasekumar and Chong,

1998), and the mangrove trees enhance the forest complexity that increases the level of

biodiversity (Gratwicke and Speight, 2005).

The nursery function of mangrove forests has been well documented, especially

in Caribbean forests. Many juvenile reef fishes use Caribbean forests as feeding grounds

(Mumby et al., 2003; Nagelkerken and Velde, 2004; Dahlgren et al., 2006). The larger

tidal range than the Caribbean within the Indo-Pacific mangrove forests may reduce the

activity of feeding reef fish (Nagelkerken and Velde, 2004). Research into the

Figure 1.6, Wood-dwelling cryptic fauna removed from fallen logs in Indo-Pacific

mangrove forests. a, a large lycosid spider waits in camouflage on a mangrove log b, an

octopus with eggs found inside a fallen log c, a giant Scolopendra also found inside a

mangrove log and d, one of many early juvenile octopus found inside a mangrove log.

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mangrove-nursery function is focused upon juvenile fishes and invertebrates exploiting a

variety of connected marginal habitats such as seagrass beds and reefs (Sheaves, 2005;

Unsworth et al., 2008; Luo et al., 2009). Connectivity of adjacent ecosystems,

mangrove-seagrass-reef linkages within Indonesian marine habitats are not common

(Tomascik et al., 1997), unlike than in the Caribbean. The movement of different fish

species between habitats in the Caribbean are either facultative or obligate meaning that

some animals are not bound to any particular habitat and some are (Mumby et al., 2003).

However, some species are dependent exclusively upon the resources available within

that habitat. For example, the herbivorous fish, Scarus guacamaia is specifically bound

to life in the mangrove forests (Mumby et al., 2003). If it were not for the resources

available within the forests the abundance and distribution of Scarus will suffer local

extintions (Mumby et al., 2003). The same fate may also be true for mangrove-

dependent animals in the Indo-Pacific.

1.2. The Teredinidae (Mollusca: Bivalvia)

The wood-boring family Teredinidae (Bivalvia) consists of fifteen genera and

seventy-one species, and they are sedentary molluscs (Turner, 1966). Teredinids create

an extensive labyrinth of tunnels within fallen wood through their boring-action (Figure

1.7) (Manyak, 1982; Robertson and Daniel, 1989a). The tunnels they create remain as

their home for the duration of their adult life. Teredinids are widely distributed, from

tropical to temperate seas; where they are the dominant consumers of fallen wood along

coastlines (Distel, 2003). They may be dispersed either as adults in floating wooden

debris or as planktonic larvae drifting near the sea surface (Scheltema, 1971).

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Teredinids have long been considered as economic pests (Laverty, 2002;

Borojevic et al., 2010). They damage man-made wooden structures in marine

environments such as boats, piers and pilings (Laverty, 2002; Godwin, 2003; Borojevic

et al., 2010). It has been estimated that the cost of damage to marine structures, ranging

from ships, docks, wharfs, piers and fishing equipment was one billion dollars U.S in

1986 (Distel, 2003). However, there has been no attempt to investigate the ecological

Figure 1.7, Teredinid shell morphology and teredinid wood processing. a, A teredinid shell, b, a

close-up of the teredinid shell showing the denticulate teeth that help create the tunnels within fallen

wood, c, a cross section sample of fallen wood attacked by the Teredinidae highlighting many

openings of teredinid tunnels and d, a heavily fragmented piece of wood exposing tunnels created

by extensive teredinid boring-activity.

100µm

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benefit of teredinids within natural habitats such as mangrove forests. Teredinids process

large volumes of dead wood within mangrove habitats due to their tunnelling and wood

digestion (Distel, 2003), and by doing so they enhance nutrient recycling (Robertson and

Daniel, 1989a).

Investigations of mechanical wood degradation have mainly focused upon

coleopteran larvae in Caribbean mangrove forests (Feller and Mathis, 1997; Feller,

2002; Sousa et al., 2003). However, research investigating the decomposition of trees

from the activity of teredinids remains limited (Robertson, 1990; Filho et al., 2008). It

has been estimated that teredinids process up to 50% of dead mangrove wood

(Robertson and Daniel, 1989a). Without teredinid activity, there would be a major

increase of LWD build-up in Indonesian mangrove forests.

1.3. Study Site, The Wakatobi Marine Park

This investigation was conducted between 2006 and 2011 within the WMP,

which is the second largest marine park in Indonesia covering an area of 1.39 million

hectares (05° 12’ - 06° 10’ S, 123° 20’ - 124° 39’ E). The park is situated within the

middle of the Wallacea region – the centre of marine biodiversity (Kwakkel-Hol, 2006).

The marine park consists of four islands, the largest and most northern being Wangi-

Wangi. Southeast to Wangi-Wangi is Kaledupa, and then followed by Tomia and the

Binongko Islands (Figure 1.8). The first two letters of each island make up the name of

the marine park, Wakatobi (Kwakkel-Hol, 2006). There are about 10,000 people living

in the WMP (Clifton and Unsworth, 2010), and the majority of them are either farmers

or fishermen (Kwakkel-Hol, 2006). Over recent years declines in fish stocks due to

artisanal fishing practices (Cullen et al., 2007; Cullen, 2010) and increases of mangrove

16

forest harvesting have been reported (Cragg and Hendy, 2010) - to the detriment of the

WMP (Pilgrim et al., 2007).

Despite extensive research of the Indo-Pacific mangrove forests (Tomascik et al.,

1997), there has to date been only one study detailing the ecology of the Wakatobi

mangrove forests. The study found that of the 70 known mangrove tree species

Figure 1.8, The location of the Wakatobi Marine Park, SE Sulawesi, Indonesia. a, The four

Islands that make the Wakatobi, b, the mangrove sites used in this study. On Kaledupa Island are the

Sombano, Langira, Galua and Laulua mangrove forests, and on the Derawa Island are the mangrove

forests Kaluku, Loho, One Onitu and Gili.

a

b

17

(Polidoro et al., 2010), 24 species are found in the forests on the Kaledupa and Derawa

Islands within the WMP (Figure 1.9). There have been various studies from the WMP

where research has concentrated on very detailed investigations of single species

(Barnes, 2003; Jimenez and Bennett, 2005; Taylor et al., 2005). However, no

investigation has attempted to study whole mangrove ecosystems in various locations

within the WMP.

Many large mangrove forests within Indonesia grow on muddy fluvial sediments

(Tomascik et al., 1997) though there are forests associated with coarse, sandy sediments

such as the mangrove forests located in Jakarta Bay and Berau Islands (Tomascik et al.,

1997). Sulawesi has a much smaller area of mangrove forests due to the mountainous

and rocky topography and unsuitable substratum (Yulianto et al., 2004). However, there

are islands within Sulawesi where mangrove forests thrive, such as the islands of

Kaledupa and Derawa within the WMP. Much of the coastlines from these islands have

calcareous mud or sandy sediments that cover areas of fissured raised fossil coral. The

forests from these islands are small and some have a close proximity with large areas of

seagrass beds and fringing reefs. Such connectivity has rarely been studied along the

coasts of Indonesia (Tomascik et al., 1997).

18

1.4.

1.5.

1.4. Research Aims and Objectives

The main aims of this investigation were to determine whether the trees within

each mangrove forest of the WMP provides a source of nutrients to food webs via LWD

(Chapter 2), and to determine if the Teredinidae are ecosystem engineers (chapters 3, 4,

5 and 6). This study also aims to determine if LWD from mangrove trees provides a

refuge from predation for mangrove fauna (Chapters 5 and 6). The diversity of animals

removed from teredinid-attacked LWD was studied – to establish if any relationships

occur between a greater number of tunnels and a greater number of animals (Chapter 5).

In addition, drilled wooden blocks were used in the forests to investigate the recruitment

and succession of animals in tunnelled wood. This work investigated details of the

animal biodiversity that vacant teredinid-tunnels may promote. Of particular interest was

a fish, Parioglossus interruptus (Ptereleotridae) found in teredinid tunnels when

emersed, and a spider, Desis martensi (Desidae) found in teredinid tunnels when

immersed (Chapter 6). This study also aims to reveal an unusual ecosystem service – the

WMP

Figure 1.9, The distributions of the world’s mangrove forests according to the number of different tree

species. The world’s mangrove forests illustrated as different colours according to the number of different

tree species common to those areas. The forests of the WMP are located in the region with the greatest

number of different trees, between 36 – 46 species. Figure adapted from Polidoro et al., (2010).

19

promotion of biodiversity created by teredinids by understanding how and why animals

exploit vacant teredinid tunnels. Finally, this study draws upon the results and then

reviews the data within a wider context by discussing implications of the effect of

increasing sea-levels and decreasing pH upon mangrove tree distributions, the

biodegradation processes and the Teredinidae (Chapter 7).

Using allometric equations, basal areas of mangrove trees were used to calculate

biomass. Regression methods were not used, as the felling of trees is required (Kairo et

al., 2009). The volume of fallen wood was measured within mangrove forests from the

strandline to the seaward edge to determine the amount of LWD available to organisms.

All organisms found within teredinid-attacked LWD were identified to their lowest

achievable taxonomic classification. Salinity, emersion time, and temperature were

measured to determine if the abundance and distribution of all biodegrading organisms

and mangrove fauna within vacant teredinid tunnels were influenced by those variables.

This study tested the hypotheses that mangrove forests in the WMP will have 1.

site-specific biodegrading organisms upon woody detritus, and 2. mangrove forests in

the WMP will have specific environmental factors that influence the distribution of the

biodegrading organisms upon LWD. Furthermore, the Teredinidae will, 3. significantly

breakdown LWD through their tunnelling, and 4. enhance ecosystem-level biodiversity

within the mid- to low- intertidal areas of the forests through their tunnelling. Finally,

this study predicts that through teredinid modification of the environment and habitat

creation for other animals, the Teredinidae should be considered as ecosystem engineers.

20

Chapter 2

MANGROVE FORESTS OF THE WAKATOBI MARINE PARK,

EAST SULAWESI, INDONESIA

2.1. Introduction

Mangrove trees are a source of leaf litter and carbon via large woody detritus

(LWD) (Donato et al., 2011), and fallen trees support food webs (Robertson and

Daniel, 1989a, Maria and Sridhar, 2003). However, the contribution of fallen wood is

much less understood than that of leaf litter with respect to nutrient recycling

(Kristensen et al., 2008), even though the majority of mangrove biomass is wood (Ong

et al., 1995). The standing stock of mangrove-derived carbon can rival and surpass that

of other marine systems such as coral reefs (Alongi, 2007; Alongi, 2009). One very

detailed investigation of Indo-pacific mangrove forests has estimated whole ecosystem

carbon storage, which demonstrated that these forests are effective carbon sinks, and

they are the most carbon-rich ecosystems in the Indo-Pacific (Donato et al., 2011).

Mangrove forest biomass can vary greatly with latitude and within sites (Komiyama et

al., 2008; Alongi, 2009; Donato et al., 2011).

Mangrove forest above-ground biomass varies from as low as 7.9 t ha-1

for a

Rhizophora mangle forest in Florida (Lugo and Snedaker, 1974) to as high as 436.4 t

ha-1

for a Bruguiera-dominated forest in eastern Indonesia and 460 t ha-1

in a

Rhizophora apiculata dominated forest in Malaysia (Komiyama et al., 2008).

Patchiness in above-ground biomass has also been reported within individual

mangrove forests. The differences of biomass can change with the tidal heights of

21

mangrove trees. In an Indonesian mangrove forest, Sonneratia sp. found at the

outermost seaward edge had the lowest total biomass, 169.1 t ha-1

, in the mid-intertidal

estimates for Rhizophora sp. totaled 356.8 t ha-1

and for the Bruguiera sp. recorded at

the strandline a total above-ground biomass of 436.4 t ha-1

was recorded (Komiyama et

al., 2008), with much of the carbon sequestered into mangrove sediments (Donato et

al., 2011).

Pristine, well-developed mangrove forests contain trees with a greater basal area,

tree height, density and species diversity (Roth, 1992) - such as the mangrove forests of

the large deltaic systems in Papua (Tomascik et al., 1997; Alongi, 2009).

There are many ways to define the structure and composition of a mangrove

forest. Forest structure and composition are determined by the tree species, density,

dominance and the distribution of trees (McElhinny et al., 2005). The diversity of tree

taxa within a forest can be used as a measure of mangrove forest complexity (Bosire et

al., 2006). Mangrove tree basal-area can be used as a measure of woody biomass -

studies have demonstrated that tree girths alone can be used to calculate biomass using

various allometric equations (Komiyama et al., 2008). However, tree girths and the

distributions of trees are determined by environmental variables such as the degree of

tidal immersion (Jimenez and Sauter, 1991; Pi et al., 2009), soil chemistry and salinity

(Joshi and Ghose, 2003; Krauss et al., 2008).

This study aims to determine whether the mangrove trees within each forest are a

source of LWD that may serve mangrove food webs. Also, do the mangrove trees have

particularly large basal areas compared with other forests? Tree species basal areas

within each forest were used to calculate mangrove tree biomass, using allometric

equations (Komiyama et al., 2005; Komiyama et al., 2008) as this method is less

22

intrusive and less destructive than regression methods – as the felling of trees is required

to determine their dry weights (Kairo et al., 2009). This study also aims to reveal the

environmental variables that determine tree-species dominance, abundance and their

distributions within different mangrove forests within the WMP.

2.2. Materials and methods

2.2.1 Belt transects, tree identification, and measurements of emersion time and

salinity

Forest structure surveys were conducted during five 10-week expeditions to the

WMP, Banda Sea, Southeast Sulawesi from June to September on Kaledupa Island (05°

27.53’’S, 123° 46.33’’E) and the Derawa Islands (5° 33'9"S, 123° 52'3"E). The areas of

each mangrove forest - Sombano, Langira, Kaluku, Loho, One Onitu and Gili (see

chapter 1) - were calculated using a Garmin 76Csx GPS, by way-pointing the

perimeters. Continuous belt-transects (2 metres either side of the tape) were completed

within the forests beginning at the strandline and ending at the outer edge of each forest.

Depending on the size of the forest investigated, between three and five transects were

established by calculating the area of each forest. A number of measurements were made

along every transect, each mangrove tree within two metres either side of the transect

tape was recorded and identified. Tree heights were calculated by using measured

distances from a Nikon Laser Rangefinder 550 or by estimating tree height using a two

metre wooden pole. The substratum of the entire transect was also recorded. Ground

water salinities were measured using a Bellingham and Stanley E-Line Aquatic hand-

held refractometer. To determine the tidal profile within the forest, high tide level was

23

marked on mangrove trees using high visibility string. At low tide, the distances from

the substratum to the mark on each tree were measured and then subtracted from the

mark of seawater at high tide to establish the height above sea level. Emersion times

were estimated by relating the tidal heights to chart datum in regional tide tables.

2.2.2. Mangrove forest descriptions

Sombano

The Sombano mangrove is a large land-locked forest with mature Excoecaria -

and Bruguiera trees, where tidal flooding occurs during only spring tides or other

exceptionally high tides. Tidal flooding in Sombano is peculiar; seawater percolates

from under a raised fossil coral plateau, at the seaward end of the forest.

Sombano has several species of mangroves. The forest has large trees with girths

of B. gymnorhiza measuring up to more than two metres. The forest also has a modest

mixed sapling bank from the strandline to the seaward edge. Extensive stands of twenty

to twenty-five metre high Excoecaria agallocha and Bruguiera gymnorhiza trees

dominate, with emergents of twenty metre Rhizophora apiculata and Xylocarpus spp.

The most dominant species is E. agallocha, which was found in high numbers. Many of

the larger B. gymnorhiza trees have been cut down, therefore reducing the mean tree

girths for B. gymnorhiza in Sombano. Very large mature R. apiculata trees are also

harvested in Sombano (Figure 2.1 a). In periods of heavy rainfall, freshwater run-off

enters the Sombano forest from the landward edge in the form of small streams (Figure

2.1 b).

Langira

The Langira strandline is situated at the base of the fossil-coral plateau that

24

marks the end of the land-locked Sombano forest. The forest is established on a fossil-

coral plateau that extends down to mean sea level. The sediments over-laying the plateau

are a mix of mud at the strandline changing to a mixture of sand and shells at the

outermost seaward edge.

25

a b

c d

e f

g

Figure 2. 1 Images of mangrove sites on Kaledupa and Derawa. a, A mature felled Rhizophora apiculata tree in

the inland Sombano forest. Note the straight-edged planks cut from a mobile saw mill; evidence of forest harvesting

b, Freshwater run-off streaming in to the Sombano forest strandline c, The fringing Langira forest. Small stands of R.

stylosa trees grow in pockets of soft sediments in fissured coral holes within the coral-plateau. A sapling Bruguiera

gymnorhiza tree can be seen in the foreground d, Dense R. stylosa stands in the Kaluku forest on Derawa e, The

landward zone of Loho. The fossil-coral shore line of Loho can clearly be seen in the background f, The inland Gili

forest on Derawa. The fossil-coral strandline can be seen in background behind the large mature B. gymnorhiza trees

in the foreground and f, One Onitu at low tide, exposing the dense prop-roots of the many R. stylosa stands.

26

The substratum is interspersed with many crowns of fissured coral-rocks

protruding through. In places, the fossil-coral becomes exposed, with numerous coral

holes consisting of calcareous mud. Langira had many large open channels also

consisting of calcareous mud with dense seagrass beds over laying these channelled

areas. Distinct zonation patterns of trees was observed, with Rhizophora apiculata found

at the strandline, and R. stylosa populations extending out into the eulittoral zones. The

Rhizophora trees in Langira were very shrubby, and were established in coral sink-holes

(Figure 2. 1 c). Tree canopies are very patchy, and maximum tree heights reach no more

than twelve metres, with trees averaging four meters.

The Rhizophora and Bruguiera trees attained the largest basal area within

Langira. Thus, those trees were important contributors to the total forest biomass. High

densities of R. stylosa were found in Langira. Bruguiera gymnorhiza had the greatest

tree-girths with some trees measuring almost two metres in girth as did a few

Xylocarpus granatum trees. Xylocarpus spp. were found only at the strandline.

Kaluku

The Kaluku forest (Figure 2. 1 d) is constrained at the landward edge by a fossil-

coral wall. The forest is inundated by all tides, and no salinity gradient was found.

Kaluku had almost mono-specific stands of R. stylosa, with very few S. alba trees.

Located at the landward edge of Kaluku outside of the chosen plots, Bruguiera

gymnorhiza, Xylocarpus granatum and Pemphis acidula were present. R. stylosa trees

were densely populated in Kaluku, the girth of these trees were comparatively small and

therefore the total basal area was also small compared to the very large biomass of the

few S. alba trees.

27

Loho

The Loho forest was the largest of the mangrove forests surveyed on Derawa.

The forest is established within a sheltered bay and contains a large abundance of R.

stylosa trees. Lining the Loho strandline was a large fissured, over-hanging fossil-coral

embankment (Figure 2. 1 e). Within the forest from the strandline and out to the seaward

edge, R. stylosa was the dominant species in relation to both abundance and basal area.

B. gymnorhiza stands were also present, this species was only located at the landward

zones within the plots with trees up to sixteen meters in height located within the belt

transect.

Gili

The Gili forest on Derawa was separated with the One Onitu forest by a fossil-

coral plateau, similar to that of the Sombano and Langira mangrove forests. The Gili

forest is an inland forest surrounded by a fossil-coral wall (Figure 2. 1 f).The forest is

the smallest of all the sites studied. Seawater enters the forest through a tunnel under the

fossil-coral plateau that separates Gili and One Onitu. The Gili forest is inundated by all

tides, except neap tides less than 1.4 metres above sea level. No difference of tidal

height was found from the strandline to the seaward edge. The middle region of the

forest had the lowest recorded emersion times when compared to the landward and the

outermost seaward edges suggesting that the middle region of the forest was ‘sunken’

compared to the outer edges of the forest - similar to the topography of the Sombano

forest. The composition of the substratum changed with distance from the land. Within

the landward regions, the substratum consisted of a thick organic-rich mud - in places

the mud was more than forty centimeters deep. The middle area of the forest had a

calcareous mud substratum, although the area where seawater enters into the forest the

28

substrata was predominantly sand. The changing substratum was a determining factor

for the tree distributions within Gili. S. alba were found only in sand-dominated

substrata, whereas R. apiculata dominated in areas of thick organic-rich mud. The most

abundant tree species within Gili was Bruguiera gymnorhiza and the forest also had a

young bank of Rhizophoraceae saplings. Large, mature Sonneratia alba trees were

present at the seaward zone, and Rhizophora apiculata were in the landward regions.

One Onitu

On the exposed seaward edge of the fossil-coral plateau in front of the inland

Gili forest is One Onitu (Figure 2. 1 g). Like the Langira forest, One Onitu also has

connectivity to seagrass and reefs. The entire One Onitu forest is established in the high

intertidal and no difference was found with emersion time across the forest. B.

gymnorhiza trees were found in areas with higher emersion times. Furthermore, the

substratum in the forest consisted of calcareous mud. R. stylosa trees were the most

common species in One Onitu with very few B. gymnorhiza and S. alba trees.

In the Derawa forests, anthropogenic impact was slight and removal of mangrove

material was minimal. However, the Kaledupan mangrove forests, Sombano and Langira

are exposed to a high level of wood harvesting. The constant sound of chain-saws

echoed in Sombano. Frequent evidence of felled mature R. apiculata and B. gymnorhiza

trees are observed with many clearings with fresh milled debris consisting of saw dust

and straight-edged cut planks being found within Sombano. Large bundles of newly

felled young B. gymnorhiza trees were also found and large amounts of B. gymnorhiza

trees were observed in storage beneath the houses of local residence living on Kaledupa.

Furthermore, the abundant R. stylosa trees in Langira were cut on a daily basis. Unlike

the case in Sombano, whole trees in Langira were not often cut down; however branches

29

were harvested for fish fences. The level of cutting in Langira is high, with almost every

tree within the forest experiencing some degree of harvesting.

2.2.3 Tree densities and species basal area

Along each of the transects within the Sombano and Langira mangrove forests,

replicate 20 x 20 m plots were selected at random from a total of between five and 25

plots depending upon the length of the transect. Sombano had a total of 22 plots and

Langira had a total of 19 plots. For the forests in Derawa two 10 x 10 m plots were

selected at random from a total of between three and 12 plots depending upon the length

of each transect. In the Kaluku forest a total of 12 plots in six transects were established.

In the Loho forest, 10 plots in five transects were established. In the One Onitu forest, 15

plots in five transects were established. In the Gili forest six plots in three transects were

established (Table 2.1). To determine the basal areas of each tree species within the plots

between the sites, diameter at breast height (DBH), or the circumference at breast height

(CBH) of each tree were recorded using the equation r2

(where = 3.142 x radius2).

The radius was calculated by dividing the circumference by x 2, or by dividing the

diameter by 2.

30

Plots

Site Transect 1 2 3 4 5 Sombano 1 100 140 240 260 340

2 100 140 240 260 340

3 100 140 240 260 340

4 100 140 240 260

5 100 140 240 Langira 1 0 160 320 440 460

2 0 160 320 440 460

3 0 160 320

4 0 160 320

5 0 160 320

Kaluku 1 20 30

2 0 10

3 0 20

4 0 20

5 10 20

6 0 50

Loho 1 10 40

2 0 20 40

3 10 50

4 80 150

5 20 One Onitu 1 0 20 30 60

2 10 40 50 70

3 0 40 60

4 40 70

5 30 70

Gili 1 30 70

2 0 10

3 10 30

Table 2.1 Plots labelled 1-5 used to measure mangrove tree basal areas and tree

species density within each site and transect. Numbers within each site are the

distance from the landward edge – the strandline (metres).

31

2.3 Data analysis

The univariate and non-parametric multivariate techniques, of multidimensional

scaling plots (MDS) distance-based linear modelling (DISTLM) and DIVERSE analyses

contained in the PRIMER 6 (Plymouth Routines in Multivariate Ecological Research)

package were used to explore forest characteristics. Similarities of botanical

communities between the sites were displayed using non-metric MDS plots. To

investigate spatial patterns of similarity, each mangrove forest was grouped by

overlaying data from a Bray-Curtis Cluster analysis. DISTLM was employed to verify

relationships between emersion time, distance from the land (DFL), salinity and

substratum type with the mangrove trees. DISTLM produces a sequential test, which

assesses the variation each predictor (environmental variable) has on its own, and a

conditional test, which explains the variation of all the variables (McArdle and

Anderson, 2001). The most parsimonious model was identified using the Akaike

information criterion (AIC). AIC ranks models from all possible combinations of the

environmental variables. Distance-based redundancy analyses (dbRDA) were used for

visualizing the results as an ordination, constrained to linear combinations of the

predictor variables. The DISTLM was based on abundance data with 4999 permutations.

To measure variation in botanical diversity between forests the following

measurements were used, total species = S, total individuals = N, Pielou’s evenness = J’

and Shannon-Weiner diversity index = H’. The Shannon-Weiner index is calculated by,

H’ = - pi ln pi, where pi is the proportion of individuals that taxon i contributes to the

total sampled population. Pielou’s evenness was expressed by; J¢ = H¢/H¢max, where

32

H¢max is the maximum value of diversity for the number of taxa present (see Magurran,

2004 for details).

2.4 Results

2.4.1. Mangrove area and botanical distributions

The Sombano and Langira forests cover the largest area of all the sites studied, 50

and 60 ha respectively. The mangrove forests on Derawa - Kaluku, Loho, One Onitu and

Gili are very small, with areas of 0.5 ha, 3.1 ha, 1, and 0.9 respectively (Table 2.2).

Site Area (ha) Transect length (mean ± SE)

Sombano 50.0 444.0 ± 42.6

Langira 60.0 388.0 ± 16.2

Kaluku 0.5 37.8 ± 5.9

Loho 3.1 103.6 ± 18.0

One Onitu 1.0 91.8 ± 6.4

Gili 0.9 71.3 ± 16.7

Tree distributions within the WMP (Table 2.3) such as Rhizophora stylosa were

found in the mid- to low- areas of each mangrove forest. The only mangrove forest

Table 2. 2, Areas of mangrove forests investigated and mean distance from the strandline to

the seaward edge. The area of the sites are in hectares and the transect lengths are in metres

(mean ± SE).

33

Table 2. 3, Mangrove plant species found in the WMP. Sites: S = Sombano, L = Langira, K =

Kaluku, Lo = Loho, O = One Onitu & G = Gili. Taxonomic authorities were obtained from the

International Plant Names Index.

investigated without R. stylosa is the land-locked Sombano forest. Rhizophora apiculata

was found in every forest accept Loho and One Onitu. Bruguiera gymnorhiza occurred

at each forest and Sonneratia alba was found in every site except Sombano.

Species Family Sites

Acanthus ebracteatus Vahl. Acanthaceae S

Acrostichum speciosum Willd. Pteridaceae S

Aegiceras floridum Roem. & Schult. Myrsinaceae L

Avicennia marina Vierh. Avicenniaceae L

Bruguiera cylindrica Blume. Rhizophoraceae S

Bruguiera gymnorhiza (L.) Sav. Rhizophoraceae S, L, K, Lo, O, G

Casuarina equisetifolia J.R. Forst. & G. Forst. Casuarinaceae L

Cordia subcordata Lam. Boraginaceae L

Crinum asiaticum L. Amaryllidaceae L

Derris trifoliata Lour. Leguminosae S

Drynaria quercifolia (L.) J. Sm. Polypodiaceae S

Dolichandrone spathacea K. Schum. Bignoniaceae S

Excoecaria agallocha L. Euphorbiaceae S

Ficus sp. Moraceae S

Heritiera littoralis (Dryand.) Sterculiaceae S

Hibiscus tiliaceus L. Malvaceae L

Nypa fruticans Wurmb. Arecaceae S

Osbornia octodonta F. Muell. Myrtaceae L

Pemphis acidula Forst. Lythraceae L, K

Rhizophora apiculata Blume. Rhizophoraceae S, L, K, G

Rhizophora stylosa Griff. Rhizophoraceae L, K, Lo, O, G

Sonneratia alba Griff. Sonneratiaceae L, K, Lo, O, G

Xylocarpus granatum Koen. Meliaceae S, L, K

Xylocarpus moluccensis M. Roem. Meliaceae S, L

34

2.4.2. Environmental factors

Salinity

The lowest salinity levels of this study were recorded from Sombano, which had

a brackish water environment (Table 2.4). In Sombano a gradient of salinity from the

strandline was recorded, beginning at zero PSU and increasing to twenty-eight PSU at

the seaward edge (refer to Figure 2.2). Conversely, no salinity gradients were observed

in Langira, Kaluku, Loho, One Onitu and Gili - as salinities were almost fully marine

ranging from 31.5 – 34.8 PSU.

Site Salinity

Sombano 15.3 ± 0.7

Langira 33.3 ± 0.1

Kaluku 34.4 ± 0.2

Loho 31.5 ± 0.2

One Onitu 32.2 ± 0.2

Gili 34.8 ± 0.2

Emersion

Emersion times (hours) within the high, middle and low intertidal zones differed

within and between the mangrove forests (Table 2.5). The Sombano and Gili forests had

Table 2.4, Mangrove forest variation of salinity levels. Salinity

measurements defined as PSU were recorded along each transect at

five metre intervals within every forest studied (mean ± SE).

35

the greatest emersion times in each intertidal zone when compared with the other sites.

Sombano and Gili are basin-type mangrove forests, which explain the long emersion

times recorded from the low-intertidal zones.Langira, Kaluku, Loho and One Onitu each

had similar emersion times when compared with each other within each intertidal zone.

Mangrove forest area

Site Strandline Centre Seaward

Sombano 18.5 ± 0.4 18.4 ± 0.3 20.8 ± 0.4

Langira 9.6 ± 1.1 6.5 ± 0.1 5.4 ± 0.1

Kaluku 8.8 ± 0.6 7.0 ± 0.2 5.3 ± 0.5

Loho 9.4 ± 1.1 6.4 ± 0.1 5.7 ± 0.2

One Onitu 8.6 ± 0.6 7.4 ± 0.7 7.3 ± 0.2

Gili 12.4 ± 0.1 11.9 ± 0.2 13.2 ± 0.4

Table 2.5, Variation in emersion time between different mangrove forests. The

intertidal zones of each forest include, the strandline designated as the high intertidal,

the centre of the mangrove is considered as the mid intertidal and the seaward fringing

areas have been classified as the low intertidal zones. Emersion is the time each

mangrove forest zone is not immersed in seawater over a 25 hour spring tidal cycle

(hours, mean ± SE).

*The Sombano and Gili forests both have a sump-like shore height profile. The centre

regions of both forests have the lowest recorded height above sea levels compared

with the strandline and seaward edges.

36

2.4.3. Canopy-forming trees and forest characteristics

The investigation into the canopy forming trees and forest characteristics of the

sites (Figure 2.2) revealed that the tallest trees were found in the Sombano forest with

heights of trees greater than 23 metres. The Gili forest also had very large trees, ranging

up to 22 metres. However, the forest canopies within Langira, Kaluku, Loho and One

Onitu were notably lower. The tallest trees from those forests ranged in heights between

8 and 16 metres.

The main substratum in Sombano and Gili was organic-rich mud. However,

beyond 70 metres from the strandline within the Gili forest, the substratum changed

from organic-rich mud to sand. Langira also had organic-rich mud, but only between 0-

200 metres from the strandline. Extending from 200 metres from the strandline and out

to the seaward edge in Langira the substratum consists of calcareous mud and sand with

some seagrass beds. Kaluku, Loho and One Onitu each have a calcareous mud and sand

substratum from the strandline to the seaward edges. In addition, each mangrove forest

had protrusions of raised fossil-coral.

