The Pennsylvania State University

The Graduate School

College of Earth and Mineral Sciences

THE ROLE OF LEAF TRAITS IN DETERMINING FLAMMABILITY

IN SOUTHERN AMAZON FORESTS

A Thesis in

Geography

by

Amoreena L. Thissell

© 2014 Amoreena L. Thissell

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Master of Science

May 2014

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The thesis of Amoreena L. Thissell was reviewed and approved* by the following:

Jennifer K. Balch

Assistant Professor of Geography

Thesis Adviser

Alan Taylor

Professor of Geography

Karl Zimmerer

Professor of Geography

Head of the Department of Geography

*Signatures are on file in the Graduate School

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ABSTRACT

Intensifying land use practices and global climate change are leading to increased forest

fragmentation and more severe droughts in the southeastern transitional forests of the Brazilian Amazon.

The combination of land use and droughts has increased fire frequency, intensity, and extent in the region.

Various plant traits can either limit or promote flammability, as demonstrated in many seasonally dry

environments (e.g. Mediterranean shrublands), which are home to species that are adapted to frequent

fire. However, little research has been done to associate flammability with the leaf traits of humid tropical

forest species that are experiencing fire with greater frequency and severity than historically recorded. In

this study, the leaf traits and consequent burning characteristics of seventeen species abundant in a

transitional forest plot in Mato Grosso, Brazil were analyzed through controlled combustion experiments

and trait measurements. Principal components analysis and linear regression were employed to compare

leaf traits and their ability to predict flammability. The results reported herein show that these species

demonstrate variability in flammability. Individual leaf surface area and leaf volume were found to be the

most significant predictors of flammability among these species. The most flammable species were those

with thin, lightweight leaves that become arranged in loosely packed, highly aerated fuelbeds and would

be able to drive rapidly moving, high intensity fire across the forest floor, consuming a larger amount of

fuel. The less flammable species were characterized by thick, heavy leaves that create dense fuelbeds,

potentially inhibiting fire spread and the overall consumption of available fuels. Analyzing the dynamics

between leaf traits and plant flammability with forest composition, successional trajectories and future

fire behavior could lead to an examination of overall landscape effects in which certain species with fire-

adaptive strategies could outcompete more fire-sensitive species, therefore influencing future fire

regimes. Furthermore, given a scenario of increasing fire, this knowledge can lead to more effective

conservation and land use policies in tropical regions.

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TABLE OF CONTENTS

List of Tables ………………………………………………………………………………………….…... v

List of Figures ……………………………………………………………………………………….……. vi

Chapter 1: INTRODUCTION ……………………………………………….…………………………...... 1

Components of Flammability and the Potential Effects of Plant Traits …...……….…………..… 4

Chapter 2: MATERIALS AND METHODOLOGIES …………………………………………….…….... 7

Litter Sampling ……………………………………………...………………….………………… 8

Leaf Measurements …………………………………………………………….………….……… 9

Combustion Experiments ……………………………………………………….…………..…….. 9

Data Analyses ………………………………………………….……………..……..…….…….. 11

Chapter 3: RESULTS ……………………………………………………………………….…….……… 13

Major Gradients of Flammability and Leaf Traits ……………………..…...……………………. 16

Relationships between Flammability Clusters and Leaf Traits ……..……………………...……. 19

Modeling Leaf Traits as Predictors of Flammability ………………..………………………...…. 22

Chapter 4: DISCUSSION AND CONCLUSIONS …………………………....……………………….… 25

Potential Trends Following Fire in Southeastern Amazonian Forests …………………………... 27

Conclusions ...………………………….....…………………………………………………...… 33

Appendix A: Box and Whisker Plots for Measured Flammability Metrics ………...……………………. 35

Appendix B: Box and Whisker Plots for Measured Leaf Traits ………………………………………….. 37

References ……………..................................................................................................………………… 39

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LIST OF TABLES

Table 1: Ranked abundance and Importance Value Index (IVI) for the seventeen

species included in the flammability assessment. Source: Balch et al. (2008) ….…………….….. 8

Table 2: Summaries by species of stems that were burned during the first experimental

burn event. The chi-squared statistic (χ²), the χ² critical value, degrees of freedom

(DF) and p-value are reported from the Pearson’s chi-squared proportions test …...……………. 13

Table 3: Mean and SE values for laboratory burning characteristics of the 17 species

examined in the flammability assessment. n = 5 ……..…………………………..………..…….. 14

Table 4: Mean and SE values for foliar characteristics of the 17 species examined in the

flammability assessment. n = 5 …………………………...………………………………….….. 15

Table 5: Factor loadings from the principal components analysis (PCA) on the five

flammability metrics and nine foliar characteristics …..……………………......…………….….. 17

Table 6: Variables included in the final regression model of flame heights with their

standardized coefficients and p –values. n = 85 ……………….....…………….…………….….. 23

Table 7: Comparison of conditions and results from past lab-based combustion experiments

with those from this study. Conditions include forest type, sample size (g), temperature

(C°), relative humidity (%), oven drying temperature (C°), and drying length (h). Main

results reported include maximum flame height (cm), flaming durations (s), and mass

loss (%) …………………………………………………………………..……………………… 25

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LIST OF FIGURES

Figure 1: The risk of fire in 2004, based on modeled anthropogenic and climatic risk factors.

Anthropogenic risks included distance from roads, towns, previously deforested

areas or location on or near protected areas. Climatic risk was determined by

the frequency of experiencing fire-favorable conditions as defined by a locations

vapor pressure deficit (VPD). The “arc of deforestation” coincides with the red areas

on the map. Source: Silvestrini et al., 2011. ………..…………………………………..………… 3

Figure 2: Location of experimental burn plot located in the southern portion of the land

holding, Fazenda Tanguro, Mato Grosso, Brazil (left). Experimental burn plot

(150 ha) and its three subplots (A-control; B-burned every three years; C-burned

annually (right). Source: Balch et al., 2008. ….….……………………………………………….. 7

Figure 3: The combustion experiment set up ………….…………………………………….....………… 10

Figure 4: (A) Principal components analysis and primary gradients of five flammability

for the 17 species. Flammability metrics include, maximum flame height (flht.mean),

flame duration (fldur.mean), smoldering duration (smdur.mean), time to ignition

(tig.mean) and mass loss (msls.mean). (B) Principal components analysis and primary

gradients of nine leaf traits for the 17 species. Leaf measurements include curl height

(crlht.mean), edge thickness (edthk.mean), perimeter (prm.mean), surface area

(sa.mean), volume (vlm.mean), dry mass (mass.mean), surface area to volume ratio

(savlm.mean), specific leaf area (sla.mean) and fuel sample depth (sdeep.mean) ..……………... 18

Figure 5. Leaf measurements overlaid onto ordination of flammability metrics. Species points

are colored by cluster membership. Direction of the vectors of leaf measurements

(blue arrows) show positive gradients and their length expresses their proportional

correlation with the flammability ordination (gray arrows). Fitting leaf measurements

was done with the envfit function in the package Vegan available in R

(Oksanen et al., 2013) …………………………………………………………..……………….. 20

Figure 6. Hierarchical clustering dendrogram for the five flammability measurements of the

17 examined species. Five clusters were identified at a dissimilarity height of 2.0 and

are classified by relative flammability (highly flammable, moderately flammable, less

flammable, and least flammable. Leaf profiles are shown scaled to mean length

measurements of each species ………………………………………………………………….... 21

Figure 7. Individual relationships between maximum flame height and leaf traits

(standardized) colored by species ……………………………………………………………..… 24

Figure 8. Measured flame temperatures (°C) throughout entire burning durations. All five

combustion experiments were averaged for each species. Lines represent mean

temperature (red) and one standard error above and below the mean (blue) ……………………. 28

Figure 9. Results from the hierarchical clustering of species based on the five flammability

characteristics, grouped with observations from past studies conducted at the

experimental burn plot at Fazenda Tanguro, Mato Grosso, Brazil. Three levels of

bark thickness are depicted including thin (open squares; 2-8 mm), moderate (checkered

squares; 8-14 mm), and thick (solid squares; 14-20 mm). Observed pioneer tendencies

and proportion of stems regenerating via resprouting after consecutive burns are reported

as they relate to life history strategies. Percentage of burn stems after one fire event

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and mortality rates per year following three consecutive burns show damage and

levels of resistance to fire. Cerrado presence indicates that the species may have

had a historical exposure to more frequent fire, as is prevalent in this region ……….………….. 29

Figure 10. Experimental burn plot (150 ha) and its three subplots: Control (right); B3yr

(center) – burned every three years; B1yr (left) – burned annually. Darker areas

correspond to areas that have burned more, while white areas have never burned .......………… 31

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Chapter 1

INTRODUCTION

At the transitional boundary of the southeastern Brazilian savanna, or cerrado, and the

Amazonian humid forests, vegetation is experiencing a vast transformation due to a new and rapidly

changing fire regime. These transitional tropical forests are experiencing frequent and high intensity

anthropogenic understory fires that are affecting large portions of the landscape (Davidson et al., 2012).

