Movements, Behaviors and Threats to Loggerhead Turtles ...

Movements, Behaviors and Threats to Loggerhead Turtles (Caretta caretta) in the

Mediterranean Sea

A Thesis

Submitted to the Faculty

of

Drexel University

by

Samir Harshad Patel

in partial fulfillment of the

requirements for the degree

of

Doctor of Philosophy

November 2013

ii

ACKNOWLEDGMENTS

I want to express gratitude to the Betz Chair of Environmental Science at Drexel

University, the Leatherback Trust and NASA for funding this project.

I am very grateful to my two advisors, Jim Spotila and Steve Morreale, without

whom this project would not have been as successful. Steve not only made his knowledge

and expertise in ecology and sea turtle biology accessible to me; he also opened up his

home. Steve has gone from being my mentor and advisor, to now being a great friend.

Even with my unproven record, Jim accepted me as a Ph.D. student in 2009. He has since

transformed me from an ignorant bystander in the field to now a confident and more

knowledgeable ecologist. His confidence in me sustains my sense of pride and

accomplishment as I gain this degree.

I would like to thank my committee, Sue Kilham, Mike O’Connor and Hal Avery

for always being available to help me even though I spent so little time at Drexel. Their

doors were always open and they provided advice without hesitation. They taught me

how to be an effective ecologist both formally through their excellent lectures and

informally during ecology seminars and personal communications.

I would like to thank Frank Paladino, who spent a considerable amount of time,

money and effort ensuring my success. From spending time with us in Greece to sending

me to Africa so that I could gain important field experience, Frank has always been a

source of great support and I very much appreciate his commitment to this project and

my future. I would also like to acknowledge Bob George, Helen Bailey and especially

Vince Saba for their incredible amount of help, generosity and sincere kindness.

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Thank you to ARCHELON, The Sea Turtle Protection Society of Greece and

especially its most humble founder Dimitris Margaritoulis. With the support and

infrastructure provided by ARCHELON I was able to focus my time on executing this

project instead of worrying about surviving in the field. Furthermore, the positive nature

of Dimitris Margaritoulis has shown me the value of committing one’s life to

conservation. To the volunteers and field leaders of ARCHELON, thank you for your

help on a daily basis during the field season and I applaud your altruism. Thank you to

Aliki Panagopoulou (my “academic wife”), without whom I would not have had this

great opportunity. Aliki provided invaluable support both through her expertise in sea

turtle biology and also through resolving 99% of the logistics required for the field

research.

Thanks to all the people of the Drexel University Departments of Biology and

Biodiversity, Earth and Environmental Science. I am very grateful to both Susan Cole

and Brenda Jones-Bowden for allowing me to live away from Drexel without

complication. To the graduate students past and present, I thank you for being of the

highest caliber and showing me how to make the best of this process. Thank you to those

of the class who entered in 2008, it has been a pleasure gaining this degree alongside of

you. You all have been a part of some of the greatest memories I have from this

experience and I look forward to working with you all in the future.

Thank you to the incredible field assistants, Julianne Koval, Avalon Mehta, Emily

Bell and Liz Long. You all not only made my work easier, but also more enjoyable, I

hope you found the experience worthwhile. Special thanks to Nathan Robinson, who

went from field assistant to great friend. Thank you for editing all of my writing and

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always being a positive influence. Thank you to the Morreale family. I appreciate all of

the advice and love from Rebecca and all of the help from Jonah. He made sea turtle field

work seem effortless.

I would like to thank my family for continuing to support me as I traveled the

world and on various occasions prioritized this project over them. Thanks to my parents

for teaching me that no matter what I do, I should do it at the highest level. Thanks to my

in-laws for being patient with me as I left their daughter home alone for several months at

a time. Finally, I would like to give a very special thank you to my real wife, Jennifer

Patel, for always being accommodating to the needs of this project and for keeping me

grounded throughout the process. Without your love and support, I would not have

reached this milestone.