Figure 2.2 Mangrove canopy-forming trees and site-specific environmental variables. (a), the

distribution of canopy-forming trees, (b) hydrographic conditions and (c), substratum type along

transects at the six mangrove forests investigated - continues from page 36 to 41.

37

0

5

10

15

20

25

0 50 100 150 200 250 300 350 400 450

Tre

e h

eig

ht

(m)

Bruguiera gymnorhiza Excoecaria agallocha Tree stumps Heritiera littoralis

Nypa fruticans Rhizophora apiculata Xylocarpus granatum Xylocarpus moluccensis

0

5

10

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30

35

40

0

5

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15

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0 50 100 150 200 250 300 350 400 450

Sa

lin

ity

Em

ersi

on

(h

)

Emersion Salinity

Sombano

Substratum type

Distance from strandline (m)

= Raised fossil coral = Organic-rich mud

a

c

b

38

0

5

10

15

20

25

0 50 100 150 200 250 300 350 400

Tre

e h

eig

ht

(m)

Rhizophora apiculata Rhizophora stylosa Sonneratia alba Xylocarpus granatum Bruguiera gymnorhiza

0

5

10

15

20

25

30

35

40

0

5

10

15

20

25

0 50 100 150 200 250 300 350 400

Sa

lin

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Em

ersi

on

(h

)

Emersion Salinity

Langira

Substratum type

a

c

b


= Raised fossil coral = Organic-rich mud = Calcareous mud = Seagrass beds

39

0

5

10

15

20

25

0 5 10 15 20 25 30 35

Tre

e h

eig

ht

(m)

Rhizophora stylosa

0

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25

30

35

40

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5

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15

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25

0 5 10 15 20 25 30 35

Sa

lin

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(h

)

Emersion Salinity

Kaluku

Substratum type

a

c

b

= Raised fossil coral = Sand = Calcareous mud


40

0

5

10

15

20

25

0 20 40 60 80 100 120

Tre

e h

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ht

(m)

Bruguiera gymnorhiza Rhizophora stylosa

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35

40

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0 20 40 60 80 100 120

Sa

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on

(h

)

Emersion Salinity

Loho

Substratum type

a

c

b

Distance from strandline (m) = Raised fossil coral = Calcareous mud

41

0

5

10

15

20

25

0 20 40 60 80 100

Tre

e h

eig

ht

(m)

Bruguiera gymnorhiza Rhizophora stylosa Sonneratia alba

0

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40

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0 20 40 60 80 100

Sa

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(h

)

Emersion Salinity

One Onitu

Substratum type

a

b

c


= Sand = Calcareous mud

42

0

5

10

15

20

25

0 10 20 30 40 50 60 70 80 90 100

Tre

e h

eig

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(m)

Bruguiera gymnorhiza Rhizophora apiculata Rhizophora stylosa Sonneratia alba

0

5

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5

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0 10 20 30 40 50 60 70 80 90 100

Sa

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Em

ersi

on

(h

)

Emersion Salinity

Gili

Substratum type

a

c

b


= Organic-rich mud = Calcareous mud = Sand = Raised fossil coral

43

2.4.4. Tree species dominance - basal areas, biomass and tree densities

Basal areas of the species found varied considerably (Table. 2.6). Within

Sombano, E. agallocha and B. gymnorhiza were the most dominant species. The Langira

forest had lower basal areas in comparison to Sombano. However, the most dominant

species in Langira were B. gymnorhiza and R. stylosa. In Derawa, R. stylosa was

dominant within all forests except Gili. In Kaluku, the most dominant species was S.

alba, although only one species was recorded within the plots. Bruguiera gymnorhiza

was dominant in One Onitu and Gili, and S. alba had a large basal area within the Gili

forest – however, only one species was also recorded within the plots.

Basal area measurements of the E. agallocha trees in Sombano (Figure 2.3) were

dominant in each of the 22 plots investigated. Bruguiera gymnorhiza was also very

dominant, however in the landward regions this species was less dominant compared

with E. agallocha. Rhizophora apiculata was dominant in areas of the forest – but this

species was patchy. Heritiera littoralis was dominant at the strandline; however the

basal area measurements of this species decreased with increasing distance from the

strandline.

44

Tree Species Site

Sombano Langira Kaluku Loho One Onitu Gili

Bruguiera cylindrica 0.02 ± 0.08 Bruguiera gymnorhiza 9.98 ± 1.93 1.63 ± 0.44

1.7 ± 1.14 21.08 ± 7.87 16.31 ± 3.56

Excoecaria agallocha 11.04 ± 1.2 Heritiera littoralis 2.74 ± 1.97 Rhizophora apiculata 3.24 ± 1.25 0.32 ± 0.16

7.1

Rhizophora stylosa

1.37 ± 0.25 10.75 ± 1.4 14.75 ± 2.1 7.36 ± 2.06 Rhizophoracae saplings

0.14 ± 0.1

Sonneratia alba

0.35 ± 0.26 12.16 ± 12.16

13.25 ± 7.5 33.8

Xylocarpus granatum 0.96 ± 0.47 0.66 ± 0.66 Xylocarpus moluccensis

0.03 ± 0.03

Table 2.6, The variation of tree-species basal area measurements from each of the mangrove forests investigated. All basal area measurements (m2 ha

-1)

were recorded from trees within designated plots in each mangrove forest (mean ± SE).

45

0

5

10

15

20

25

100 140 240 260 340

Bruguiera gymnorhiza

0

0.1

0.2

0.3

0.4

100 140 240 260 340

Bruguiera cylindrica

0

5

10

15

20

25

100 140 240 260 340

Ba

sal

are

a (

m2 h

a-1

)

Excoecaria agallocha

0

5

10

15

20

25

100 140 240 260 340

Rhizophora apiculata

0

5

10

15

20

25

100 140 240 260 340


Xylocarpus granatum

0

5

10

15

20

25

100 140 240 260 340


Heritiera littoralis

Figure 2.3, Basal areas of mangrove species in Sombano. Differences between mangrove

tree basal areas (mean ± SE) recorded from within plots (n = 22) at different distances from

the strandline. *The y-axis of the figure belonging to B. cylindrica is a different scale to all

other figures, due to the very low basal area.

46

Within the Langira forest, Rhizophora stylosa was dominant in each of the 19

plots, the basal area measurements increased with increasing distance from the

strandline (Figure 2.4). Bruguiera gymnorhiza was also dominant within the plots

from Langira. R. apiculata was found only in regions at the high-intertidal.

Sonneratia alba had a low abundance and was very patchy, but the basal area was

large as these species have a large circumference. Xylocarpus granatum also had a

very low abundance in Langira and this species was found only at the strandline,

with some very large individuals.

In the plots from Kaluku only two tree species were recorded (Figure 2.5).

Rhizophora stylosa was very dominant and found in 11 of the 12 plots. Although

Sonneratia alba had a very large basal area measurement, this species was found

only in 1 plot located at the strandline.

Within the Loho forest (Figure 2.6), Rhizophora stylosa was very dominant.

This species was found in 9 of the 10 plots. However, Bruguiera gymnorhiza had a

comparatively low basal area and was found close to the strandline.

Bruguiera gymnorhiza was dominant within the One Onitu forest from the

mid-intertidal and below (Figure 2.7). Rhizophora stylosa had a similar distribution

to B. gymnorhiza however this species was less dominant. Sonneratia alba was very

patchy, and found only from the strandline and down to the mid-intertidal - S. alba

was very dominant with very large basal area measurements.

The most dominant tree species in the Gili forest was Bruguiera gymnorhiza

(Figure 2.8). However, there were emergent Rhizophora apiculata trees found within

the mid-intertidal areas and Sonneratia alba trees found only at the seaward edges.

47

Only one S. alba tree was recorded within the plots, however this specimen had a

very large basal area.

0

2

4

6

8

10

0 160 320 440 460

Rhizophora stylosa

0

2

4

6

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0

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sal

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a (

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Sonneratia alba

0

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Xylocarpus granatum

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 160 320 440 460


Xylocarpus moluccensis

Figure 2.4, Basal areas of mangrove species in Langira. Differences between mangrove tree

basal areas (mean ± SE) recorded from within plots (n = 19) at different distances from the

strandline. * The y-axis of the figure belonging to X. moluccensis is a different scale to all other

figures, due to the very low basal area.

48

0

20

40

60

80

100

120

140

0 10 20 30 40 50

Ba

sal

are

a (m

2 h

a-1

)

Rhizophora stylosa

0

20

40

60

80

100

120

140

0 10 20 30 40 50

Basa

l are

a (

m2 h

a-1

)


Sonneratia alba

Figure 2.5, Basal areas of mangrove species in Kaluku.

Differences between mangrove tree basal areas (mean ± SE)

recorded from within plots (n = 12) at different distances from

the strandline.

49

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150

Basa

l are

a (

m2 h

a-1

) Rhizophora stylosa

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150

Basa

l are

a (

m2 h

a-1

)



Figure 2.6, Basal areas of mangrove species in Loho. Differences

between mangrove tree basal areas (mean ± SE) recorded from

within plots (n = 10) at different distances from the strandline.

50

0

10

20

30

40

50

60

70

80

90

0 10 20 30 40 50 60 70

Brugueira gymnorhiza

0

10

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40

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60

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90

0 10 20 30 40 50 60 70

Basa

l are

a (

m2 h

a-1

)

Rhizophora stylosa

0

10

20

30

40

50

60

70

80

90

0 10 20 30 40 50 60 70


Sonneratia alba

Figure 2.7, Basal areas of mangrove species in One Onitu. Differences between

mangrove tree basal areas (mean ± SE) recorded within plots (n = 15) at different

distances from the strandline.

51

Biomass estimates from the basal area measurements were calculated using

allometric equations (Komiyama et al., 2005; Komiyama et al., 2008) (Table 2.7).

Sombano had the greatest estimates of biomass, followed by Langira. The mangrove

forests in Derawa, Kaluku, Loho, One Onitu and Gili had comparatively low

estimates of biomass.

0

5

10

15

20

25

30

35

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Ba

sal

are

a (

m2 h

a-1

)


0

0.1

0.2

0.3

0.4

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0.6

0.7

0 10 20 30 40 50 60 70

Rhizophoracea saplings

0

5

10

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20

25

30

35

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Ba

sal

are

a (

m2 h

a-1

)



0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70


Sonneratia alba

Figure 2.8, Total basal areas of mangrove species in Gili. Differences of the total

basal areas (mean ± SE) recorded for each individual mangrove tree within plots (n = 6)

at different areas from the strandline. * The y-axis of the figure belonging to

Rhizophoracea saplings is a different scale to all other figures, due to their low basal

areas.

52

Species Site (t ha)


Bruguiera cylindrica 0.4 ± 0.1

Bruguiera gymnorhiza 328.6 ± 0.1 50.3 ± 0.3 1.3 ± 0.1 32.3 ± 0.6 7.8 ± 0.1

Excoecaria agallocha 605.8 ± 0.1

Heritiera littoralis 223.6 ± 1.4

Rhizophora apiculata 236.8 ± 1.0 13.3 ± 0.1 1

Rhizophora stylosa 83.0 ± 0.03 18.5 ± 0.03 28.3 ± 0.04 21.6 ± 0.05

Rhizophoracea saplings 0.1 ± 0.003

Sonneratia alba 12.2 ± 1.5 3.4 21.4 ± 1.4 3.4

Xylocarpus sp. 66.4 ± 0.3 111.2 ± 26.7

Table 2.7, Biomass estimates of mangrove species from each of the sites studied. Differences of biomass estimates (mean ± SE) of mangrove

basal areas recorded from plots within each forest. Allometric equations were used to calculate biomass. Wood density constants for B.

gymnorhiza, B. cylindrica, B. saplings, S. alba = 0.186*DBH+2.31, R. saplings, R. stylosa = 0.128*DBH+2.6, X. spp. = 0.0823*DBH+2.59, E.

agallocha, H. littoralis = 0.168*DBH+2.47 and R. apiculata = 0.235*DBH+2.42.

*The breakdown of the allometric biomass equations for e.g. Rhizophora apiculata 0.235*DBH+2.42; where 0.235 = wood density + 2.42 (constant) x log10 of

the DBH (diameter at breast height). To obtain the biomass in kgs, the log10 mass is exponentialy raised to the power of 10 and then divided by 1000 to calculate

the biomass weight in tons.

53

The densities of trees between the sites varied considerably (Table 2.8). There were

more than 750 Bruguiera gymnorhiza trees per hectare in Sombano, however less than 65 B.

gymnorhiza per hectare were estimated to be in Langira. Differences of numbers of

Rhizophora stylosa were also found. In the Langira forest there were less than 260 R. stylosa

trees per hectare. However, there were more than 900 R. stylosa per hectare in the Loho

mangrove forest. The least abundant mangrove trees were B. cylindrica in Sombano, and

Xylocarpus moluccensis found in the high intertidal areas within Langira.

54

Tree Species Site


Bruguiera cylindrica 2 ± 1.4

Bruguiera gymnorhiza 766 ± 231.42 61 ± 22.9

100 ± 32.38 333.3 ± 88.18

Excoecaria agallocha 563 ± 105.4

Heritiera littoralis 51 ± 18.1

Rhizophora apiculata 77 ± 26.18 42 ± 20.8

16 ± 16.66

Rhizophora stylosa

255 ± 42 781 ± 64.4 930 ± 98.95 420 ± 115.5

Rhizophoracea saplings

216.7 ± 79.24

Sonneratia alba

6 ± 5.06 0.1 ± 0.1

40 ± 23.5 16 ± 16.66

Xylocarpus granatum 67 ± 38.5 3.0 ± 2.2

Xylocarpus moluccensis

1.0 ± 1.0

Table 2.8, Densities of different tree species in mangrove forests within the study sites. Tree densities per hectare were recorded from

plots within each of the mangrove sites investigated (mean ± SE).

55

2.4.5. Site similarity and tree species diversity

A Multidimensional Scaling plot (MDS) of mangrove forest similarities of

the composition and abundance of trees was used to compare patterns of tree

diversity between each mangrove forest (Figure 2.9). The inland mangrove forests,

Sombano and Gili were more similar to each other compared to the seaward forests

with 50 % similarity to each other. The Kaluku and Loho forests are established in

sheltered bays and they share an 80 % similarity. The MDS plot also grouped One

Onitu and Langira with 50 % similarity – both forests are established in exposed

coastal areas.

Transform: Fourth root

Resemblance: S17 Bray Curtis similarity (+d)

SitesSombano

Langira

Kaluku

Loho

Onitu

Gili

2D Stress: 0.1

Figure 2.9, An MDS plot illustrating similarities between mangrove tree community

structure and abundance of trees within each of the mangrove forests investigated. The data

were square root transformed and a Bray Curtis similarity matrix was used to calculate inter-

sample similarities within each of the forests.

56

Analyses of the diversity of mangrove trees (Table 2.9) determined that

Sombano has the highest tree diversity, and abundance of species. The Langira forest

had a relatively high diversity and evenness. The analysis for both Loho and Kaluku

revealed they had the lowest tree diversity. This was also mirrored with low evenness

values from the forests – also due to the dominance of R. stylosa. Although One

Onitu had a low density and abundance of species, the Pielou’s evenness value was

higher than any of the other mangrove forests.

Site S N J’ H’

Sombano 6 1526 0.627 1.124

Langira 6 368 0.515 0.922

Loho 2 980 0.291 0.202

Onitu 3 560 0.648 0.712

Kaluku 2 782 0.002 0.001

Gili 4 583 0.643 0.891

Distance-based redundancy analysis (dbRDA) was used for visualizing the

correlations of the trees with emersion time, substrate and salinity (environmental

variables) measured from each forest and plot as an ordination, constrained to linear

combinations of the predictor variables. The environmental variables influencing the

dbRDA ordination axis 1 (Figure 2.10 a) showed that 94.7 % of the environmental

data explains 45.2 % of the total variation and for axis 2, 5 % of the environmental

Table 2.9, Comparison between the various indices of tree species between

the mangrove forests investigated. S = number of species, N = total individuals,

J’ = Pielou’s evenness, H’ = Shannon-Weiner diversity index.

57

data explains 2.4 % of the total variation. The distributions of trees within each

mangrove forest except Sombano were strongly affected by emersion time and the

substratum type (Figure 2.10 b) and the trees within Sombano were strongly affected

by salinity (Figure 2.10 b). However, a few trees from Langira were also grouped

within Sombano. The trees, R. stylosa, R. apiculata and B. gymnorhiza were affected

by emersion time and substratum type (Figure 2.10 c). However, E. agallocha, X.

granatum and H. littoralis were strongly correlated with lower salinity (Figure 2.10

c). Two distinct groups were found, as the Sombano forest was different from the

other forests.

Figure 2.10, dbRDA ordinations. a, the distribution of trees identified from plots within each mangrove

forest. Different coloured symbols signify different mangrove forests, b, the environmental vectors that

influence the trees within each mangrove site and, c, the tree distribution within the mangrove forests

explained as vectors. Ea = Excoecaria agallocha, Hl = Heritiera littoralis, Xg = Xylocarpus granatum, Ra

= Rhizophora apiculata, Bg = Bruguiera gymnorhiza and Rs = Rhizophora stylosa. PSU = practical salinity

units.

a

b c

58

A conditional test revealed that emersion time explains 94.7 % of the total

variation, followed by salinity and mud with 5% and 0.3% of the total variation

respectively. All three variables were retained, therefore no correlation. In the

distance based linear modelling (DISTLM) test, the sequential test revealed that the

trees from the mangrove forests were correlated with emersion time, salinity and

substrate type (Table 2.10). The most parsimonious model (AIC = 596. 18, R-Sq =

0.48) for the mangrove forests explains 47.7% of the variation, with emersion time

explaining 40 % followed salinity explaining 4%, and then mud explaining 3%.

Predictor variables AIC SS (trace) Pseudo-F P-

value Proportion Accumulative df

Emersion 603.3 66543 56.33 < 0.001 0.4 0.40429 83

Salinity 598.81 7200.9 6.4997 < 0.01 0.04 0.44804 82

Mud 596.18 4824.2 4.5426 < 0.05 0.03 0.47735 81

2.5 Discussion

Inland forests, such as the Sombano and Gili forests and the coastline-

dominating Langira and One Onitu forests which are linked to other ecosystems have

rarely been studied within Indonesia (Tomascik et al., 1997). This type of

topography is not common to Indonesia; however the forests do contain mangrove-

tree species combined with zonation patterns often reported for Southeast Asia

(Tomascik et al., 1997; Giesen et al., 2006; Cragg and Hendy, 2010).

Table 2.10 Distance-based linear modelling (DISTLM). Sequential test results relating the

mangrove trees within each site (abundance data) with emersion time, salinity and mud recorded

from each of the mangrove forests.

59

Zonation patterns of trees were found in Sombano, with Heritiera littoralis

found only at the strandline and more salt-tolerant species, Bruguiera and

Excoecaria found further towards the sea. The mix of Bruguiera gymnorhiza and

Excoecaria agallocha trees may be due to the intolerances of environmental

variables. Both species are commonly found in the same areas within mangrove

forests (Duke, 1992). Very subtle changes of tidal emersion were found in Sombano

(Figure 2.2), therefore waterlogging of mangrove root-tissues did not create distinct

zonation patterns between the Excoecaria and Bruguiera trees. As differences of

immersion time; the waterlogging of mangrove roots may contribute to species-

specific zonation patterns. Bruguiera gymnorhiza is more tolerant to immersion than

Excoecaria agallocha, which is more tolerant than the Heritiera littoralis trees. The

differences in tolerance to waterlogging between different mangrove trees are related

to their anatomical features of cortex root-tissues, epidermis and hypodermis (Pi et

al., 2009). The Sombano substratum consisted of organic-rich mud and the forest

was established in the high intertidal zone. Those factors did not affect the zonation

patterns of plants within Sombano. The distribution of trees within Sombano is

controlled by salinity, which increased in concentration with distance from the

landward edge.

The bank of mixed saplings within Sombano is an indication of young stands.

Older trees have greater girth measurements and are less densely distributed (Alongi,

2002). The sparser, but large Xylocarpus spp. in Sombano may contribute to

increases of the total above-ground biomass with increasing age. A similar pattern

was found in mangrove forests in Vietnam - where stands also become less dense,

due to increases in tree girths (Alongi, 2002).

The low salinities and long emersion times recorded at the strandline within

60

Sombano explains the limited distribution of Nypa fruticans and Heritiera littoralis.

The presence of N. fruticans is an indicator of freshwater environments, and is often

found adjacent to H. littoralis stands (Tomascik et al., 1997) and these palms do not

tolerate salinities above fifteen PSU (Blasco et al., 1996; Alongi, 2007).

Furthermore, N. fruticans does not tolerate more than three hours of inundation per

day (Blasco et al., 1996), which the same thing is seen from this study as N. fruticans

were found in areas from Sombano with less than three hours of immersion and

salinities less than fifteen PSU.

Adjacent and seaward to the Sombano forest is the Langira mangrove forest.

Emersion time was found to influence the zonation patterns within that forest.

Rhizophora apiculata was established in areas of the forest with increased emersion

times. However, R. stylosa and S. alba were more common in areas less frequently

inundated. The Langira forest is established on a large coral-rock plateau. Hard

coralline substrata are often dominated by R. stylosa (Tomascik et al., 1997).

However, hard substrata may prevent Rhizophora propagules from embedding and

therefore establishing. Rhizophora propagules need to be anchored in to the

sediment; this is an important factor for their survival (Kathiresan and Bingham,

2001). Thus, the fossil-coral substratum in Langira may impede and reduce the

successful establishment of propagules, which may explain the patchy canopy within

Langira. Sonneratia alba were found only at the outermost seaward-edges of the

forest, which had the highest salinity levels. S. alba commonly grows on the

outermost seaward margins, especially in sandy and rocky areas that are fully marine

(Tomascik et al., 1997; Giesen et al., 2006).

Within Langira, Xylocarpus spp. were found only in areas with the longest

emersion time and lowest recorded salinities. These environmental factors determine

61

the distributions of Xylocarpus spp. Within other southeast Asian mangrove forests,

Xylocarpus spp. were also reported in areas only inundated by high-tides, in the

landward regions and in areas of lower salinities (Tomascik et al., 1997; Giesen et

al., 2006). Although individual Xylocarpus spp. within the Langira forest are very

large, those trees were not dominant due to their very low abundance within the

forest.

Higher mangrove tree densities have reduced basal areas (Alongi, 2002). The

same thing was seen with this study; the Sombano forest had the largest density of B.

gymnorhiza trees, but those trees had small girths. Langira and Loho had the lowest

densities of B. gymnorhiza, but those trees were larger in comparison with Sombano

- which highlights the importance of these larger mature trees. Less distributed,

larger trees are not only an indication of age, but they also significantly contribute to

an increase of biomass for the forest (Along, 2002). The mean recorded

circumference for B. gymnorhiza in Langira and Loho was greater than those

reported from Sombano. However, many of the larger mature B. gymnorhiza trees

from Sombano had been felled. Thus, much of the Sombano tree biomass had been

removed.

Langira had the lowest recorded densities of R. stylosa, but a lower basal area

for this species. The lower measurements of mean girth of the R. stylosa stands

recorded from Langira may be due to the result of the heavy harvesting pressures

imposed upon the forest (Walters, 2005a; Walters et al., 2008). The reduced

structural complexity of the R. stylosa stands, low densities and low canopy height

within Langira, may also be attributed to forest age (Alongi, 2002), as tree densities

decline, with age. However, some trees within Langira were not harvested – such as

the large Xylocarpus spp.

62

Within each of the mangrove forests the basal areas of the trees differed. The

differences of tree girths may be attributed to species densities, changes of

environmental conditions and harvesting pressures (Alongi, 2002; Giesen et al.,

2006; Walters et al., 2008). The differences of tree-girths recorded between the

forests suggest that the total dominance and living biomass of the tree species within

each forest also differs.

Using basal-area measurements as an indication of tree-species dominance

and of the quantity of living biomass within the forests of the WMP, comparisons of

woody biomass can be made with other forests, using allometric equations

(Komiyama et al., 2008). The numerous large trees from Sombano provided

estimates of forest biomass that were similar to the extensive mangrove forests

reported from other areas in Indonesia, Malaysia and Papua New Guinea, which had

biomass values ranging from 430 to 600 tonnes per hectare (Komiyama et al., 2008;

Alongi, 2009). Values reported from Langira were lower than Sombano, but higher

than estimates from the mangrove forests on Derawa. The biomass of trees within

Langira is similar to those reported from other Indonesian mangrove forests that

range up to 170 tonnes per hectare for Rhizophora-dominated forests (Komiyama et

al., 2008). The largest contributors of living biomass within Langira are the

Xylocarpus spp. demonstrating that even a very few trees can significantly contribute

to the total above-ground forest biomass (Ong et al., 1995; Alongi, 2002). The lowest

estimates of forests biomass were recorded from the mangrove forests on Derawa.

The Kaluku, Loho, One Onitu and the Gili forests are similar to the ranges of

mangrove forest biomass reported from Florida and Kenya, where biomass estimates

range between 8 – 20 tonnes per hectare (Lugo and Snedaker, 1974; Kairo et al.,

2009).

63

Mangrove forests develop best in areas associated with high rainfall and

freshwater input (Lira-Medeiros et al., 2010), such as Papua New Guinea with a

mean annual rainfall of 3,485 mm year-1

(Spalding et al., 1997) where impressive

thirty to forty metre tall Bruguiera and Rhizophora trees develop (Alongi, 2007).

However, the mean annual rainfall for Sulawesi is much lower - 1,525 mm year-1

(Dechert et al., 2005). Within the WMP the mean annual rainfall varies between 850

– 3300 mm year-1

(Crabbe and Smith, 2005). This may explain the lower tree heights

and shrubby appearance of the mangrove trees within the seaward mangrove forests

of the WMP.

Mangrove productivity, biomass and growth, increases with decreasing

salinities combined with increases of nutrient input (Lugo, 1980; Clough, 1984;

Sherman et al., 2003) - such as Sombano and the landward regions of Langira. The

Sombano forest has a thick covering of organic-rich mud and the lowest salinities of

the forests in this study. Thus, these environmental factors may explain the relatively

high dominance, diversity and evenness of the trees within Sombano when compared

with all the other forests studied in this investigation. It is known that mangrove

forests attain their greatest biomass, diversities, canopy heights and productivities in

areas where salinities are between ten and twenty-five PSU (Robertson, 1990;

Tomascik et al., 1997; Joshi and Ghose, 2003; Sherman et al., 2003). The Sombano

forest contains trees that reach their greatest heights compared to the other mangrove

forests researched in the WMP.

Many Rhizophora and Bruguiera trees in Langira have been heavily cut for

fuel wood. Removal of wood from a mangrove forest will reduce the habitat

heterogeneity (Gratwicke and Speight, 2005). In general, there are many

environmental implications from habitat loss (Granek and Ruttenburg, 2008);

64

mangrove forests protect coastlines from storm damage (Walters, 2005b; Walters et

al., 2008) – and they also serve as vital nurseries and feeding grounds for many

invertebrates and fish species (Kathiresan and Bingham, 2001). Although the plant

diversity is high, wood-harvesting is common practice within Sombano and in the

adjacent seaward Langira forest. Unsustainable harvesting of wood has long-term

detrimental effects (Bosire et al., 2006), and the intensity and frequency of

disturbance can have permanent effects on forest structure and tree composition

(Hauff et al. 2006).Harvesting will lead to a change in ecosystem function due to

increasing canopy gaps. Gaps within the forest canopy lead to abiotic changes of

light penetration and temperature, combined with increases of cyanobacteria, which

lead to a reduction of grazing animals (Granek and Ruttenburg, 2008) - such as

Terebralia sulcata, which were often found in the forests.

The Sombano and Gili forests have a high level of plant-diversity and

evenness - these forests are senescent, a type of forest that has rarely been studied

(Duke, 2001) and both are established inland and separated from direct tidal

inundation. Senescent mangrove forests may promote higher tree diversity, when

canopy gaps form due to falls of old trees the disturbance creates new opportunity for

other trees to establish (Duke, 2001).

Sombano and Gili demonstrated evidence of the larger emergent trees

becoming senescent. Up-rooted fallen trunks of large trees, and canopy gaps were

common in both forests. Determining the age of mangrove trees is challenging due to

the lack of growth rings. Nonetheless, these large trees have been estimated to be

very old (Cragg and Hendy, 2010). Another indicator of senescent forests is

pedogenesis analyses. The older the forest, the greater the organic content is

sequestered within the sediments; as the particulate organic carbon derived from

65

large woody detritus is partially retained. Organic-rich mangrove forest mud contains

ligno-cellulosic debris derived from decaying higher plants, and has ten-times the

organic content of sediments of less mature forests (Ashton and Macintosh, 2002;

Marchand et al., 2003). Sombano and Gili have organic-rich mud substrata, and both

forests contain the tallest trees. The sediment composition observed within all the

forests accept Sombano and Gili consisted of a higher proportion of calcareous

material, such as sand and shell fragments. Mangrove forests lose significant

amounts of dissolved organic carbon to coastal waters (Kristensen et al., 2008).

Thus, the less organic debris within the sediments may provide reasons for the

smaller trees recorded within the seaward forests of this study.

The estimates of living-biomass of mangrove trees reported from this study

are comparable to those from other mangrove forests and these trees are a source of

litter for the mangrove forests in the WMP, but forest harvesting and the removal of

forests-products may impact the faunal communities of the WMP (Cragg and Hendy,

2010). Many animals; fish and invertebrates rely upon large woody debris to avoid

predation, as the complexity of fallen wood offers protection for animals (Wright and

Flecker, 2004). The reduction of the mangrove forest complexity due to the

harvesting pressures imposed upon these already impacted mangrove forests - and

the loss of old trees within the WMP is accelerating. These impacts may have further

consequences as the available dead wood within these forests may be important

habitat for many animals (Cragg and Hendy, 2010).

66

Chapter 3

INVESTIGATION OF WOOD BIODEGRADATION IN

MANGROVE ECOSYSTEMS OF THE WMP

3.1 Introduction

Detrital breakdown and nutrient recycling is a fundamental ecological process

for every natural ecosystem. This process occurs in terrestrial and aquatic

environments – whether coral reefs (Hata et al., 2002), freshwater streams (Karlsson

et al., 2005; Greenwood et al., 2007), or tropical rain forests (Cerri et al., 2007).

Over fifty percent of the World’s organic carbon is sequestered in to terrestrial

ecosystems (Malhi et al., 2002), with the remaining carbon taken up by marine

systems (Muller-Karger et al., 2005). Within marine intertidal areas, mangrove

forests sequester much of the carbon and are considered to be carbon-sinks (Donato

et al., 2011). However, nutrient recycling in mangrove forests is complex as they are

sites where terrestrial and marine ecosystems directly interact.