Based on studies that examined charcoal remnants in the underlying soil, there is evidence that this

environment has experienced fires during the last 6,000 years at intervals of several centuries (Uhl and

Kauffman, 1990; Bush et al., 2008). Morton et al. (2013) examined satellite data on understory fire

frequencies between 1999 and 2010 in the southern Amazon and calculated a mean fire return interval of

3.7 years for forests that experienced repeated burning during the study period. Additionally, they found

that over 85,500 km2 of the surveyed forest were impacted by understory fires between 1999 and 2010

(Morton et al., 2013). This contrast with previously estimated fire return intervals illustrates the impacts

of changing land use practices, along with a warmer and drier climate, in creating more frequent and more

severe fires in this area.

Land use in the Brazilian Amazon mostly consists of agriculture and cattle ranching, which has

led to some of the fastest rates of forest change in the Amazon as a whole (Davidson et al., 2012).

Roughly 48% of all global humid tropical forest loss was attributed to Brazil alone between 2000 and

2005 (Hansen et al., 2008). In 2006, 84% of all Amazonian deforestation was attributed to only three

Brazilian states (Mato Grosso, Rondônia, and Para), with the majority of this forest clearing linked to

pasture expansion (Barona et al., 2010). In the past decade, deforestation in the Brazilian Amazon has

been declining, experiencing only a quarter of the forest clearing rates in 2011 (7,000 km²yr ̄ ¹) that was

recorded at the peak of deforestation in 2004 (28,000 km²yr ̄ ¹) (INPE, 2011). However, Aragão and

Shimabukuro (2010) demonstrated that the occurrence of fire increased in 59% of the areas that had

experienced drops in their deforestation rates between 2000 and 2007. Agriculture and ranching in Brazil

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do require forest to be converted at the outset, and in the case of ranching, pasture grasses need to be

maintained through vegetation management. Furthermore, expanding infrastructure systems are

facilitating access to new areas of the Amazon where deforestation can then occur, exposing new forest

edges to the threat of fire (Laurance and Williamson, 2001).

Each of these land use activities generally involves fire in some way as a tool for forest clearing.

Many fires often escape the control of the people using them, resulting in damages to the surrounding

intact forests (Bowman et al., 2009). Global and regional shifts in temperature and precipitation patterns

are lengthening and increasing the severity and length of droughts, thus causing positive feedbacks to the

fire regime by creating more fire-favorable conditions (Davidson et al., 2012; Brando et al., 2014). These

conditions become exacerbated by a positive feedback cycle in which a tract of forest is disturbed,

allowing solar radiation to penetrate the forest floor and quickly dry out available fuels, creating a highly

flammable surface. When fires burn through these areas, it opens the canopy further and increases the size

of forest edges and patches which cause that forest to become more susceptible to burning (Laurance and

Williamson, 2001). These effects are worsened during extreme drought events, especially those

associated with ENSO (El Niño Southern Oscillation) events, which have increased in frequency in the

past several decades (Schöngart et al., 2004; Trenberth, 2011). Furthermore, projections of increases in

mean temperatures of almost 2-4º C globally are becoming ever more tangible (IPCC, 2007). The “arc of

deforestation” in Brazil (Figure 1) is at the highest risk of fire due to the coalescence of compounded

anthropogenic and climatic variables (Silvestrini et al., 2011).

The transitional forests of southeastern Amazonia lie in the “arc of deforestation” at the boundary

of the seasonally-dry, savanna-like cerrado and the more northern humid forests. During the region’s

development, the natural grass vegetation of the Brazilian cerrado lent itself well to the long term

economic goals of low-productivity cattle ranching, but fire was used on a fairly frequent basis, about

every 2-3 years, as a cost-effective tool of pasture weed control (Uhl and Buschbacher, 1985). When

pastures are abandoned after grasses lose their productivity or weeds cannot be easily contained,

regeneration of forests is limited by the frequency of fires that the area has experienced in the past,

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Figure 1. The risk of fire in 2004, based on modeled anthropogenic and climatic risk factors. Anthropogenic risks

included distance from roads, towns, previously deforested areas or location on or near protected areas. Climatic risk

was determined by the frequency of experiencing fire-favorable conditions as defined by a locations vapor pressure

deficit (VPD). The “arc of deforestation” coincides with the red areas on the map. Source: Silvestrini et al. (2011).

leading to a more permanent savanna-type ecosystem (Zarin et al., 2005). Cerrado species, like many in

savanna ecosystems, have experienced a history of more frequent exposure to fire as a result of natural

(e.g. lightning) and human (e.g. agricultural) ignition sources (Miranda et al., 2002), which has led to the

evolution of plant strategies that allow a plant to cope with fire’s effects. Hoffman (1999) suggests that

plants with higher investments in belowground root structures and developing thicker bark could allow

for quicker regeneration post-fire from intact structures. Similar studies have shown cerrado species’

tendencies towards smaller growth forms (Sarmiento and Monasterio, 1983) and the development of fruits

that protect seeds from fire (Coutinho, 1990) as evolutionary traits influenced by an exposure to fire. At

present, and in the face of increasing fire risk, there is a lack in knowledge of what controls flammability

across Amazonian forest systems. More specifically, there is a need to determine how fire behavior is

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influenced by the characteristics of fuels created by different species that link community composition to

long-term fire behavior (Schwilk and Caprio, 2011).

Components of Flammability and the Potential Effects from Plant Traits

Plant traits, such as leaf morphology, regeneration strategies, seed germination responses, and

bark thickness, have been shaped through evolution by a plant’s experience with fire (Schwilk and

Ackerly, 2001; Goubitz, Werger, & Ne’eman, 2003; Gagnon et al., 2010; Keeley et al., 2011; Pausus et

al., 2012; Pausus and Schwilk, 2012). These adaptive traits, in turn, typically correlate with the general

ability of the plant’s biomass, or fuel, to burn, otherwise known as flammability. Flammability is defined

by the fuel’s ignitibility (how it begins to burn), sustainability (how long it will burn), combustibility (the

intensity of the burn), and consumability (the amount of fuel combusted) (Anderson, 1970; Martin et al.,

1994; Fernandes and Cruz, 2012). Traits that influence flammability either protect against or promote the

burning of an individual plant. However, adaptations in plants do not necessarily originate from an

exposure to fire in and of itself, but from changes in fire regimes, specifically fire frequency, intensity and

patterns of fuel consumption (Keeley et al., 2011). Adaptations also arise from the pressures of a

multidimensional environment, including, not only exposure to fire, but changes in climate, soil fertility

and various anthropogenic and natural disturbances.

Here, the terms offensive traits and defensive traits are used to refer to the particular

morphological leaf traits adaptations to fire that a plant has evolved. Offensive traits are those that

promote and enhance the flammability of a species in order to enhance rapid post-fire regeneration in a

fire-prone landscape, while defensive traits are those that provide protection from the potentially harmful

effects either before, during, or after burning. Similar terms have been used in past interpretations to

explain the same behaviors, such as “survival/avoidance” traits and “fire-embracing strategies” (Schwilk

and Ackerly, 2001) or “fire facilitators” versus “fire impeders” (Kane et al., 2008).

Previous studies of fire-related offensive and defensive traits in various plant species have been

limited to ecosystems that have experienced relatively frequent historical fire. Studies in places such as

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the Mediterranean, the western United States and Australia have documented evidence of fire-related

adaptive traits, particularly those associated with a leaf’s size. In these systems, it has typically been

found that fuelbed depth and flammability are positively correlated, with deeper fuelbeds creating hotter

and higher flames due to greater ventilation throughout the fuelbed, a function of larger, more tightly

curled leaves (Scarff and Westoby, 2006; Ganteaume et al., 2011). Species which produce larger surface

area to volume ratios (Papio and Trabaud, 1990; Dimitrakopoulos and Papaioannou, 2001), larger leaves,

in terms of both length and perimeter (Schwilk and Caprio, 2011; Engber and Varner, 2012), and thinner,

lighter leaves (Montgomery and Cheo, 1971; Kane et al., 2008) have all been linked to higher

flammability in a variety of forest types.

Chemical components in leaves, including silica-free ash and high levels of tissue phosphates

have been studied with respect to their ability to retard ignition (Rundel, 1981; Scarff and Westoby,

2008). On the other hand, highly flammable isoprenoids can be found in fire enhancing species (Alessio

et al., 2008; De Lillis, Bianco and Loreto, 2009; Ormeño et al., 2009). A leaf’s structural characteristics

and adaptations that result in water loss prevention controlling moisture content in live leaves have been

widely accepted as one of the main determinants of the fuel’s ignitibility (Dimitrakopoulos and

Papaioannou, 2001; Fletcher et al., 2007; Davies and Legg, 2011). Regeneration strategies, such as post-

fire seeding or resprouting (Cowan and Ackerly, 2010) and fire-activated establishment by serotinous

cones (Schwilk and Ackerly, 2001; Goubitz, Werger and Ne’eman, 2003) have also been studied,

particularly in the western United States. These studies have uncovered foundational knowledge on

specific traits, both structural and chemical, that influence a plant’s flammability, or its resistance to the

damaging effects of fire.