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TABLE OF CONTENTS

LIST OF TABLES.............................................................................................................vii

LIST OF FIGURES..........................................................................................................viii

ABSTRACT......................................................................................................................xii

CHAPTER 1: General introduction.....................................................................................1

Chapter 2: Changepoint Analysis................................................................3

Chapter 3: Fitness Differences....................................................................4

Chapter 4: Climate Change.........................................................................5

References................................................................................................................7

CHAPTER 2: Changepoint analysis: a new approach for understanding animal

movements and behaviors from satellite telemetry data...................................................12

Abstract..................................................................................................................12

Introduction............................................................................................................13

Methods..................................................................................................................14

Satellite Transmitter Attachment...............................................................16

Satellite Transmitters.................................................................................17

Post-nesting Movements and Behaviors....................................................18

Switching-State Space Model (SSSM).......................................................18

Changepoint Analysis (CPA).....................................................................19

Results....................................................................................................................21

SSSM Behavior Mode 1 – Transiting.......................................................23

SSSM Behavior Mode 2 – Area Restricted Search...................................24

CPA Behavior Mode 1 – Migration..........................................................24

CPA Behavior Mode 2 – Transition Behavior..........................................25

CPA Behavior Mode 3 – Foraging...........................................................26

CPA Behavior Modes 4 and 5 - Transition Phase and Overwintering......27

Discussion..............................................................................................................28

References..............................................................................................................34

Tables and Figures.................................................................................................39

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CHAPTER 3: Fitness differences between post-nesting loggerhead sea turtles

(Caretta caretta) from Rethymno, Crete, Greece..............................................................53

Abstract..................................................................................................................53

Introduction............................................................................................................54

Methods..................................................................................................................55

Satellite Transmitter Attachment...............................................................56

Fitness Proxies...........................................................................................57

Benthic Assessments...................................................................................58

Results....................................................................................................................59

Discussion..............................................................................................................61

References..............................................................................................................68

Tables and Figures.................................................................................................74

CHAPTER 4: Potential impacts of global warming on loggerhead turtles in the

Mediterranean Sea.............................................................................................................79

Abstract..................................................................................................................79

Introduction............................................................................................................80

Methods..................................................................................................................83

Results....................................................................................................................86

Discussion..............................................................................................................90

References..............................................................................................................97

Figures..................................................................................................................108

CHAPTER 5: Conclusions and Conservation Implications.........................................123

Changepoint Analysis..............................................................................123

Regional Fitness Differences...................................................................123

Climate Change Impacts..........................................................................124

Further Conservation Concerns..............................................................125

References............................................................................................................128

APPENDIX A..................................................................................................................129

APPENDIX B..................................................................................................................131

VITA................................................................................................................................132

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LIST OF TABLES

2.1: Summary data of the 20 satellite tracked loggerhead turtles from Rethymno,

Crete...................................................................................................................................39

3.1: Summary data of the 20 satellite tracked loggerhead turtles from Rethymno,

Crete...................................................................................................................................72

4.1: Summary information and references for the climate change models used in this

study.................................................................................................................................108

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LIST OF FIGURES

2.1: Results from the SSSM for the 15 turtles that migrated away from Crete. Each track

is colored to represent a different turtle and each circle represents a location estimate

from the SSSM. The circles are colored based on behavior mode exhibited at each

location...............................................................................................................................40

2.2: Raw Argos location data (LC: A, 0, 1, 2, or 3) for the turtles that migrated to Africa.

Each track is colored to represent a different turtle and each circle is colored to represent

a CPA behavior mode exhibited by the turtle at that location...........................................41

2.3: Raw Argos location data (LC: A, 0, 1, 2, or 3) displaying the turtles that migrated

into the Aegean Sea. Each track is colored to represent a different turtle and each circle

is colored to represent a CPA behavior mode exhibited by the turtle at that location.....42

2.4: Raw Argos location data (LC: A, 0, 1, 2, or 3) displaying the turtles that remained

near Crete. Each track is colored to represent a different turtle and each circle is colored

to represent a CPA behavior mode exhibited by the turtle at that location.......................43

2.5: Dive behavior during SSSM bmodes 1 and 2 for all turtles. Horizontal bars =

median; box = 50%; whiskers = range of observations within 1.5 times the interquartile

range from edge of the box; circles = observations farther than 1.5 times the interquartile

range...................................................................................................................................44