In mangrove ecosystems, carbon is fixed via photosynthesis to form various

plant tissues such as large woody trunks, roots and leaves (Ong et al., 1995). The

mangrove organic material is then processed in the direct transfer of energy to higher

trophic levels. The biodegradation of organic material is processed in different ways

via saprophytic decay (Sarma and Vittal, 2001; Ananda and Sridhar, 2004) and

mechanical breakdown of plant material (Robertson and Daniel, 1989a; Filho et al.,

2008). Thus, litter within mangrove forest environments, broken down in different

ways serves as the base for intricate food webs (Benner and Hodson, 1985). The

principal component of woody plants and dead plant material is lignocellulose,

which is the most abundant biomass on earth (Eggert et al., 1996; Kalmis et al.,

67

2008). Thus, the biodegradation of large woody debris (LWD) in mangrove forests is

an essential contribution to the global carbon cycle (Weedon et al., 2009; Donato et

al., 2011). The flux of carbon in an Australian mangrove forest from the gradual

degradation of LWD is reported to be similar in quantity to that of leaf litter

consumption by crabs (Robertson and Daniel, 1989a). Much of the mangrove-

derived carbon is assimilated within nearby marine ecosystems, which are typically

oligotrophic. A study of mangrove-derived organic matter outwelling in Panama

demonstrated that connectivity is important as many sessile reef invertebrates rely

upon mangrove organic matter (Granek et al., 2009).

Wood constitutes between 20-50% of the net primary production of

mangrove systems (Bunt et al., 1979, Robertson, 1990), therefore fallen wood

provides a large proportion of organic carbon to a mangrove ecosystem (Donato et

al., 2011). LWD when broke down serves to enhance the longterm flow of nutrients

in the mangrove forest ecosystem (Benner and Hodson, 1985; Krauss et al., 2005). A

study within a tropical Australian mangrove forest revealed that LWD will remain

within the ecosystem for more than fifteen years (Robertson and Daniel, 1989a).

LWD also promotes forest productivity by enhancing soil pedogenesis and providing

habitat for germinating seeds (Allen et al., 2000; Krauss et al., 2005) and animals

(Cragg and Hendy, 2010), and may even contribute to the mangrove forest nitrogen

budget when processed (Robertson and Daniel, 1989a). Thus, LWD is a key resource

within mangrove ecosystems.

Previous studies of mangrove forest litter degradation focused on leaves and

twigs (Lambert et al., 1980; Robertson, 1985). Litter input from leaves, reproductive

parts, small branches and twigs, and litter processing has been studied from both the

Caribbean (Feller and Mathis, 1997; Brooks and Bell, 2002) and Australian

68

mangroves (Robertson, 1985; Robertson and Daniel, 1989a). The animals that

process such material include coleopterans (Feller, 2002; Sousa et al., 2003), marine

intertidal crustaceans such as sphaeromatid isopods (Brooks and Bell, 2002;

Svavarsson et al., 2002), sesarmid crabs (Robertson, 1985; Schories et al., 2003) and

pulmonate gastropods (Proffitt and Devlin, 2005). However, there is a paucity of

knowledge regarding the processes affecting the breakdown of LWD with only a few

studies that provide rates of mangrove wood decay. The loss of LWD dry mass in an

Australian mangrove forest ranged from 10 – 97 grams dry weight per year, per

metre squared (Robertson and Daniel, 1989a). However, leaf litter is much more

labile than LWD and tissue loss is greater. In Caribbean mangrove forests, 27% of

leaf litter tissues remained after eight months, and 50% of LWD tissues still

remained after eighteen months (Middleton and McKee, 2001). However, the rates of

wood degradation vary over different tidal zones within mangrove ecosystems, due

to the variety of different wood degrading organisms found at different tidal zones

(Kohlmeyer et al., 1995).

The biodegrading organisms which process LWD in mangrove forests are the

direct link that enhances nutrient recycling (Kohlmeyer et al., 1995; Babu et al.,

2010). This consortium of organisms forms a diverse group from the terrestrial to the

marine regions of the forests - such as the basidiomycetes (Fryar et al., 2004;

Lonsdale et al., 2008; Ravikumar et al., 2009), coleopterans (Feller and Mathis,

1997; Feller and Mckee, 1999; Mckeon and Feller, 2004), termites (Leponce et al.,

1995) and teredinid bivalves (Robertson and Daniel, 1989a; Filho et al., 2008).

Saprophytic degradation of LWD is slow (Benner and Hodson, 1995), and is

caused by basidiomycetes which occur above the hightide mark in mangrove forests

(Kohlmeyer et al., 1995). There are three types of decay recognised in fungi;

69

ascomycete fungi create soft rot and decay the cellulose and hemicellulose (Bucher

et al., 2004). Soft rot is usually restricted to the surface of wood and results in

minimal lignin degradation (Bucher et al., 2004). The second form of decay is white

rot, which facilitate a rapid decay of all the components of wood. This type of decay

is usually caused by basidiomycetes, which affect even the most recalcitrant

component of wood, lignin. Thus, the basidiomycetes are essential for the decay of

LWD in the supratidal areas in the mangrove forests. The third type of decay is

brown rot, which causes the rapid decay of cellulose and hemicellulose. This type of

decay is not found in wet or waterlogged wood. Thus, brown rot is not found in

aquatic environments (Bucher et al., 2004).

However, in the mid- to low- intertidal regions of mangrove forests,

biodegradation is accelerated when LWD is exposed to wood-borers, in particular

animals belonging to the family Teredinidae (Robertson and Daniel, 1989a;

Middleton and Mckee, 2001; Filho et al., 2008). Thus, LWD will break down at

different rates, by a variety of different pathways. This variation will depend on the

plant species composition within the mangrove forests and the distribution of wood-

decaying and wood-boring animals (Robertson, 1990; Middleton and Mckee, 2001).

The Teredinid boring activity is particularly important in forests where there

is a high level of woody biomass consisting of fallen trunks (Robertson, 1990;

Kohlmeyer et al., 1995).Teredinids process fallen logs into fine fragments of faecal

material that contribute to nutrient recycling and reducing the build-up of LWD in

mangrove ecosystems (Filho et al., 2008). Teredinids cannot tolerate regular

prolonged emersion; therefore the distributions of LWD along a tidal gradient in

mangrove forests will influence the activity of the Teredinidae (Robertson, 1990). In

the mid- to low- intertidal zones of a Rhizophora-dominated Australian mangrove

70

forest, approximately fifty percent of the original woody mass of large fallen logs

had been processed by the Teredinidae over two years, whereas, in the high-

intertidal only five percent of the original mass of fallen logs had been lost over two

years, as the teredinids were absent (Robertson, 1990).

This study describes the biodegradation processes from the terrestrial regions

of the mangrove forest to the marine regions of the forest by linking the degradation

processes to the environmental gradients within the forests. Biodegrading organisms

associated with the degradation and recycling of LWD each have a specific role

within mangrove ecosystems. The aims of this study were to identify the organisms

that break down woody detritus within mangrove forests and to determine the

environmental factors that affect their distribution within those forests. This study

also aimed at comparing the rate of LWD fragmentation caused by teredinid

tunneling in intertidal mangrove forests and at nearby coral reef sites.

LWD biomass in the mangrove forests was measured in a very precise way to

determine the volume of fallen wood available to the biodegrading organisms. All

organisms that break down LWD within each mangrove forest were identified.

Salinity and emersion were measured to determine if the distribution of wood-

degrading organisms were influenced by those variables. Two distinct forests that

had terrestrial and marine biodegrading organisms were chosen to investigate the

biodegradation boundary of LWD determined by the sharp change between

terrestrial and marine wood-degrading organisms. Panels were also used to determine

both the environmental variables and the level of wood degradation by teredinids.

This work tested the hypothesis that the biodegrading communities in the mangrove

forests, 1. change with increasing distance from the land and, 2. are influenced by the

environmental factors of salinity and emersion time.

71


3.2.1 Measurement of wood-loss in panels

A total of sixty-five wooden panels, cut from Bruguiera gymnorhiza planks

were placed within the Sombano and Langira forests and Kal 1 reef site to determine

the dry-weight losses of wood from teredinid activity (Figure 3.1 c). Panels had a

volume of 275 cm3

and measured. All panels were exposed for twelve months. The

dry-weight loss of wood was determined by oven drying the panels for 48 hours at

60°C. The percentage of the sectional area of the panel containing teredinid tunnels

was calculated using the digital analysis package ImageTool Version 3.00 (The

University of Texas Health Science Centre at San Antonio).

Panels (n = 5) were placed 0, 20, 100, 240, 380 and 500 metres from the

landward edge within the Sombano forest. The panels within the Langira forest were

placed at 720, 820, 940, 980 and 1070 metres from the Sombano landward edge.

Panels on the Kal 1 reef site were placed at 10 metres depth, 1500 metres from the

Sombano landward edge (Figure 3.1 c).

To determine wood-loss from teredinids, 25 panels within Langira, 60 panels

within Galua and 20 panels each in Kaluku, Loho and One Onitu (Figure 3. 1 a) were

placed. Twenty panels were positioned at a depth of 10 metres from three sub-tidal

reef sites; in the Kal 1, Pak Kasim’s and the Ridge 1 reefs (Figure 3.1 c) in July 2010

and removed in July 2011. The percentage of wood fragmentation attributed by the

activity of the Teredinidae was estimated from the panels from the mangrove forests

and each reef site. All panels were cut longitudinally to determine the level of wood

fragmentation attributed by teredinid activity. The percentage of the sectional area of

each panel represented by tunnels and the area of panel remaining was estimated.

72

The panels were positioned in areas of each mangrove forest where natural

LWD had been attacked by teredinids. Panels within the Derawa forests, Kaluku,

Loho and One Onitu were placed in areas inundated by all high tides. All teredinid

pallets were removed after 12 months exposure by carefully splitting each panel

open. Each teredinid pallet was used to identify the different teredinid species using

the teredinid identification key of Turner (1971).

3.2.2 The measurement and collection of dead wood and arbitrary scale

classification and wood-loss from teredinid attack

Five transects extending from the strandline and ending at the seaward fringe

were established in the Sombano and Langira forests on Kaledupa Island (see chapter

2 methodologies). In Sombano a total of 22, 20 x 20 m plots were used to measure

the biomass of LWD and in Langira 19, 20 x 20 m plots were used to measure the

biomass of LWD. All pieces of LWD, defined as being more than 2 cm in diameter,

were measured to estimate their volume.

73

The height above sea level of each individual piece of LWD was measured.

The high tide marks were recorded on mangrove trees using high visibility string. At

low tide, the distance from the substratum to the mark on the trees were measured

and then subtracted from the marks on the trees to establish height above sea level.

Figure 3.1 Sites within Kaledupa and Derawa Island used for sampling the variety of

biodegrading organisms and to reveal the environmental factors that determine the

biodegradation of LWD. a, map of Kaledupa demonstrating the geographical distribution of

each site; b, mangrove forests have been colour-coded by their site-specific biodegradation

process (terrestrial = brown, marine = blue) and height above sea level (mean ± SE). The

boundary between the terrestrial and marine biodegradation is indicated by the red line within

the Galua and Laulua forests; and c, the three reef sites used in this study. The red dotted line

is the transect used to determine wood-loss.

a b

c

74

Emersion times for the LWD were estimated by relating their tidal heights to data in

regional tide tables.

A total of 168 LWD samples were collected at low tide from the five

transects within the Sombano and Langira forests. Sombano is 0 – 500 metres from

the landward edge and Langira is 700 – 1100 metres from the landward edge of the

Sombano strandline. These forests are separated by a 200 metre wide fossil-coral

plateau. Levels on the scale of wood biodegradation detailed in Table 3.1 were

assigned to each LWD item to define the levels of biodegradation in the Sombano

and Langira forests. Wood-degrading organisms processing each LWD item were

identified to their lowest achievable taxonomic classification.

Level Condition and appearance of specimen

0 No visible signs of deterioration or degradation from both inside and out of the woody debris.

1 The tough outer covering of bark reveals signs of flakiness. Some initial epiphytic fungal fruiting bodies

are visible in areas.

2 Areas of bark can be pulled off by hand and is soft in areas. Fungal fruiting bodies increase. Some

exposure of sapwood, with initial softening.

3 Bark is very flaky, and in most areas can be pulled off with relative ease. Sapwood is easily penetrated

to a depth of 2 – 4 cm using a knife. Sapwood begins to deteriorate revealing holes – sometimes with

fungal growths.

4 Bark, if present is very soft/flaky. The sapwood has numerous holes, which is often soft to the

heartwood.

5 The bark, when visible, crumbles easily. The woody debris can appear to be ‘collapsed’. Both sapwood

and heartwood are very soft. Often, under story plants grow through the woody debris. In addition,

basidiomycete activity upon the detrital material is common.

1

Table 3.1 A scale used to describe level of wood degradation. The level of degradation

imposed upon the LWD in the Sombano and Langira mangrove forests.

*IWH developed the decay-scale from field observations of fallen trees within the mangroves from

this study.

75

3.2.3 Wood degrading organisms and environmental factors in the Galua and

Laulua mangrove forests

Two mangrove forests, Galua and Laulua with no disruption of

environmental gradients by a fossil-coral plateau were chosen to investigate the

environmental factors that create the boundary change between terrestrial and marine

wood-degrading organisms (Figure 3.1 b). Eight, 10 m wide belt transects were used

to study the degradation boundary in the Galua forest and three, 30 m wide belt

transects were used to study the degradation boundary for the Laulua forest to

determine the biodegradation processes. In both mangrove forests the transects began

in areas dominated by terrestrial wood-degrading organisms, well above the high

intertidal zones and ended in areas where marine wood-degrading organisms

dominated at the seaward edges. A total of 583 and 332 pieces of LWD were

examined in the Galua and Laulua forests respectively. The volume of LWD items

were calculated for every piece investigated, and all wood-degrading organisms from

the LWD samples were identified. Salinities were measured using a Bellingham and

Stanley E-Line Aquatic hand-held Refractometer. Emersion times for the LWD items

in each transect was calculated using the results obtained from the shore heights

above sea level of from each transect and the local tide tables for Kaledupa.

Identification of marine and terrestrial woody detrital decomposers

Coleopteran larvae, worker and soldier termites, and pallets (the diagnostic

calcareous hard parts of teredinids) were stored in absolute ethanol and identified in

the laboratory. Digital images of all basidiomycete fruiting bodies and termites,

focussing on morphology and colour characteristics were used for identification

76

within the Galua, Laulua and Sombano forests using an Olympus E-510 SLR with a

50mm Macro-lens.

3.3 Data analysis

Mean values of the volumes of LWD between the sites, and at different tidal

heights were tested for statistical significance using an ANOVA, with sites and tidal

height as factors. A 1-way ANOVA was used to test for differences between the dry

weights of panels and distance from the strandline. A regression analysis was used

to determine differences between the percentage of the sectional area represented by

teredinid tunnels and the level of fragmentation imposed to each panel in the forests

and reefs. The non-parametric Kruskal-Wallis test was used to test for differences of

wood-decay. All percent data were normalized using Arcsin transformations. A

Tukey’s pairwise comparison test separated values into statistically distinct subsets

in all ANOVAs using MINITAB (MINITAB Inc, version 13.20).

Distance-based linear modeling (DISTLM) was employed to verify

relationships between different wood-degrading organisms and emersion time,

distance from the land (DFL) and salinity. DISTLM produces a sequential test,

which assess the variation each predictor (environmental variable) has on its own,

and a conditional test, which explains the variation of all the variables (McArdle and

Anderson, 2001). The most parsimonious model for predicting the distribution of

biodegrading organisms affected by emersion time, distance from the land, and

salinity was identified using the Akaike information criterion (AIC). AIC ranks

models from all possible combinations of the environmental variables. Distance-

based redundancy analyses (dbRDA) were used for visualizing the results as an

ordination, constrained to linear combinations of the predictor variables. The

DISTLM was based on presence/absence data with 4999 permutations and a

77

Sorensons transformation. DISTLM was performed using PRIMER+PERMANOVA

version 6.1.11.

3.4 Results

3.4.1 Wood degradation within the landward, Sombano and seaward, Langira

forests

The levels of decay estimated from 168 LWD samples within the Sombano

forest (Figure 3. 2 a) had the greatest percentage of the highest categories of

degradation - levels 4 and 5, and the lowest percentage of non-degraded LWD - level

zero. A decline in degradation at 400-500 metres was determined by the reduced

percentage frequency of the level 5 categories and increases of non-decayed level

zero LWD. Furthermore, in the Langira forest beyond the fossil-coral plateau at 700

metres from the landward edge, the decay levels of the LWD were very low,

evidenced by the high percentage of the level zero ratings combined with no level 5

ratings. The level of degradation is significantly lower with further distances from

the land (Kruskal-Wallis test, degradation rating vs. distance from land, P = < 0.001).

3.4.2 Sombano, Langira & Kal 1 panel analysis – wood loss

The percentage dry-weight loss of wood from the panels within the Sombano

and Langira forests and the Kal 1 reef site showed significant differences with

increasing distance from land (Figure 3.2 b). More wood was lost with increasing

distances from the land. No weight losses were detected from panels exposed within

Sombano. With increasing distance from the strandline and decreasing emersion

time, panels lost > 50 % of their weight.

78

3.4.3 The biodegrading organisms found on LWD

The basidiomycetes

Basidiomycetes were found only in the Sombano and Galua forests (Table

3.2). Both forests had distinct basidiomycete mycoflora, with the exception only of

Ganoderma sp. and Pycnoporus sanguineus, which were found in both forests

(Figure 3.3). The basidiomycetes mycoflora consisted of eight families and 13

species. Auricularia cornea, Favolus spp., Oudimansiella canari, Panaelus spp. and

Schizophyllum commune were found only in Galua even though their host substrata,

fallen Xylocarpus granatum trees, were common to both forests. Similarly, Lenzites

acuta were found only in Sombano even though its host, Bruguiera gymnorhiza is

found in both forests.

79

0

10

20

30

40

50

60

70

80

90

100

Fre

qu

ency

of

LW

D d

eca

y c

ate

go

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%)

Level 5

Level 4

Level 3

Level 2

Level 1

Level 0FOSSIL

CORAL

PLATEAU

a a a a a

a bcd

b cd

d

cd d

0

5

10

15

20

25

0

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0 20 100 240 380 500 720 820 940 980 1070 1500E

mer

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(ho

urs

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% D

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eig

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(gra

ms)


Sombano Langira Emersion time (hours)

FOSSIL

CORAL

PLATEAU

Figure 3.2 Wood decay levels and wood loss in areas of the mangrove forests with

different emersion times with increasing distance from the land a, The frequency (%)

of decay levels assigned to the LWD (n = 168) within Sombano and Langira (refer to

Table 3.1); b, The percentage dry-weight loss of wooden panels (mean ± SE, 1-way

ANOVA, distance from land vs. percentage dry weight; F11, 48 = 178.75, p = < 0.001)

exposed for 12 months deployed in different areas of the Sombano and Langira forests

exposed to different emersion times (dashed line).

a

b

80

Common name Family Species Site Substratum

Bracket fungi (basidiomycetes) Auriculariaceae Auricularia cornea Ehrenb.:Fr. G Xg

Entolomataceae Entoloma sp (Fr.) P. Kumm. S Ea

Ganodermataceae Ganoderma sp P. Karst S,G Xg

Panaeoleae Panaeolus sp (Fries) Quel. G Xg

Physalacriaceae Oudimansiella canari (Jungh.) Hohnel G Xg

Polyporaceae Favolus sp P. Beauv. G Xg

Lenzites acuta Berk. S. Bg

Microporus xanthopus P. Beauv S Ea

Pycnoporus sanguineus (L.) Murrill S,G Xg

Trametes elegans (Fr.) Fr. S Ea, Bg

Trametes versicolour (L.:Fr) Pilat G Ct

Schizophyllaceae Schizophyllum commune Fr. G Xg

Stereaceae Stereum ostrea (Blume and T. Nees) Fr. G Bg

Beetle (coleopteran) larvae Cerambycidae

S, G

Elateridae

S

Oedemeridae

S, G, Lau, L

Tenebrionidae

S, G

Termites Kalotermitidae Cryptotermes Ga, Lau In decaying wood

Rhinotermitidae Coptotermes Ga, Lau Arboreal

Prorhinotermes Ga Arboreal

Termitidae Microcerotermes Ga, Lau In decaying wood

Nasutitermes Ga, Lau Arboreal

Limnoriids Limnoriidae Limnoria insulae Menzies, 1957 L, Lo, O,

L. pfefferi Stebbing, 1904 L, Lo, O,

L. sellifera Cookson et al., 2012 L, Lo, O,

L. unicornis Menzies, 1957 Lo,

Shipworms (teredinids) Teredinidae Bactronothorus thoracites Gould, 1856 La, Ga

Dicyathifer caroli Iredale, 1936 Ga

Lyrodus massa Lamy, 1923 La, On, Lo, Ka

Spathoteredo obtusa Sivickis, 1928 La, On, Ka, Lo

Teredo fulleri Clapp, 1923 La, Lo, On

T. furcifera von Martens, 1894 La, On, Ka, Lo

T. mindanensis Bartsch, 1923 La, Ga, On, Lo, Ka

Table 3.2 The biodegrading organisms recorded from the forests within the Wakatobi

Marine Park (WMP). Wood on which organisms found: Xg = Xylocarpus granatum, Ea =

Excoecaria agallocha, Bg = Bruguiera gymnorhiza and Ct = Ceriops tagal. Sites: G = Galua, S

= Sombano, Lau = Laulua, L = Langira, On = One Onitu, Lo = Loho and Ka = Kaluku.

81

Ganoderma sp. and Pycnoporus sanguineus were recorded from both forests, with

both basidiomycetes degrading fallen Xylocarpus granatum trees. All recorded

basidiomycetes within Sombano and Galua had host-specific substrata.

Schizophyllum commune was ubiquitous in the landward regions in the Galua forest,

on dead Xylocarpus granatum trees only. However, one exception was observed with

Trametes elegans which was found only in the Sombano forest, on Excoecaria

agallocha and Bruguiera gymnorhiza trees.

b a

c d

Figure 3.3 Basidiomycetes fruiting bodies decaying LWD. a, Pycnoporus sanguineus on a

fallen Xylocarpus sp. tree in the Galua forest; b, the fruiting bodies of Microporus xanthopus

on an Excoecaria agallocha snag in Sombano; c, Lenzites acuta decaying a fallen Bruguiera

gymnorhiza tree in Sombano; and d, Trametes elegans on a chopped E. agallocha tree in

Sombano.

82

Coleopteran larvae

Larvae from four coleopteran families were found; Cerambycidae, Elateridae,

Oedemeridae and Tenebrionidae (Figure 3.4 and Table 3.2). The Sombano forest

contains all four coleopteran families. The Galua forest had three coleopteran

families. The Langira and Laulua forests had one coleopteran family, the

Oedemeridae. In addition, the Oedemeridae were found within all sites except

Sombano.

Within Sombano, many Excoecaria agallocha trees had 3 – 4 cm diameter

circular blisters created by Aeolesthes holosericeus belonging to the family

Cerambycidae. A. holosericeus caused damage within many live and dead E.

agallocha trees in the Sombano forest.

Figure 3.4 Dorsal views of coleopteran larvae removed from LWD. a, a beetle larva

in the family Cerambycidae from the Galua forest; b, an Elatrid larva from Sombano; c,

a beetle larva in the family Oedemeridae from the Laulua forest; and d, a beetle larva

from to the family Tenebrionidae from the Sombano forest.

a

d c

b

83

Termites

There were three termite families consisting of five genera in the Galua and

Laulua forests (Figure 3.5 and Table 3. 2). Of the five genera, Cryptotermes and

Microcerotermes were found in decaying wood from both Galua and Laulua.

Prorhinotermes, Coptotermes and Nasutitermes were found in arboreal nests above

spring high tide.

Figure 3.5 Dorsal views of soldier termites removed from LWD. a, frequently found

in decaying mangrove wood, Cryptotermes from Galua and Laulua; b, Prorhinotermes

found well above the hightide mark in Galua; c, Microcerotermes found in Galua and

Laulua decaying wood; d, Coptotermes common to Galua and Laulua (dorsal and ventral

view); and e, Nasutitermes found in arboreal nest in the landward/and supratidal areas of

Galua and Laulua.

a

e d

c b

84

Limnoridae

Superficial biodegradation of the LWD identified as small ridges on the wood

surface were created by limnoriid isopods, including a new species identified from

the forests of Derawa - Limnoria sellifera (Cookson et al., 2012). In total, four

limnoriid species were found, Limnoria insulae, L. pfefferi, L. unicornis, and L.

sellifera (Figure 3.6). No limnoriids were recorded from the landward forests,

Sombano and Gili. In addition, L. insulae, L. pfefferi and L. sellifera were found in

the Langira, Loho and One Onitu forest sites (Table 3.2). L. unicornis was found

only in the Loho forest.

Teredinidae

Figure 3.6 SEM images of limnoriid isopods removed from LWD. a, lateral view of L.

unicornis; b, a new described species of limnoriid, L. sellifera with its unusual saddle-

shaped pleotelson exposed; c, the pleotelson of L. insulae; and d, a ventral view of L.

pfefferi.

a

d c

b

85

Five species belonging to the family Teredinidae were found in experimental

panels (Figure 3.7): Teredo furcifera, T. fulleri, T. mindanensis, Lyrodus massa and

Spathoteredo obtusa. Teredinids were recorded from all forest sites except Sombano

(Table 3.2). Bactronophorus thoracites and Dicyathifer manni were only found in

LWD.

Figure 3.7 Teredinid pallets - diagnostic features of teredinids - removed from panels in the

mangrove forests of the WMP. Pallets belonging to a, Teredo mindanesis; b, Lyrodus massa; c, T.

fulleri; d, T. furcifera; and e, Spathoteredo obtusa.

a b

e

d c

86

Polypore fungi, lignocellulose-degrading basidiomycetes are ubiquitous in

Sombano. All basidiomycetes were found on decaying fallen logs above the high tide

water mark. Other organisms including termites, Cryptotermes and Nasutitermes are

also common within Sombano, with extensive termite galleries frequently found

inside the LWD. Coleopteran larvae are also very common within decaying wood in

Sombano.

Beyond the fossil-coral plateau that separates Sombano from Langira, in the

seaward region of the forest distinct changes of the biodegradation of LWD were

found. These changes were evident by the rapid reduction of saprophytic decay with

increasing distance from the landward edge. The terrestrial biodegrading organisms;

basidiomycetes, termites and coleopteran larvae are not the main decomposers of

wood in the mid- to low- areas of the forests.

The Galua and Laulua forests contained the same wood-degrading organisms

found in LWD from Sombano and Langira. The coleopteran and termite

communities in the Laulua forest had similar distributions of those recorded from

Galua. Neither coleopteran larvae nor termites were found beyond 170 metres from

the land in the Galua forest. Combinations of termites and coleopteran larvae,

termites and basidiomycetes, and coleopteran larvae and basidiomycetes were found

together processing twenty-two items of fallen wood in the high intertidal of Galua.

One item of LWD in the Laulua forest contained termites and coleopteran larvae in

the high intertidal. Furthermore, only two items of LWD from the Galua and Laulua

forests contained teredinids and coleopteran larvae together in the low intertidal. All

other wood-biodegrading organisms identified from the LWD in Galua and Laulua

forests were found exclusively on their own.

87

3.4.4 The volume of LWD in mangrove forests

The total volumes of LWD varied between the sites (ANOVA, F3, 66 = 18.31,

p = < 0.001). Sombano had the greatest volume of LWD, when compared to the

Langira, Galua and Laulua forests (Figure 3.8). The volume of LWD also varied at

different tidal heights between the sites (ANOVA, F3, 66 = 9.58, p = < 0.001). The

volume of LWD pieces from Sombano was 0.16 ± 0.025 m3

and the largest log

recorded was 9.6 m3. The volume of LWD pieces from Langira was 0.03 ± 0.004 m

3

and the largest log was 0.4 m3. The height above sea level recorded for Sombano was

2 ± 0.11 metres above sea level and the mean height above sea level recorded for

Langira was 1 ± 0.35 metres above sea level. In the Galua forest, the total volume of

dead wood was significantly greater at the strandline, more than 2m above sea level,

when compared to areas further out to the seaward edge, which are between 1.99 -

1.90 and less than 1.90m above sea level. The largest log located in Galua at more

than 2.0 metres above sea level was 1.83 m3. The largest logs at 1.99 – 1.90 and less

than 1.90 metres above sea level were 0.48 m3

and 0.32 m3

respectively. The volume

of dead wood for the Laulua forest was lower than that in the Galua forest. The

largest log located at Laulua was also found at more than 2.0 metres above sea level

was 0.5 m3, and 0.08 m

3 and 0.05 m

3 at 1.99 – 1.90 and less than 1.90 metres above

sea level respectively.

88

0

20

40

60

80

100

120

140

> 2 1.99-1.9 < 1.9

LW

D (

m3 h

a-1

)

Sombano

a ab

b

0

2

4

6

8

10

> 2 1.99 - 1.9 < 1.9

LW

D (

m3 h

a-1

)

Langira

a

b b

0

5

10

15

20

25

30

> 2 1.99 - 1.9 < 1.9

LW

D (

m3 h

a-1

)

Galua

a

ab

b

0

0.2

0.4

0.6

0.8

1

1.2

1.4

> 2 1.99 - 1.9 < 1.9

LW

D (

m3

ha

-1)

Height above sea level

Laulua

Figure 3.8 The volume of LWD (m3

ha-1

) found in areas of different tidal heights in

different mangrove forests. The volume of decaying wood recorded from: a, Sombano;

b, Langira; c, Galua; and d, the Laulua mangrove forest (mean ± SE). Letters above the

bars = Tukeys Pairwise comparisons. Note: y-axes are different scales.

a

b

c

d

89

3.4.5 Wood-degrading organism distribution and environmental variables –

emersion, distance from the land and salinity

In Galua, basidiomycetes had the greatest emersion time (Figure 3.9 a, 1-way

ANOVA, emersion time vs. Galua biodegradation processes; F3, 442 = 318.52, p = <

0.001). The termites and coleopteran larvae had no difference of emersion time,

although both animals had a lower recorded emersion time than basidiomycetes. The

Teredinidae had the lowest emersion time compared with the emersion times of all

the terrestrial wood-degrading organisms recorded in this study.

Similar observations were found from Laulua (Figure 3.9 b 1-way ANOVA,

emersion time vs. Laulua biodegradation processes; F2, 103 = 211.77, p = < 0.001).

The differences of the emersion times calculated for each of the biodegradation

processes, clearly demonstrate that the Teredinidae had the least emersion time

compared with the terrestrial wood-degrading organisms.

Differences of salinity levels from the strandline out to the seaward edge

were found in Laulua. The soil salinity levels recorded in areas where the

coleopteran larvae, termites and the Teredinidae dominated were 42.4 ± 1.0, 44.2 ±

1.1 and 33.4 ± 0.2 respectively (1-way ANOVA: F2, 103 = 103.15, p = < 0.001). The

mean distances from land for the coleopteran larvae, termites and the Teredinidae

were 59.14 ± 9.07, 59.48 ± 10.43 and 201.37 ± 2.12 metres respectively (1-way

ANOVA: F2, 103 = 207.91, p < 0.001).

90

In all areas of each forest where terrestrial wood-degradation occurred the

heights above mean sea level were higher than in areas of the forest exposed to

marine biodegradation only - refer to map (Figure 3.1 b, 1-way ANOVA, height

above sea level vs. intertidal zone, F5,644 = 236.84, p = < 0.001).