The goal of this study is to apply what is already known regarding plant traits and flammability to

a region where little is understood about the association between them: the transitional forests of

southeastern Amazonia. Specifically, this study’s first main objective is to determine if there is any

variability in burning characteristics between species by analyzing the burning behavior and leaf traits of

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seventeen abundant species found in a forest plot of this region. If significant variability is found, then the

next step is to identify which leaf traits determine differential plant flammability among these species.

Based on these objectives, four hypotheses have been made. First, it is expected that there is high

variability in flammability, or pyrodiversity, between the species being examined in this study. Second, it

is likely that the lightest, thinnest and most tightly curled leaves will result in the most flammable litter,

from which will produce high flame heights and more rapid total burn time because of the higher aeration

within the fuelbed due to a loose packing ratio and higher surface area to volume ratio of fuels. Third,

contrasting with the second hypothesis, it is probable that species with thick, densely packed leaves,

regardless of their relative surface area, will produce less flammable litter due to their lower surface area

to volume ratios and characterized by overall less aeration of their available fuel, causing them to burn

very slowly while consuming less fuel. Fourth, it is expected that there will be high variability in the

maximum burning temperatures of litters produced by certain species.

By using these results to analyze a link between leaf traits and plant flammability with forest

composition, successional trajectories and future fire behavior could lead to an examination of overall

landscape effects in which certain species with fire-adaptive or fire-related strategies could influence fire

regimes. Chapter 2 introduces the study site and outlines the methodologies and data analyses used.

Chapter 3 discusses the results that provide the determination of key plant traits and their influence on fire

behavior in the area of interest. Finally, Chapter 4 summarizes these results and their significance, and

provides a concluding discussion of the study and its potential in influencing future work.

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Chapter 2

MATERIALS AND METHODOLOGIES

The hypothesis that species with certain foliar characteristics affect flammability was tested by

linking physical leaf traits with flammability metrics identified in burn experiments. The sampling for this

research was conducted at a privately owned farm called Fazenda Tanguro in the Brazilian state of Mato

Grosso (13º04’35” S, 52º23’ 08” W). The land holding contains a 1.5 × 1.0 km (150 ha) experimental plot

in a tract of the property’s legally protected forests at the southern edge of one of the property’s cattle

pastures (Figure 2). The experimental plot is separated into three 0.5 × 1.0 km (50 ha) treatment subplots

(Figure 2), including a control (Plot A), a plot burned three times (Plot B; burned in 2004, 2007, and

2010) and a plot that has been burned six times (Plot C; burned in 2004, 2005, 2006, 2007, 2009, and

2010). In the weeks immediately following the experimental fires, each monitored stem (> 10 cm dbh;

Figure 2. Location of experimental burn plot located in the southern portion of the land holding, Fazenda Tanguro,

Mato Grosso, Brazil (left). Experimental burn plot (150 ha) and its three subplots (A-control; B-burned every three

years; C-burned annually (right). Source: Balch et al. (2008).

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N = 6570 along 6 transects per plot) was visited to determine the percent of the stem bole that had burned

and the height of charring. This information from the first burn was used as an indicator of the likelihood

of an individual tree’s leaf litter to burn, under the assumption that the majority of the leaf litter at the

base of an individual stem was from the tree itself.

Litter Sampling

Leaf litter was collected from 17 of the most common species, which represent 70.62% of the

Importance Value Index (IVI) in this forest plot (Table 1). Litter samples were collected only from the

control (A) plot so that any effects of previous burns were eliminated. Samples for each of the 17 species

were taken directly from the forest floor beneath randomly selected individuals, with five separate 50 g

(dry weight) samples taken for each species. When sampling, any debris or leaves from adjacent species

were excluded, therefore isolating the flammability characteristics specific only to that species

(Ganteaume et al., 2011). Samples were then oven-dried for 48 hours at 65 °C at the facility where the

burn experiments were conducted. After drying, 15 g (± 0.08 g) subsamples were removed for burning

experiments and the residual litter was held and subsampled for later leaf measurements.

Table 1. Ranked abundance and Importance Value Index (IVI) for the seventeen species included in the flammability assessment.

Source: Balch et al. (2008).

Family Genus Species Species Code IVI % of IVI

Rubiaceae Amaioua guianensis Aubl. AMAGUI 23.45 7.82

Lauraceae Ocotea acutangula Mez. OCOACU 22.59 7.53

Apocynaceae Aspidosperma excelsum Benth. ASPEXC 19.24 6.41

Lauraceae Ocotea guianensis Aubl. OCOGUI 18.49 6.16

Anacardiaceae Tapirira guianensis Aubl. TAPGUI 17.60 5.87

Sapotaceae Micropholis egensis (A. DC.) Pierre MICEGE 13.25 4.42

Burseraceae Trattinnickia burserafolia Mart. TRABUR 12.30 4.10

Elaeocarpaceae Sloanea eichleri Schum. SLOEIC 12.02 4.01

Burseraceae Trattinnickia rhoifolia Willd. TRARHO 11.16 3.72

Sapotaceae Pouteria ramiflora (Mart.) Radlk POURAM 10.82 3.61

Burseraceae Trattinnickia glaziovii Swart. TRAGLA 10.26 3.42

Burseraceae Dacryodes microcarpa Cuart. DACMIC 9.29 3.10

Annonaceae Xylopia amazonica R.E.Fries XYLAMA 8.40 2.80

Myrtaceae Myrcia multiflora (Lam.) DC. MYRMUL 8.27 2.76

Vochysiaceae Vochysia vismiifolia Spr. Ex warm. VOCVIS 7.92 2.64

Burseraceae Protium guianense (Aublet) Marchand ssp. Pilosissimo (Engl) Daly PROGUI 3.66 1.22

Mimosoideae Enterolobium schomburgkii (Benth.) Benth. ENTSCH 3.12 1.04

Total % of IVI 70.63

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Leaf Measurements

Leaves were subsampled for measurements by randomly selecting 40 leaves (eight from each of

the five individual samples) from each of the 17 tree species. Individual dry leaf mass was recorded to the

nearest 0.01 g. Maximum leaf curl (height above a flat surface) was measured to the nearest millimeter

with a standard ruler. Leaf thickness was measured at the edge of each leaf to the nearest 0.001 g,

between primary veins, using an electronic caliper. Using a flatbed scanner, digital images were obtained

for all leaves which were then used in the image processing program ImageJ (Rasband, 2012) to measure

length (including petiole), width (at the widest point), perimeter, and surface area. Leaf volume was

calculated by multiplying the leaf thickness by the one-sided surface area. Surface area to volume ratio

was then found by summing edge thickness and two-sided surface area and then dividing by volume

(Engber and Varner, 2012). Specific leaf area was calculated by dividing the leaf’s one-sided surface area

by its dry mass (Cornellisen et al., 2003).

Combustion Experiments

Litter was experimentally burned at a facility near the forest plot. Experiments took place

outdoors, in the shade and during the warmest time of the day (between 12:00 and 18:00) to mimic

understory fuelbed conditions when fires are typically set by farmers and escape into adjacent forest plots.

Ambient environmental conditions were monitored. Mean temperature during experiments was 32.5 (±

1.1) °C and mean relative humidity (RH) was 32.3 (± 3.3) %. Wind remained at 0 m/s during all of the

experiments.

Leaf litter samples were subjected to the burn experiments using a randomized block design over

four consecutive days. The 15 g leaf samples were removed from the drying oven and immediately

transferred to a round metal container (20 cm diameter). Fuelbed depth was measured to the nearest

millimeter with an electronic depth caliper and included in the metrics of leaf traits, as it relates to fuelbed

bulk density, which has been well documented as a significant driver of fire behavior (Rothermel, 1972).

The samples were then inverted onto a steel mesh grate (base, 305 x 390 mm; mesh holes, 15 x 5 mm)

10

and the grate was suspended 15 cm over a fire bench constructed from fiber cement. Three thermocouples

(type k with 3.17 mm diameter) were centered over the sample at three different heights (10cm, 20cm and

40cm) and connected to a computer to log temperature variation during each burn. A ruler was placed

behind the bench and each burn experiment was recorded on video to visually estimate maximum flame

height (cm). Details of the burn experiment are shown in Figure 3.

The sample was ignited at the center from below at a consistent distance with a standard lighter.

Time to ignition (s), flaming duration (s), and smoldering duration (s) were measured using a stopwatch.

Mass loss (%) was measured by calculating weight loss (starting sample weight minus residual weight)

and dividing this by the sum of weight loss and residual litter weight. The five flammability metrics

recorded (maximum flame height, time to ignition, flaming duration, smoldering duration and mass loss)

represent the fundamental components of flammability (Anderson, 1970; Martin et al., 1994). Maximum

flame temperatures (°C) were recorded and averaged for each species to determine the heat, and therefore,

destructive potential when burning among species.

Figure 3. The combustion experiment set up.

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Data Analyses

In order to test the hypothesis that flammability varies across Amazonian tree species, a Pearson’s

chi-squared proportions test was performed on the counts of individual stems that burned of the seventeen

species during the first experimental fire in the forest plot at Fazenda Tanguro. The proportions of living

stems that burned (i.e., exhibited charring on the bole) were calculated from census data that was

collected after the first burn, which included all stems above 10 cm diameter at breast height (Balch et al.,

2008). This test compares observed proportions against expected proportions that are modeled based on

the null hypothesis that these observations occur randomly. If it is determined that the variation between

the expected and observed occurrences is significantly different, the null hypothesis is rejected and would

show significant variability in flammability across these seventeen species.