2.6: Dive behavior during SSSM bmode 1 for turtles based on migratory strategy (Africa:

n = 9; Aegean: n = 6). Horizontal bars = median; box = 50%; whiskers = range of

observations within 1.5 times the interquartile range from edge of the box; circles =

observations farther than 1.5 times the interquartile range................................................45

2.7: Dive behavior during SSSM bmode 2 for turtles based on migratory strategy (Africa:

n = 6; Aegean: n = 5; Crete: n = 4). Horizontal bars = median; box = 50%; whiskers =

range of observations within 1.5 times the interquartile range from edge of the box;

circles = observations farther than 1.5 times the interquartile range.................................46

2.8: Dive behavior during each CPA behavior mode (1-5) for all turtles. Horizontal bars =

median; box = 50%; whiskers = range of observations within 1.5 times the interquartile

range from edge of the box; circles = observations farther than 1.5 times the interquartile

range...................................................................................................................................47

2.9: Dive behavior during CPA behavior mode 1 for turtles based on migratory strategy

(Africa: n = 9; Aegean: n = 6). Horizontal bars = median; box = 50%; whiskers = range

of observations within 1.5 times the interquartile range from edge of the box; circles =


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(Africa: n = 7; Aegean: n = 4; Crete: n = 3). Horizontal bars = median; box = 50%;

whiskers = range of observations within 1.5 times the interquartile range from edge of the

box; circles = observations farther than 1.5 times the interquartile range.........................49






(Africa: n = 1; Crete: n = 1). Horizontal bars = median; box = 50%; whiskers = range of

observations within 1.5 times the interquartile range from edge of the box; circles =






3.1: Relationship between fitness proxies and foraging sites. Boxplots of CCL, SCL and

clutch sizes for the 3 migratory strategies. Horizontal bars = median; box = 50%;

whiskers = range of observations within 1.5 times the interquartile range from the edge of

the box; circles = observation farther than 1.5 times the interquartile range.....................75

3.2: Abundance (inds/ha) of loggerhead prey within the Gulf of Gabes, Tunisia (El

Lakhrach et al., 2012) and locations of foraging loggerhead turtles. The yellow circles

represent the location data of the nearshore resident turtles (n = 4), while the red circles

represent the location data of the offshore residents (n = 4)..............................................76

3.3: Abundance (inds/ha) of loggerhead prey within the Aegean Sea (Karakassis

unpublished data) and locations of foraging loggerhead turtles. The pink circles represent

the location data for the resident turtles within this region (n = 6)....................................77

3.4: Abundance (inds/ha) of loggerhead prey within the waters of Crete (Karakassis

unpublished data) and locations of foraging loggerhead turtles. The orange circles

represent the location data for the resident turtles within this region (n = 4)....................78

4.1: Map of the Mediterranean Sea indicating the 5 high usage sites for loggerheads....112

4.2: Mean daily sand temperatures from May 21—Aug 1 at the surface (0 cm) and at nest

depth (50 cm) at 3 monitored nesting locations on the beaches of Rethymno................113

x

4.3: a) Mean annual SST during the breeding months at the nesting sites of Crete and

Zakynthos/Kyparissia. Solid lines are the linear trend lines (Crete R2 = 0.477; Zak/Kyp

R2 = 0.370). b) Relationship between day of first female emergence and mean SST during

the breeding months in Zakynthos Island (R2 = 0.830). c) Projections of the day of first

female emergence through 2100 based on 13 climate model estimations of the increase in

SST during the breeding months at Zakynthos Island. d) Projected change in mean SST

during the breeding months for Crete based on results from 13 climate change models. e)

Projected change in mean SST during the breeding months for Zakynthos and Kyparissia

based on results from 13 climate change models...................................................114 – 115

4.4: a) Mean annual SST at the 5 high usage areas for loggerheads in the Mediterranean.