As emersion time decreases, the biodegrading organisms processing LWD

change from terrestrial to marine organisms (Figure 3. 10 a and b).

a

b b

c

0

5

10

15

20

25

Basidiomycetes Coleopteran

larvae

Termites Teredinids

Mea

n e

mer

sio

n (

h)

Galua

a a

b

0

5

10

15

20

25

Basidiomycetes Coleopteran

larvae

Termites Teredinids

Mea

n e

mer

sio

n (

h)

Wood-degrading organism

Laulua

Absent

in forest

a

b

Figure 3.9 Emersion times (hours) of wood-degrading organisms removed from

LWD. a, wood-degrading organisms from Galua; and b, Laulua (mean ± SE).

a

91

The environmental variables influencing the dbRDA ordination axes (Figure

3.11) showed that the distance from the land and emersion time are best correlated

with axis 1 for both Galua (Figure 3.11 a), and Laulua (Figure 3.11 b). In the Galua

forest, 93.4 % of the environmental data explains 42.2 % of the total variation. In the

Laulua forest, 97.2 % of the environmental data explains 52.9 % of the total

variation. In the Galua forest, axis 2 of the dbRDA ordination revealed that 5.2 % of

the environmental data explains 2.3% of the total variation. In the Laulua forest, axis

2 of the dbRDA ordination revealed that 2.8% of the environmental data explains

1.5% of the total variation. For both forests, distance from shore increases, and

emersion time decreases for the Teredinidae.

0

20

40

60

80

100

0510152025

Item

s o

f L

WD

Emersion (h)

Basidiomycetes Coleopteran larvae Termites Teredinids

0

5

10

15

20

25

30

0510152025

Item

s o

f L

WD

Emersion (h)

Coleopteran larvae Termites Teredinids

Figure 3.10 The biodegrading organisms found at different tidal heights within

mangrove forests upon LWD. a, The Galua; and b, Laulua mangrove forests. Different

symbols signify different wood-biodegrading organisms.

a

b

92

Figure 3.11 dbRDA ordinations. a, in the Galua forest the vectors of presence/absence of wood-degrading

organisms in LWD with bubble-plots showing environmental variables that have the strongest influence on the wood-

degrading organisms. The dbRDA axes explain the percentage variation of the most parsimonious fit; and b, in the

Laulua forest. Inset boxes - show each environmental variable: DFL = distance from land (m), and emersion time (h).

a

b

93

A conditional test for Laulua revealed that DFL explains 97.2 % of the total

variation, followed by emersion with 2.8 %. In the DISTLM test, for Laulua the

sequential test revealed that the wood-degrading organisms in LWD were correlated

with distance from land (DFL), emersion time and salinity (Table 3.3). The most

parsimonious model (AIC = 629.35, R-Sq = 0.54) for the wood-degrading organisms

explains 54% of the variation, with DFL explaining 50% followed emersion

explaining 2 %, and then salinity explaining 2%.

A conditional test for Galua revealed that emersion explains 93.4 % of the

total variation, followed by DFL and salinity with 5.2 % and 1.4 % respectively. For

Galua the sequential test revealed that the wood-degrading organisms in LWD were

correlated with emersion, DFL and salinity (Table 3.3). The most parsimonious

model (AIC = 2731.6, R-Sq = 0.45) for the wood-degrading organisms explains 45%

of the variation, with emersion explaining 39% followed by DFL explaining 5 %,

and then salinity explaining 2 %.

94

Site Predictor

variables AIC SS (trace) Pseudo-F P-value

Proportion Accumulative df

Laulua DFL 634.72 40971 104.73 < 0.001 0.5 0.5 104

Emersion 631.4 1990.6 5.2989 < 0.05 0.02 0.53 103

Salinity 629.35 1451.3 3.9748 < 0.05 0.02 0.54 102

Galua Emersion 2776.4 141960 282.2 < 0.001 0.39 0.39 444

DFL 2742.2 17413 37.454 < 0.001 0.05 0.44 443

Salinity 2731.6 5768.8 12.737 < 0.001 0.02 0.45 442

3.4.6 The change between terrestrial and marine wood-degrading organisms

A distinct change between wood-degrading organisms was found in LWD

from Galua and Laulua. A biodegradation-boundary, determined by the sharp change

between terrestrial and marine wood-degrading organisms in LWD from Galua and

Laulua was recorded within a shore height of 0.07 metres of each other (Figure 3.12).

The change between basidiomycetes, teremites, coleopteran larvae and teredinids in

LWD from Galua and Laulua occurred at 1.89 ± 0.01 (mean ± SE) metres above sea

level and 1.82 ± 0.02 metres above sea level respectively.

Table 3.3 Distance-based linear modelling (DISTLM). Sequential test results relating

wood-degrading organisms (presence/absence transformed with a dummy variable) with

emersion time distance from land (DFL) and salinity in areas where LWD was found in the

Galua and Laulua forests.

95

0

100

200

300

400

500

600

700

800

900

1000

0 50 100 150 200 250 300

Dis

tan

ce f

rom

sh

ore

lin

e (m

)

Distance along strandline (m)

Basidiomycetes Coleopteran larvae Teredinidae

Termites Boundary

0

50

100

150

200

250

0 20 40 60 80 100 120 140 160 180 200

Dis

tan

ce f

rom

sh

ore

lin

e (m

)

Distance along strandline (m)

a

b

Galua

Laulua

Figure 3.12 The distribution of wood-degrading organisms in LWD. a, wood-degrading

organisms identified as different symbols in the Galua; and b, Laulua forests. Dotted line =

boundary between terrestrial and marine wood-degraders. All LWD items with no visible

degradation were not plotted, and the area between 220 – 600 metres in Galua was not sampled.

96

3.4.7 Teredinid panel-fragmentation

Analysis of panel fragmentation demonstrated that with increasing teredinid

attack intensity an increasing percentage of the panel broke-up (Figure 3. 13,

Regression analysis, R-Sq (adj) = 0.41, p = < 0.001). Within mangrove forests and in

reef sites, the percentage of the sectional area represented by tunnels vs. the

fragmentation of panels remaining found that teredinid activity and panel

fragmentation increased in the reef sites compared with panels exposed in the forests.

Across the longitudinal section of each panel from the mangrove sites, the percentage

of the sectional area represented by teredinid tunnels was 35.1 ± 4.3 % (mean ± SE, n

= 30) and the percentage surface area of mangrove panel-loss (fragmentation) was

1.8 ± 0.6 %. Within the reef sites across the longitudinal section of each panel, the

percentage of the sectional area represented by teredinid tunnels was 92.4 ± 1.4 %

(mean ± SE, n = 30), and the percentage surface area of the reef panel-loss was 29.1

± 4.3 %.

0

10

20

30

40

50

60

70

80

0 20 40 60 80 100

% o

f to

tal

pan

el l

oss

% of total area represented by teredinid tunnels

Intertidal Subtidal

Figure 3.13 Wood loss through teredinid activity within panels in mangrove forests and coral

reefs. The percentage of total panel loss estimated from panels exposed to different levels of teredinid

attack within intertidal (grey dots) and subtidal (black dots) environments (regression analysis,

teredinid attack intensity vs. panel fragmentation; F1,58 = 41.32, p = < 0.001).

97

The mangrove forests in the Tukang Besi Archipelago have a wide range of

LWD volume, comparable with other mangrove forests from different countries

(Table 3.4). The Sombano forest had an LWD volume similar to the upper ranges of

LWD volume reported from Micronesia (Allen et al., 2000) and Florida mangrove

forests hit by hurricanes (Krauss et al., 2005).

Country Mangrove LWD volume (m3 ha

-1) Reference

Micronesia

Yap 35.1 Allen et al., 2000

Pohnpei 43.1

Kosrae 104.2

USA

Taylor River 12.6 Krauss et al., 2005

Johnson Mound

Creek

56

Everglades 147.9

Malaysia

160 Chan, 1982

Indonesia

Laulua 0.8 This study

Langira 4.6

Galua 8.1

Sombano 102.9

3.5 Discussion

The volume of LWD estimated from the Galua and Langira forests are

similar to the small forests found in Florida. However, in the Laulua forest the

volume of LWD was very low. This is not surprising as this mangrove forest had

been heavily harvested. In addition, the volume of living biomass reported in chapter

two reflect the volume of LWD produced from those same forests. The carbon

Table 3.4 Volume estimates of LWD (metre cubed per hectare) from different

mangrove forests. LWD volume data reported from mangrove forests outside of

Indonesia were obtained from other studies.

98

contained within the LWD is important, as carbon is retained within the sediments

(Donato et al., 2011), and the mineralization of LWD items provide energy for many

different trophic pathways when degraded (Benner and Hodson, 1985; Robertson and

Daniel, 1989a).

In a study of mangrove wood degradation in the Caribbean the mineralization

rate of mangrove wood was found to be ten times slower when compared to the rates

of leaf litter (Benner and Hodson, 1985). When in anaerobic sediments, the rate of

wood mineralization is thirty times lower compared with aerobic mineralization rates

(Benner and Hodson, 1985). This means that LWD will remain in anaerobic

sediments for a long time, which may explain the very large volume of LWD in the

Sombano forest – as the sediment in Sombano is anoxic.

The environmental factor that determines differences of dead wood volumes

between Sombano and Langira is emersion time. In a two year study from a tropical

Australian mangrove forest more than fifty percent of the mass of LWD was lost in

the mid- and low- intertidal regions of the forest (Robertson, 1990). However, only

five percent of the woody mass had been lost in the high intertidal zone (Robertson,

1990). The large loss of LWD was attributed to the wood-boring activity of the

Teredinidae. This study demonstrates that tidal inundation is the environmental

factor contributing to the differences of woody-mass from the panels – as the

distribution of wood-degrading organisms within mangrove ecosystems are affected

by immersion (Kohlmeyer et al., 1995). Other authors have reported upon the

influence of tidal inundation as a driving factor for wood-dependent mangrove

animals. A study of mangrove forests in East Africa determined that numbers of

wood-boring isopods increase with decreasing emersion times (Svavarsson et al.,

2002). Furthermore, in Caribbean (Kohlmeyer et al., 1995), and Australian mangrove

99

forests (Robertson and Daniel, 1989a; Robertson, 1990) teredinids also increase with

decreasing emersion times.

In Sombano, the decay of mangrove wood was very slow – no loss of wood

was found from the panels even after one year exposure. The slow degradation of

LWD may be due to the anoxic substrata and the kinds wood-degrading organisms

found within LWD in that forest. It is known that wood decay in anaerobic

environments is very slow (Benner and Hodson, 1985). However, woody debris in

Langira may be exported by tidal water flow, meaning that the usual wood

degradation processes may not have time to initiate the lignocellulose breakdown

before the physical processes such as tidal flow exports wood from the forest. Tidal

inundation is particularly important in the mid- to low-intertidal areas of mangrove

forests, as tidal flow will frequently export much of the woody debris (Boto and

Bunt, 1982; Robertson and Daniel, 1989a). Differences of degradation processes

magnify the importance of nutrient recycling in mangrove ecosystems (Lang and

Knight, 1979), as wood degrades at different rates from the high to low intertidal

regions of mangrove forests (Sherman et al., 2003) - due to differences of wood-

degrading organisms from the high to low intertidal regions (Kohlmeyer et al.,

1995).

Wood decay is accelerated further inland when compared to wood decay in

the seaward zones (Sherman et al., 2003). Wood-degradation is dependent on habitat

characteristics such as decomposer communities, tidal energies, site fertility and

ambient temperatures (Davis et al., 2003). In the Sombano forest, the biodegradation

processes that break down LWD are conducted by organisms that are also frequently

found in terrestrial forests such as beetles (Novotny et al., 2006), termites (Jones and

Eggleton, 2000) and basidiomycete fungi (Tedersoo et al., 2003).

100

However, in the Langira forest the wood-degrading organisms were different.

Unlike the Sombano, in the high-intertidal, the Langira forest extends down to mean

sea-level. Waterlogged LWD will be inhibited from saprophytic decay by obstructing

fungal growth due to the limited availability of oxygen, therefore decreasing

respiration rates - further explaining the lack of basidiomycetes in areas of the forest

with reduced emersion times (Progar et al., 2000).

In the landward regions of the Galua forest, as in Sombano basidiomycetes

were found upon many items of LWD, and this wood was very soft due to the high

level of decay. Wood-decaying fungi are essential for the functioning of forest

ecosystems (Lonsdale et al., 2008; Ananda and Sridhar, 2004), as they control the

primary breakdown of wood. This means that basidiomycetes are particularly

important in the high-intertidal regions of Galua and in the Sombano forest as there

was a large volume of LWD. Of the known 900 marine fungi, 358 have been

recorded from mangrove ecosystems (Maria and Sridhar, 2002; Maria and Sridhar,

2003). However, both terrestrial and marine fungi are involved in the decomposition

of litter in mangrove ecosystems (Ananda and Sridhar, 2004). Marine fungi are able

to tolerate salinity, anoxic sediments and tidal inundation (Kohlmeyer et al., 1995;

Gilbert and Sousa, 2002). Salt-tolerant fungi are found on a variety of substrata such

as LWD, macroalgae, seagrasses and even deep sea sediments (Ravikumar et al.,

2009). Terrestrial fungi within mangrove ecosystems are often ignored as transient

mycoflora (Maria and Sridhar, 2003; Ananda and Sridhar, 2004), even though they

contribute to substantial woody degradation due to their lignin-modifying enzymes

(Nilsson, 1973).

Differences of the mangrove mycoflora were found between the mangrove

forests. A variety of fungi develop within an assortment of different ecological

101

niches in mangrove ecosystems such as recurrently submerged decaying wood,

exposed decaying wood and damaged mangrove roots (Sarma and Vittal, 2001;

Ananda and Sridhar, 2004). These differences may have also been determined by the

distribution of the host substratum within each mangrove forest, combined with

prolonged exposure of woody debris to direct sunlight, heat and strong winds -

resulting in desiccation (Prasannarai and Sridhar, 2003). No basidiomycete species

were recorded upon the LWD in the Laulua forest. This forest has been exposed to

extensive harvesting pressures, leading to large open areas exposing the sediments

and LWD making the impacted areas arid and dry.

In Caribbean mangrove forests, which have low mangrove tree diversity, the

mycoflora have been shown to be host-specific (Gilbert and Sousa, 2002). Decaying

mangrove wood colonised by particular fungi often show preference for a specific

substratum (Sarma and Vittal, 2001). Thus, if the host is site-specific, then the fungi

processing that woody substratum will have a restricted distribution (Ananda and

Sridhar, 2004). This was evident with the mycoflora in Sombano and Galua as these

forests contained tree species specific to each site which had distinct basidiomycete

species found only on that particular tree.

Environmental factors will also determine the distributions of the

basidiomycetes, such as freshwater input (Ananda and Sridhar, 2004; Vittal and

Sarma, 2006) and height above sea-level (Ejechi, 2002). Salinity and emersion times

were found to be correlated with the distribution of the mycoflora in the Sombano

and Galua forests. The basidiomycete fruiting bodies were always found above the

high tide mark on LWD in Sombano and Galua, in regions of low salinities and high

freshwater input from rainwater. Thus, the dominance of terrestrial fungi upon

mangrove LWD may be dependent on the position of the LWD in the intertidal

102

region (Ejecti, 2002), and the duration and intensity of rain storms (Ananda and

Sridhar, 2004).

In the Sombano and Galua strandline, environmental conditions for

basidiomycete communities were favourable, with reduced salinities and prolonged

emersion times. A change in salinity and emersion will alter the distributions of the

basidiomycetes (Castillo and Demoulin, 1997; Ejechi, 2002). Factors influencing

rates of saprophytic decay directly control nutrient regeneration and indirectly affect

the rates of secondary production by animals in mangrove ecosystems (Benner and

Hodson, 1985). Thus, the flux of carbon and energy from ligninolytic activity to the

animal consumers is the foundation of an intricate and essential trophic food-web

(Babu et al., 2010). The pathways of wood breakdown were different in the Langira

forest. The reduced levels of wood degradation recorded from Langira may have

been attributed to the lack of white-rot and brown-rot decay. The basidiomycetes

were not found on LWD in the Langira forest, meaning that the breakdown of lignin

due to ligninolytic activity did not occur within LWD from Langira. The level of

wood degradation was less and the breakdown of LWD in Langira was caused by the

wood-boring activity of the Teredinidae.

The basidiomycete distributions in Galua were determined by the distance

from land and salinity. The basidiomycetes were found only at the strandline with

hightide salinities not above 16 PSU. In all cases, the basidiomycete fruiting bodies

identified from the Galua forest were found more than 2 metres above sea level,

meaning that the basidiomycete fruiting bodies were not immersed by seawater. The

limited exposure to seawater determines the presence of the basidiomycetes within

the intertidal zone of the Galua forest. This limited exposure explains the presence of

Trametes versicolor in Galua, whose growth is strongly inhibited by seawater (Jones

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and Byrne, 1976 cited in Castillo and Demoulin, 1997). The distributions of

Microporus xanthopus and Pycnoporus sanguineus in coastal forests from Papua

New Guinea were limited by their restricted abilities to cope with high salinity

concentrations (Castillo and Demoulin, 1997), which corroborates this study.

Nonetheless, P. sanguineus had similar distributions to the salt-tolerant

Schizophylum commune, a euryhaline species (Castillo and Demoulin, 1997).

Pycnoporus sanguineus were able to survive in areas of increased salinities due to

the large growth forms of the fruiting body, allowing it to maximize exposure to

periods of high rainfall that may likely limit salt accumulation (Castillo and

Demoulin, 1997).

Mechanical degradation also occurred within the Galua forest. Coleopteran

larvae and the termite communities found within LWD from Galua had very similar

distributions to each other. It is likely that both coleopteran larvae and termites were

not able to tolerate sustained periods of immersion. Coleopteran larvae are

responsible for canopy-gap formations, increased litter-falls and nutrient enrichment

due to their boring within trees (Feller, 2002). Evidence of the mangrove longhorn

beetle, Aeolesthes holosericeus was found in many standing and fallen Excoecaria

agallocha trees in the Sombano forest. The larvae of this beetle create large

characteristic circular blisters – these blisters have also been reported on E.

agallocha trees from mangrove forests in Singapore (Ng and Sivasothi, 1999). False

blister beetle larvae from the family Oedemeridae were very common in LWD from

Langira, Galua and Laulua in the high- to mid- intertidal regions of the forests. These

larvae are commonly found world-wide in marine drift wood and pilings (Arnett,

1951). Furthermore, oedermerids are able to resist tidal immersion (Arnett, 1951),

which explains their wide distribution in the intertidal regions of the forests.

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Termites were also found in LWD and in arboreal nests in the Sombano,

Galua and Laulua forests. Arboreal termites live in well-defined nests that are

separated from their foraging grounds (Korb, 2008). Tree-dwelling termites are

considered to be long distance foragers (Roisin et al., 2006), as they are able to travel

in relative safety because their runways are covered (Merritt and Starr, 2010).

Furthermore, when on the forest floor foraging for food during low tide, the arboreal

termite genera in the Galua and Laulua forests, Prorhinotermes, Coptotermes and

Nasutitermes are able to escape the incoming tide by retreating back up the trees to

their nests. However, wood-dwelling termites live within the galleries they create in

LWD from their feeding activities (Adams et al., 2007). Wood-dwelling termites,

Cryptotermes were found frequently within decaying wood in the landward zones of

the Galua and Laulua forests. Cryptotermes colonies remain within a single item of

decaying wood, which serves as both food and shelter (Korb and Lenz, 2004).

Termites within decaying wood, such as the drywood genus Cryptotermes, have

worker termites that are totipotent (Korb, 2008). Remaining within LWD will have

benefits if members of the termite colony are able explore all caste options (Korb,

2008) such as; predator and risk avoidance due to no external foraging. Cryptotermes

are also able to detect substrate-borne vibrations and these termites are able to

determine the size of their detrital food item (Adams et al., 2007; Evans et al., 2007).

Thus, vibration detection may help these termites to avoid potential immersion by

escaping areas within their galleries that may be submerged before the incoming tide

reaches them as the termite galleries in many LWD items extended from below to

above the high tide mark. The well-developed nests also provide environmental

buffering from outside unsuitable temperatures (Korb, 2008).

Other wood-degrading organisms were found in LWD in the low- to mid-

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intertidal areas of the mangrove forests, and those organisms - such as limnoriid

isopods and teredinids, are predominantly aquatic. However, these crustaceans are

not usually found in forests with freshwater input such as those forests in this study,

and are more common within Caribbean mangrove forests (Cragg, 2007). Analysis of

LWD from the Loho forest revealed a new limnoriid species, Limnoria sellifera

(Cookson et al., 2012). Further research of wood-dependent animals in the mangrove

forests of the Tukang Besi may produce other new species.

Life history strategies between teredinid species vary between those with

non-brooded and brooded larvae. Species belonging to the genera Lyrodus and

Teredo retain their larvae to the late veliger stage. After spawning, larvae from

larviparous species can be widely distributed, even though they have a short free-

swimming period (Turner, 1966). Short and long term brooded species have a

successful recruitment rate and are more likely to become world-wide in distribution

within their limits of temperature and salinity (Brearley et al., 2003). Other studies

also demonstrated that Lyrodus and Teredo have a greater abundance in LWD than

non-brooded species (MacIntosh et al., 2012). The Lyrodus and Teredo larvae are

protected during their early critical stages within the parent. Studies from Aqaba

demonstrated that T. bartschi retain their larvae in the gills. Larval release at the non-

feeding pediveliger limits larval dispersal (Cragg et al., 2009). The advanced

development of T. bartschi larvae means that they are able to settle and colonise

wood more rapidly compared to less developed larvae. Thus, brooded young have

advanced development when released, and are therefore less sensitive to

environmental variables (Turner, 1966). In contrast, Spathoteredo obtusa produce

non-brooded planktotrophic larvae. When compared to settlement rates with brooded

species, S. obtusa were less successful, as very few S. obtusa pallets were found.

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Although planktotrophic development would appear to deliver the greatest dispersal

range, oviparous teredinids are not more widely distributed compared to brooded

teredinids (Cragg et al., 2009). The teredinids, Bactronophorus thoracites and

Dicyathifer manni were found only in LWD. Other authors also reported that these

teredinids were found only in LWD and not in experimental panels (Rayner, 1983).

B. thoracites and D. manni may preferentially settle on wood with high levels of

tannins even though toxic extractives have also found to be fatal for other wood

digesting animals, Limnoria isopods (Borges et al., 2008).

Adult teredinids are sessile, and have isolated breeding populations

maintained by fragmented areas of LWD. The availability of LWD to teredinids in

mangrove ecosystems is stochastic, meaning that LWD items can be few and far

between in some areas and dense in other areas (Duke et al. 1981).

Teredinid densities in mangrove ecosystems are higher with decreasing

emersion times - due to an increased exposure to seawater (Rimmer et al., 1983;

Leonel et al., 2006). The Teredinidae are more numerous in the low intertidal,

similar to the distributions of sphaeromatid populations recorded from mangrove

forests in East Africa (Svavarsson et al., 2002). In areas of the Langira forest with

higher emersion times above nineteen hours, no loss of wood was recorded from the

panels. However, in areas with lower emersion times the dry-weight lost from the

panels was due to the activities of the Teredinidae. Larval teredinids were not able to

reach the high-intertidal areas of the forest – as evidenced by the lack of attack but

larvae might reach but not survive. Thus, the distributions of LWD from the high- to

the low- intertidal areas within mangrove ecosystems will have a large influence

upon the amount of wood-degradation and mechanical recycling - due to the inability

of the teredinids to extend up into the high-intertidal and the inability of terrestrial

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wood-degrading organisms to extend down into the low-intertidal. These differences

are attributed by the position of the LWD within the intertidal region of the forest;

therefore the sharp change of wood-loss between terrestrial and marine

biodegradation processes upon LWD, are controlled by tidal inundation.

The differences of dry-weight losses observed between the panels mirrored

the estimates of the LWD volumes recorded from Sombano and Langira. Losses of

wood were greater with increasing distance from the land. Within the low intertidal

zones of the forests, items of LWD were smaller and more fragmented than the LWD

within the high intertidal. Furthermore, the higher degree of panel fragmentation

recorded from the sub-tidal panels may have also been due to high wave energy input

upon the reefs. Indeed, the tunneling activity of the Teredinidae will reduce the

structural integrity of fallen wood. Thus, coupled with high wave-energies the

fragmentation process may be enhanced

Sharp differences of degradation processes were found between the terrestrial

and marine wood-degrading organisms in Sombano and Langira. A fossil-coral

plateau separates the Sombano and Langira forests. Thus it was not possible to

examine the environmental gradients that create the sharp differences between

terrestrial and marine wood-degrading organisms. It could be argued that the fossil-

coral plateau created the change. However, in the Galua and Laulua forests the same

terrestrial and marine wood-degrading organisms were found; Galua and Laulua are

not separated by a fossil-coral plateau, providing ideal environments to determine the

likely factors that facilitate the changes in wood-degrading organisms. Similar

distributions of wood-degradation processes between fungi and teredinds were also

reported from mangrove forests in Belize (Kohlmeyer et al., 1995). Teredinids and

fungi work in parallel – with fungi decaying wood in the high intertidal and

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teredinids processing wood in the low- intertidal regions (Kohlmeyer et al., 1995).

Each wood-degrading organism has a specific niche, although terrestrial and

marine organisms are occasionally found processing the same LWD item. However,

the niches occupied by these organisms are controlled by tidal inundation within the

intertidal mangrove forests of the WMP.

The basidiomycetes, coleopteran larvae, termites and the Teredinidae are the

essential catalysts for the breakdown of LWD from the high- to low- intertidal

regions. Those processes contribute to the release and flux of organic carbon in

mangrove habitats and maintain a complex trophic web (Benner and Hodson, 1985;

Bouillon et al., 2008; Kristensen et al., 2008). This may mean that wood-degrading

processes spanning different tidal heights within mangrove forests may be affected

by global warming, given that the change between the terrestrial and marine wood-

degrading organisms can be seen over one – two metres on the forest floor.

Rising sea-levels and increasing atmospheric CO2 leading to decreasing pH

concentrations (Guinotte and Fabry, 2008; Ries et al., 2009) may alter the

distributions of wood-degrading organisms as emersion and salinity influence their

distribution. This may have consequences for mangrove forests that will not permit

landward accretion, as mangrove-tree distribution and mangrove-tree zonation are

sensitive to different salinities, site fertility (Tomascik et al., 1997), and tolerance to

water-logging (Pi et al., 2009) . Furthermore, the effect of decreasing pH may have a

marked effect upon the success of teredinid larval settlement. The bivalves Mytilus

edulis and Crassostrea gigas both exhibit declines of calcification with increasing

pCO2 levels of 25 and 10% respectively (Gazeau et al., 2007) – the same effect may

impact the development of teredinid larvae. Decalcification of teredinid shells may

impede their ability to tunnel in to LWD, therefore reducing the amount of wood-

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degradation in the mid- to low- intertidal regions of mangrove forests.

The terrestrial processes – basidiomycetes, termites, and coleopteran larvae

are the major catalysts to the very slow turnover of LWD in the high intertidal zone.

The biodegradation of LWD attributed by these organisms is much slower when

compared with the marine wood-degraders, teredinids.

Teredinids have a remarkable ability to breakdown woody detritus, therefore

influencing the flux of carbon within intertidal mangrove forests. If teredinids were

not found in the mid- to low- intertidal areas of mangrove forests there would be a

massive build-up of detritus, leading to a reduced flow of nutrients to adjacent

coastal ecosystems. The predominant breakdown of LWD attributed by the

Teredinidae has revealed their crucial ecological niche.

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Chapter 4

THE EFFECT OF TEREDINID TUNNELLING ON MANGROVE

PROP-ROOTS

4.1 Introduction

Herbivorous animals from terrestrial to aquatic environments consume a

range of photosynthetic organisms from algae to trees. In terrestrial tropical forests,

insects such as caterpillars and beetles consume much of the foliage and trunks of the

trees (Novotny et al., 2007). Some trees are protected from herbivorous attack as

they have an active anti-herbivore defence provided by ants that predate the attacking

herbivores (Gaume and McKey, 1997), and other trees have chemical and structural

anti-herbivore defence mechanisms (Turner, 1976; Brooks and Bell, 2002). Within

forested intertidal habitats, mangrove trees are attacked by both terrestrial and marine

animals (Feller, 2002; Ellison and Farnsworth, 1996). The mangrove herbivores

range from insects such as beetles (Perry, 1988; Feller and Mathis, 1997) to wood-

boring aquatic molluscs, teredinids (Robertson and Daniel, 1989a). Mangroves also

have non-herbivorous aquatic wood-boring isopods such as sphaeromatids (Si et al.,

2002).

Damage to prop-roots may either be caused by herbivorous and non-

herbivorous attack or physical actions such as abrasion (Gill and Tomlinson, 1977),

or by falling branches from the canopy. Increased tidal inundation may also enhance

the breakdown of damaged mangrove root tissues – as densities of wood borers

become more numerous with increasing immersion times (Svavarsson et al., 2002).

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Isopods process less wood, when compared with teredinids. Sphaeromatids

bore large conspicuous holes in live prop-roots (Simberloff et al., 1978). Teredinids

on the other hand, predominantly process dead wood and create many tunnels within

the logs through their boring activity (Filho et al., 2008).

Studies of wood-boring animals upon mangrove root tissues are primarily

focussed upon sphaeromatid isopods (Perry, 1988). The destructive effect of the

sphaeromatid, S. peruvianum on live mangrove root-tissues in Costa Rica can reduce

the growth rates of Rhizophora aerial prop-roots by fifty percent (Perry, 1988). The

decrease in root growth rate is caused by sphaeromatids damaging root tips – where

somatic growth of the root occurs (Gill and Tomlinson, 1971). It is thought that

sphaeromatids are unable to burrow in to older developed roots that reach the

substratum due to the development of woody tissue in older roots (Rehm, 1976;

Perry, 1988).

Roots burrowed by the isopods at their tips may branch, (Rehm, 1976; Ribi,

1982) though it is not clear whether this harms the trees. On the one hand, the effect

of the attack of sphaeromatids upon mangrove root tissues may benefit or harm the

trees (Simberloff et al., 1978). The death of roots may lead to tree collapse (Rehm,

1976; Svavarsson et al., 2002). Rehm and Humm (1973) go further and say that the

mangrove forests are shrinking because of the destruction of the prop roots by S.

terebrans in south-western Florida. However, other authors found that sphaeromatids

may benefit mangrove forests (Simberloff et al., 1978). Isopods may enhance tree

survival by triggering an increase branching of lateral aerial roots, therefore securing

the tree from falling due to an increase of root structures (Simberloff et al., 1978;

Ribi, 1982).

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To combat increasing attack from herbivores plants release tannins (Bloch,

1952). Plants are successfully able to survive in environments where herbivores are

common due to their ability to resist or recover from repeated herbivory (Brooks and

Bell, 2002; Hanley et al., 2007). Direct defence mechanisms may reduce herbivory

or prevent herbivory on root tissue from further exacerbating root damage caused by

feeding upon the plant tissues. Post-attack, mangroves may produce chemical

defences such as secondary metabolites such as tannins (Alongi, 1987; Feller, 2002).

It is beneficial for the plant to produce these chemical compounds only when they

are required as herbivore attack is random and variable (Hol et al., 2004). As, the

energy required to produce these chemical defence exudates can be costly (Agrawal

et al., 1999; Karban et al., 1997). Indeed, particular mangrove trees may express

resistance only when it is needed to reduce energetic cost into producing the tannins.