Five of the six flammability metrics were combined using principal components analysis (PCA).

Mean maximum flame temperature was excluded from the PCA due to its low correlation with the other

variables, but is discussed later as an independent controller of fire intensity. Using standardized values

(mean = 0 and SD = 1) for each of the flammability metrics, PCA scores were calculated and the number

of retained principal components was based on a cutoff level of 80% of the total variance in the data set

(Afifi et al., 2004). Species-level means for the first two principal components of flammability (hereafter

“PCF1” and “PCF2”) were plotted and factor loadings (correlations) between each of the two principal

components and the original variables are reported and discussed. Gradients of flammability based on

factor loadings were considered and are discussed in the subsequent identification of relationships

between flammability and leaf traits.

A cluster analysis was performed on the species-level mean values for the five standardized

flammability metrics (maximum flame height, time to ignition, flaming duration, smoldering duration and

mass loss). Clustering was determined based on a group average linking strategy, where the Euclidean

distance between groups was defined by the average distance between each of the group members. The

12

designation of the five chosen clusters followed a goodness-of-fit test based on the cophenetic correlation

coefficient (here, c = 0.79), where values above 0.75 are considered a sufficient fit (Afifi et al., 2004).

Following the PCA and hierarchical clustering, linear, least squares regression was run to develop

a model that would best describe the relationship between leaf traits and maximum flame height, a proxy

of fire intensity that has been used in past flammability assessments (Nelson, 1980; Cochrane et al., 1999;

Kane et al., 2008; Alexander and Cruz, 2012). Multicollinearity was checked for among the leaf

measurements prior to running the regression. Only leaf surface area and volume were highly correlated

(R2 = 0.97). Because surface area captured more variation in leaf morphology across the seventeen

species, and the effect of volume would be accounted for in the surface area to volume ratios, individual

leaf volume was removed from the data set used in the regression modeling. Additionally, all leaf

measurements were standardized using a log transformation (mean = 0 and SD = 1) to ensure consistency

of normal distributions in the explanatory variables. In addition to the remaining eight leaf measurements,

a species-level effect was included in an initial linear model. Each variable was then submitted to

backward, step-wise model selection based on Akaike’s Information Criterion (AIC) to select the most

parsimonious model (Crawley, 2005). All statistical analyses were conducted with the R statistics

program (R Core Team, 2013).

13

Chapter 3

RESULTS

As expected, the results of the Pearson’s chi-squared proportions test showed that all seventeen

species varied widely with respect to the number of stems that burned. Proportions of individuals that

burned by species ranged from 0.00 to 0.83 (Table 2). From this range of proportions, chi-squared (χ² =

124.57) was greater than the critical value (here, 26.30) based on a 95% confidence interval and 16

degrees of freedom, leading to a rejection of the null hypothesis and a highly significant variability (p-

value < 2.2 × 10-16) in the flammability of the seventeen included species. This result suggests that leaf

litter flammability varies across species at the forest stand-level under experimental burn conditions.

All seventeen species varied widely across the flammability metrics and in their measured leaf

traits. Ranges in variable means of flammability characteristics for each species were 52-108 cm for

maximum flame heights, 2.8-10.6 s for time to ignition, 20.8-71.1 s for flaming durations, 72.4-248.0 s

Table 2. Summaries by species of stems that were burned during the first experimental burn event. The

chi-squared statistic (χ²), the χ² critical value, degrees of freedom (DF) and p -value are reported from the

Pearson's chi-squared proportions test.

Species Burned Unburned Row total Proportion burned

OCOGUI, Ocotea guianensis 214 45 259 0.83

VOCVIS, Vochysia vismilfolia 63 21 84 0.75

ASPEXC, Aspidosperma excelsum 36 14 50 0.72

POURAM, Pouteria ramiflora 48 21 69 0.70

OCOACU, Ocotea acutangula 159 78 237 0.67

TAPGUI, Tapirira guianensis 112 75 187 0.60

AMAGUI, Amaioua guianensis 151 102 253 0.60

XYLAMA, Xylopia amazonica 68 50 118 0.58

SLOEIC, Sloanea eichleri 91 69 160 0.57

DACMIC, Dacryodes microcarpa 50 40 90 0.56

MICEGE, Micropholis egensis 86 77 163 0.53

TRABUR, Trattinnikia burserafolia 17 21 38 0.45

TRAGLA, Trattinnikia glaziovii 25 32 57 0.44

TRARHO, Trattinnikia rhoifolia 17 22 39 0.44

MYRMUL, Myrcia multiflora 49 71 120 0.41

PROGUI, Protium guianense 11 19 30 0.37

ENTSCH, Enterolobium schomburgkii 0 4 4 0.00

Column total 0 0 Grand total = 2345 Average = 0.578

χ² = 124.57 DF = 16

χ² critical value = 26.30 p -value < 2.2 × 10-16

14

Table 3. Mean and SE values for laboratory burning characteristics of the 17 species examined in the flammability assessment (n = 5).

Burning characteristic

Maximum flame height (cm)

Species XYLAMA PROGUI ASPEXC MYRMUL AMAGUI OCOACU MICEGE POURAM OCOGUI DACMIC VOCVIS SLOEIC TAPGUI ENTSCH TRAGLA TRARHO TRABUR

Mean 108 106 100 91 90 84 82 73 71 70 65 65 62 62 59 55 52

SE 7 2 7 19 8 11 24 6 4 10 10 12 8 18 8 6 12

Time to ignition (s)

Species ENTSCH SLOEIC OCOACU POURAM TRARHO TRABUR DACMIC XYLAMA TRAGLA OCOGUI MICEGE TAPGUI VOCVIS PROGUI ASPEXC AMAGUI MYRMUL

Mean 10.6 10.0 9.3 7.3 7.3 6.1 5.8 5.7 5.6 5.2 4.4 4.3 3.9 3.7 3.4 3.1 2.8

SE 5.8 5.4 7.3 6.8 2.0 3.2 4.4 1.9 4.1 2.0 1.4 1.7 1.7 0.9 1.0 0.8 1.2

Flaming duration (s)

Species TRARHO VOCVIS TRAGLA MICEGE TRABUR OCOGUI TAPGUI ENTSCH OCOACU POURAM SLOEIC ASPEXC DACMIC MYRMUL AMAGUI XYLAMA PROGUI

Mean 71.1 61.7 57.3 56.6 52.6 50.1 48.1 45.7 42.9 42.4 38.8 35.7 30.5 29.7 27.5 25.4 20.8

SE 15.5 13.0 18.1 57.2 6.6 6.8 9.8 14.4 8.0 9.3 13.6 5.3 4.1 3.3 6.0 2.9 2.6

Smoldering duration (s)

Species ENTSCH POURAM TAPGUI SLOEIC TRARHO AMAGUI OCOACU XYLAMA DACMIC MYRMUL MICEGE ASPEXC OCOGUI TRABUR TRAGLA VOCVIS PROGUI

Mean 248.0 224.5 143.6 139.9 134.0 133.5 124.5 118.8 117.7 112.7 110.4 107.6 105.3 94.0 79.3 79.1 72.4

SE 94.0 68.3 25.8 20.9 47.1 45.5 47.1 35.0 36.4 8.1 22.2 21.3 32.9 25.6 18.2 21.4 21.7

Mass loss (%)

Species MYRMUL MICEGE ASPEXC AMAGUI POURAM XYLAMA TAPGUI OCOACU PROGUI SLOEIC OCOGUI TRAGLA TRABUR ENTSCH TRARHO DACMIC VOCVIS

Mean 96.54 96.48 95.75 95.49 95.38 95.02 92.98 87.56 87.24 86.07 85.93 85.35 84.91 84.91 84.50 84.50 81.73

SE 0.71 0.72 1.05 1.23 0.78 0.34 0.55 2.22 3.19 4.73 1.70 1.94 2.40 4.19 3.24 3.15 4.32

Maximum flame temperature (°C)

Species OCOGUI ASPEXC MICEGE VOCVIS TRAGLA MYRMUL TAPGUI OCOACU AMAGUI ENTSCH SLOEIC POURAM XYLAMA DACMIC TRARHO PROGUI TRABUR

Mean 468.38 461.61 432.87 408.74 405.84 397.29 394.68 388.66 383.63 377.89 374.10 372.80 362.81 361.08 349.05 324.80 308.03

SE 90.66 62.54 59.96 51.48 90.93 60.82 62.90 59.85 19.25 78.72 90.80 83.58 22.59 25.84 123.75 48.17 51.11

Note: AMAGUI, Amaioua guianensis ; ASPEXC, Aspidosperma excelsum ; DACMIC, Dacryodes microcarpa; ENTSCH, Enterolobium schomburgkii ; MICEGE, Micropholis egenisis ; MYRMUL, Myrcia

multiflora ; OCOACU, Ocotea acutangula ; OCOGUI, Ocotea guianensis ; POURAM, Pouteria ramiflora ; PROGUI, Protium guianense ; SLOEIC, Sloanea eichleri ; TAPGUI, Tapirira guianensis; TRABUR,

Trattinnickia burserafolia ; TRAGLA, Trattinnickia glaziovii ; TRARHO, Trattinnickia rhoifolia ; VOCVIS, Vochysia vismiifolia ; XYLAMA, Xylopia amazonica

15

Table 4. Mean and SE values for foliar characteristics of the 17 species examined in the flammability assessment (n = 5).