Solid lines are the linear trend lines (Adriatic R2 = 0.311; Aegean R

2 = 0.560; Crete R

2 =

0.674; Gabes R2 = 0.474; Zak/Kyp R

2 = 0.393). b) Projected change in mean annual SST

for the Adriatic Sea based on results from 13 climate change models. c) Projected change

in mean annual SST for the Aegean Sea based on results from 13 climate change models.

d) Projected change in mean annual SST for the waters of Crete based on results from 13

climate change models. e) Projected change in mean annual SST for the Gulf of Gabes

based on results from 13 climate change models. f) Projected change in mean annual

SST for Zakynthos Island and Kyparissia Bay based on results from 13 climate change

models....................................................................................................................116 – 117

4.5: a) August SST at the 5 high usage areas for loggerheads in the Mediterranean. Solid

lines are the linear trend lines (Adriatic R2 = 0.046; Aegean R

2 = 0.555; Crete R

2 = 0.499;

Gabes R2 = 0.190; Zak/Kyp R

2 = 0.251). b) Means of the projectd changes in August SST

for all 5 regions based on results from 13 climate change models..................................118

4.6: a) Mean Ta during the breeding months at 3 nesting site for loggerheads in Greece.

Solid lines are the linear trend lines (Crete R2 = 0.133; Kyparissia R

2 = 0.252; Zakynthos

R2 = 0.467). b) Relationship between day of first female emergence and mean Ta during

the breeding months in Zakynthos Island (R2 = 0.705). c) Projections of the day of first

female emergence through 2100 based on climate model (n = 14) estimations on the

increase in Ta during the breeding months at Zakynthos Island. d) Projected change in Ta

for Crete during the breeding months based on results from 14 climate change models. e)

Projected change in Ta for Zakynthos/Kyparissia during the breeding months based on

results from 14 climate change models..................................................................119 – 120

4.7: a) Projected change in precipitation rate for Crete based on results from 14 climate

change models. b) Projected change in precipitation rate for Zakynthos/Kyparissia based

on results from 14 climate change models. c) Mean of the projectd changes in

precipitation rates for Crete and Zak/Kyp during the breeding months based on results

from 14 climate change models.......................................................................................121

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4.8: a) Relationship between number of nests per season at Zakynthos and the mean

annual SST at the 5 foraging sites 2 years prior. Solid line is the linear trend line (R2 =

0.190). b) Relationship between number of nests per season at Rethymno and the mean

annual SST at the foraging sites (Gulf of Gabes, Aegean Sea and Crete) 2 years prior.

Solid line is the linear trend line (R2 = 0.572).................................................................122

APPENDIX A: a) Projected change in mean SST (oC) during August for the Adriatic Sea

based on results from 13 climate change models. b) Projected change in mean SST (oC)

during August for the Aegean Sea based on results from 13 climate change models. c)

Projected change in mean SST (oC) during August for Crete based on results from 13

climate change models. d) Projected change in mean SST (oC) during August for the Gulf

of Gabes based on results from 13 climate change models. e) Projected change in mean

SST (oC) during August for Zakynthos and Kyparissia Bay based on results from 13

climate change models...........................................................................................129 – 130

APPENDIX B: a) Projected change in mean precipitation (mm/month) during April, May

and June for Crete based on results from 14 climate change models. b) Projected change

in mean precipitation (mm/month) during April, May and June for Zakynthos and

Kyparissia based on results from 14 climate change models..........................................131

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ABSTRACT

Movements, Behaviors and Threats to Loggerhead Turtles (Caretta caretta) in the

Mediterranean Sea

Samir H. Patel

James R. Spotila, Ph.D., Advisor

Stephen J. Morreale, Ph.D., Advisor

The purpose of this study was to determine the at-sea behavior of loggerhead

turtles (Caretta caretta) in the Mediterranean Sea in order to gain a better understanding

of the various environmental factors that play a role in their survival. By determining the

environmental conditions that have a controlling force over foraging and nesting success,

more accurate projections can be made on the future of this declining subpopulation of

loggerheads. I deployed 20 satellite transmitters on postnesting adult loggerhead turtles

from Rethymno, Crete, Greece, with 19 functioning through migration. Using a

changepoint analysis model, I determined that loggerheads in the Mediterranean

exhibited 5 behavior modes. Within these modes were migration, foraging and

overwintering, along with newly discovered transition modes between each established

sea turtle behavior. Overall, the turtles exhibited 3 unique postnesting strategies, 9

migrated to the North African coast, 6 migrated into the Aegean Sea and 4 remained