Energy expenditure may eventually lead to a decrease in fitness - in this case,

root death. The loss of fitness may be due to increased energy investments and use

of resources (Agrawal, 1999). Conversely, herbivory may be beneficial (Paige and

Whitham, 1987; Paige, 1992). Herbivory on plants elicits a physiological response

which can create an overcompensation of tissue regrowth (Lennartsson et al., 1998).

Increased plant growth may ultimately achieve greater fitness (Paige and Whitham,

1987).

Though damage by wood-boring isopods upon mangrove roots is widely

reported, there are few reports of teredinids damaging Rhizophora prop-roots

(Roonwal, 1954, see Figure 4.1). Larval teredinds are unable to infest living trees, as

the bark contains high tannin content (Rimmer et al., 1983; Kohlmeyer et al., 1995).

However, the teredinid Bactronophorus thoracites (Gould) is able to penetrate living

woody tissues (Roonwal, 1954), as this species may settle preferentially on wood

113

with a lot of tannins. Other teredinid species are not so successful, larval Lyrodus

pedicellatus died when trying to settle upon Dalbergia retusa, Panamanian rosewood

(Turner, 1976). The dominant heartwood extractive of Dalbergia is obtusaquinone, a

quinone. Quinones are produced by many tropical trees, and they prevent the

production of well-formed shells and pallets of teredinids and therefore hinder

settlement of Lyrodus larvae (Turner, 1976). Toxic extractives have also been found

to be fatal for the wood boring isopod Limnoria (Borges et al., 2008), and chemicals

such as terpenoids, triterpenes and flavonoids - present in the root bark of Bruguiera

gymnorhiza trees (Han et al., 2004) are toxic to other invertebrates (Spurr and

McGregor, 2003).

Tannins are defence mechanisms. Terrestrial plants also express resistance to

herbivory via strategies labelled as tolerance mechanisms (Paige, 1999; Brooks and

Bell, 2002). Tolerance mechanisms are defined as tissue repair and regrowth.

Mangrove plants may likely use the tolerance strategy against damage (Brooks and

Bell, 2002). Tolerance to herbivory or the ability to recover and regrow tissues after

damage is an additional plant strategy, which may have evolved in response to

herbivore attack (Strauss and Agrawal, 1999).

Teredinids contribute to the breakdown of large woody detritus in the mid- to

low-intertidal regions of the mangrove forests (Robertson, 1990). Much of the dead

wood consumed by teredinids is replaced by the many tunnels they create through

their boring of the wood (Robertson, 1990; Distel, 2003; Filho et al., 2008).The

Teredinidae are particularly important in mangrove forests where there are high

levels of detrital woody biomass consisting of fallen trunks, branches and prop-roots

as they mechanically break down the woody biomass (Robertson, 1990; Kohlmeyer

et al., 1995). Although, teredinid attack may occur only after the bark has

114

deteriorated (Kohlmeyer et al., 1995) and the toxic extractives have leached away

(Borges et al., 2008). The colonised decaying wood may take anywhere from two to

fifteen years to completely break down (Robertson and Daniel, 1989a; Kohlmeyer et

al., 1995). Eventually, the broken-down woody fragments, teredinid faeces and

teredinid biomass may be consumed by marine organisms in adjacent ecosystems

(Robertson and Daniel, 1989a; Granek et al., 2009). This means that wood-borers

may benefit mangrove ecosystems by breaking down dead plant material, even

though they do cause damage to living tissues (Barkati and Tirmizi, 1991).

Figure. 4.1, Rhizophora stylosa prop-roots. a, undamaged healthy prop-roots – a typical

view of roots demonstrating no obvious evidence of damage to their epiblema (outer layer),

and b, a compromised root showing extensive damage resulting in root death, not

commonly found. The arrow indicates the opening of an old teredinid tunnel.

115

As long as their epiblema remains intact, mangrove roots are very effective at

keeping wood-borers such as teredinids at bay (Kohlmeyer et al., 1995). However,

soon after the outer layer is damaged and the inner root-tissues are exposed, larval

teredinids can settle on the wood, and begin to process the tissues (Kohlmeyer et al.,

1995).

This study aims to determine the colonisation of teredinids and the

regenerative capabilities of mangrove prop-root tissues under different levels of

damage. This work tested the prediction that Rhizophora roots with a low level of

damage will not be attacked by teredinids after one year and will make a full

recovery, roots with a moderate level of damage will elicit an over-compensatory

level of tissue re-growth, and roots with a severe level of damage will die due to

teredinid attack after one year.

Rhizophora prop roots were experimentally damaged in the forests to

determine which prop-root surfaces are colonisable by teredinids. The protective

layers of the roots were removed to measure the ability of prop-roots to recover and

the extent of infestation by teredinids exposed to different levels of damage. This

investigation reveals how prop-root tissues respond to different levels of damage and

the affect of teredinids upon those damaged areas.


4.2.1 Root scar experiment

The long-term effects of experimental damage to mangrove roots were

examined. The experiments took place in three inter-tidal Rhizophora stylosa-

dominated mangrove forests in the Tukang Besi archipelago, Kaluku, Loho and One

116

Onitu (see chapter 2 for site details). Three ten by ten metre plots within each forest

were designated for the experimental damage. The plots were chosen in these areas

because teredinids were found and no evidence of disturbance was recorded. The

damage consisted of one of three surgical treatments of increasing severity at the

base upon individual roots. Within each plot, each treatment was conducted on three

roots, totalling nine roots per plot, and twenty-seven roots per site. Within all the

sites, a total of eighty-one roots were used.

The first surgical treatment (superficial) consisted of removal of the

outermost layer of the bark, the epiblema (Figure 4.2 a). The second treatment

(moderate) consisted of additionally removing the starch-rich parenchyma cells

(Figure 4.2 b). The third treatment, (severe) consisted of additionally removing the

inner radial and tangential walls of the endodermis containing lignin and suberin-rich

tissues (Figure 4.2 c). All surgical treatments were cut into live Rhizophora roots

using a diver’s knife. Each root-scar measured 4 cm in diameter by 10 cm in length.

Digital images were taken of each treated root over twelve months. All root

circumferences and scar depths were measured before and during the twelve month

period using a tailors tape and callipers.

4.2.2 Root biscuit analysis

Root scars on twenty-four of the experimentally damaged roots were cut

transversely into biscuit sections after twelve months after the damage. For each of

the levels of damage, eight roots were used. For the superficially damaged roots, a

total of forty biscuits were cut, and for the moderately damaged roots, thirty-six

biscuits and for the severely damaged roots a total of thirty-five biscuits were cut.

Each biscuit from the damaged roots was inspected for evidence of necrotic cellular

117

damage and then measured to calculate the area of cellular rehabilitation or loss. If

present, all teredinid tunnels in each biscuit were counted, and percentage surface

area of tunnels within each biscuit were estimated using ImageTool Version 3.00

(The University of Texas Health Science Centre at San Antonio).

Figure. 4.2 Three treatments of root scars characterised by different levels of damage. a, the

removal of the outer epiblema layer, superficial damage, b, removal of the carbohydrate-rich cortex

tissue, moderate damage, exposing the epidermis layer, c, removal of the lignin-rich endodermis layer,

severe damage. Ep = epiblema, Co = cortex, En = endodermis, Ls = longitudinal section and Ts =

transverse section.

superficial moderate severe

Ep Co En

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4.3 Data analysis

Biscuit analysis

Values of percentage surface area of tissue regrowth/loss and the number of

teredinid tunnels within root-biscuits were tested for differences of teredinid tunnels

in roots exposed to different surgeries using Box Plots.

Live roots

Upon the live roots, differences of the percentages of root tissue re-

growth/loss over one year were tested using a 2-way ANOVA with treatment and

time as factors. All percentage data were normalized using the arcsin transformation.

All statistical analyses were performed using MINITAB (MINITAB Inc, version

13.20).

4.4 Results

4.4.1 Root scar analysis upon live roots

Twelve months after the initial surgeries more than 95 % of roots exposed to

the superficial damage had a complete recovery of tissues and total regrowth of the

epiblema. No roots died when exposed to this level of damage. Almost 80% of roots

exposed to a moderate level of damage had a full recovery with 30% of those roots

exceeding the initial size of the root before surgery (Table 4.1). However, 14.8% of

the roots exposed to the moderate level of damage died. More than 60% of the roots

exposed to a severe level of damage made a full recovery with 25% of those roots

exceeding the initial size of the root before surgery. However, 7.4% of the roots

exposed to the severe level of damage died. The greatest percentage regrowth of

root-tissue was recorded from roots exposed to a moderate and severe level of

damage (mean ± SE).

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Exposure after surgery Root Damage

Superficial Intermediate Severe

0 days 95.7 ± 0.5 70.9 ± 0.6 64.8 ± 1.1

12 months 102.4 ± 0.4 90.2 ± 7.6 93.4 ± 5.6

Differences were found with the percentages of root-tissue regrowth after 12

months when compared from the initial surgery between the roots with increasing

levels of damage (2-way ANOVA, Table 4.2).

Factors DF F-value P-value

Treatment 2,156 8.2 < 0.001

Time 1,156 18.8 < 0.001

Treatment*Time 2,156 5.7 < 0.005

Tissue colour changes were observed and timed over 2 hours after each

surgery. The colour changes within the outer cortex layer after removal of the

epiblema occurred within thirty minutes on roots with superficial damage (Figure 4.3

a). These colour changes signify an almost immediate physiological defence-

response by the plants. In comparison to the superficial damaged roots, colour

changes observed from the moderately (Figure 4.3 b) and severely damaged roots

(Figure 4.3 c) were more rapid and conspicuous.

Table 4.1, Tissue regrowth measurements (%) of roots exposed to three levels of damage.

The percentage of root tissue remaining after the initial surgery (0 days) and the percentage of

tissue regrowth of those tissues after 12 months from the three levels of damage.

Figure 4.3 Timed colour changes and wound healing of the release of tannins in prop-roots

exposed to increasing levels of damage. a, roots exposed to superficial, b, moderate and c,

severe levels of damage over 12 months. Continues from page 114 to 116.

Table 4.2, 2-way ANOVA results. Root treatments = A,

B and C, and Time (treatments at zero days and

treatment regrowth after 12 months).

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0 days 15 min 45 min 5 days

10 days 20 days 35 days 12 months

a

121

0 days 65 min 25 min


105 min

b

122

0 days 20 min 35 min 65 min


c

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4.4.2 Root biscuit analysis

Differences were found between roots exposed to increasing levels of

damage with the percentage of tissue rehabilitation or loss (Figure 4.4 a). Roots

exposed to superficial damage had the lowest recorded percentage of tissue regrowth.

The percentage of tissue regrowth for the 40 biscuits from superficially damaged

roots showed no changes with quartiles (Q) 1 and 2. Q3 and Q4 had between 1.5 and

2.4 % of tissue regrowth after 12 months. The percentage of tissue regrowth for the

36 biscuits cut from moderately damaged roots demonstrated that Q1 and Q2 had

between -7 and 5.7 % of tissue loss and regrowth respectively. Q3 and Q4 of the

biscuits from moderately damaged roots had between 13.5 and 21.3 % of tissue

regrowth respectively. Two outliers were found with the biscuits from moderately

damaged roots, with losses of -9.1 and -15.7 % of tissues over one year. The

percentage of tissue regrowth for the 35 biscuits from severely damaged roots

demonstrated that Q1 and Q2 had between -41.1 and -21.8 % of tissue loss

respectively over one year. Q3 and Q4 had between 11.2 and 16.5 % respectively of

tissue recovery over one year.

Differences of teredinid tunnels within the root-biscuits were also found

(Figure 4.4 b). No teredinid tunnels were recorded within the superficially damaged

biscuits. With each quartile of the biscuits from moderately damaged roots, no

teredinid tunnels were recorded. However, two outliers were found with 1 and 2

teredinid tunnels. Biscuits from roots severely damaged were different from both the

biscuits from superficial and moderately damaged roots with Q3 and Q4 having 1

and 2 teredinid tunnels respectively. The analysis of the biscuits from severely

damaged roots revealed three outliers, with 3, 6 and 10 tunnels.

124

Regression for the root biscuit analyses highlighted that with increasing tissue

losses leading to root death, teredinid tunnels also increased (Figure 4.5 a). The

regrowth of tissues for root biscuits not attacked by the Teredinidae was 4.74 ± 1.6 %

Figure. 4.4 Box plot analyses of the roots exposed to increasing levels of damage. a, The variation

of root tissue loss and regrowth estimated from biscuits obtained from roots with superficial, moderate

and severe levels of damage and b, the number of teredinid tunnels within sections exposed to

superficial, moderate and severely damaged roots. The boundaries of the boxes indicate the 25th and

75th percentiles. The line within the box marks the median. Outliers are marked as *.

b

a

125

(mean ± SE) of new tissue after twelve months. The loss of tissues for root biscuits

attacked by the Teredinidae was 10.23 ± 8.6 % (mean ± SE) of root tissue loss over

twelve months. The greatest numbers of teredinid tunnels observed in individual root

biscuits were six and ten tunnels, associated with – 41.15 % and – 27.11 % losses of

tissue over twelve months respectively.

Regression analyses for root-tissue regrowth after 12 months vs. number of

teredinid tunnels for each scar treatment demonstrated that there were no correlations

with the root-biscuit analyses of the superficial and moderately damaged roots.

However, a strong negative correlation was found with decreasing root-tissues and

increasing teredinid tunnels with severely damaged roots (Figure 4.5 b).

4.4.3 Atypical growth of lignified tissues

A lateral out-growth of lignin-like tissue growing from the cylindrical

endodermal layer was found after analysis of the moderate and severely damaged

root-biscuits (Figure 4.6). Three-quarters and one quarter of all moderately and

severely damaged biscuits respectively, had the atypical growth of the cylindrical

lignin-rich endodermal layer.

126

-50

-40

-30

-20

-10

0

10

20

30

0 2 4 6 8 10

Ro

ot

tiss

ue

reg

row

th (

%)

aft

er 1

2 m

on

ths

Number of teredinid tunnels

Without teredinid tunnels With teredinid tunnels

y = 5.5x + 4.8

R2 (adj) = 0.34

-50

-40

-30

-20

-10

0

10

20

30

0 2 4 6 8 10

Ro

ot

tiss

ue

reg

row

th (

%)

aft

er 1

2 m

on

ths

Number of teredinid tunnels

Superficial Intermediate Severe

Figure. 4.5 Regression analyses of root tissue loss and increasing teredinid

tunnels. a, The loss of root tissue exposed to increasing teredinid tunnels (mean ±

SE, R2 (adj) = 0.34, F1, 109 = 57.23, p = < 0.001 ) b, The loss of tissue of biscuits

from the superficial and moderately damaged roots revealed no significant

differences (R2 (adj) = 0.02, F1, 74 = 2.49, p = 0.119). The roots with severe levels of

damage had the greatest level of teredinid attack, coupled with the greatest loss of

tissues (mean ± SE, R2 (adj) = 0.48, F1, 33 = 32.03, p = < 0.001).

a

b

Severe damage

y = 6.35x + 5.81 R

2 (adj) = 0.48

127

4.5 Discussion

The roots with a moderate level of damage, removal of the parenchyma

tissues demonstrated an example of the tolerance mechanism – an over compensation

of tissue regrowth (Brooks and Bell, 2002). Parenchyma cells have the ability to

change; suggesting that post tissue damage will alter the cell physiology and regulate

cell growth (Bloch, 1952). Parenchyma cell differentiation has the ability to change

from parenchyma to cork and sclerenchyma cells (Wier et al., 1996). This study

revealed similar results to those reported by Brooks and Bell (2002), demonstrating

that the tolerance mechanism of the increases of tissue regrowth seen from the

removal of the parenchyma tissues was remarkable recovery. Indeed, this increase of

parenchyma tissue regrowth may be considered as an over-compensatory reaction of

the damaged areas (Paige, 1992; Brooks and Bell, 2002).

a b

Figure. 4.6 Atypical growth of new lignin-rich tissues. a, A biscuit section cut

from a prop-root exposed to a moderate level of damage. The white arrows

highlight the lateral lignin-like out-growths observed from the lignin-rich

cylindrical endodermal layer and b, A biscuit section cut from a prop-root

exposed to superficial damage (for comparison).

128

Less energy investment is required by the plant needed for repair when

exposed to superficial damage, when compared to the energy required by the plant to

compensate for a moderate or severe level of damage, which may be exacerbated by

teredinid tunnelling. Not all roots were tolerant to exposure of tissue removal.

Between fifteen and thirty percent of roots exposed to moderate and severe damage

respectively demonstrated tissue degeneration and death after twelve months. This

may be due to the variation and frequency of teredinid attack coupled with the

severity of damage imposed upon each root.

Almost forty percent of all biscuits from roots with severe damage had a loss

of nearly thirty percent of tissues. The variations of tissue regrowth between

increasing severities of root damage may be due to the degree of tolerance the

damaged mangrove roots were exposed to. The degree of tolerance can be expressed

as compensation to the plants ability to tolerate herbivore attack (Strauss and

Agrawal, 1999). There are many extrinsic and intrinsic factors the plant needs to

compensate for, such as frequency of attack from herbivores, chemical defence

investment, nutrient availability and competition (Brooks and Bell, 2002). Thus,

energy investment for wound healing, leading to a full recovery may vary spatially

between the sites and within site, which may explain the variability of tissue

regrowth between the damaged roots as the frequency of herbivorous attack from

teredinids was found only in the moderate and severly damaged roots – but the

greatest frequency of teredinid attack was found in the severly damaged roots.

Roots exposed to a moderate and severe level of damage demonstrated a

dedifferentiation of cellular regrowth, attributed by a new lignified outgrowth from

the endodermis layer. When tissue patterns arise which differ conspicuously from the

norm, or when a lack of pattern is encountered the cellular regrowth can be classified

129

as atypical (Bloch, 1952). Other authors have reported the same lignified outgrowth

of tissue in Rhizophora prop-roots when damaged (Wier et al., 1996). As renewed

parenchyma tissue grows over the damaged area, a new formation of the radial

endodermal layer is produced that appears to grow into the new cortex regrowth. The

atypical growth of the new lignin-rich tissues may provide some structural rigidity

for the new cellular regrowth of parenchyma cells. This adaptation may be induced

by over compensation of the tolerance mechanism (Haukioja and Koricheva, 2000;

Brooks and Bell, 2002). The damaged area produces an increase of parenchyma

tissues from that of the original volume recorded prior to the initial surgeries, the

new outgrowth of non-radial woody endodermal layer may offer structural rigidity

for the increased mass of cortex tissues as it develops. In addition, a constituent

component of the endodermal layer is suberin. Mechanical wounding of the plant

tissues activates genes that induce the production of proteins, such as phenylalanine

ammonia lyase (PAL) (Karban and Myers, 1989; Doorn and Cruz, 2000). PAL can

create the biosynthesis of phenols, such as suberin. An increase of suberin deposits

produce increases of parasitic resistance or immunity to further infection in to the

damaged tissues (Bloch, 1952; Karban and Myers, 1989); therefore enhancing the

plants defence and increasing overall fitness and survival.

The plant’s abiotic and biotic environment such as salinity concentrations and

immersion time can also affect its tolerance to herbivory (Strauss and Agrawal,

1999). All root-scar experiments within the three sites were conducted in areas of the

forest where teredinid populations thrive – in areas of prolonged tidal immersion

(Rimmer et al., 1983; Kohlmeyer et al., 1995; Leonel et al., 2006).

Differences of degree of teredinid tunnelling between root-treatments were

found: with increasing severities of tissue damage the level of teredinid tunnelling

130

increases. No teredinid tunnels were found in roots with superficial damage after

twelve months. A few teredinid tunnels were found in the moderately damaged roots.

But, severely damaged roots had the greatest frequency of teredinid tunnels. The

rapid recruitment of the teredinids found in severely damaged roots may have been

facilitated by the removal of the lignin-rich endodermal layer that protects the inner

vascular cylinder. Cells contained within the vascular cylinder are tannin-free (Gill

and Tomlinson, 1971); making teredinid settlement possible (Turner, 1976), and thus

compromising root fitness.

The morphological and physiological resilience of these unusual trees

enhance their survival in mangrove habitats. This study demonstrates the

regenerative capabilities of Rhizophora prop-roots, highlighting their resilience to

damaged tissues. The regenerative abilities of Rhizophora prop-roots and the plant’s

fitness are dependent upon the level of damage imposed to those tissues, coupled

with extrinsic factors such as intensity of herbivory.

Sphaeromatid and teredinid activity is different within mangrove tissues.

Sphaeromatids may benefit the plant by inducing increases of lateral out-branching

of new aerial-roots (Ribi, 1982). But, sphaeromatids are unable to bore in to woody

prop-roots (Perry, 1988). Teredinids are able to attack prop-roots, and their affect

within the root will frequently result in the death of that root, but only when the level

of damage upon the root is severe. Thus, root death may generate woody detritus

within the mangrove forests. The activity of the teredinids within woody debris

creates many tunnels, which when vacant may provide niches for many fauna (Cragg

and Hendy, 2010).

This study demonstrates the remarkable ability of mangrove trees to combat

herbivorous activity by either deposition of anti-herbivore chemicals and/or an over-

131

compensatory of tissue regrowth. However, the tunnelling of teredinids in live

damaged prop-roots in the low-intertidal regions of mangrove forests can be

detrimental. These data demonstrate that Rhizophora prop-roots are able to defend

against teredinid larval settlement when exposed to superficial damage, however

when the loss of tissues exposes the tannin-free cells normally protected by the

endodermal layers, teredinid larvae are able to settle and tunnel in to the prop-root.

132

Chapter 5

HABITAT CREATION FOR ANIMALS BY TEREDINIDS

5.1 Introduction

Mangrove ecosystems have long been considered as not particularly

biodiverse (Duke et al., 1998; Alongi, 2002), especially when compared with other

tropical marine ecosystems such as coral reefs (Connell, 1978). However, mangrove

forests provide a variety of niches to creatures that depend upon the mangrove

ecosystem (Nagelkerken et al., 2008). Animals commonly found in mangrove forests

include sesarmid crabs, which break down and recycle much of the leaf litter

(Robertson, 1990), beetles that processes large woody debris (LWD) in the high- to

mid-intertidal areas of the forests (Feller, 2002). Thus, mangrove forests have

organisms commonly found in terrestrial and aquatic habitats (Nagelkerken et al.,

2008). The structural complexity of mangrove forests provides a wide number of

niches that maintain the high level of biodiversity, driven by substrata such as

mangrove roots (Gratwicke and Speight, 2005).

The complexity of root structures provides cover and protection for small

and juvenile fish communities (Ronnback et al., 1999; Correa and Uieda, 2008;

Wang et al., 2009), to decrease their risk of becoming predated upon (Verweij et al.,

2006; Tse et al., 2008; MacDonald et al., 2009). The structural heterogeneity

provided by the roots may either impede the movement of hunting predatory fish or

the prey-fish are able to reduce their visibility by using the roots to hide behind

(Laegdsgaard and Johnson, 2001; Kruitwagen et al., 2010) – therefore the diversity

of animals and the abundance of individuals are largely considered to be attributed

133

by deterministic factors such as habitat complexity combined with animal

recruitment rates (Syms and Jones, 2000).

Although the mangrove roots have been studied for their role as a nursery

habitat, little is known about the mangrove faunal communities relying upon fallen

wood as a habitat; in particular wood that has been attacked by teredinid bivalves.

Teredinids create many tunnels in LWD (Filho et al., 2008). However, when the

teredinids die, the tunnels may support biodiversity when vacant for animals to

exploit (Cragg and Hendy, 2010). This means that LWD may provide an ecosystem

service as a micro-habitat within intertidal areas (Storry et al., 2006). When trees fall

in to freshwater ecosystems they attract a high level of biodiversity. The riparian

zone in freshwater ecosystems is important as this zone is habitat for many aquatic

animals. Thus, LWD serves as an important link between terrestrial and aquatic

ecosystems (Roth et al., 2007).

Initially, the study reported in this chapter aimed to compare the most

biologically diverse substratum within the mangrove forests of the Tukang Besi

Archipelago by using biodiversity indices as an indicator of habitat importance. This

study also aims to investigate the ecological role of the Teredinidae in creating

niches for faunal communities within LWD. The complexity of the mangrove forest

determines the habitat for many fauna (Gratwicke and Speight, 2005; Nagelkerken et

al., 2010). Thus, the internal structural complexities within woody detritus created by

teredinid tunnels was quantified and measured, and correlated with the level of

animal diversity recorded from within each LWD sample.

To investigate the diversity of fauna within teredinid-attacked LWD samples

of LWD were collected and the area occupied by teredinid tunnels within LWD was

estimated as a measure of complexity. The fauna within the tunnels were removed to

134

determine if there are relationships of increasing amounts of teredinid tunnels within

LWD combined with increasing levels of faunal diversity within those vacant

tunnels. Drilled wooden blocks mimicking teredinid tunnels were deployed in the

mangrove forests to determine the recruitment and succession of fauna in to the

tunnels.

This study tested the hypotheses that fallen wood will be the most bio-diverse

substrata, when compared to the sediments and root structures within the forests. A

subsidiary hypothesis tested that with increasing teredinid tunnels there will be an

increasing level of animal diversity within fallen wood, and that the first animals to

colonise the teredinid tunnels will have a greater mobility than animals that colonise

later and the size of the tunnel will affect the species present.


5.2.1 Assessing the sediment macro-infauna, root epifauna and LWD

cryptic fauna

Four mangrove forests, Kaluku, Loho, One Onitu and Gili were used to

compare the biodiversity of sediment infauna, root epifauna and cryptofauna from

LWD (see chapter 2 for site descriptions). In each forest, three transects extending

from the strandline and ending at the seaward edge, samples of LWD (n = 101) were

collected and all cryptic macrofauna were removed. All items of LWD 2 metres each

side of the transect tape were sampled. Adjacent to each LWD item in the forests, a

sample of sediment (n = 101) was removed using a trowel for macro-infauna and five

prop roots (n = 510) were inspected for epifauna.

135

For each sediment sample, a volume of 4000 cm3

was collected at a depth of

10 cm and placed on to a plastic sheet and all macro-infauna were carefully removed

from the sediment. For each root, the length and circumference were measured to

determine the surface area and all attached epifauna were identified. For each LWD

sample, the volume of the wood piece was calculated. All animals were identified to

the lowest achievable taxonomic level with resources available locally.

5.2.2 Assessing the effect of teredinid tunnelling on LWD in mangrove

forests

Five mangrove forests were used to investigate animal communities within

LWD attacked by teredinids. These were, Langira, Kaluku, Loho, One Onitu and Gili

(see chapter 2 for site descriptions). Within each forest, LWD samples were collected

from five transects extending from the strandline and extending out to the seaward

edge (see chapter 2 for details). At ten metre intervals within the Langira forest, a

total of 70 items of LWD were collected. Within Kaluku, Loho, One Onitu and the

Gili mangrove forests a total of 20, 44, 32 and 30 items of LWD respectively were

collected at five metre intervals. A scale of teredinid attack intensity (Table 5.1) was

used within the samples of LWD to categorise the level of teredinid tunnelling. The

percentage of the surface occupied by teredinid tunnels was estimated across the

longitudinal section of each woody detrital sample using the digital analysis package,

Image Tool Version 3.00 (The University of Texas Health Science Centre at San

Antonio). All animals were removed from each LWD sample and identified.

136

Level Teredinid tunnels in detrital samples

0 No sign of borer attack

1 Very few tunnels, covering no more than 15 % of the total area

2 No more than 25 % of the total area is comprised of tunnels

3 Integrity of wood compromised – between 25 % and 50 % of the total area are tunnels

4 Severe attack – more than 50 % of the sample is comprised of tunnels

5.2.3 The recruitment and succession of animals to drilled wooden blocks

mimicking teredinid-attacked LWD

A total of 135 drilled Bruguiera gymnorhiza blocks were exposed within

three mangrove forests (Kaluku, Loho, and One Onitu) over the period from June

2009 to August 2009 to determine the recruitment and succession of fauna within

tunnel-like niches. Three ten by ten metre plots were chosen at random in areas

where teredinids dominate within each forest.

The volume of each test block was 512 cm3. To replicate the diameter of

teredinid tunnels in naturally occurring LWD, each block had 3 x 20 mm drilled

holes, 3 x 10 mm drilled holes, 3 x 5 mm drilled holes and 3 x 2.5 mm drilled holes

(Figure 5.1). All drilled holes were made using an electric drill. The blocks were

attached to Rhizophora stylosa prop-roots within the three plots in each of the three

forests, giving a total of forty-five blocks in each forest. Three blocks were removed

from each plot every ten days over 50 days. All fauna present within the mimicked

tunnels were collected and photographed. All animals were identified to the lowest

achievable taxonomic resources available.

Table 5.1, The scale of teredinid-attack intensity used to categorise LWD within the mangrove

forests of the Tukang Besi Archipelago. Levels 0 – 4 correspond to the percentage surface area of

teredinid tunnels.

137

5.3 Data analysis

To test for differences of abundances of animals between the sites, a One-way

analysis of variance (ANOVA) was used. A 1-way ANOVA was used to determine

differences between values of Shannon-Weiner biodiversity indices calculated from

root epifauna, sediment macro-infauna and LWD cryptic fauna. A 2-way ANOVA

was used to test for differences of the abundance and numbers of species in drilled

wooden blocks between three mangrove sites and over fifty days, with site and time

as factors. Regression analyses were used to reveal relationships of faunal diversity

within vacant teredinid tunnels and environmental factors, distance from the land,

volume of LWD and surface area of teredinid tunnels. Tukey’s pairwise comparison

test separated values into statistically distinct subsets for ANOVA. All data were

Figure 5.1, A drilled wooden block with various diameter tunnels to

replicate a teredinid-attacked piece of woody detritus. The wooden block

is tethered to a Rhizophora stylosa prop-root using a nylon cable-tie.

138

checked for normality, residuals were inspected to ensure that assumptions for

ANOVA were not compromised. Count data were square root transformed and all

percentage data were arcsin transformed. Statistical analyses were performed using

MINITAB (MINITAB Inc, version 13.20).

Univariate and non-parametric multivariate techniques, biodiversity indices

tests and a 1-way, 3-level PERMANOVA, based on a Bray-Curtis similarity matrix

was used to determine differences between the sediments, roots and LWD in the

PRIMER 6 (Plymouth Routines in Multivariate Ecological Research). Post-hoc pair-

wise tests were applied after the PERMANOVA to highlight the similarities between

the different substrata. Diversity indices were used for the fauna collected from

different substrates, teredinid-attacked LWD, the fauna collected from within

different diameter tunnels, and the recruitment of fauna to the tunnels (see chapters 2

and 3 for indices description).

5.4 Results

5.4.1 Comparisons of animal diversity in different substrata

Differences of the faunal communities between substrata were significant

(Table. 5.2 a, one-way PERMANOVA pair-wise test, pseudo-F 2,732 = 47.03, p =

< 0.01). The LWD and root fauna had the lowest similarity between the different

habitats with 38.5 % when compared with each of the substrata (Table. 5.2 b).

The sediments and roots were most similar with 70.5%.

139

Habitat t P (perm)

Roots, Wood 8.3 < 0.01

Roots, Sediment 3.8 < 0.01

Wood, Sediment 6.7 < 0.01

Roots Wood Sediment

Roots 62.8

Wood 38.5 31.4

Sediment 70.5 43.5 83.0

The greatest levels of diversity (H`) and total number of species (S) were

recorded from LWD attacked by teredinids (Table. 5.3). The sediment samples had

the lowest recorded indices of diversity and numbers of species.