Foliar characteristic

Leaf curl height (mm)

Species SLOEIC VOCVIS AMAGUI TAPGUI MICEGE ASPEXC TRARHO POURAM MYRMUL OCOACU ENTSCH DACMIC XYLAMA PROGUI TRABUR OCOGUI TRAGLA

Mean 31 29 27 23 23 23 21 19 19 19 19 18 17 17 16 14 12

SE 9 5 1 5 3 4 6 4 2 9 5 2 4 3 4 1 1

Leaf edge thickness (mm)

Species TRARHO VOCVIS OCOACU TRABUR TAPGUI SLOEIC OCOGUI POURAM ASPEXC TRAGLA ENTSCH MICEGE AMAGUI DACMIC PROGUI MYRMUL XYLAMA

Mean 0.46 0.33 0.30 0.29 0.29 0.28 0.27 0.27 0.26 0.26 0.25 0.22 0.22 0.18 0.14 0.13 0.12

SE 0.20 0.03 0.06 0.11 0.10 0.03 0.05 0.10 0.06 0.07 0.03 0.08 0.03 0.03 0.01 0.02 0.02

Leaf perimeter (mm)

Species ENTSCH SLOEIC AMAGUI OCOACU VOCVIS POURAM OCOGUI DACMIC TAPGUI ASPEXC TRARHO TRABUR PROGUI MICEGE MYRMUL TRAGLA XYLAMA

Mean 240.35 60.91 36.16 34.08 31.06 28.21 25.83 25.45 24.18 22.59 22.56 21.48 19.83 17.97 16.72 16.39 14.22

SE 54.58 6.08 2.44 5.33 2.46 1.96 2.25 3.50 2.53 3.42 2.45 2.62 2.08 2.16 1.26 1.43 2.96

Leaf surface area (cm²)

Species SLOEIC OCOACU AMAGUI VOCVIS POURAM DACMIC TAPGUI ENTSCH TRARHO ASPEXC OCOGUI TRABUR PROGUI MICEGE TRAGLA MYRMUL XYLAMA

Mean 198.10 63.81 61.95 46.28 37.90 36.39 31.01 28.95 27.28 25.77 24.98 23.02 19.43 14.95 13.16 11.49 6.63

SE 33.43 23.83 7.21 8.41 7.11 10.99 6.95 4.83 6.51 8.23 3.39 5.19 3.65 3.72 2.00 2.36 1.69

Leaf volume (cm³)

Species SLOEIC OCOACU VOCVIS AMAGUI TRARHO POURAM TAPGUI ENTSCH ASPEXC TRABUR OCOGUI DACMIC TRAGLA MICEGE PROGUI MYRMUL XYLAMA

Mean 5.62 1.94 1.51 1.41 1.34 1.05 0.90 0.73 0.70 0.70 0.69 0.67 0.34 0.33 0.28 0.15 0.08

SE 1.14 0.51 0.28 0.31 0.93 0.51 0.37 0.18 0.38 0.41 0.19 0.31 0.08 0.13 0.04 0.03 0.01

Leaf dry mass (g)

Species TAPGUI SLOEIC VOCVIS ENTSCH OCOACU AMAGUI POURAM TRARHO DACMIC OCOGUI ASPEXC TRABUR TRAGLA MICEGE PROGUI MYRMUL XYLAMA

Mean 1.61 1.59 0.80 0.78 0.69 0.61 0.55 0.51 0.41 0.40 0.37 0.36 0.20 0.14 0.14 0.11 0.07

SE 2.55 0.11 0.09 0.08 0.27 0.13 0.14 0.18 0.12 0.06 0.15 0.10 0.05 0.02 0.03 0.03 0.01

Leaf surface area to volume ratio (cm²·cm¯³)

Species XYLAMA MYRMUL PROGUI DACMIC MICEGE AMAGUI ENTSCH TAPGUI POURAM TRAGLA ASPEXC OCOGUI TRABUR SLOEIC OCOACU VOCVIS TRARHO

Mean 166.85 162.52 142.30 120.24 105.54 97.87 89.26 87.86 87.33 84.34 81.17 79.19 78.73 72.69 67.35 62.82 52.78

SE 26.23 21.61 11.88 18.92 34.54 9.11 11.53 14.92 32.83 19.91 12.10 13.28 25.84 8.62 8.04 5.69 21.06

Specific leaf area (mm²·mg)

Species PROGUI SLOEIC MYRMUL OCOACU AMAGUI XYLAMA MICEGE DACMIC ASPEXC TRAGLA POURAM TRABUR TAPGUI OCOGUI VOCVIS TRARHO ENTSCH

Mean 163.84 129.69 119.74 112.39 108.75 108.19 106.77 89.77 72.82 71.62 70.74 67.52 65.70 62.70 58.28 55.87 38.28

SE 37.34 20.23 29.38 23.60 15.08 33.91 24.31 9.55 8.58 6.01 7.17 6.92 4.16 4.90 6.77 7.83 4.58

Fuel sample depth (mm)

Species SLOEIC PROGUI AMAGUI VOCVIS OCOACU ASPEXC ENTSCH DACMIC POURAM XYLAMA TAPGUI MYRMUL TRABUR MICEGE OCOGUI TRARHO TRAGLA

Mean 125 120 95 83 81 77 75 74 74 71 71 70 64 64 61 59 56

SE 13 26 6 16 14 11 19 15 18 11 6 10 5 8 9 5 13

Note: AMAGUI, Amaioua guianensis ; ASPEXC, Aspidosperma excelsum ; DACMIC, Dacryodes microcarpa; ENTSCH, Enterolobium schomburgkii ; MICEGE, Micropholis egenisis ; MYRMUL,

Myrcia multiflora ; OCOACU, Ocotea acutangula ; OCOGUI, Ocotea guianensis ; POURAM, Pouteria ramiflora ; PROGUI, Protium guianense ; SLOEIC, Sloanea eichleri ; TAPGUI, Tapirira

guianensis; TRABUR, Trattinnickia burserafolia ; TRAGLA, Trattinnickia glaziovii ; TRARHO, Trattinnickia rhoifolia ; VOCVIS, Vochysia vismiifolia ; XYLAMA, Xylopia amazonica

16

for smoldering durations, 81.73-96.54% for mass loss, and 308.03-468.38 °C for maximum flame

temperatures (Table 3; see also Appendix A). Ranges in species’ mean values for the leaf trait

measurements were 12-31 mm for maximum leaf curl height, 0.12-0.46 mm for leaf edge thickness,

14.22-240.35 mm for leaf perimeter, 6.63-198.10 cm2 for leaf surface area, 0.08-5.62 cm3 for leaf volume,

0.07-1.61 g for leaf dry mass, 52.78-166.85 cm2·cm-3 for leaf surface area to volume ratio, 38.28-163.84

mm2·mg for specific leaf area and 56-125 mm for fuel sample depths (Table 4; see also Appendix B).

Here, gradients of flammability are identified, relationships between flammability and leaf traits are

discussed, and the results of the multivariate regression show the key role that plant traits play in

predicting fire intensity.

Major Gradients of Flammability and Leaf Traits

Of the seventeen species examined in the flammability assessment, the most flammable were A.

guianensis, A. excelsum, M. multiflora, P. guianense, and X. amazonica; those that produced the tallest

flame heights (maximum = 120 cm), short flaming times (mean range 20-35 s), and substantial mass loss

(> 87%). Species that consistently burned less intensely included O. guianensis, T. burserafolia, T.

glaziovii, T. rhoifolia and V. vismiifoloia. These species had the shortest flame heights (minimum =

41cm), longest flaming durations (mean range 50-71 s), and low levels of mass loss (< 85%). There was

no pattern of maximum flame temperatures observed that was consistent with the other gradients among

species. Leaves of O. guianensis burned the hottest (mean maximum temperature = 468.38 °C), while

leaves of T. burserafolia burned at the lowest temperatures (mean maximum temperature = 308.03 °C).

The seventeen species displayed obvious gradients across the nine foliar characteristic measured

in the assessment. The highly flammable species, particularly M. multiflora, P. guianense, and X.

amazonica, were characterized by having the thinnest leaves (< 0.21 mm), the lowest individual leaf

volumes (< 0.51 cm3), the lightest leaves (< 0.23 g), and the shortest leaf perimeters (< 28.71 mm). These

three also had the highest leaf surface area to volume ratios of the seventeen species (> 95 cm²·cm-³).