within the waters of Crete. These three strategies corresponded to fitness differences

between the turtles. The northern turtles were larger and had larger clutch sizes than those

foraging near Crete and Africa. This corresponded to the abundance of prey from each

region. The benthic environment of the Aegean had the largest prey abundance compared

to the other sites. Around Crete there is very limited benthic environment to support

loggerhead foraging, and in the Gulf of Gabes the prey abundances are reduced due to a

xiii

high influx of industrial runoff. The Gulf of Gabes is home to ~40% of loggerheads

nesting in Greece, and as global warming continues, the rising temperature is expected to

exacerbate the deterioration of the benthic environment. Furthermore, there is already a

strong female bias in sex ratio for Mediterranean loggerheads, which is expected to

continue to get stronger as beach temperatures rise and precipitation declines.

Loggerheads may be able to compensate for these changes, and I found that their nesting

phenology is expected to shift earlier by as much as 52 - 74 days by 2100; however the

factors threatening the survival of this species may be too strong to overcome.

1

CHAPTER 1: General introduction

Among sea turtles, loggerhead turtles (Caretta caretta) are one of the most

ecologically generalized species in terms of feeding, foraging and nesting behavior

(Bolton, 2003). While this generalist behavior may contribute to a greater resilience, this

species is still globally endangered (IUCN 2013). Like all sea turtles, loggerheads face a

variety of human induced threats both on land and at sea. Due to their nature of nesting

within the highest latitudinal range, loggerhead nesting beaches tend to be in developed

countries (Witherington, 2003). This has the benefit of being within the controlling range

of such protective legislation as the Endangered Species Act of the United States;

however, also means these beaches are highly sought after by tourists and further

development (Witherington, 2003). The vast latitudinal range also puts loggerheads in the

path of a broad set of fishing vessels. Estimates suggest that pelagic longline fisheries

alone account for between 220,000 and 250,000 loggerheads caught globally as bycatch

(Lewison et al., 2004). Furthermore, with the changes expected to occur as global

temperatures continue to increase, a loss of nesting beaches due to sea level rise, a

demographic shift towards a female bias due to increased beach temperatures and a

reduction of benthic prey abundance due to rising sea temperatures may pose the largest

threats to the overall survival of loggerheads (Witt et al., 2010; Vaquer-Sunyer and

Duarte, 2008). To advance the understanding of the at-sea behavior and threats from

climate change on loggerhead turtles, I chose to study the loggerheads of Greece with an

emphasis on the nesting population of Rethymno, Crete, as this population is relatively

understudied compared to the larger nesting populations in the region.

2

Within the Mediterranean Sea, loggerheads are widely distributed, with juveniles

and sub-adults from nesting grounds in the Atlantic Ocean residing in the Western basin

to resident nesting populations in the Eastern basin (Laurent et al., 1998; Margaritoulis,

2003; Carreras et al., 2006). The nesting populations of the Eastern Mediterranean Sea

comprise a unique subpopulation of loggerheads due to morphological (smaller carapace

sizes) and genetic differences to their Atlantic counterparts (Bowen et al., 1993;

Margaritoulis et al., 2003). Monitoring sea turtle nesting behavior within the Eastern

Mediterranean Sea primarily occurs in the countries of Greece, Cyprus and Turkey

(Margaritoulis et al., 2003). Greece is home to the largest nesting populations within the

region with Zakynthos Island, Kyparissia Bay and Rethymno being the 3 most important

nesting beaches within the country (Margaritoulis et al., 2003). ARCHELON, The Sea

Turtle Protection Society of Greece began beach monitoring in Zakynthos Island in 1982,

while monitoring started in Kyparissia Bay in 1984 and in Rethymno in 1990

(Margaritoulis et al., 2001; 2005; 2009). During the first 6 years of monitoring in

Rethymno, nest numbers per season ranged from 336 to 516 (Margaritoulis et al., 2009).

However, since beach monitoring began annual nests numbers have significantly

declined (Margaritoulis et al., 2009). This population is considered an important stepping

stone genetically between western Greek and further eastern Mediterranean nesting

populations (Carreras et al., 2007). Since the decline in nests per season is not attributable

to a decline in nesting beach protections, preservation of the nesting loggerheads in

Rethymno cannot be controlled by beach monitoring alone and requires identifying

threats away from the nesting beaches. Rather, we need to identify their at-sea behavior

and the oceanographic and climatic conditions that may be impacting nest success.