Table 5.2 PERMANOVA comparisons of the pair-wise similarity between the

fauna of the different substrata. a, the differences between the three substrata b, The

percentage similarity between sites for each substratum. a

b

140

Habitat Site S J' H'

Sediment Gili 5 0.84 1.36

Kaluku 3 0.95 1.04

Loho 7 0.96 1.87

One Onitu 4 0.68 0.94

Roots Gili 8 0.84 1.75

Kaluku 12 0.86 2.13

Loho 16 0.79 2.19

One Onitu 16 0.79 2.19

Wood Gili 13 0.85 2.18

Kaluku 26 0.83 2.72

Loho 28 0.84 2.81

One Onitu 21 0.86 2.62

Significant differences between the three substrata were found (Figure 5.2).

Sediments had the lowest recorded diversity and the mangrove roots had a slightly

greater level of diversity, but not significantly different. However, woody detritus

had the greatest recorded mean level of diversity within the mangrove forests. Fallen

wood attacked by teredinids within the forests were on average 5.7 times more

Table. 5.3, Biodiversity indices of animals recorded from roots, sediments and

LWD. S = number of species, J’ = Pielou’s evenness, H’ = Shannon-Weiner diversity

index.

141

biodiverse than the root structures and 9.3 times more diverse than the infauna within

mangrove sediments.

The identified fauna from the roots, sediments and LWD were categorised by

their trophic levels. The epifauna upon the roots consisted mainly of filter feeders.

The macro-infauna within the mangrove sediment was dominated by detritivores.

The fauna within the teredinid attacked LWD had a broad spectrum of trophic levels

with carnivores, detritivores, filter feeders, herbivores and omnivores (Figure 5. 3).

a a

b

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Sediment Roots Wood

Div

ersi

ty (

H`)

Substrata

n = 101

Figure 5.2 The Shannon-Weiner diversity of fauna recorded from four

mangrove sites within the Tukang Besi Archipelago. Tukey’s test reveals no

difference of biodiversity recorded between the sediments and root substrata

(letters above the bar). However, a clear significant difference was found with

biodiversity of cryptic fauna compared with other substrata from the

mangroves (mean ± SE, F2, 732 = 114.56, p = < 0.001).

n = 510

n = 101

142

5.4.2 Biodiversity in teredinid tunnelled wood

Greater biodiversity was observed in more wood tunnelled by teredinids

(Figure 5.4 a and b, 1-way ANOVA, p = < 0.001). The Gili forest (Table 5.4 a) had a

total of 30 LWD samples, and the greatest abundance of animals were found in LWD

samples with a teredinid attack category of 3, with 63 animals. No level 4 teredinid

attack categories were recorded in LWD from the Gili forest.

The greatest numbers of different species in Kaluku (Table 5.4 b) were found

in LWD samples with a level 4 category of teredinid attack, with 25 species. No

animals were recorded in the analyses of LWD within the level 0 category of

0

10

20

30

40

50

60

70

80

90

100

Roots Sediments LWD

Tro

ph

ic l

evel

(%

)

Substrata

Suspension feeders

Scavengers

Omnivores

Herbivores

Filter feeders

Detritivores

Carnivores

Figure 5.3 The trophic levels of fauna identified from mangrove roots, sediments and

LWD from the mangrove forests of the WMP. All epifauna, macro-infauna and cryptic

fauna identified from the roots, sediments and LWD respectively were categorised by their

feeding mode (%).

143

teredinid attack intensities. The greatest abundances of animals were also found in

the level 4 categories, with a total of 315 animals.

The greatest numbers of different species in Langira (Table 5.4 c) were found

in LWD samples with a level 4 category of teredinid attack, with 30 species. The

greatest abundance of animals was also found within LWD samples with a level 4

category of teredinid attack, with a total of 478 animals. The lowest number of

species was recorded with the level 0 category of teredinid attack, with 6 species.

The greatest numbers of different species in Loho (Table 5.4 d) were found in

woody detrital samples with a level 4 category of teredinid attack, with 26 species.

The greatest abundance of animals was also recorded within LWD samples with a

teredinid attack level of 4, with a total of 271 animals. No animals were found in

LWD samples with a teredind attack intensity level of 0.

The greatest numbers of different species in One Onitu (Table 5.4 e) were

found in detrital samples with a teredinid attack intensity of level 4, with 18 species.

The greatest abundance of animals was also found in LWD samples with a teredinid

attack level of 4, with a total of 73 animals. Whereas, the lowest recorded number of

species and abundance was recorded within LWD with a level 0 category of teredind

attack, with 5 species and a total of 6 animals respectively.

There is a strong relationship of increasing numbers of different species

found within detrital samples of increasing percentage surface areas of teredinid

tunnels (Figure 5.5 a). A similar relationship was found with the abundance of

individuals with an increasing amount of teredinid tunnels. A regression analysis

demonstrated that with increasing surface areas of teredinid tunnels within LWD, the

abundance of animals will also increase (Figure 5.5 b).

144

a a

bc c

ab ab

bc

d

a b ab

abc c

a

b bc

d

a a

ab ab

b

0

10

20

30

40

50

60

70

0 1 2 3 4

Ab

un

da

nce

of

ind

ivid

ua

ls

Gili Kaluku Langira Loho One Onitu

*

a

ab

c c

ab

ab

c

d

ab

a

bc

bc

c

ab

c

c

d

a

b

bc bc

c

0

2

4

6

8

10

0 1 2 3 4

Nu

mb

er o

f sp

ecie

s

Teredinid attack level

Figure 5.4, The abundance of animals (a) and numbers of species (b)

removed from teredinid-attacked LWD in mangrove forests from the

WMP. LWD from each site was categorised by the amount of teredinid

tunnels (refer to Table 5.1) and all fauna removed (mean ± SE). * = No LWD

collected with this level of teredinid attack intensity. Letters above the bars =

Tukeys Pairwise test.

a

b

*

145

Category of Teredinid attack

Phylum Class Order Family Species 0 1 2 3 4 Mollusca Gastropoda Basommatophora Ellobiidae Pythia sp. A ***

Cassidula sp. A *

Annelida Polychaeta Aciculata Nereididae nereid spp. *** *

Amphinomidae amphinomid sp. A * *

Arthropoda Chilopoda Scolopendromorpha Cryptopidae centipede sp. A * **

Insecta Coleoptera Cerambycidae cerambycid sp. A *** *** *** ***

Orthoptera Gryllidae Apteronemobius asahinai *

Malacostraca Amphipoda Talitridae Microrchestia sp. A * * *** ***

Decapoda Grapsidae Metapograpsus spp. * * *

Xanthidae xanthoid spp. * * * ***

Atyidae Caridina propinqua *

Isopoda Cirolanidae Cirolana sp. A * ***

Chordata Actinopterygii Perciformes Ptereleotridae Parioglossus interruptus *

Total species 4 6 10 8 0

Total abundance 17 10 36 63 0

Number of LWD samples 13 7 4 6 0

Gili

Table 5.4, Animals collected from teredinid-attacked LWD from five mangrove forests in the WMP. Taxonomic identification of the class, family and species

(where possible) of animals removed from LWD with different levels of teredinid attack. Abundances of species where classed as: * = rare, ** = common, and ***

= abundant within each category of attack. Blank spaces = none found. Total number of species, abundance and number of LWD samples analysed per category of

teredinid attack are also demonstrated.

a

146

Category of teredinid attack

Phylum Class Order Family Species 0 1 2 3 4 Platyhelminthes Rhabditophora Polycladida Gnesiocerotidae Styloplanocera sp. A * *

Nemertea Enopla Hoplonemertea Prosorhochmidae Pantinonemertes sp. A *

Mollusca Bivalvia Pterioida Isognomonidae Isognomon ephippium * *

Mytiloida Mytilidae Xenostrobus sp. A ***

Gastropoda Neogastropoda Marginellidae marginellid sp. A *

Mitridae Strigatella sp. A *

Littorinimorpha Assimineidae assimineid sp. A *

Systellommatophora Onchidiidae Onchidium nigram *

Heterostropha Pyramidellidae pyramidellid sp. A *

Sipuncula Phascolosomatidea Phascolosomatida Phascolosomatidae Phascolosoma arcuatum *

Annelida Polychaeta Aciculata Nereididae nereid spp. **

Amphinomidae amphinomid sp. A ** ***

Eunicida Eunicidae eunicid sp. A * *** * ***

Terebellida Terebellidae terebellid spp. **

Arthropoda Arachnida Araneae Desidae Desis martensi *

Chilopoda Scolopendromorpha Cryptopidae centipede sp. A *

Insecta Coleoptera Cerambycidae cerambycid sp. A * *

Malacostraca Amphipoda Talitridae Microrchestia sp. A ***

Decapoda Grapsidae Metapograpsus sp. A * * * ***

Xanthidae xanthoid spp. *

Atyidae Caridina propinqua ** *

Alpheidae Alpheus sp. A * *

Diogenidae Diogenes sp. A *

Isopoda Cirolanidae Cirolana sp. A ** *** ***

Chordata Actinopterygii Perciformes Ptereleotridae Parioglossus interruptus *




b Kaluku

147

Category of Teredinid attack intensity

Phylum Class Order Family Species 0 1 2 3 4

Platyhelminthes Rhabditophora Polycladida Gnesiocerotidae Styloplanocera sp. A *

Nemertea Enopla Hoplonemertea Prosorhochmidae Pantinonemertes sp. A

*

Mollusca Bivalvia Mytiloida Mytilidae Xenostrobus sp. A

*

*

Pterioida Isognomonidae Isognomon ephippium

*

Gastropod Littorinimorpha Assimineidae assimineid sp. A

* *

Neotaenioglossa Cypraeidae Cypraea interrupta

*

Systellommatophora Onchidiidae Onchidium nigram

* *

Neogastropoda Mitridae Strigatella sp. A

*

Muricidae Thais gradata

*

Nassariidae Nassarius sp. A

*

Columbellidae Pseudanachis basedowi

*

Caenogastropoda Cerithiidae Clypeomorus sp. A

*

Cephalopoda Octopoda

octopod sp. A

*

Sipuncula Sipunculidea Phascolosomatida Phascolosomatidae Phascolosoma arcuatum

*

*

Annelida Polychaeta Aciculata Nereididae nereid spp. * * *** ** ***

Amphinomidae amphinomid sp. A

** *

***

Eunicida Eunicidae eunicid sp. A * ** *

**

Terebellida Terebellidae terebellid spp.

*

**

Arthropoda Arachnida Araneae Desidae Desis martensi

*

**

Insecta Coleoptera Cerambycidae cerambycid sp. A *** ** * ** *

Malacostraca Amphipoda Talitridae Microrchestia sp. A

*

Decapoda Grapsidae Metapograpsus sp. A * * *** ** **

Xanthidae xanthoid spp.

** * * **

Atyidae Caridina propinqua * *

*

Alpheidae Alpheus sp. A

* *

*

Diogenidae Diogenes sp. A

*

*

Pilumnidae Pilumnus vespertilio

*

*

Isopoda Cirolanidae Cirolana sp. A * * ** * *

Chordata Actinopterygii Perciformes Ptereleotridae Parioglossus interruptus

*

* *

Anguilliformes Muraenidae Gymnothorax richardsoni

*

c Langira

148

Echinodermata Echinoidea Echinoida

Urchin sp. A

*

Ophiuroidea Ophiurida Amphiuridae Ophiactis sp. A

*

*





Phylum Class Order Family Species 0 1 2 3 4 Porifera Homoscleromorpha Porifera sp. A *

Platyhelminthes Rhabditophora Polycladida Gnesiocerotidae Styloplanocera sp. A

* * *

Nemertea Enopla Hoplonemertea Prosorhochmidae Pantinonemertes sp. A

*

Annelida Polychaeta Aciculata Nereididae nereidae spp.

** *** *** ***


* * * **

Eunicida Eunicidae eunicid sp. A

* * *

Terebellida Terebellidae terebellid spp.

* * **

Canalipalpata Sabellidae sabellid sp. A

*


* *

Chilopoda Scolopendromorpha Cryptoidae centipede sp. A

*

Insecta Coleoptera Cerambycidae cerambycid sp. A

** * * *


* **

**

Decapoda Grapsidae Metapograpsus sp. A

* * * **


* * *


*

*

Isopoda Cirolanidae Cirolana sp. A

*

** ***

Mollusca Bivalvia Mytiloida Mytilidae Xenostrobus sp. A

** * * ***

Pterioida Isognomonidae Isognomon ephippium

*

Gastropoda Littorinimorpha Assimineidae assimineid sp. A

* *

Neotaenioglossa Cypraeidae Cypraea interrupta

*

Thiaridae Melanoides sp. A

*

Loho d

149

Neogastropoda Nassariidae Nassarius sp. A

*

Marginellidae marginellid sp. A

*

Polyplacophora

Chiton sp. A

*


octopod sp. A

*

Sipuncula Sipunculidea Phascolosomatida Phascolosomatidae Phascolosoma arcuatum

*


***





Phylum Class Order Family Species 0 1 2 3 4 Mollusca Gastropoda Littorinimorpha Assimineidae assimineid sp. A *

Neogastropoda Marginellidae marginellid sp. A *

*

Muricidae Thais gradata

*

Systellommatophora Onchidiidae Onchidium nigram

*

Heterostropha Pyramidellidae pyramidellid sp. A

*

Sipuncula Phascolosomatidea Phascolosomatida Phascolosomatidae Phascolosoma arcuatum

*

Annelida Polychaeta Aciculata Nereididae nereid spp.

*


***

***

Eunicida Eunicidae eunicid sp. A

*

*

Terebellida Terebellidae terebellid spp. * *

**


* *

*

Insecta Coleoptera Cerambycidae cerambycid sp. A

* * *** *


*

e One Onitu

150

Decapoda Grapsidae Metapograpsus sp. A *

* *

Xanthidae xanthoid spp. *

* *


*

Atyidae Caridina propinqua

*

Isopoda Cirolanidae Cirolana sp. A * ***

* **


**

*

Blenniidae blennie sp. A

*

Ascidiacea Phlebobranchia

Tunicate sp. A

*




151

Regression analyses were used to determine the factors that contribute to

increasing numbers of different species within LWD. No difference was found with

y = 0.07x + 1.09

R² (adj) = 0.45

0

2

4

6

8

10

12

14

0 20 40 60 80 100

Nu

mb

er o

f sp

ecie

s

% of section tunnelled

y = 0.25x + 2.17

R² (adj) = 0.32

0

20

40

60

80

100

120

140

160

0 20 40 60 80 100

Nu

mb

er o

f in

div

idu

als


Figure 5.5 Numbers of different species and abundance of animals in teredinid-

attacked LWD. a, The number of different species removed from detrital samples (R2

(adj): 0.45, F1,193 = 159.3, p = < 0.001) and b, the abundance of individuals of cryptic

fauna removed from detrital samples categorised by the level of teredinid attack intensity

(R2 (adj): 0.32, F1,193 = 93.3, p = < 0.001).

a

b

152

animals in wood with increasing distance from the land (P = 0.908) and no difference

was found with the area of the mangrove forest (P = 0.816). A significant difference

was found with increasing volume of LWD when correlated with increasing numbers

of different species (F1, 193 = 8.12, p = < 0.01), although a low correlation was

determined R2 (adj) = 0.04. The percentage surface area of teredinid tunnels was also

significant (F1, 193 = 159.34, p = < 0.001), however a strong correlation was found, R2

(adj) = 0.45.

The greatest level of teredinid attack within LWD from One Onitu, Loho,

Langira and the Kaluku forests had the highest recorded diversity (Table 5.5). No

LWD samples were located in the Gili forest with a level 4 category of teredinid

attack. LWD samples with increasing levels of teredinid attack had lower evenness

values (J`) compared with detrital samples with a lower level of teredinid attack.

LWD samples with a percentage surface area of teredinid tunnels between 0 –

19 % had the lowest levels of diversity (H’) with 0.35 ± 0.06 (mean ± SE, n = 97,

Figure 5.6). No difference of diversities were found in detrital samples with 20 – 35,

50 – 65 and more than 65 % surface area of teredinid tunnels, although there was a

trend with increasing percentage surface area of teredinid tunnels and increasing

diversity. Detrital samples with more than sixty percent of teredinid tunnels have on

average 4.5 times more species, 6.8 times more individuals and 4 times the diversity

when compared to detrital samples with twenty percent or less of teredinid tunnels.

153

Site Attack level S N J' H'

One Onitu 0 5 5 0.99 1.59

1 7 9 0.97 1.88

2 4 8 0.94 1.31

3 5 6 0.95 1.52

4 18 29 0.97 2.80

Loho 0 0 0 0 0

1 7 12 0.97 1.89

2 12 20 0.97 2.40

3 12 27 0.94 2.34

4 26 68 0.93 3.03

Langira 0 6 9 0.93 1.67

1 13 22 0.96 2.47

2 13 19 0.96 2.47

3 8 14 0.97 2.02

4 29 91 0.92 3.09

Kaluku 0 0 0 0 0

1 4 6 0.99 1.37

2 2 3 0.98 0.68

3 9 14 0.96 2.12

4 25 68 0.92 2.95

Gili 0 4 7 0.85 1.18

1 6 7 0.98 1.75

2 10 17 0.96 2.20

3 8 19 0.90 1.88

4 0 0 0 0

Table 5.5, Biodiversity indices of fauna removed from LWD in the WMP. S

= number of species, N = total individuals, J’ = Pielou’s evenness, H’ =

Shannon-Weiner diversity index.

154

To determine if the volume of LWD had influenced the biodiversity, all LWD

samples were standardised to 1 m3 to remove the variable of LWD volume. The

abundance of individuals was tested (Figure 5.7). The abundance of animals was

lower in LWD per cubic meter with less than 20 % surface area of teredinid tunnels.

No significant difference was found with the abundance of animals from LWD

samples with levels of teredinid attack intensity increasing from 20 - 35 % to more

than 65 % surface area of teredinid tunnels. However, LWD with more than sixty-

five percent surface area of teredinid tunnels will have 7.4 times the individuals

compared to wood of the same volume with twenty percent or less surface area of

teredinid tunnels.

a

bc

b

bc

c

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

< 20 20 - 35 35 - 50 50 - 65 > 65

Sh

an

no

n-W

ein

er d

iver

sity

(H

`)


Figure 5.6, The diversity of animals recorded from detrital samples categorised by the

level of teredinid-attack intensity. Faunal diversity indices are expressed by the Shannon-

Weiner index (mean ± SE, 1-way ANOVA, diversity vs. % surface area of teredinid

tunnels, F4,190 = 24.83, p = < 0.001). Letters above the bars = Tukey’s comparisons.

155

LWD with higher levels of teredinid-attack had greater numbers of different

species, and abundance of individuals (Figure 5.8). The curve representing the level

4 category of teredinid attack begins to level-out.

a

b b

b

c

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

< 20 20 - 35 35 - 50 50 - 65 > 65

An

ima

ls i

n L

WD

(m

3)


Figure 5.7 Variation in numbers of infauna with degree of teredinid attack

collected from LWD (metre3). Abundance of individuals removed from LWD

categorised by the level of teredinid attack intensity standardised to 1m3(mean ± SE,

F4,190 = 9.3, p = < 0.001).

156

The Gili and One Onitu forests had the least abundance and number of

species removed from teredinid-attacked LWD of the five mangrove forests.

However, Langira, Loho and Kaluku have the greatest abundance and number of

species within teredinid-attacked LWD (Figure 5.9).

0

5

10

15

20

25

30

35

40

0 200 400 600 800 1000 1200

Nu

mb

er o

f sp

ecie

s

Total number of individuals

Level 0

Level 1

Level 2

Level 3

Level 4

Figure 5.8, Species accumulation curves of infauna removed from LWD categorised by

the level of teredinid attack. Infauna removed from all levels of teredinid-attacked LWD

within five mangrove forests. Each level of teredinid attack is categorised by different coloured

symbols.

157

The degree of teredinid-tunnelling in LWD samples within each mangrove

forest was considered (Figure 5.10). Teredinid attack levels in LWD in four of the

forests were statistically indistinguishable, while the level of attack in Gili was

significantly lower than Langira, Loho and Kaluku.

0

5

10

15

20

25

30

35

0

100

200

300

400

500

600

700

800

Gili One Onitu Langira Loho Kaluku

Nu

mb

er o

f sp

ecie

s

To

tal

ab

un

da

nce

Site

Abundance Species

Figure 5.9, The total abundance and number of species removed from teredinid-attacked

LWD from each mangrove forest. Animals were removed from teredinid-attacked LWD and

counted.

158

5.4.3 Recruitment and succession of animals within drilled wooden blocks

mimicking teredinid tunnels

The removal of animals within Kaluku, Loho and the One Onitu forests from

drilled wooden blocks (Table 5.6) demonstrated that as time increases, the numbers

of species recorded from the drilled wooden blocks also increase. After 10, 20, 30,

40 and 50 days, 3, 6, 11, 8 and 11 species were recorded, respectively. The earliest

recruiting animals were the grapsoid crabs, attributed by their high abundance after

ten days. Suspension feeders (the bivalve Xenostrobus sp. and tunicates) only

appeared after fifty days.

No significant differences of the numbers of species and individuals were

found between the three sites (2-way ANOVA, F2, 128 = 1.89 and 2.53, p = 0.155 and

a

ab

b b

b

0

5

10

15

20

25

30

35

40

45

50

Gili One Onitu Langira Loho Kaluku

% S

A o

f te

red

inid

tu

nn

els

Site

Figure 5.10, The variation between five mangrove forests in degree of

teredinid tunnelling. The percentage surface area of teredinid tunnels within each

piece of LWD from each forest (mean ± SE1-way ANOVA, teredinid attack

intensity vs. site highlighted significant differences, F4,191 = 6.52, p = < 0.001).

Letters above the bars indicate a Tukey’s comparison test.

159

p = 0.084 respectively). However, significant differences were found with the

numbers of species and abundance of individuals recruiting to the drilled wooden

blocks mimicking teredinid tunnels over the fifty days (F4, 128 = 5.29, and 6.59, p = <

0.01 and p = < 0.001 respectively).

Day ten had the lowest recorded number of different species (Figure 5.11 a,

mean ± SE, n = 27). The greatest numbers of different species were recorded from

day forty. The abundance of animals recorded from the three forests also increased

with time (Figure 5.11 b), with the greatest abundance also found at day forty.

a a

ab

b

ab

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Day 0 10 Day 20 Day 30 Day 40 Day 50

Nu

mb

er o

f sp

ecie

s

Time (d)

a a

b b

ab

0

0.5

1

1.5

2

2.5

3

Day 0 Day 10 Day 20 Day 30 Day 40 Day 50

Ab

un

da

nce

of

an

ima

ls

Time (d)

Figure 5.11, Numbers of species and individuals removed from drilled wood blocks

over an exposure of 50 days. a, The number of species (1-way ANOVA, number of

species vs. time: F4, 130 = 5.21, p = < 0.01), and b, abundance of individual animals

removed from drilled wooden blocks over ten day intervals in the Kaluku, Loho and One

Onitu forests (mean ± SE, n = 27, 1-way ANOVA, abundance vs. time; F4, 130 = 6.44, p =

< 0.001). Letters above the bars are the results from a Tukey’s test.

a

b

160

PHYLUM CLASS ORDER FAMILY SPECIES Day 10 Day 20 Day 30 Day 40 Day 50 Porifera Homoscleromorpha

Porifera sp. A

* *

Mollusca Gastropoda Littorinimorpha Assimineidae assimineid sp. A

*

*

Caenogastropoda Cerithiidae cerithiid sp. A

* *

*

Basommatophora Ellobiidae ellobiid sp. A

* *

Heterostropha Pyramidellidae pyramidellid sp. A

*


octopod sp. A

*

Bivalvia Mytiloida Mytilidae Xenostrobus sp. A

* Annelida Polychaeta Aciculata Nereididae nereid spp. A **

*

*

Arthropoda Malacostraca Decapoda Alpheidae Alpheus sp. A

* * * *

Diogenidae Diogenes sp. A

** * *** **

Grapsidae grapsoid spp. *** *** *** *** ***


*

Isopoda Cirolanidae Cirolana sp. A * ** * * *

Amphipoda Talitridae Microrchestia sp. A

** ** *** **


* Ascidiacea Phlebobranchia Tunicate sp. A *


Table 5.6, Animals collected from drilled wooden blocks in three mangrove forests in the Tukang Besi over a period of 50 days after installation. All animals

were removed every 10 days from drilled holes in wooden blocks. Species abundance; *** = very common, ** = common, * = rare, blank cells = none found.

161

The biodiversity indices of the fauna removed from the drilled wooden blocks

demonstrates that the evenness increases rapidly and then drops at day 30, meaning

that the dominance of a particular species has increased (Figure 5.12). The

biodiversity increases, as time increases.

In the fifty day experiment, within each site the most dominant species

recruiting to the wooden blocks were grapsoid crabs, demonstrated by their early

recruitment in each site (Figure 5.13). The high dominance of the Grapsidae within

the sample units is further illustrated by their initial high peaks of the rank abundance

curves that rapidly taper off.

The least dominant species to occur from the sample units differed between

each of the three sites. The bivalve, Xenostrobus sp. were the least abundant and least

dominant species collected from the sample units in the Kaluku forest, found only at

day 50 of the experiment. The least abundant and least dominant species recorded

0

0.5

1

1.5

2

2.5

0.86

0.88

0.9

0.92

0.94

0.96

0.98

Day 10 Day 20 Day 30 Day 40 Day 50

Sh

an

no

n-W

ein

er d

iver

sity

Ev

enn

ess

Number of days

Evenness Shannon Weiner

Figure 5.12, Community indices of fauna removed from drilled holes in wooden

blocks over time. Evenness is a measure of the faunal community structure and the

Shannon-Weiner diversity index measures the level of biodiversity.

162

from the Loho forest were tunicates, also observed at day 50. The least dominant

species recorded from the One Onitu forest within the sample units were the

detritivore isopods, Microrchestia sp., also found at day 50.

The first and most dominant animals to recruit in to the drilled wooden blocks

were; Grapsidae>Taltridae>Diogenidae>Cirolanidae> Alpheidae (Malacostraca)

>Nereididae (Polychaeta) >Cerithiidae>Ellobiidae = Assimineidae (Gastropoda)

>Porifera >Tunicate (Ascidiacea) = Mytilidae (Bivalvia). The order by which the

animals are arranged are categorised by decreasing dominance. The most dominant

species recorded from the sample blocks belonged to the Malacostraca, a highly

motile class of animals such as grapsoid crabs, Microrchestia sp., mud hoppers and

cirolaniid isopods, fish lice. The least dominant species recorded were Xenostrobus

sp., sessile filter feeding bivalves. Of the motile fauna recorded, the least dominant

class of animals were the Gastropoda, such as the slow-moving ellobiids and

assimineids.

The number of different species and diversity of animals increased with

increasing diameter of tunnels (Table 5.7). Drilled tunnels 2.5 mm in diameter had

the lowest number of species and diversity of fauna. However, the greatest numbers

of species and diversity were recorded from tunnels measuring 10 mm diameter, with

12 species. Species commonly found in 2.5 mm and 5 mm diameters drilled holes

were cirolanids and Microrchestia sp. The most common species found in 10 mm

and 20 mm diameter drilled holes were grapsoids.

Figure 5.13, The frequency and rank abundance of species within drilled wooden

blocks within the mangrove forests. Numbers of animals are the total abundance

recorded from the drilled wooden blocks within each forest. Pages 159 – 161.

163

Kaluku

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Number of individuals Species rank

10 days

50 days

40 days

30 days

20 days

164

Loho

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce


10 days

50 days

40 days

30 days

20 days

165

One Onitu

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

S

pec

ies

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce

Ab

un

dan

ce


10 days

50 days

40 days

30 days

20 days

166

Tunnel Diameter Number of Secies J' H'

2.5 1 0 0

5 5 0.9 1.5

10 12 0.9 2.2

20 10 0.9 2.0

5.5 Discussion

Within the mangrove forests of the Tukang Besi Archipelago very few

animals were found in the sediments, mainly consisting of Uca spp. Although

mangrove sediments are generally anoxic, fiddler crabs bioturbate the sediments

(Bouma et al., 2009) and even enhance the growth of the mangroves (Smith et al.,

2009). Burrowing by fiddler crabs increases the growth of Caribbean trees and

decreases pore-water salinity (Smith et al., 2009). Upon the mangrove roots, a large

proportion of the epifauna were sessile filter-feeders, sponges, mussels and oysters.

Mangrove roots with epifauna have been found to enhance fish abundance

(MacDonald et al., 2008). Furthermore, sponges not only take-up much of the

available hard surfaces of the roots, they also provide an important ecosystem service

by protecting the roots from herbivorous attack by isopods (Ellison and Farnsworth,

1990; Ellison and Farnsworth, 1992). The root epifauna within the Gili mangrove

forest was distinct from the root epifauna recorded from all other sites. Gili is

established further inland compared to the other mangrove forests and no sessile

filter-feeding animals were found as tidal conditions were unsuitable for sessile

filter-feeding invertebrates to colonise. Mangrove roots within Gili had a greater

number of motile fauna ranging from grapsoid crabs to potamid gastropods. The

Table 5.7, Biodiversity indices of fauna removed from different diameter drilled tunnels

after 50 days. S= number of species, J’ Pielou’s evenness, H’ = Shannon-Weiner diversity index.

167

LWD fauna-taxon and density was the richest compared with the other substrata.

LWD is more structurally complex compared to the sediments and roots. A greater

faunal richness is found with increasing habitat complexity (Taniguchi and Tokeshi,

2004).

The fauna collected from the teredinid-attacked LWD in the mangrove forests

were recruited during sporadic episodes of colonisation, but maintained by a habitat-

specific structure – teredinid tunnels inside the LWD. Non-deterministic

environmental interactions may also have an effect upon site-specific animal

communities (Poff and Allan, 1995). For example, hydrological processes shape

waterways, by creating random processes that characterise and structure the animal

assemblages (Poff and Allan, 1995; Grossman et al., 1998). Thus, the animals

recorded from each site from this study may have varied due to the intricate small

tidal channels and streams within the forests.

Species diversity is positively correlated with increasing habitat complexity

(Petren and Case, 1998; Saha et al., 2009), such as is created by teredinids. LWD

within aquatic ecosystems are important constituents in the structure and complexity

of water ways and LWD will probably become colonised by a wide variety of

animals (Hilderbrand et al., 1997; Storry et al., 2006). Thus, LWD represents a vital

resource providing a spatial subsidy within the ecosystem (Polis et al., 1997). Wood

enhances habitat complexity (Shirvell, 1990; Brooks et al., 2004), the deposition of

sediments and the retention of organic matter (Bilby and Likens, 1980; Smock et al.,

1989). Thus, removal of wood increases sediment discharge and leads to a reduction

of habitat structural complexities (Larson et al., 2001; Brooks et al., 2004). LWD is

therefore an important component within aquatic ecosystems (Shields et al., 2006).

Thus, a major threat to the mangrove ecosystem is wood harvesting (Valiela et al.,

168

2001; Sanchirico and Mumby, 2009), which could reduce ecosystem-level mangrove

faunal diversity due to the reduction of wood (Benke et al., 1985; Wright and

Flecker, 2004).