Species from the low flammability group, specifically O. guianensis and T. rhoifolia, had considerably

17

lower specific leaf areas (< 78 mm2 · mg) and, along with T. glaziovii, the lowest fuel depths (range = 43-

74mm). The bipinnate leaves of E. schomburgkii had the longest leaf perimeters (range 125- 405 mm) and

the lowest specific leaf areas (< 55 mm2·mg), while S. eichleri possessed the largest leaves in terms of

surface area (range 96-280 cm2). The leaves of X. amazonica were consistently the smallest in terms of

surface area, perimeter, volume and mass. There was no obvious gradient of maximum curl height that

was consistent with the other observed gradients of foliar characteristics, most likely due to the high

variability in leaf size across the seventeen considered species.

The first two axes identified by the principal components analysis (PCA) on the five flammability

metrics explained 79% of the variance among the seventeen species. The two axes also reflected the

gradients observed within the raw data set (Figure 4A). The first principal component (PCF1) accounted

for 50.73% of the variation in the data and was controlled mostly by flame height and, to a lesser degree,

flaming duration, mass loss, and time to ignition (Table 5), relating to the fuels’ ignitibility,

combustibility and consumability. The second axis (PCF2) contributed to the remaining 28.27% of

variance in the flammability metrics with smoldering duration, a measure of the fuels’ sustainability,

having the most significant effect, followed by time to ignition. Species with characteristics of high

flammability had large negative values along PCF1 and values close to zero along PCF2. The less

Table 5. Factor loadings from the principal components analysis (PCA) on the five flammability

metrics and nine foliar characteristics.

PCA Flammability PCA Leaf Traits

Variable PCF 1 PCF 2 Variable PCL 1 PCL 2

Maximum flame height -0.57 -0.13 Curl height -0.38 -0.10

Time to ignition 0.44 -0.48 Edge thickness -0.24 0.47

Flaming duration 0.47 0.31 Perimeter -0.11 0.14

Smoldering duration 0.20 -0.75 Surface area -0.45 -0.17

Mass loss -0.46 -0.3 Volume -0.47 -0.10

Leaf dry mass -0.42 0.08

Surface area to volume ratio 0.29 -0.44

Specific leaf area -0.01 -0.58

Fuel sample depth -0.30 -0.42

% variance 50.73 28.27 45.54 29.90

Note: The total variance explained ("% variance") by each principal component (PCF) is reported.

18

Figure 4. (A) Principal components analysis and primary gradients of five flammability for the 17 species.

Flammability metrics include, maximum flame height (flht.mean), flame duration (fldur.mean), smoldering duration

(smdur.mean), time to ignition (tig.mean) and mass loss (msls.mean). (B) Principal components analysis and primary

gradients of nine leaf traits for the 17 species. Leaf measurements include curl height (crlht.mean), edge thickness

(edthk.mean), perimeter (prm.mean), surface area (sa.mean), volume (vlm.mean), dry mass (mass.mean), surface area

to volume ratio (savlm.mean), specific leaf area (sla.mean) and fuel sample depth (sdeep.mean).

Note: AMAGUI, Amaioua guianensis; ASPEXC, Aspidosperma excelsum; DACMIC, Dacryodes microcarpa; ENTSCH,

Enterolobium schomburgkii; MICEGE, Micropholis egenisis; MYRMUL, Myrcia multiflora; OCOACU, Ocotea acutangula;

OCOGUI, Ocotea guianensis; POURAM, Pouteria ramiflora; PROGUI, Protium guianense; SLOEIC, Sloanea eichleri; TAPGUI,

Tapirira guianensis; TRABUR, Trattinnickia burserafolia; TRAGLA, Trattinnickia glaziovii; TRARHO, Trattinnickia rhoifolia;

VOCVIS, Vochysia vismiifolia; XYLAMA, Xylopia amazonica.

19

flammable species had high positive values along both PCF1 and PCF2. The species with the

intermediate measures of flammability were grouped around the origin of the principal component plot.

The PCA of leaf traits resulted in the first two axes explaining 75.44% of the variation in the data

set and also revealed similar gradients among the seventeen species in terms of their respective leaf traits

(Figure 4B). The first axis (PCL1) contributed to 45.54% of this variance, with leaf surface area, volume

and dry mass controlling the axis the most (Table 5). The second axis (PCL2) was controlled mostly by

specific leaf area, followed by leaf edge thickness, surface area to volume ratio, and fuel sample depth.

The species with small, light leaves had large positive values along PCL1, while the larger, heavier leaves

had large negative values, particularly S. eichleri. Thicker leaves and those with lower specific leaf areas

and surface area to volume ratios had larger positive values along PCL2 compared with the thinner leaves

which had relatively large negative values along the same axis. By overlaying the fitted leaf traits onto the

ordination space determined by the flammability metrics, positive gradients and correlations between the

two sets of variables become clear (Figure 5). This helps to inform the initial steps in the least squares

regression analysis.

Relationships between Flammability Clusters and Leaf Traits

The hierarchical cluster analysis run on the five flammability metrics produced a dendrogram that

could be split into five individual clusters of flammability for the 17 species. The dendrogram had a

cophenetic correlation coefficient of 0.79 and clusters were split at a dissimilarity value of 2.00 (Figure

6). Cluster A was classified as the highly flammable group and was characterized by small, thin and

lightweight leaves that produced the highest flame heights (maximum = 120 cm) and had the shortest

ignition times (mean range 2.82-5.5 s) and flaming durations (mean range 20.7-35.7 s).

Cluster B and C are grouped together as the moderately flammable group, but clustered

separately mainly due to their differences in mass loss percentages and ignition times. The species in

Cluster B had consistently higher mass losses (range 92.9-97.1%) and faster time to ignition (range 1.7-

20

Figure 5. Leaf measurements overlaid onto ordination of flammability metrics. Species points are colored by cluster

membership. Direction of the vectors of leaf measurements (blue arrows) show positive gradients and their length

expresses their proportional correlation with the flammability ordination (gray arrows). Fitting leaf measurements was

done with the envfit function in the package Vegan, available in R (Oksanen et al., 2013).

5.8 s) compared to the lower mass losses (range 78.6-91.3%) and slower time to ignition (range 2.2-21.6

s) of species in Cluster C. Leaves from species in Cluster B were generally smaller than those from

Cluster C in terms of perimeter and surface area, and Cluster B species exhibited much shallower sample

depths than Cluster C species.

Cluster D is categorized as the less flammable group and is controlled mostly by long flaming

durations (range 40.6-92.9 s) and the some of the lowest mass loss percentages (range 74.3-88.5%) of the

seventeen species. These species had intermediate ignition times (mean range 3.9-7.3 s) and low

smoldering durations (excluding T. rhoifolia, mean range 79.1-105.3 s). The leaves of Cluster D species

had relatively low surface area to volume ratios and specific leaf area measurements. Except for V.

vismiifoloia, these species also had more compact fuelbeds. These species spanned a broad range in

measurements of leaf edge thickness, surface area, volume and mass (Table 4).

Cluster E species, E. schomburgkii and P. ramiflora, were separated out from the rest of the

21

Note: AMAGUI, Amaioua guianensis; ASPEXC, Aspidosperma excelsum; DACMIC, Dacryodes microcarpa;

ENTSCH, Enterolobium schomburgkii; MICEGE, Micropholis egenisis; MYRMUL, Myrcia multiflora;

OCOACU, Ocotea acutangula; OCOGUI, Ocotea guianensis; POURAM, Pouteria ramiflora; PROGUI,

Protium guianense; SLOEIC, Sloanea eichleri; TAPGUI, Tapirira guianensis; TRABUR, Trattinnickia

burserafolia; TRAGLA, Trattinnickia glaziovii; TRARHO, Trattinnickia rhoifolia; VOCVIS, Vochysia

vismiifolia; XYLAMA, Xylopia amazonica.

Figure 6. Hierarchical clustering dendrogram for the five flammability measurements of the 17 examined species.

Five clusters were identified at a dissimilarity height of 2.0 and are classified by relative flammability (highly

flammable, moderately flammable, less flammable, and least flammable. Leaf profiles are shown scaled to mean

length measurements of each species.

22

seventeen species first, making them the most dissimilar from the others and were considered to be the

least flammable. This separation was a result of these species having significantly higher smoldering

durations than any of the other species (range 113.3-348.6 s). They did share similar, intermediate

flaming durations (mean range 42.4-45.7 s). The leaves of E. schomburgkii were the only bipinnate leaves

in the seventeen examined species and therefore had the largest leaf perimeters (maximum = 406 mm)

and the lowest specific leaf area measurements (range 23.3-55.3 mm2·mg). P. ramiflora had intermediate

values in all of the leaf traits that were measured (Table 4).

Modeling Leaf Traits as Predictors of Flammability

The linear, least squares regression and step-wise model selection found the most parsimonious

model with seven of the eight leaf measurements and the species-level influence, accounting for 69.7% of

the variability in maximum flame heights (AIC = 638; p < 0.0001). The significant variables (including

species-level influences), standardized coefficients, and p-values of the best model are shown in Table 6.