3

Chapter 2: Changepoint Analysis

The use of satellite telemetry on marine turtles has risen exponentially since the

first successful radio and satellite tracking of sea turtles in 1978 and 1980 (Standora, et

al. 1982; Stoneburner 1982). As of 2007, there were 38 satellite telemetry studies on

loggerheads with 12 occurring within the Mediterranean (Godley et al. 2007). As the

amount of satellite telemetry data has increased, new statistical tools have developed to

interpret animal movement behavior. The most common tool currently is the State-Space

Model (SSM), used to study animal movement behavior since 1991 and first utilized on

sea turtle data by Jonsen et al. (2003). A few years later, Jonsen et al. (2007) and Bailey

et al. (2008) utilized a Switching State-Space Model (SSSM) and designed the model to

fit sea turtle telemetry data as it included parameters that would estimate the behavior of

the animal based on horizontal movement. Under the conditions of the SSSM, location

data are analyzed to determine when a change in the turn angle and rate of the animal

occurs (Jonsen et al., 2007). This change in horizontal movement is used to identify a

switch in behavior from, in the case of sea turtles, transiting to area restricted search

(Bailey et al., 2008). This method, however, only works in the 2 dimensional plane of

latitude and longitude and does not take diving behavior into consideration. Due to this

limitation, the model is unable to determine the complexities of sea turtle at-sea behavior.

As a result, I have developed a model based on the changepoint analysis developed by

Killick et al. (2012). In this model, dive behavior is accounted for along with location

data, thus a 3 dimensional interpretation. In chapter 2, I describe the methods and results

of this model using the data from 19 satellite transmitters I deployed from Rethymno,

Crete on postnesting female loggerheads.

4

Chapter 3: Fitness Differences

Sea turtles, like many large marine vertebrates, migrate great distances due to

resource availability (Boyle and Conway, 2007; Corkeron and Connor, 1999; Morreale et

al., 2007). These resources play a strong role in controlling many fitness parameters.

During times of low food availability, marine iguanas shrink in size by 20% and fish

species reduce their foraging activity (Sograd and Olla, 1996; Wikelski and Thom, 2000).

In sea turtles specifically, food availability controls the reproductive fitness of

leatherbacks (Dermochelys coriacea) in the Atlantic and eastern Pacific Oceans, along

with loggerheads in the western Pacific Ocean (Wallace et al., 2006; Saba et al., 2007,

2008; Chaloupka et al., 2008). In the Mediterranean Sea, a fitness dichotomy has been

identified, whereby northern foraging loggerheads are larger and produce larger clutch

sizes than their southern foraging counterparts; however no mechanism for this trend has

been identified (Zbinden et al., 2011). As adult loggerheads throughout the Eastern

Mediterranean forage from the benthic environment, the differences in fitness parameters

of subpopulations residing in different foraging grounds may be a proxy for prey value

and abundance from those regions. In chapter 3, I discuss the differing prey values and

abundances from the major foraging sites as a possible mechanism for the fitness

differences between the 3 unique foraging strategies exhibited by the loggerheads I

tracked via satellite telemetry. Those foraging in the Aegean Sea had longer curved and

straight carapace lengths and produced larger clutch sizes than those turtles foraging

within the waters of Crete or along the North African coast.

5

Chapter 4: Climate Change

Although the warming of the oceans is 3 times slower than air temperature on

land, marine species are shifting distributions and phenology at a greater rate than those

in terrestrial systems (Poloczanska et al., 2013). According to the IPCC (2007), “warming

of the climate system is unequivocal… [resulting in] increases in global average air and

ocean temperatures… and rising global average sea level.” Thermal expansion of the

oceans is contributing 57% of the total estimated sea level rise; the remainder is as a

result of the decline of land-based polar ice, glaciers and ice caps (IPCC 2007). Extreme

climatic events are expected to increase in frequency along with steady, yet dramatic,

changes for example a 0.3 - 0.5 decrease in ocean pH (IPCC 2007). All of these products

of global warming have a profound effect on species from all realms of the globe. These

include phenological shifts in bird migrations, flowering plants and sea turtle nesting to

altitudinal and latitudinal range shits of plants and animals alike to widespread habitat

destruction as coral reefs continue to decline and glaciers steadily melt (Parmesan and