Indeed, the results from this study corroborate previous research that woody

detritus does increase animal diversity (Everett and Ruiz, 1993; Wright and Flecker,

2004). However, this study links the role of the Teredinidae with increasing

ecosystem-level biodiversity. Teredinids create niches as they consume LWD, by

creating tunnels for a wide range of animals when those tunnels become vacant. As

the number of teredinid tunnels increase within LWD, the abundance and diversity of

animals also increase. The increasing species diversity with increasing numbers of

teredinid tunnels may likely be due to a higher proportion of refuges from predation

(Willis et al., 2005). The refuge provided by woody detritus exploited by grass

shrimp significantly reduces their risk of predation (Everett and Ruiz, 1993).

Vulnerable animals have more options for avoiding and escaping potential predation

in habitats containing a greater number of niches. Structurally complex habitats may

reduce visual contact, encounter rates and aggressive behaviour between competitors

(Jones et al., 2001; Willis et al., 2005).

The results from this study magnify the contribution of woody detritus in

mangrove ecosystems to biodiversity maintenance. Mangrove forest biodiversity is

significantly enhanced by a large volume of teredinid attacked LWD. Non-tunnelled

LWD has a limited number of species and abundance of individuals due to the

reduced niche availability. A lack of teredinid tunnels within woody detritus will

create a reduced habitat complexity that may likely increase predator-prey

encounters. Differences of spatial structure will influence the frequency of

interactions such as predation or niche exploitation for animals (Warfe and Barmuta,

169

2004; Nurminen et al., 2007). This may also be the case for the spatial structure

teredinid tunnels provide in LWD, which explains the sharp change in animal

assemblages and diversity of animals in LWD without tunnels when compared to

LWD that have been attacked by the Teredinidae. These data clearly illustrate that

the faunal assemblages change and the diversity is increased when the surface area of

LWD increases, attributed by the activity of the Teredinidae.

When considering species diversity, the Shannon-Wiener Index is the most

frequently used diversity indices when measuring the fauna of benthic ecology (Reiss

and Kroucke, 2005). Shannon-Wiener combines species richness with the

community evenness. However, this index is dependent on the sample size

(Magurran, 2004), as larger samples are likely to contain additional resources and

therefore increased species. To effectively rule out the factor of sample size from this

study all LWD samples were calculated to the same volume. Teredinid tunnels

significantly enhance the animal diversity within detrital samples of the same

volume.

The Teredinidae also influence faunal diversity on whole ecosystem level in

the WMP. The Gili forest had the lowest level of teredinid attack on LWD, and the

lowest level of cryptic biodiversity of the sites investigated. Kaluku and Loho had

the highest degree of teredinid tunnelling in LWD. This study demonstrates that,

although LWD is essential for the biodiversity of both the specialist and more

generalist animals (Hilderbrand et al., 1997; Kappes et al., 2009); teredinid tunnels

will increase the internal structural complexity within LWD and the tunnels

significantly enhance ecosystem-level biodiversity within these particular Indonesian

mangrove forests.

170

Teredinid tunnels are home to many animals which cannot bore into the very

hard, undecayed wood. It is for this reason that the Teredinidae can be classed as

ecosystem engineers.

The colonisation and recruitment of fauna in to the drilled wooden blocks

revealed that as time increased the number of different species and number of

individuals colonising also increased. The initial low diversity of animals recorded

from day ten may be due to a lack of microorganism colonisation and thus a lack of

microbial biofilms (Gulis et al., 2004) or that it takes time for organisms to find the

wood. The formations of microbial biofilms have been linked with the colonisation

and presence of invertebrates (Spanhoff et al., 2001; Gulis et al., 2004). As biofilms

increase, invertebrates will colonise (Tank and Winterbourn, 1995; Tank and

Wintrbourn, 1996; Collier and Halliday, 2000).

Other factors may also determine the rate at which animals colonise new

habitats, by means of their mobility threshold (Arsuffi and Suberkropp, 1989),

expressed as the foraging range of an animal deemed safe within the limits of

potential predation risks and foraging for food. Animals are likely to be less selective

feeders when food items and other resources are widely dispersed relative to their

foraging range because the risk of predation increases as distance between food items

become greater (Schoener, 1971). Thus, less mobile animals will likely be the least

frequent to colonise new habitats. Animals with a greater mobility are found to be

more selective about the quality of food items than their less mobile congeners.

However, mobile species become less selective when their mobility threshold is

breached (Karieiva, 1982).

The invertebrate fauna examined by Arsuffi and Suberkropp (1989) ranked

fauna by their mobility capabilities, they demonstrated that the more mobile the

171

forager, the greater its ability to be more discriminate (Arsuffi and Suberkropp,

1989). The recruitment of fauna to drilled wooden blocks also revealed a mobility

gradient, with the most common recorded species from the drilled wooden blocks

being the most mobile to the least common fauna being sessile. Thus, more mobile

species will have a greater chance of occupying the available tunnel niche.

The level of complexity also had an influence upon the colonisation of the

drilled wooden blocks. This was demonstrated by the larger holes within the drilled

blocks, as they had the greatest number of species and diversity. It is likely that the

increased surface area of tunnels were less difficult to locate compared to smaller

tunnels.

The tunnelling of teredinids within the mangrove forests of the Tukang Besi

provides many niches within LWD. Thus teredinids increase microhabitat

heterogeneity due to their tunnelling action. It is the behaviour of the teredinids that

create a high complexity of tunnels that lead to a broad range of co-existing animals

within LWD. The activity of the Teredinidae within Indonesian mangrove forests

will increase the faunal diversity at whole ecosystem level and the fauna from the

teredinid-attacked LWD range in animals found in tropical terrestrial forests to sub-

tidal marine habitats in the mangroves from the WMP. Spatial heterogeneity is a

fundamental property of the natural world (Kostylev et al., 2005) and heterogeneity

within an ecosystem is a vital component for the interaction of co-existing animals

(Petren and Case, 1998; Gratwicke and Speight, 2005). By comparison structurally

simple habitats are not able to support the same levels of biodiversity when

compared with habitats consisting of high levels of complexity and rugosity (Levin,

1992).

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Chapter 6

BIODIVERSITY MAINTENANCE BY VACANT TEREDINID

TUNNELS

6.1 Introduction

In mature mangrove forests there are considerable quantities of large woody

debris (LWD) in the intertidal zone which are tunnelled by teredinids (Cragg, 2007;

Filho et al., 2008). These animals are prolific excavators of wood and through their

tunnelling they influence the flux of carbon in mangrove forests by the amount of

wood they process (Robertson and Daniel, 1989a; Filho et al., 2008). Within the logs

the numbers of teredinids can be huge (Distel, 2003). Teredinids will create a

complex mass of tunnels (Figure 6.1 a). The tunnels are cylinders that range in size

and diameter which taper to a small opening at the wood surface. However, many

openings emerge when wood is heavily tunnelled and the surface is broken open.

Teredinid death may support biodiversity as teredinids leave niches for animals to

exploit the vacant tunnels (Cragg and Hendy, 2010).

In general, mangrove forests are known to support biodiversity as an

ecosystem service (Kathiresan and Bingham, 2001; Nagelkerken et al., 2008),

provided by the huge amount of wood. Prop-roots belonging to the mangrove trees

Rhizophora provide cover to many vulnerable and small fish, which are drawn to the

complexity of the roots to decrease their risk of predation (Verweij et al., 2006).

However, at low tide this refuge may not be available. Animals living within

teredinid-attacked LWD probably do so to avoid predators. The main purpose for

seeking refuge for animals in cryptic habitats is to avoid predation (Ruxton et al.,

173

2004). Many animals seek refuge in teredinid-attacked LWD in the Wakatobi

mangrove forests (Cragg and Hendy, 2010). Two examples of animals found in

vacant teredinid tunnels were of particular interest, a fish Parioglossus interruptus,

and a spider Desis martensi.

In a study of the animals living within mangrove wood on islands of the

Tukang Besi Archipelago, Indonesia, the interrupted dartfish, Parioglossus

interruptus (Suzuki and Senou, 1994) and the intertidal spider, Desis martensi (L.

Koch, 1872) were commonly found within teredinid tunnelled wood (Figure 6.1 b

and c, Cragg and Hendy, 2010). Interrupted dartfish are also known from Iriomote

Island, Japan (Suzuki and Senou, 1994) and New Guinea (Rennis and Hoese, 1985).

Dartfish (Ptereleotridae) are bathypelagic gobioids inhabiting warm, temperate to

tropical tidal estuaries and mangrove forests throughout the Western Pacific and

Indian Oceans (McDowall, 2001). These fish typically occupy structurally complex

habitats such as seagrass beds or mangrove roots that provide protection from

predators as well as access to the zooplankton upon which they feed (Keith et al.,

2004). Desis martensi (Desidae) are known from Singapore. These spiders are

thought to forage for food at night and seek refuge in rock crevices and shells to

avoid tidal immersion (The Singapore Red Data Book, 2008). Desids have a wide

distribution spanning from the Galapagos to the South China Sea (Roth, 1967).

Both of these species are interesting due to their unusual nature; an aquatic

species, that frequently experiences episodes of emersion and an intertidal species

that frequently experiences episodes of immersion. Fish follow the ebbing tide out

(Sheaves, 2005) and wetland spiders migrate to higher elevations (Adis and Junk,

2002) to avoid emersion and immersion; however P. interruptus and D. martensi

174

remain within the Tukang Besi mangrove habitats throughout the complete tidal

cycle.

The mangrove forests belonging to the islands of the Tukang Besi

Archipelago experience large diel changes in water temperature, oxygen levels and

salinity (Taylor et al., 2005; Cragg and Hendy, 2010). Such rapid changes of salinity

and temperature are common with intertidal mangrove forests (Tomascik et al.,

1997). These environmental fluctuations may be buffered within the teredinid tunnel

niche. Dartfish and spiders may seek refuge within tunnelled wood for protection

from high temperatures, while avoiding desiccation as well as predation. This study

examined whether the niche provided by teredinid-tunnelled wood utilised by

dartfish and desids is critical for their distribution. This study tested the hypotheses

that dartfish and spiders 1. reduce their risk of predation by taking refuge in

teredinid-tunnelled wood at low tide, and 2. are protected by the tunnels from

extreme temperatures. This study describes a previously unreported cryptic, wood-

dwelling behaviour for dartfish and desids. In addition, this study also reveals the

biodiversity maintenance provided by the cryptic habitat of vacant teredinid tunnels

and assesses the significance of this behaviour in the autecology of the fish and

spiders.

Samples of LWD from the Langira forest were collected to determine the

abundance and distribution of fish and spiders during low tides. Numbers of dartfish

not in wood were quantified at high tide and foraging desids were searched for

during day and night time hours. Size comparisons of dartfish collected from within

wood and dartfish caught at hightide, not in wood were determined. Measurements

of dartfish and desid diameters and tunnels were compared to establish if they have a

close geometric fit within the tunnels.

175

Laboratory experiments investigating fish and spiders were conducted to

provide insights of their behaviour and ecology. Individual spiders were observed in

plastic tubs to determine if they emerge from tunnels during day time and night time

hours. Spiders were coaxed in to glass tubes to observe their leg arrangement when

inside teredinid tunnels. When inside the glass tubes, the spiders were immersed in

seawater to demonstrate the water-tight properties of their webs. Dartfish were

observed in aquaria that contain the calcareous linings of teredinid tunnels to

determine their behaviour within those tunnels. In addition, fewer tunnels were

placed into each aquarium than dartfish to determine if the fish bunch within the

tunnels. A range of different diameter tunnels were used in each aquarium to

establish if dartfish behaviour changes with increasing area of cryptic habitat. Using

data loggers, temperature was recorded within woody detritus. Ambient air

temperatures and water temperatures adjacent to each detrital sample containing

temperature loggers were also recorded. Temperature cooling in wood was examined

using a thermometer and a wind tunnel. To compare fluctuations of the temperature

data, inside and outside LWD, non-invasive temperature tolerance experiments were

used for P. interruptus. Critical Thermal Maxima (CTM) of P. interruptus

determined if their physiological temperature tolerance is suited to the changes of

abiotic temperatures within the mangrove environment.


6.2.1 Field studies

Samples of LWD, defined as wood pieces more than 20 mm in diameter,

were collected from all LWD encountered along eight transects in the Rhizophora

stylosa-dominated mangrove forest, Langira, Kaledupa Island. The transects

extended perpendicularly from the strandline extending out to the seaward fringe for

176

a mean distance of 380 m. A total of 196 pieces of LWD were collected from the

transects. These were split lengthwise and photographed to estimate the proportion of

wood removed by teredinid tunnelling, then broken open to remove all fauna

occupying teredinid tunnels. The same transects were used to estimate the abundance

and distribution of Desis martensi not in LWD during day-time (8am – 3pm) and

night-time (10pm – 3am) low tides. Dartfish (n = 188) and desids (n = 58) living

within the LWD were counted and measured (± 0.1 mm). Measurements of dartfish

in wood were compared with lengths of dartfish (n = 271) not in wood and caught at

high tide. The internal diameters of 1455 randomly chosen teredinid tunnels in LWD

from Langira were measured using callipers. Measurements of dartfish and desid

diameters (for fish, standard diameter recorded at the operculum base and for spiders,

the diameter of the abdomen was recorded) and tunnels were also compared.

Measurements of length and diameters were made from images of the sampled fish

and spiders using the digital analysis package ImageTool Version 3.00 (The

University of Texas Health Science Centre at San Antonio). Within this text D.

martensi body length refers to the cephalothorax + abdomen.

Numbers of free-swimming dartfish in tidal mangrove creeks and in the water

between Rhizophora prop roots fringing open water were counted by snorkel visual

census at high tide during day time and at night using a dive torch. During the day,

counts were made in belt transects measuring 25 x 4 metres placed at random along

creeks in the low- (n = 9), mid- (n = 9) and high intertidal (n = 9) areas of the forest,

and at night, transects (n = 4) were established in the same areas and tidal zones

respectively. Visual census was not extended beyond the fringing areas as densely

packed roots prevented access.

177

Temperatures inside tunnelled wood and in adjacent shallow tidepools were

measured (± 0.5 °C, hourly intervals) over a period of one month. The temperature

loggers, six Thermochron iButtons®

were placed in the mid- and low-intertidal areas

of the forest, 1.5 to 1.0 and less than 1.0 m above mean sea level, respectively for ten

days each.

To compare temperature fluctuation inside tunnelled wood and adjacent

ambient air accessible to sunlight-temperatures, loggers were used at 20 min

intervals for 20 consecutive days in the mid-intertidal zone. Within tunnelled wood

(n = 6) and adjacent exposed areas (n = 6), one logger was placed within a fallen log

and one logger was placed outside the log exposed to direct sunlight.

To determine the heights above sea level across the tidal gradients within

Langira the high tide marks on mangrove trees were recorded using high visibility

string. At low tide, the distance from the substratum to the mark on each tree was

measured and then subtracted from high-tide tidal-height to establish height above

sea level. Emersion times for the LWD were estimated by relating their tidal height

to data in regional tide tables.

6.2.2 Laboratory studies

Wood cooling

To replicate the temperature change of emersed fallen wood in the mangrove

forest a 60 x 20 cm Perspex wind tunnel was used to determine if evaporative

cooling occurred within LWD samples. The airflow-induced wind speed was 3 m

sec-1

. Cooling rates were recorded within and at the surface of teredinid tunnelled

wood approximately 64 cm3 in volume (n = 45). Using a calibrated thermocouple

thermometer (Oakton WD-35427-00 Temp 10 Type J), temperature changes were

178

recorded over 30 minutes within the wind tunnel. The thermometer had two

temperature probes; one probe was placed upon the wood surface and the other 3 cm

below the surface of the LWD sample. Within the wind tunnel, each wood sample

was placed on a mesh-box to ensure that all sides received equal air-flow.

Critical thermal maxima of dartfish

The upper thermal tolerance of dartfish was determined using groups of

twenty dartfish some with, and some without access to teredinid tunnels in three

aquaria. The dartfish were acclimated for 7-10 days at 27 or 35 °C. The low and high

acclimation temperatures chosen represent the approximate average temperature of

open water and representative high temperatures in tidepools around Kaledupa,

respectively (Taylor et al., 2005; Eme and Bennett, 2009a). The aquaria were placed

within a 95-L bath. The water in each aquarium was aerated by a linear air pump.

Approximately 30% of the water was changed daily. Heat in the bath was provided

by a 300 W glass AZOO® heater (AZOO, Taikong Corp, Taiwan), and water in the

bath was circulated using two AZOO® pumps. Dartfish were fed Sera

® Vegetarian

Diet flake food (Montgomery, PA, USA) once per day but not fed 24 h prior to the

critical thermal maximum (CTM) trials. Fish acclimated to 35 C were brought to

this constant acclimation temperature by increasing the water temperature 1.9 ± 0.9

°C d-1

for 4 d, and then held at this constant temperature for 7d. Fish acclimated to 27

C were held at this constant acclimation temperature for 7d.

Following 7 d of acclimation, each fish was exposed to a CTM trial which

consisted of a temperature increase of 0.3 °C min-1

until loss of equilibrium (LOE)

was observed. For each CTM trial, randomly selected fish were placed into 250-ml

Nalgene® beakers filled with clean seawater at appropriate constant acclimation

179

temperature. Beakers were suspended within a 20-L, insulated, recirculating water

bath and provided with moderate aeration to prevent thermal stratification. A

mercury thermometer (certified Fisherbrand® NIST) was used to monitor the

temperature in each beaker. Water temperature in the CTM bath was raised using

600-800W of aquarium heater wattage until final LOE was reached. LOE was

defined as the inability to maintain dorso-ventral orientation for at least one minute

(Beitinger et al., 2000). For trials with teredinid tunnels, fish were placed into CTM

beakers with a piece of calcareous lining from a teredinid tunnel measuring 3-5 cm in

length and kept at acclimation temperature at least 6 hours prior to the trial.

Following experiments, fish were released at their site of capture.

Dartfish behaviour observations

Ten dartfish were placed into each of four aquaria. Each aquarium contained

nine teredinid tunnels. Observations of dartfish locations were recorded hourly each

day during day-time (8am-3pm) and night-time (9pm-2am). After four days, the

dartfish in each aquarium were replaced three times with a new group of ten fish, and

given 24 hours to acclimate. All fish were released at their site of capture following

experiments.

Desid behaviour

Spiders collected from decaying logs were placed in plastic tubs with a small

piece of teredinid-attacked wood. To determine if spiders remained within wood day-

time and night-time observations were made. Observations for each spider were

recorded for 3 - 5 days. The total number of observation days for the desids was 75

days.

180

Fish and spiders were collected under permit LIPI

04/TKPIPA/FRP/SM/IV/2011. Animals in the laboratory studies were treated

according to a protocol approved by the University of West Florida, Animal Care

and Use Committee (reference #2010-002).

6.3 Data analysis

6.3.1 Field studies

One-way analysis of variance was used to compare the quantity of LWD

between the low, mid and high intertidal in the Langira mangrove forest. A two-way

ANOVA was used to compare the temperature within wood and adjacent tidepools at

night and day times when immersed and emersed. Regression analyses were used to

determine correlations between D. martensi body length versus the ratio of body

length to body width and to investigate correlations between wood and pool water/air

temperatures. Dartfish lengths were compared between fish collected from LWD at

low tide and fish collected at high tide, not in wood using a two-sample t-test. Paired

t-tests were used to compare animal abundance and distributions for fish and spiders

collected from LWD at low tide and fish collected at high tide between Rhizophora

roots and open channels. Chi-Squared tests were used to compare dartfish abundance

in wood with different levels of teredinid attacked wood defined by the percentage

surface area of tunnels and in areas of the mangrove forests with different emersion

times. Chi-Squared tests were also used to determine if desids prefer to remain in

LWD or venture away.

181

6.3.2 Laboratory studies

Analysis of Covariance (ANCOVA) was performed across the two

temperature treatments, 27 and 35C, with body mass as the covariate and CTmaximum

as the response variable. 1-way ANOVA was used to compare CTmaxima across

Figure 6.1 The tunnelled niche created by teredinids and fauna removed from

vacant teredinid tunnels. a, the prolific effect of the wood-boring teredinid activity

demonstrated by the extensive tunnels, b, a fully exposed dartfish. In the background

openings of tunnels within the fallen log can be seen created by the teredinids and c, an

exposed D. martensi individual removed from within its teredinid tunnel.

182

acclimation treatments and between tunnel treatments. Comparisons of day and night

time numbers of dartfish within tunnels were tested using Chi-Square tests. Tukey’s

Studentised Range (TSR) post-hoc test separated values into statistically distinct

subsets for all ANOVAs. Count data were square root transformed and all

measurements were log transformed. All statistical significance were determined

based on α = 0.05. Statistical analyses were performed using MINITAB (MINITAB

Inc, version 13.20).

6.4 Results

6.4.1 Temperature analysis

Mean temperatures measured within emersed wood were lower than in tide

pools adjacent to the wood (Figure 6.2 a-b: 2-way ANOVA, with wood/pool,

emersion/immersion and night/day as factors, F1,1272 = 61.68, p = < 0.001). This

difference was more marked in the mid intertidal zone (Figure 6.2 a). The

temperature differential between tunnels in wood and adjacent tide pools was most

marked when tide pool temperatures peaked (10am – 4 pm), which occurred at low

tide during day-time in the mid intertidal. Temperature lowering within wood was

most marked when tide pool temperatures peaked (Figure 6.2 c and d), which

occurred at low tide, during day-time (10am – 4pm) in the mid-intertidal when

compared with night time hours and immersed wood (Tukey’s pairwise

comparisons).

183

b

Temperature lowering in wood was most marked when temperatures of sun-

exposed wood substratum was emersed during low tide at day-times (10am – 4pm) in

the mid-intertidal (Figure 6.3, R-Sq (adj) = 0.69, F1, 1182 = 2646.25, p = < 0.001).

a

c

ab

cd d

e

b

d

23

24

25

26

27

28

29

30

Peak

day

Night Peak

day

Night

Emersed Immersed

Tem

per

atu

re (

°C) pool wood

a

c

a

b b

d

a

c

23

24

25

26

27

28

29

30

Peak day Night Peak day Night

Emersed Immersed

Tem

per

atu

re (

°C)

pool wood

y = -0.33x + 7.35

R² = 0.16

-7

-5

-3

-1

1

25 30 35 40

Dif

feren

ce (

°C)

wit

hin

wo

od

Temperature (°C) of tide pool

y = -0.42x + 11.32

R² = 0.52

-7

-5

-3

-1

1

25 30 35 40

Dif

feren

ce (

°C)

wit

hin

wo

od

Temperature (°C) of tide pool

Figure 6.2, Analysis of variance and regressions of temperatures recorded within

the Langira mangrove. a Temperature differences recorded at night (6 pm – 6 am)

and day (10 am – 4 pm) times during high and low tides within wood and tide pools

from the mid-intertidal zone (mean ± SE), and, (b) the low-intertidal zone. Letters

above the bars = Tukey’s pairwise comparisons, (c) the temperature differential within

the mid and (d) low zones between wood and tide pools.

Mid-intertidal Low-intertidal a

c d

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When tunnelled wood was subject to airflow, temperatures were slightly

reduced (approximately 1 degree C) at the surface, but by over two degrees C in the

tunnels (Figure 6.4). The rate of cooling was 6.7 times greater inside teredinid

tunnelled wood compared to the surface. The mean rate of cooling on the wood

surface was 0.03 ± 0.01 °C min-1

(mean ± SE, n = 45) and the rate of cooling within

the centre was 0.2 ± 0.01 °C min-1

.

y = -0.66x + 16.8

R² = 0.69

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

15 20 25 30 35 40 45

Dif

feren

ce (

°C)

wit

hin

wo

od

Temperature (°C) of ambient air

Figure 6.3, Variation in temperature differential between air and

wood recorded from Langira. Variation across the range of air

temperatures measured at Langira in the temperature differential between

interior of tunnelled wood and air outside the wood.

185

6.4.2 Parioglossus interruptus autecology analysis

The CTmaxima of dartfish acclimated to 35 °C, was significantly higher

compared to dartfish acclimated to 27 °C (Figure 6.5: ANOVA, with acclimation

temperature and tunnel position as factors; F1, 53 = 183.47, P ≤ 0.001). This is an

acclimation response of an increase of 1.8 °C, or 0.23 °C of tolerance for every 1 °C

increase in acclimation temperature.

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

0 5 10 15 20 25 30

Tem

per

atu

re d

iffe

ren

tia

l

(in

tern

al

- su

rfa

ce,

°C)

Time (min)

Figure 6.4, Wind-tunnel induced cooling of LWD. The temperature

differential between the surface and centre of tunnelled wood samples (n =

45) over 30 minutes (mean ± SE).

186

Very few of the teredinid tunnels had a smaller diameter than the dartfish,

and most dartfish had diameters that overlapped the diameter range of the most

numerous tunnel sizes (Figure 6.6 a). The lengths of dartfish collected at high tide,

not in LWD tended to be longer than that of dartfish collected from within wood at

low tide, 2.6 ± 0.02 cm (mean ± SE, n = 271) compared with 2.1 ± 0.03 cm (n = 188)

respectively (Figure 6.6 b: Two-Sample t-test; dartfish at high tide vs. dartfish in

wood, t = 14.48, P ≤ 0.001).

40

40.5

41

41.5

42

42.5

43C

riti

cal

Th

erm

al

Ma

xim

um

(°C

)

No tunnels Tunnels

35°C

27°C

Figure 6.5, Critical thermal maxima of dartfish. Fish acclimated to 27 °C

and 35 °C had no difference of temperature tolerance with or without out

tunnels. Significant differences of temperature tolerance between acclimated

fish to 27 °C and 35 °C were found (mean ± SE).

187

0

5

10

15

20

25

30

35

40

45

50

Fre

qu

ency

(%

)

Diameter (mm)

Tunnel

Dartfish

0

5

10

15

20

25

30

Fre

qu

ency

(%

)

Length (cm)

in wood

in water

a

b

Figure 6.6 Measurements of dartfish and teredinid tunnels. a, Size distributions

of dartfish diameters (n = 168) compared against teredinid tunnel diameters (n =

1455), b, Size distributions of dartfish removed from woody detritus (n = 188) at low

tide and dartfish (n = 271) captured during high tide between prop-root systems.

188

Analysis of the LWD samples revealed that wood with a higher percentage

surface area of teredinid tunnelling had a greater frequency of dartfish occupying the

vacant tunnels (Figure 6.7: Chi-Squared P ≤ 0.001).

The degree of tidal emersion also affected the degree of LWD occupancy of

dartfish (Figure 6.8). With increasing emersion time (h), the amount of wood

occupied by dartfish was reduced. The greatest proportion of wood occupied by

dartfish was collected in areas of the forest with less than five hours of emersion

(Chi-Squared P ≤ 0.001).

97

34

36

17

12

0

5

10

15

20

25

30

35

40

45

< 20 20 - 35 35 - 50 50 - 65 > 65

% O

ccu

pie

d b

y d

art

fish


Figure 6.7, Samples of teredinid-attacked LWD categorised by the level of teredinid

activity imposed upon each woody detrital sample. The percentage of total woody items

(n = 196) occupied by dartfish. Numbers above the bars indicate the number of detrital

samples analysed.

189

Estimated abundances of dartfish during high tide within the Langira forest

were significantly higher from between the root structures (11433 ± 1690.7 fish ha-1

,

mean ± SE) than abundances of dartfish from the channels (222 ± 155.5 fish ha-1

,

Paired t-test: open channels vs. roots, t = -5.57, P < 0.001). No dartfish were found

between roots or in open channels during high tides at night-time (10 pm – 3am).

The numbers of dartfish estimated to be in LWD during day-time low tides in the

Langira forest were 4304 ± 805. 7 fish ha-1

.

Observations of fish in aquaria containing pieces of teredinid tunnel linings

revealed a marked and significant difference of use of the tunnels between day and

night time. The majority of night-time observations of fish location were of fish

within the linings (88.2%) while the majority day-time fish location observations

11

83

44

22 36

0

5

10

15

20

25

30

< 5 5 - 7 7 - 9 9 - 11 > 11

% O

ccu

pie

d b

y d

art

fish

Period of emersion (h)

Figure 6.8, The variation of dartfish occupying LWD removed from the forest in

areas exposed to different periods of emersion (hours). With decreasing emersion,

LWD (n = 196) containing dartfish increase. Numbers above the bars indicate the

number of detrital samples analysed.

190

were of fish free in the water (84.4%) (percentages relate to 4200 observations each

for day and night time conditions, Chi-Squared, P< 0.001).

6.4.3 Desis martensi autecology analysis

Desis martensi were not observed outside wood during lowtide from transects

(n = 8) totalling 1.6 ha within the Langira forest either during day time hours or night

time hours. The D. martensi population density within teredinid attacked LWD was

1161 ± 587 (mean ± SE) individuals per ha within the Langira forest.

Laboratory observations of D. martensi distributions revealed that over 95 %

(n = 21) of the total individuals remained within teredinid-attacked LWD (Paired t-

test, in tunnels vs. foraging: p = < 0.001). Of the 22 observed individuals, 1 specimen

ventured outside from within its tunnel. No significant difference (Chi-Squared, P =

0.699) was found with D. martensi distributions between night and day-time

observations.

The largest proportion of desids were found in decaying logs in areas of the

mangrove forest immersed in water 15 – 20 hours per day during a spring high tide

(Figure 6.9). The shortest immersion times of LWD containing individuals of D.

martensi was 5.6 hours per day and the longest immersion time was estimated to be

21.9 hours per day.

191

Size frequency analysis of the desid populations revealed that the most

common diameter was between 1-2 mm. The smallest individual found within the

detrital samples measured 0.6 mm, and the largest specimen measured 4.5 mm in

diameter. When compared with size ranges of teredinid tunnel diameters (Figure

6.10), the size distributions of spiders had a similar fit to the majority of tunnel

diameters.

0

10

20

30

40

50

60

70

80

90

0 - 5 5 - 10 10 - 15 15 - 20 >20

Pro

port

ion

(%

) o

f D

. m

art

ensi

pop

ula

tion

Immersion (h)

0

10

20

30

40

50

60

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 > 14

Fre

qu

ency

(%

)

Diameter (mm)

Tunnels Spiders

Figure 6.9, Proportions of the desid population found in LWD in areas of the

forest subject to a range of immersion times. Desid individuals removed from

teredinid-attacked LWD from Langira.

Figure 6.10, The size ranges of desid and teredinid tunnel diameters. Size

distributions of D. martensi individuals (n = 58) removed from teredinid-attacked

woody detritus (n = 82) compared against teredinid tunnel diameters (n = 1455).

192

Replicating teredinid tunnels, desids coaxed in to glass tubes revealed that

their legs I, II, and III bunch anteriorly, and the posterior legs “leg IV” are positioned

directly behind of the opisthosma (Figure 6.11 a) . Figure 6.11 b, reveals a D.

martensi individual with a body length of 12 mm (19.4 mm including legs) turning

180° inside an 8 mm diameter glass tube. D. martensi also have dense scopulate

(bush-like) plumose hairs on each tarsus and metatarsus (Figure 6.11 c), which

probably provides an increase in surface area enabling D. martensi to have the ability

to walk on water (Figure 6.11 d).

Figure 6.11 Images of D. martensi illustrating morphological characteristics. a, The body

and leg arrangement of D. martensi in a constricted space (dorsal view), and b, a D. martensi

(12 mm body length) turning 180°C with ease within an 8 mm glass tube, c, an S.E.M image

of dense scopulate plumose hairs on the leg I tarsus of D. martensi and d, an individual of D.

martensi walking on water.