The only leaf measurement that was removed in the step-wise selection was curl height, showing

that its independent influence is not significant in predicting flammability between species, most likely

due to the high degree of variability in leaf surface areas, which influences curl height, in a highly

species-rich forest system. In other words, the flammability influence of a very curly leaf with a small

surface area will not be captured by measuring only maximum curl height, because a larger leaf with the

same maximum curl height would not have the same degree of curling. Leaf curl is more adequately

captured in fuelbed depths and surface area to volume ratios and their inherent links to fuelbed aeration, a

main driver of fire intensity.

Individually, the leaf traits included in the final model were highly significant variables in

predicting changes in flame heights, thus controlling flammability (Figure 7). Although the p-value for

leaf surface area is the lowest of all the variables in the model (i.e. the most significant), when taken into

consideration alone, it has the lowest R2 value (0.06), suggesting that all of the leaf traits in the model are

good predictors of flame heights. The independent variables with the highest R2 values were edge

23

thickness (R2 = 0.29), surface area to volume ratio (R2 = 0.28), and specific leaf area (R2 = 0.26). This

supports the idea that species with fine, lightweight leaves will produce the highest flame heights and

burn more intensely. Importantly, the regression model included the influence of general species-level

variations. When this categorical variable was removed from the model, it reduced the predictive power

of the model by 27% (R2 = 0.42; AIC = 679). This suggests that additional characteristics of leaves that

are important in determining differences in flammability among species but that were not included in the

parameters of this study.

Table 6. Variables included in the final regression model of flame

heights (n = 85) with their standardized coefficients and p -values.

Variable Std. Coefficient p - value

Edge thickness 2.06 0.022718

Leaf mass -1.60 0.008166

Leaf surface area 2.50 0.000624

Leaf perimeter -1.75 0.016601

Surface area to volume ratio 2.67 0.013443

Specific leaf area -0.64 0.051767

Fuel sample depth 0.22 0.064103

Species:

AMAGUI NA NA

ASPEXC 4.94 0.038002

DACMIC -0.39 0.016077

ENTSCH 4.18 0.068130

MICEGE 0.02 0.960712

MYRMUL 0.31 0.465630

OCOACU -0.06 0.672368

OCOGUI 0.02 0.907792

POURAM -0.09 0.407242

PROGUI 2.67 0.379644

SLOEIC -0.53 0.012354

TAPGUI -0.78 0.066199

TRABUR -0.96 0.016574

TRAGLA -0.45 0.272821

TRARHO -0.32 0.107800

VOCVIS -0.23 0.170029

XYLAMA 0.44 0.040978

R² = 0.6974

AIC = 638

24

Figure 7. Individual relationships between maximum flame height and leaf traits (standardized) colored by species.

25

Chapter 4

DISCUSSION AND CONCLUSIONS

As hypothesized, the most abundant tree species in this forest system demonstrated a high degree

of variation in relative flammability. Furthermore, the leaf traits that were measured accounted for a large

proportion of this variability among species. This finding points to the importance of how forest

community composition can influence fire behavior in tropical forests. More specifically, it illustrates

how high biodiversity forests, like those in the Amazon, create high pyrodiversity, or differences in

species-level flammability, throughout the system. However, fire science studies like this one have not

been completed for any other Amazonian forest ecosystem. This is likely due to their relatively recent

exposure to high frequency fire events, as compared to fire prone and better-studied ecosystems across the

globe, such as those in the Mediterranean and the western United States (Table 7). The flammability-

related metrics that were measured from the Amazonian species in this study and were the most

responsible for controlling variability between species were mean maximum flame heights (range = 52-

108 cm), flaming durations (range = 20.78-71.1 s), and mass loss (range = 81.7-96.5%), which relate to a

fuel’s combustibility and consumability. Compared with other lab-based combustion experiments using

similar sample sizes (15 g), flame heights reached only 46-82 cm for western and eastern United States

pine species (Fonda, 2001), 33-81cm for southeastern United States oaks (Kane et al., 2008), and 13-83

cm for California oak species (Engber and Varner, 2012). These experiments also resulted in substantially

longer flaming durations, reaching 63.5-195.4 seconds, 50.4-91.4 seconds and 34.1-157.9 seconds,

Table 7. Comparison of conditions and results from past lab-based combustion experiments with those from this study. Conditions include

forest type, sample size (g), ambient mean temperature (°C), ambient mean relative humidity (%), oven drying temperature (°C) and drying

length (h). Main results reported include maximum flame height (cm), flaming durations (s), and mass loss (%).

Reference Forest type

Sample

size

(g)

Mean

temp

(°C)

RH

(%)

Drying

Temp

(°C)

Drying

Length

(h)

Range in

mean max

flame heights

(cm)

Range in

mean

flaming

durations

(s)

Range in

mean mass

loss

(%)

This study Amazonian transitional 15 32.5 32.3 65 48 52-108 21-71 82-97

Fonda (1999) Western and eastern USA pine 15 - - 103 72 46.4-82.3 63.5-195.4 60.7-92.0

Kane et al. (2008) Southeastern USA oak 15 - - 75 72 33.6-81.4 50.4-91.4 70.0-90.2

Engber and Varner (2012) Western USA oak 15 20.8 40.8 40 24 13.8-83.0 34.1-157.9 29.3-92.5

26

respectively. Percentage of biomass consumed during burning was also much lower for these studies, with

losses of 60.7-91.9%, 70.0-90.2%, and 29.3-92.5%, respectively. This comparison may suggest that this

group of Amazonian species is more capable of intense, rapid fires which consume a substantial amount

of fuel in its path. Furthermore, the differences in sampling, ambient conditions, measurement techniques

and flammability assessments between these studies, and many others, highlight a need for a standardized

lab protocol for combustion experiments involving leaf litter, similar to that set forth by Etlinger and

Beall (2004) which was developed to test the flammability of whole plants.

From the seventeen species included in this work, the group (Cluster A) that produced the highest

flame heights when burned were characterized by thin, lightweight leaves with a high surface area to

volume ratio. These leaves were also typically arranged in loosely packed, highly aerated fuelbeds which

would be able to drive a rapidly moving, high intensity fire across the forest floor, consuming a larger

amount of fuel in its path. Conversely, the less flammable groups (Clusters D and E) produced leaves that

were very thick, heavy and had lower surface area to volume ratios. The lack of leaf curling in these

species led to the development of dense fuel beds that would inhibit fire spread and the overall

consumption of available fuels. By comparing two species, one from the high flammability group (Myrcia

multiflora) and the other from the low flammability group (Trattinnickia rhoifolia), the differences in leaf

morphology and their importance in influencing flammability become clear. These two species burn at

very different intensities, with M. multiflora having high flame heights (mean = 91 cm) and the highest

observed mass loss (mean = 96.54%). On the other hand, T. rhoifolia had very low flame heights (mean =

55 cm) and relatively low mass loss (mean = 84.50%). The main leaf traits that distinguish these two

species from one another are leaf thickness (MYRMUL mean = 0.13 mm; TRARHO mean = 0.46 mm)

and, in turn, surface area to volume ratio (MYRMUL mean = 162.52 cm2·cm-3; TRARHO mean = 52.78

cm2·cm-3). The range in measurements of the leaf morphologies of these two species, and their resulting

burning characteristics, are an important result in terms of looking at a high diversity forest producing

many types of litter, which eventually become fuels for different kinds of fires.

27

Although it was found that species-level differences in the measured leaf traits play a key role in

predicting flammability, there may also be other components of plant flammability that were not

measured here, but would show strong influences in a species’ burning behavior. The clusters identified

from the five main flammability metrics are not cohesive with the variation among species based solely

on measurements of maximum flame temperature (Figure 8). Only two of the five species which produce

the highest temperatures during combustion belong to the high flammability group (Cluster A; A.

excelsum and A. guianensis). Conversely, all three members of the Trattinnickia species only produce

three of the four lowest temperatures, all with very short combustion times. This suggests that there may

be other important factors controlling these differences that lie outside the scope of this work. One

potentially important influence could be the chemical composition in leaves that facilitate intense burning

behaviors (Alessio et al., 2008; De Lillis, Bianco and Loreto, 2009; Ormeño et al., 2009), particularly for

the species observed at the study site in the Lauraceae family, which are known to have leaves and bark

with essential oils (Gentry, 1993). Litter from species that produce extremely hot fires have a high

capability of damaging neighboring individuals regardless of the neighboring species’ relative

flammability. Studies in the future that examine the variations and influence of chemical traits in leaves

would be able to add to this new knowledge of flammability in southeastern Amazonian forests.

Potential Trends Following Fire in Southeastern Amazonian Forests

After the data collected for this study was analyzed, other observed effects of fire were gathered

from studies that have been conducted in the same forest plot at Fazenda Tanguro (Figure 2) in order to

gain a more comprehensive insight on both broader spatial and temporal scales. These effects were subset

to include the seventeen species in focus and were compared to the flammability cluster results (Figure 9).

The first comparison was made using observed life history strategies for the species in question,

including bark thickness, whether the species had been observed as a pioneer, and post-fire regeneration

capabilities. Bark thickness can be described as a defensive fire trait due to its ability to provide

protection to the vital vascular cambium layer in trees and reduces the likelihood of fire-induced mortality

28

Figure 8. Measured flame temperatures (°C) throughout entire burning durations. All five combustion experiements were averaged for each species. Lines represent mean temperature

(red) and one standard error above and below the mean (blue).