Yohe, 2003; Barnett et al., 2005; Hoegh–Guldberg et al., 2007; Hawkes et al., 2009;

Newson et al., 2009; Poloczanska et al., 2013). Oceanographic and climatic conditions

such as sea surface temperature, air temperature and precipitation have been identified as

a major driving forces in the behavior and success of sea turtle nesting and foraging (Sato

et al., 1998; Hays et al., 2002, 2003; Mazaris et al., 2004, 2008, 2009; Weishampel et al.,

2004; McMahon and Hays, 2006; Pike et al., 2006; Hawkes et al., 2007; Houghton et al.,

2007; Saba et al., 2007, 2012; Chaloupka et al., 2008; Santidrián Tomillo et al., 2012;

Luschi et al., 2013).

6

Sea turtles, like many large marine animals, require a variety of habitats for their

various life stages, both in water and on land. Nesting beaches are critically important

due to the value of eggs and hatchling success in contributing to the future success of the

species. Unfortunately, beaches are impacted by the increase in sea level and temperature

and extreme climatic events such as hurricanes having the potential to cause severe

damage (Hawkes et al., 2009). Rise in sea level may lead to a variety of repercussions.

For example, Baker et al. (2006) forecast a sea level increase of 0.9 m would inundate 40

% of a Hawaiian nesting beach for Chelonia mydas. Such a loss in nesting area could

easily contribute to a decline in reproductive success due to increased nest density,

intense erosion and increased interaction with coastal development (Hawkes et al., 2009).

Furthermore, Saba et al. (2012) predict that the changes in beach conditions (air

temperature and precipitation), expected to occur under climate change models, will

cause a 7 % decline in the leatherback nesting population of Playa Grande per decade. In

Zakynthos, Mazaris et al. (2008, 2009) identified trends between nesting behavior and

sea surface temperature within the Mediterranean Sea. These trends include a shift in

nesting phenology and a reduction in nests per season corresponding to an increase in sea

surface temperature at both the foraging and nesting sites (Mazaris et al., 2008; 2009). In

chapter 4, I compare nesting in Zakynthos, Kyparissia Bay and Rethymno to historical

climatic and oceanographic conditions (air temperature, precipitation and sea surface

temperature). Furthermore, I discuss how the foraging and nesting environments will

change under conditions of climate change and project how nesting phenology in

Zakynthos will shift as air and sea temperature continues to increase.

7

References

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2008. Identifying and comparing phases of movement by leatherback turtles using

state-space models. Journal of Experimental Marine Biology and Ecology 356:

128 – 135.

Baker, J.D., C.L. Littnan, and D.W. Johnston. 2006. Potential effects of sea level rise on

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Hawaiian Islands. Endangered Species Research 4: 1 – 10.

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Bowen, B., J.C. Avise, J.I. Richardson, A.B. Meylan, D. Margaritoulis, S.R. Hopkins-

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northwestern Atlantic Ocean and Mediterranean Sea. Conversation Biology 7:

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Boyle, W.A. and C.J. Conway. 2007. Why migrate? A test of the evolutionary precursor

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Carrera, C., S. Pont, F. Maffucci, M. Pascual, A. Barceló, F. Bentivegna, L. Cardona, F.

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12

CHAPTER 2: Changepoint analysis: a new approach for understanding animal

movements and behaviors from satellite telemetry data

Abstract

During the 2010 and 2011 nesting season in Rethymno, Crete, Greece, I deployed

20 satellite transmitters on post-nesting loggerhead turtles to monitor their at-sea

behavior. Of these, 19 transmitters provided location and dive data during migration and

foraging, and eight continued transmitting while the turtles exhibited overwintering

behavior. The satellite-tracked turtles exhibited three discrete migratory and foraging

strategies, with nine turtles migrating southwards to the coasts of Africa, six turtles

migrating northwards into the Aegean Sea, and four turtles remaining resident in the