193

Regression analysis of body length vs. body/width revealed a significant

correlation (F1, 40 = 26.05, p = < 0.001, R-Sq = 0.39). As D. martensi develop from

juveniles in to adults they become more elongate (Figure 6.12).

6.5 Discussion

The effects of teredinid activity may extend after death as the solid wood

becomes riddled with tunnels that can be exploited by other organisms. The use of

teredinid tunnels by dartfish is an unusual and virtually unknown behaviour among

fishes. Juvenile morays, Gymnothorax richardsoni have also been reported to

occasionally occupy tunnelled wood, as do a range of marine invertebrates and

terrestrial arthropods (Cragg and Hendy, 2010). In tropical Atlantic mangrove

ecosystems, the mangrove rivulus, Kryptolebias marmoratus exploits galleries

created by terrestrial insects in decaying mangrove logs (Taylor et al., 2008); a

y = 1.27x + 2.47

R² = 0.39

0

10

20

30

40

50

60

0 2 4 6 8 10 12 14

Ra

tio

(b

od

y l

eng

th/w

idth

)

Body length (mm)

Figure 6.12, The change in body proportions of D. martensi

individuals. The regression demonstrates the ratio of body length and

width against the body length.

194

similar niche, but distinctly higher in the intertidal than the teredinid-tunnelled wood

examined in this study. Indeed, the mangrove rivulus are amphibious even to the

point of foraging on land and may also emerge under damp leaf litter, in crab tunnels

and beneath plastic debris (Davis et al., 1995; Taylor et al., 2008). Dartfish,

however, appear specifically bound to the teredinid-tunnel niche as no other refuge

besides decaying wood was available. In addition, dartfish occupy the tunnel niche

during low tides, which result in those exposed logs and the adjacent tidepools to

experience rapid fluctuations in temperature (minutes to hours). Indeed, mangrove

forests frequently have large-diel fluctuations in temperature (Taylor et al., 2005).

However, the Tukang Besi islands have a diverse array of hyperthermic fishes

common to the Indo-Pacific region, and mangrove forests in this area contain many

fishes with unusual behaviour (Bennett, 2010).

Dartfish show similar thermal tolerance values to many shallow water fishes

in the Tukang Besi islands, particularly tidepool-resident goby species (Eme and

Bennett, 2009a), as they exhibit approximately twice the acclimation response of

tidepool-resident gobies from around Kaledupa Island. Dartfish also have critical

thermal maxima that are higher than those of reef fish species (Eme and Bennett,

2009b; Bennett, 2010). Thus, the dartfish’s thermal biology is that of a robust,

shallow-water fish that has an upper thermal tolerance sufficient to deal with

temperatures above 40 C. However, dartfish may obtain environmental buffering by

avoiding the warmest tidepool temperatures by taking refuge within the cooler vacant

teredinid tunnels. Dartfish would probably have a lower resting metabolic rate inside

the vacant tunnels. Avoiding the most extreme fluctuations in tidepool temperatures

allows for a relatively stable thermal environment. As temperatures become lower

195

within the tunnels the fish may also benefit from evaporative cooling, making

desiccation within LWD unlikely for dartfish.

Considerable numbers of vacant teredinid tunnels were observed within LWD

from the shore to the seaward edge of the mangrove forest. Dartfish probably use

teredinid tunnels to avoid moving into open water during the ebbing tide, therefore

the tunnels may provide a novel predation refuge. Within teredinid-attacked wood,

dartfish occlude the majority of teredinid tunnels; maintaining a close geometric fit

within this cryptic habitat may reduce predation risks as larger predators are not able

to access dartfish within the narrow tunnels. Dartfish will bunch within teredinid

tunnels during the night time. Similar behaviour described as log packing was

reported with K. marmoratus in decaying logs attacked by termites and coleopteran

larvae (Taylor et al., 2008). Dartfish bunching in groups within teredinid tunnels may

reduce their risks of predation, as higher numbers of fish will plug the teredinid

tunnel and may prevent access by predators.

Length measurements of dartfish reveal that the populations removed from

decaying logs were smaller than those caught from between the roots at high tide.

Thus, the more vulnerable smaller individuals in a population are more likely to seek

refuge in wood, and the larger fish make less use of these cryptic refugia.

Furthermore, adult dartfish range up to 3 cm in length (Allen et al., 2003), suggesting

that the smaller dartfish found in the LWD represents an important refuge function

for the vulnerable smaller stages of this species in mangrove forests. It is likely that

the dartfish found in LWD belong to the same population of fish that is found

between the roots and open channels during high tide. Thus, estimates of fish density

in LWD at day-time low tides indicate that almost 40% of dartfish from the Langira

mangrove seek teredinid-attacked LWD. Observations of dartfish swimming at high-

196

tide during night-time revealed zero encounters during extensive surveys of the

mangrove forest. This corroborates our laboratory experiments, which showed that

88% of dartfish were observed within the refuge of teredinid tunnels during night-

time.

During high tide, large numbers of dartfish were frequently seen swimming

in schools between and around the complex Rhizophora root-systems. Other authors

report that small and juvenile fish reduce their risk of predation by hiding among the

mangrove roots (Laegdsgaard and Johnson, 2001; Verweij et al., 2006; MacDonald

et al., 2009). Although dartfish use teredinid tunnels to avoid being carried in to

permanent mangrove creeks or being stranded on mud flats, it appears that they do

follow the ebbing tide out to the outermost seaward edge of the forest. Fallen wood

exposed at low tide at the seaward edge of the forest would have the least exposure

to high temperature fluctuations meaning that the cryptic dartfish have less

probability of desiccation due to lower emersion times, which may explain the higher

numbers of dartfish found in wood at the seaward fringe.

Non-aquatic, intertidal species such as Desis martensi are challenged by

immersion. Many species of spiders live in aquatic ecosystems such as saltmarshes

(Morse, 1997; Petillon et al., 2008; Petillon et al., 2009), and flood plains

(Rothenbucher and Schaefer, 2006) but spider ecology has not been studied in

mangrove ecosystems.

Commonly within the LWD, nests created by D. martensi were found

containing juveniles along with adults in groups from 2 – 5. No foraging desids were

found away from teredinid tunnels at low tide in the forest at day or night times.

However, D. martensi have been reported to forage on the shore at low-tide during

night-times in intertidal regions found in Singapore (The Singapore Red Book,

197

2008). Remaining in tunnels will provide relative safety for the spiders, and the wood

may provide an important energy subsidy; due to high levels of fauna (see chapter 5;

Cragg and Hendy, 2010), which acts as a prey aggregation device.

When in the tunnels, D. martensi produces a water-proof web that protects

them from being immersed. Within wetland habitats spiders either migrate to the

shore or move to higher ground in order to avoid immersion. For example, Pirata

hygrophilus (Lycosidae) will climb trees to avoid immersion (Adis and Junk, 2002).

However, for Desis remaining in teredinid-attacked wood may also reduce the risk of

being predated. Being exposed and visible to predators will have obvious risks,

especially in less complex environments (Marczak and Richardson, 2007). Desis also

prefers to remain in LWD found in the low intertidal, where there is a greater level of

the tunnel niche due to increased teredinid activity in the low-intertidal. Furthermore,

due to high availability of the many tunnels in the low intertidal, there may be a high

level of prey items for the spiders.

D. martensi may also use the LWD to avoid extreme temperatures, therefore

reducing their risk of desiccation. During low tide, day time ambient air temperatures

within the mangrove forest peaked at more than 40°C. During the same time the

internal temperature of LWD was recorded below 30°C, a difference of more than

12°C. Spiders are more abundant and active in cooler, shaded areas within their

environment (Riechert and Tracy, 1975). Extreme temperature may be a limiting

factor for the foraging capabilities of spiders. Spiders prefer cooler areas with less

prey items than areas of increased temperatures with higher densities of prey

(Riechert and Tracy, 1975). Thus, the cooler temperatures within wood coupled with

the high level of prey items provide an avoidance strategy from high temperatures

combined with an enhanced exposure to food items. The benefits of avoiding adverse

198

temperatures and having plenty of prey items at your doorstep highlight teredinid-

attacked LWD as an ideal habit for D. martensi.

Very few spiders are obligately aquatic. Those that are show a range of

interesting adaptations, Argyroneta aquatica, is an air-breathing spider that spends

the majority of its life submerged in freshwater habitats (Seymour and Hetz, 2011).

A. aquatica builds a dome-shaped web between aquatic plants. The spider fills the

dome-web with air carried from the surface by use of a plastron, hydrofuge hairs that

trap air bubbles. The air-filled dome can take up dissolved O2 from the surrounding

water acting as a physical gill; pO2 diffuses from the water and through the web in to

the spiders nest (Seymour and Hetz, 2011). Terrestrial spiders also have this ability

to build underwater webs that have similar properties to an anatomical gill (Rovner,

1987). Dysdera crocata and Ariadna bicolor are both terrestrial spiders that have the

ability to survive underwater for up to ten days when in their nests (Rovner, 1987).

Nonetheless, for the intertidal specialist Desis marina, the physical gill effect did not

increase their survival time when underwater as these desid species are found living

within their web nests in the holdfast cavities of kelp - which have adequate air

supplies (McQueen and McLay, 1983 cited in Rovner, 1987). When out of water, D.

marina has been reported to venture out of their kelp holdfasts and forage for food

(Rovner, 1987), though this present study suggests this may not be necessary. Unlike

D. marina, D. martensi may likely be obligate to decaying wood as they appear not

to venture out of the teredinid tunnels when their woody habitat is emerged.

More than 40% of desids within teredinid-attacked LWD were between 1 - 2

mm. The maximum sizes of desids ranged up to 4 – 5 mm diameter. This suggests

that Desis martensi has a life history strategy centred on strong parental care, with

lots of energy invested in to its young. D. marina individuals from a rocky shore in

199

New Zealand laid eggs from September – January, and hatching is complete by May

(McLay and Hayward, 1987). The first two instars after hatching remain in the nest

until July – August. It was also noted that female D. marina laid 3 to 4 eggs (McLay

and Howard, 1987). Thus, the common frequency and occurrence of 2 – 5 individual

D. martensi, usually 1 adult with 2 – 4 juveniles within teredinid tunnels from

Langira suggest that D. martensi have a similar reproductive strategy to D. marina.

D. martensi are physically and morphologically adapted to their intertidal

habitat within teredinid tunnels. These data demonstrate that as D. martensi mature

from juveniles to adults they become increasingly longer than wide; producing

elongate body morphology. Other authors state that the body, cephalothorax and

opisthosoma of D. martensi is longer than it is wide (Roth, 1967). The elongate body

structure is the ideal shape for living within a vacant teredinid tunnel. Moreover,

similar to dartfish, desids also occlude the most frequent size ranges of teredinid

tunnels. When the spiders enter teredinid tunnels they adopt a constrained leg

arrangement making a narrow stance within the tunnel. When in the tunnels the

anterior limbs, legs I, II and III are forward positioned. In addition, the anterior limbs

have tarsal trichobothria, sensory hairs (Roth, 1967), that may aid for prey capture

when the spider is in its tunnel. D. martensi presumably waits in ambush within its

tunnel for small crustaceans such as cirolanids and/or taltrids to come in to contact

with the long sensory hairs on the anterior legs which may in turn trigger D. martensi

to strike.

The spiders have other diagnostic features and characteristics that make life

within teredinid-attacked LWD easier. D. martensi have a malleable body. Spider

flexibility is not uncommon (personal communication, Dr Hannah Wood). The

flexible turning ability within narrow diameter tunnels is advantageous for D.

200

martensi as it enables them to turn with ease within narrow tunnels when hunting

prey items. Suitable tunnel location is also essential. The complex inter-twining

teredinid tunnels within fragmented decaying wood when emersed can be water-

filled and/or drained, closed off by either sediment or from the calcareous cap the

teredinids produce at the distal end of their tunnels or from other predators. Thus, the

ability to be hyper-flexible and remaining mobile is a huge advantage in order to

avoid potential risks within teredinid tunnels, such as immersion or being predated

upon.

D. martensi have large tracheae confined to the abdomen (Roth, 1967).

Desids are aquatic and amphibious, and their tracheae are important adaptation to

being able to spend many hours immersed (Selden, 2001). More than eighty percent

of D. martensi populations within the Langira mangrove forest are immersed for

more than eighteen hours per day during spring high tides. It has been hypothesised

that the tracheae are more efficient than other respiratory organs, such as book lungs

in preventing water loss from spiders (Levi, 1967); this is vital for D. martensi as the

saline environment may increase osmotic stress (Gross, 1957; Pierce, 1982;

Gimenez, 2003). D. martensi also possess heavily scopulate plumose hairs, which are

dense bush-like hairs at the tips of their legs. The scopulate plumose hairs may

enhance D. martensi’s ability to walk on water; an advantageous ability for an

intertidal animal within an aquatic environment.

This study is the first to report a likely obligatory exploitation by a fish and a

spider of an intertidal niche provided by teredinid tunnels and unequivocally reveals

the fundamental role of the Teredinidae in niche creation. Vacant teredinid tunnels

provide a novel ecosystem service within LWD in seaward mangrove forests. This

study also demonstrates that seeking environmental buffering by remaining cryptic

201

within teredinid tunnels is an important issue for these species. Lastly, the

exploitation of LWD by dartfish and desids emphasises the detrimental impact of

forest harvesting. Mangrove forests that are logged will likely impact the abundance

and distribution of dartfish and desids in Indonesian mangrove forests, as well as

numerous other cryptic, wood dwelling organisms.

202

Chapter 7

GENERAL DISCUSSION

The mangrove forests in the WMP are connected to sea grass beds and coral

reefs. Such connectivity of important ecosystems has rarely been studied in

Indonesia (Tomascik et al., 1997). These ecosystems are important for their nursery

function (Xavier et al., 2012), and flow of energy between the habitats (Granek et al.,

2009). Indeed, damage to these ecosystems, whether natural or anthropogenic, will

disrupt the flow of nutrients across the ecosystems and reduce the biodiversity. The

most biologically diverse substratum in the WMP mangrove forests is large woody

detritus (LWD), in particular LWD that had been attacked by teredinids. These items

of LWD provide a spatial subsidy that permits fish to remain in the mangrove forests

at low tide and non-aquatic animals to remain at high tide. Remaining within the

mangrove forests limits migrations, therefore remaining within the forests may

reduce predation risks (Wang et al., 2009), particularly for vulnerable species and

juveniles. LWD within the forests provides alternative refuges for the mangrove

fauna if the complexity of the mangroves has declined (Sheaves, 2005).

If the rate of wood harvesting within Indonesian mangrove forests continues

then this may have a direct threat to the abundance and distribution of fauna that

depend upon the vacant teredinid tunnels within LWD. Fallen wood is an important

resource within the mangrove forests, and the tunnelling of teredinids enhances the

habitat complexity. Chapters 3, 5 and 6 reveal that teredinids are ecosystem

engineers. Chapter five demonstrated that increases of habitat complexity driven by

teredinids can positively affect ecosystem-level species-richness. To increase species

richness at ecosystem level the engineering species must create conditions not

203

present elsewhere in the landscape and other animals must be able to live only in the

engineer-created patches (Wright et al., 2002). This means that for an animal to be

considered as an ecosystem engineer, species other than that of the engineering

species must be obligate to the habitat created by the ecosystem engineer; such

animals are discussed in Chapter Six.

Chapter six demonstrated that vacant teredinid tunnels within LWD are used

by many animals within mangrove forests in the WMP, including juveniles and

vulnerable species. Thus, LWD enhances biodiversity maintenance and predation

refuges in mangrove ecosystems, as a large proportion of individuals exploit this

resource. The role of mangrove forests as a predation refuge may be a consequence

of the relationship between habitat complexity and predation success (MacDonald et

al., 2008). The success of juvenile and vulnerable animals in mangrove habitats are

due to the increased niche availability, which reduces predator-prey interactions

(Warfe and Barmuta, 2004; Saha et al., 2009).

Within natural undisturbed ecosystems, teredinids may be considered as

ecosystem engineers. Ecosystem engineering accounts for the interaction between an

organism and its environment. The engineering species activity results by directly or

indirectly transforming the availability of resources to other species (Jones et al.,

1994). Ecosystem engineers modify their environment by creating changes in biotic

or abiotic materials, which will ultimately result in the modification, maintenance

and creation of new habitats or niches leading to increased habitat heterogeneity

(Jones et al., 1994; Wright et al., 2002; Berkenbusch and Rowden, 2003). Although,

in areas of marine environments that necessitate the use of man-made wooden

substrata teredinids are considered as pests because they incur much damage to

wharfs and pilings (Laverty, 2002). However, the findings reported in parts of

204

chapters three, five and six suggest that teredinids are ecosystem engineers within the

seaward edge of mangrove forests of the Tukang Besi as they break down large

volumes of LWD, increase ecosystem-level biodiversity of these otherwise species-

poor habitats (Duke et al., 2007) and create a predation refuge for vulnerable and

juvenile animals. Thus, the abundance and distribution of the fauna dependent upon

LWD may be affected by harvesting of the mangrove wood (Donato et al., 2011).

The biodegradation of LWD by herbivory and decay within the mangrove

ecosystems serves as the basis for an elaborate food-web. A consortium of organisms

break down the fallen trees in the WMP mangrove forests. Such organisms range

from coleopterans, termites, basidiomycetes and teredinids. These organisms process

much of the fallen trees that enter the detrital food-chain, recycling the organic

carbon back into the ecosystem. LWD will increase habitat complexity (O’Connor,

1991), nutrient enrichment from mineralisation (Gulis et al., 2004), and enhance

deposition and stabilisation of fine sediments (Diez et al., 2000; Haschenburger and

Rice, 2004). Within the mid- to low- intertidal areas of mangrove ecosystems,

teredinids have a key role in the mechanical-breakdown of LWD (Robertson and

Daniel, 1989a; Kohlmeyer et al., 1995) as they enhance the recycling of nutrients

after they have processed the fallen wood (Robertson and Daniel, 1989a).

Recent research has highlighted the fact that mangrove forests are under

threat, with an estimated 1 – 2 % each year disappearing globally as a result of wood-

harvesting practices (Duke et al., 2007; Donato et al., 2011; Lewis et al., 2011),

mainly due to production of prawn farms (Martinez-Alier, 2001). Of the 146,500 km2

of global mangrove forests, 34,931 km2

or 23.8% are located in Indonesia (Spalding

et al., 1997). It is estimated that more than 31% of Indonesian mangrove forests have

disappeared in the last 30 years (Wilkie and Fortuna, 2003). Thus, more than 1 % of

205

Indonesian mangrove forests are being cleared every year with no sign indicating

that it is reducing. Indeed, mangroves cleared for prawn farms incur much damage to

the natural environment with declines of invertebrates and fish due to the loss of

habitat from uprooted mangrove trees (Martinez-Alier, 2001). The loss of ecosystem

services as a result from forest harvesting will be reduced predation avoidance for

juvenile fish and invertebrates and reduced deposition of fine sediments as

mangroves stabilise sediments. Thus, forest harvesting will decrease species richness

and increase water turbidity of adjacent ecosystems. Of the mangrove forests

surveyed from this study the greatest impact was found in the Laulua forest (Figure

7.1 a). This forest was heavily cleared with vast areas of bare substrata, and

mangrove forest dead-zones with no fauna observed compared to undisturbed areas.

Within the WMP mangrove forests, local demand of mangrove-derived materials for

artisanal fishing and construction is great (Cullen, 2010). The harvesting of

mangrove wood may lead to a socio-economic issue. Livelihoods are dependent

upon fish catches, meaning that the maintenance and up-keep of fish catching

devices is necessary (Figure 7.1 b). Thus, the WMP mangroves are under constant

harvesting pressure (Figure 7.1 c and d). This harvesting will lead to an ecological

negative feed-back loop, as the harvesting of mangroves will impact the biodiversity,

therefore human livelihoods will decline (Martinez-Alier, 2001).

206

Global warming may also be a threat to mangrove forests (Mcleod and Salm,

2006). Melting polar-ice leading to rising sea levels, and increasing atmospheric CO2

concentrations leading to decreasing seawater pH (Fabry et al., 2008; Doney et al.,

2009), may impact the forests (Kjerfve and Macintosh, 1997; Mcleod and Salm,

2006). Studies on the impact of mangrove forests on global warming is focused upon

the inland migration of mangrove forests driven by rising sea levels (Ellison, 2000),

erosion and increased immersion to mangrove plants (He et al., 2007; Yusef and

Figure 7.1 Mangrove forest clearing and wood harvesting within the WMP. a, large exposed

areas of bare sediment from the aftermath of up-rooting trees in the Laulua mangrove forest, b, an

artisanal fishing method, a fish fence constructed from mangrove wood, c, Bruguiera saplings cut

and put in bundles ready to be collected to make fish fences and d, a store of harvested mangrove

wood removed from the WMP mangrove forests.

207

Francisco, 2009). However, the impact of global warming upon the biodegradation

processes within mangrove ecosystems has not been considered. Sea-levels for the

year 2050 are estimated to increase by 0.4 metres (McInnes et al., 2003), therefore

consequences upon the distributions of trees and biodegrading organisms may alter

the ecology of those habitats.

In the case of the Galua and Laulua forests, the boundaries between terrestrial

and marine biodegradation processes from Laulua and Galua were recorded at 1.82 ±

0.05 and 1.89 ± 0.01 meters above sea level respectively. However, an estimated rise

in sea level of 0.4 metres by the year 2050 means that the boundary between

terrestrial and marine wood degrading organisms within Laulua and Galua is

predicted to be ≤ 2.22 and 2.29 meters above sea level respectively (Figure 7.2).

208

0

1

2

3

4

0 100 200 300 400 500 600 700 800 900

Hei

gh

t a

bo

ve

sea

lev

el (

m)


Predicted biodegradation boundary 2050

0

1

2

3

4

0 20 40 60 80 100 120 140 160 180 200 220

Hei

gh

t a

bo

ve

sea

lev

el (

m)


Predicted biodegradation boundary 2050

a

b

Figure 7.2 The present day biodegradation boundaries in two mangrove forests of the WMP with predicted boundaries in 2050. a, the shore height

profile of Galua; and, b, Laulua, the black dashed line represents the present day estimated boundary of biodegradation of LWD between terrestrial and

marine organisms driven by emersion time, and the dashed red line represents the estimated biodegradation boundary at the year 2050.

Biodegradation boundary 2010

Biodegradation boundary 2010

209

As Figure 7.2 illustrates, the threat to Indonesian coastal and intertidal areas

from global warming is sea level rise - with the greatest impact imposed upon

mangrove ecosystems (Gilman et al., 2008; Yusef and Francisco, 2009). The range

of projected sea-level rise is under some conjecture with estimated ranges between

0.1 – 0.4 m above present day levels for 2050 (Michener et al., 1997; McInnes et al.,

2003; Bosello et al., 2007). The majority of research of sea-level rise in mangrove

forests is focused upon the upper and lower limits of potentially changing mangrove

forest distribution (Ellison and Stoddart, 1991; Mcleod and Salm, 2006; Yusef and

Francisco, 2009). The distribution and community structure of biodegrading

organisms discussed in chapter three within the Galua and Laulua forests will be

altered. As a consequence, this may alter the breakdown pathways and flux of

nutrients from LWD available to other consumers.

In the event of rising sea-levels, the breakdown of lignin by the activity of the

basidiomycetes in the terrestrial region of the Galua forest will no longer be possible

due to increased salinity caused by the rising seawater. The slow depolymerisation of

lignin by white-rot and brown-rot decay (Worrall et al., 1997), will not take place in

the landward regions of the Galua forest.

The hypothesis of the landward retreat of mangrove plants as an adaptation to

rising sea-levels (Gilman et al., 2007; Gilman et al., 2008; Yusef and Francisco,

2009) does not apply with some of the forests within the WMP, as fossil-coral walls

crown the shorelines of the archipelago making mangrove recruitment unlikely.

Increasing sea-levels will also increase immersion times for LWD in the

intertidal regions of the WMP. This change would probably drive teredinid

populations further into the high intertidal zone by increasing exposure of larval

teredinid veligers to areas where there are greater volumes of LWD. The rise in sea

210

levels would probably decrease the abundance and distribution of the coleopteran

larvae and termite communities within the intertidal regions due to increased

exposure to immersion. The breakdown processes of LWD and how the

consequently generated organic carbon may then be re-introduced back into the

forest may be drastically altered by shifting wood biodegradation processes driven by

rising sea-levels.

Mangrove forests such as those from this study will likely be sensitive to

rising sea-levels due to their inability to migrate landward. If the rate of sea-level rise

is greater than the rate of change in forest surface elevation, then this would hinder

the landward retreat of trees (Gilman, 2004; Gilman et al., 2007). The landward

succession of trees would likely depend upon the ability of those trees to colonise

new habitats such as increasing shore height elevation (Gilman et al., 2007).

However, many of the forests discussed within the chapters of this research have a

landward boundary characterised by fossil-coral walls. Thus, any potential landward

migration of those forests would not be possible. The lack of landward migration,

coupled with elevated rises in sea levels would likely have adverse consequences for

the re-distribution of the biodegradation processes that breakdown the LWD.

Increasing levels of atmospheric CO2 are also linked to global warming,

further contributing to problems within marine environments such as coral reefs

(Hoegh-Guldberg et al., 2007; Doney et al., 2009) and calcium carbonate-producing

organisms (Parker et al., 2009). Although, increasing atmospheric CO2 may have

significant ecological problems for coral reefs and animals such as oysters, such

consequences have not been considered for teredinids within mangrove forest

environments. The biodegradation boundary of LWD in mangrove forests between

terrestrial and marine processes would be changed. The effect of decreased pH upon

211

teredinid populations will have complications for their life histories and ecology due

to a reduction of their calcareous hard-parts.

This is evident with other biogenic calcium carbonate secreting organisms

such as hard corals as they undergo a reduction of calcification, with loses of 20-60%

when exposed to partial pressures that reach levels of 560ppmv which is double pre-

industrial CO2 concentrations (Guinotte and Fabry, 2008). Atmospheric partial

pressures of CO2 may increase from the present day levels of 380ppmv, to

concentrations of 700ppmv by the end of the century (IPCC, 2001 and 2007). The

primary concern of an elevated pCO2 in seawater is a net decrease of calcium

carbonate saturation, which greatly alters the calcification rates of biogenic calcium-

carbonate producing organisms such as molluscs (Royal Society, 2005). These

changes create a change in seawater chemistry by decreasing the pH; generating a

more acidic marine environment (Fabry et al., 2008; Jokiel et al., 2008; Ries et al.,

2009).

Experiments manipulating decreased pH levels in seawater demonstrated that

calcifying species experienced reduced calcification rates. Oyster larvae exposed to

seawater with decreased pH concentrations displayed malformed shells (Kurihara et

al., 2007; Parker et al., 2009). The bivalves Mytilus edulis and Crassostrea gigas

both exhibit declines of calcification with increasing pCO2 levels of 25 and 10%

respectively (Gazeau et al., 2007). The emphases of these studies indicate that the

early life history strategies of bivalve molluscs are greatly compromised by acidic

oceans (Kurihara et al., 2004). The increased de-calcification rates of oysters and

mussels can be reflected to other bivalve molluscs such as the Teredinidae. If the

shells of the teredinid veliger are greatly compromised, successful recruitment within

LWD would not be possible – making survival unlikely as the postlarval shell is

212

needed for burrowing (Turner, 1976). Upon development, proteinaceous and

calcareous material is added to the juvenile teredinid shell, which has teeth-like

projections used for rasping. Teredinids also produce calcareous pallets - exclusive to

the family (Turner, 1966). Teredinid boring rates ranges from 0.03 to 3.85mm day-1

,

which accelerates with increasing length of the body (Manyak, 1982).

If decreasing pH inhibits teredinid settlement, this may consequently transfer

the competitive benefit to non-calcifying animals. If global warming increases sea-

levels and ocean acidification as predicted; there would be a reduction with the

volume of LWD processed in mangrove ecosystems. The reduced wood-

biodegradation in the mid- to low- intertidal areas of the forests would have further

detrimental consequences, as LWD serves as an integral and essential source of

nutrients (Gee and Somerfield, 1997), and is the base of an elaborate food web

(Benner and Hodson, 1985).

As a consequence of global warming, increasing sea level rise and partial

pressures of CO2 concentrations has revealed the need to investigate the effect of

global warming upon the distribution of the terrestrial and marine biodegradation

processes. Global warming may induce shifts of the biodegradation processes within

mangrove ecosystems, with unknown consequences. The forests from the Tukang

Besi Archipelago have a wide tidal range extending from mean sea level to the high

intertidal. Conversely, mangrove forests from the Caribbean have a comparatively

limited tidal regime that range in height by 20 to 40 cm (Ilka C. Feller, personal

communication). The investigation of the biodegradation boundary of LWD in

forests from the Caribbean is necessary, due to the limited tidal flow. A different

suite of biodegradation processes may be found within Caribbean mangrove forests

due to the reduced emersion time. Differences of the biodegradation processes may

213

provide insights into the effect of wood-degradation within permanently and tidally

inundated forests. Increasing ocean acidification may have ecological implications

for the marine biodegrading detritivores in mangrove ecosystems, which may

ultimately affect the flow of nutrients to other ecosystems.

Final conclusions

Despite being considered as economic pests, the Teredinidae are the

dominant biodegraders of LWD within the seaward edges of mangrove forests. The

fragmentation of LWD in the mid to low intertidal areas of the forests are enhanced

by teredinids. Much of the LWD within the mangrove forests is processed and

recycled back into the ecosystem due to the mechanical effect and digestion by

teredinids. The tunnelling activity of teredinids significantly modifies the

environment, increases the mangrove faunal diversity at ecosystem level and creates

niches for animals that exhibit obligate behaviour to that substrate. Furthermore,

teredinid-attacked LWD has the greatest faunal diversity compared to mangrove

forest sediments and Rhizophora prop-roots within the mangrove forests of the

WMP. These data demonstrate that the teredinid populations within the forests of the

Tukang Besi Archipelago can be defined as ecosystem engineers.

Teredinids and their tunnelling of LWD within Indonesian forests will be

affected by increasing wood harvesting pressures and global warming. If wood

harvesting continues there will be a reduction of mangrove faunal diversity, due to

the reduced woody habitat and lack of teredinid tunnel niches. If sea levels rise and

ocean pH levels decrease as predicted there will be a redistribution of the wood-

biodegrading organisms ultimately leading to potentially changing plant zonation,

with fewer nutrients sequestered within the mangrove forest sediments combined

214

with a build-up of LWD and reduced flow of recycled mangrove-derived organic

carbon to adjacent ecosystems.

Priorities for further research in this area are needed to address issues

concerning global warming. Experiments to determine the de-calcification rates of

larval and adult teredinid populations would provide insights into reduced boring

rates and estimates of increasing volumes of LWD in mangrove forests. Experiments

could be used to replicate global warming-induced ocean acidification, and to

investigate the effect of decreased pH upon the Teredinidae – as the recycling of

organic carbon may be compromised in these coastal habitats due to global warming.

Successful mangrove forest management depends on their current status and

the prediction of detrimental ecological issues after the ecosystem structure and

function has been altered. Thus, projects that maintain the mangrove forest habitat

complexity after the trees have been harvested by way of implanting fallen logs may

enhance the faunal diversity of impacted mangrove areas in the WMP and maintain

the flow of organic carbon from LWD.

215

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