29

Figure 9. Results from the hierarchical clustering of species based on the five flammability characteristics, grouped

with observations from past studies conducted at the experimental burn plot at Fazenda Tanguro, Mato Grosso,

Brazil. Three levels of bark thickness are depicted including thin (open squares; 2-8 mm), moderate (checkered

squares; 8-14 mm), and thick (solid squares; 14-20 mm). Observed pioneer tendencies and proportion of stems

regenerating via resprouting after consecutive burns are reported as they relate to life history strategies. Percentage

of burn stems after one fire event and mortality rates per year following three consecutive burns show damage and

levels of resistance to fire. Cerrado presence indicates that the species may have had a historical exposure to more

frequent fire, as is prevalent in this region.

Sources: 1) Brando et al., 2011; 2) Balch et al., 2011; 3) Balch et al., 2013.

* Ribeiro et al., 1999; ** Lorenzi, 2000; + Ter Steege and Hammond, 2001.

Note: AMAGUI, Amaioua guianensis; ASPEXC, Aspidosperma excelsum; DACMIC, Dacryodes microcarpa;

ENTSCH, Enterolobium schomburgkii; MICEGE, Micropholis egenisis; MYRMUL, Myrcia multiflora;

OCOACU, Ocotea acutangula; OCOGUI, Ocotea guianensis; POURAM, Pouteria ramiflora; PROGUI,

Protium guianense; SLOEIC, Sloanea eichleri; TAPGUI, Tapirira guianensis; TRABUR, Trattinnickia

burserafolia; TRAGLA, Trattinnickia glaziovii; TRARHO, Trattinnickia rhoifolia; VOCVIS, Vochysia

vismiifolia; XYLAMA, Xylopia amazonica

30

(VanderWeide and Hartnett, 2011; Brando et al., 2012). Brando et al. (2012) examined bark thickness and

fire-induced mortality of species found in the same experimental burn plot that was sampled from for this

work and found that mortality was lower for trees with thick bark (>18 mm) after fire. Comparing the

levels of bark thickness to the flammability clusters identified here, the species in the high flammability

group (Cluster A) had thinner bark than those in the less flammable groups (Clusters D and E). This

pattern may be a disproportionate result of measured diameter at breast height (DBH) for these

individuals, many of which are sub-canopy species, pointing to the possibility that trees with thin bark (2-

9 mm) could also simply be smaller trees. However, further studies on flammability that control for size-

class while looking at bark thickness would be able to validate this pattern among species. Species that

have been identified as having pioneer tendencies can play an important role in species composition,

particularly following fire. Pioneers possess the ability to quickly move into gaps created by disturbance

and grow quickly in order to reach reproductive capability (Holdsworth and Uhl, 1997). The species

found in this forest known to display pioneer characteristics could have an advantage in this system that is

experiencing more regular, intense fires that create canopy gaps. It has also been observed that species in

this forest which have a greater ability to regenerate via resprouting increased in abundance following fire

(Balch et al., 2013). Similar to pioneers, species that can resprout from underground root systems or from

damaged stems (i.e. coppicing) may be able to expand into areas where neighboring individuals were

killed during fires. From the seventeen species examined, resprouting proportions varied greatly (0 –

0.70), with the highest proportions coming from species in both high (MYRMUL = 0.70) and low

(OCOGUI = 0.57) flammability groups. It remains to be explored if there is, in fact, an emerging trend

towards lower diversity forests that consist of species with increased fitness following fire, or at least a

greater ability to survive and recover from fire damage.

A connection between species-level flammability and stand-level interactions in this forest

system has the potential to illustrate likely scenarios of species composition in forests experiencing more

frequent fires. Following the first experimental burn, observations of the percent of actual burned stems

showed high variability by species (37-83%; Table 2; Balch et al., 2008). Only four individuals of

31

Enterolobium schomburgkii were observed in the forest inventory and none of these stems burned during

the first fire. This may be due to its densely packed, low flammability fuels that may have been abundant

on the forest floor before being exposed to experimental fire. When linked to mortality rates after three

consecutive burns, there was also high variability in fire-induced mortality (1.0-22.6% per year) as it

related specifically to the number of stems that had burned. The three species that experienced the highest

rates of mortality were P. guianense (22.6% per year), V. vismiifolia (15.5% per year), and T. guianensis

(11.6% per year) and belong to Clusters A, D, and B, respectively. During the first fire, 36.7%, 75%, and

60% of individual stems burned from P. guianense, V. vismiifolia, T. guianensis, respectively. Spatial

observations across the plot show pockets of forests that have consistently burned during each of the 6

experimental fires (2004-2010) and areas that have never burned (Figure 10). Further analysis needs to

Figure 10. Experimental burn plot (150 ha) and its three subplots: Control (right); B3yr (center)-burned every three

years; B1yr (left)-burned annually. Darker areas correspond to areas that have burned more, while white areas have

never burned.

32

be conducted to determine if there are any patterns in the species that are prevalent in both highly burned

and unburned locations within the plot and if those species display high or low flammability leaf litter

characteristics. The high variation in spatial and temporal responses to fire suggests that other variables

are driving these fire-sensitive and fire-resistant pockets at the stand level. Such variables could include

long term climate variability in conjunction with more localized, short term weather patterns connected to

the spatial distribution of open or dense canopies. This would influence the amount and intensity of solar

radiation reaching the forest floor, affecting the rates at which fuels would dry out and become readily

ignitable. Currently, little is known regarding the variation in species-specific leaf litter production and

decomposition rates, both of which would be important for explaining fuel loads and burning behaviors

across the forest floor. Species producing higher volumes of litter, possibly possessing the highly

flammable leaf traits found here, but which then dry out more rapidly, could create a more fire-sensitive

fuelbed.

The final factor of potential significance in this group of species and their relative burning

characteristics is having a presence in the cerrado region, which may indicate more frequent exposure to

fire over longer periods of evolutionary time. Fires occurring in the cerrado are typically more intense,

with flame heights reaching 0.8-2.8 m (Frost and Robertson, 1987), compared with 0.3 m, measured

during the first experimental burn in the forest plot at Fazenda Tanguro (Balch et al., 2008). From the

species examined here, 7 of the 10 species from the more flammable groups (Clusters A, B and C) are

present in the cerrado, while only 1 of the remaining 7 in the lower flammability groups (Clusters D and

E) have been observed in the cerrado (Figure 10). Species which may have originated in the cerrado and

are now found in transitional forests may have had the opportunity to evolve adaptations that allow them

to prevent fire damage and/or recovery from the effects of fire.

Two species from this study that each possess a very unique suite of characteristics that may have

developed in response to fire are Myrcia multiflora and Pouteria ramiflora. The first, M. multiflora was

placed in the high flammability group (Cluster A) based on its high flame heights, short ignition and

flaming times, and the highest mass loss. It typically yields very thin, small leaves with high surface area

33

to volume ratios. After the first experimental burn, only 41% of its stem had been burned, but following

the third consecutive burn, its mortality rate was relatively high (8.2% per year). However, it had the

greatest observed proportion of stems regenerating via resprouting (0.70) following consecutive burns.

This species has been observed in the cerrado and is a pioneer. These characteristics point to a strategy of

resilience post-fire in which, even in the face of higher mortality risk, the ability to quickly regenerate

from subterranean root structures allows it to persist in this environment. Another notable species, P.

ramiflora, was classified as one of the least flammable species (Cluster E) based on its leaves’ longer time

to ignition and duration of smoldering. Its leaves are larger than those of M. multiflora, but compared to

all other sixteen species, its leaf measurements were relatively moderate, falling in the median of ranges

for each of the variables. In contrast to M. multiflora, it experienced a high percentage of char damage to

its stems (70%) after the first fire, but had low mortality after three fire events (1.9% per year). This

species also has thick bark (range = 5-35 mm) which could be an adaptation that evolved from its

historical exposure to fire in the cerrado. Both of these species exhibit different strategies and traits that

provide greater resilience and resistance, respectively, to the effects of fire. These are examples of species

which may have the advantage in systems experiencing more frequent, intense fires and could point to a

trend in selecting for species similar to these, with the potential for creating less diverse, more fire-

tolerant Amazonian forests.

Conclusions

Increasing rates of forest conversion to agriculture and cattle pasture, compounded with a

warming climate creating more severe drought events, are significantly impacting the fire/forest

interactions in the southeastern Brazilian Amazon. There is the possibility that this increasing fire activity

has been, and will be, selecting for species with fire-related offensive or defensive traits and that this shift

could lead to a lasting change in the composition and structure of these forests. The documentation of

flammable and fire-resistant traits in previously studied fire-prone regions of the world has allowed for a

better understanding of short- and long-term fire susceptibility. Flammability studies in the Amazon will

34

lead to the same recognition of these forests’ vulnerability. By being able to predict an ecosystem’s

vulnerability to fire, land use policies and conservation strategies can be more effective in the future.

35

APPENDIX A

Box and Whisker Plots for Measured Flammability Variables

36

37

APPENDIX B

Box and Whisker Plots for Measured Leaf Traits

38

39

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