waters of Crete. To analyze the telemetry data, I employed both a Bayesian switching

state-space model (SSSM) and a changepoint analysis model (CPA). The SSSM only

analyzed horizontal movement patterns, while the CPA accounted for more dimensions,

incorporating both horizontal and vertical movement data. I used both models to identify

the changes in the behavior of the turtles, such as the switches from migration to foraging

and from foraging to overwintering. The SSSM distinguished only when and where

turtles exhibited transiting and area restricted behaviors, whereas the CPA was able to

distinguish migration, foraging and overwintering behaviors, as well as highlighting the

transition phases between each behavioral mode. By using this improved CPA model to

characterize at-sea behavior modes of sea turtles, I have enhanced the suite of analytical

tools to elucidate specific animal behaviors from remotely sensed telemetry data.

Furthermore, this enhanced knowledge can lead to better conservation and management

solutions.

13

Introduction

It has long been acknowledged that the Mediterranean Sea provides important

breeding and foraging areas for the loggerhead turtle, Caretta caretta, and that

individuals migrate freely between these regions. As of 2007, 38 studies on satellite

tracking of loggerhead turtles were published worldwide, with 12 focused in the

Mediterranean Sea (Godley et al., 2007). From these numerous studies, it has been

identified that loggerhead turtles occupying different nesting beaches in the

Mediterranean Sea exhibit a range of unique migratory strategies, travelling between 200

to 2500 km from the nesting beaches (Broderick et al., 2007; Godley et al., 2003;

Zbinden et al., 2008; Margaritoulis and Rees, 2011). In addition to the broad range of

horizontal movements, loggerheads in the Mediterranean can forage in benthic

environments up to 100 m deep (Zbinden et al., 2008), and can spend up to 10 hours

submerged during overwintering (Broderick, et al., 2007).

The major nesting sites for the loggerheads in the Eastern Mediterranean are on

the beaches of Greece, Turkey and Cyprus (Margaritoulis, 2003); whereas foraging

mainly occurs in the Gulf of Gabes, Tunisia and in the Adriatic and Aegean Seas

(Margaritoulis and Rees, 2011), due to the wide continental shelves found in these

regions (Coll et al., 2010). Despite long-term protection of many loggerhead turtle

nesting beaches in Greece, nesting populations continue to decline (Margaritoulis et al.,

2009; 2011). One population of particular conservation concern is the third largest

nesting population in Greece, located at Rethymno, Crete. This population is considered

an important component of gene flow between western Greek and more eastern

Mediterranean nesting populations (Carreras et al., 2007).

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Despite the importance of Rethymno, very limited research has been done there.

Beyond the efforts centered on beach protection and flipper tagging, only one satellite

transmitter has been deployed on a single nesting turtle (Margaritoulis and Rees, 2011).

The data from a total of 356 flipper tags, placed on turtles since 1990, has yielded

movement information from only 17 tags that have been recovered at-sea (Margaritoulis

and Rees, 2011). These first-level data on movements of turtles nesting at Crete have

been informative, but knowing more precisely how these turtles make use of the

Mediterranean, both through horizontal and vertical movement data, undoubtedly would

provide a clearer picture for conservation and management actions (Godley et al., 2007).

The objective of this study was to reveal and document the at-sea behavior of the

understudied nesting population of loggerhead turtles of Rethymno, Crete by employing a

new statistical approach to incorporate the full suite of telemetry data available from

current satellite transmitters. A broader goal of this study was to improve regional

conservation and management plans by identifying migratory pathways and potential

foraging and overwintering areas, as well as the various vertical movements associated

with the three phases of sea turtle at-sea behavior of loggerheads: 1) migration, 2)

foraging and 3) overwintering (Carr, 1967).

Methods

During the 2010 and 2011 loggerhead nesting seasons, I deployed 20 satellite

transmitters to track the post-nesting behavior of adult female loggerheads both

horizontally and vertically throughout the Mediterranean Sea. To statistically analyze the

movements and behaviors of these animals, I used a switching state-space model (SSSM;

Jonsen et al., 2007; Bailey et al., 2008) and augmented this standard analysis with a

15

changepoint analysis model (CPA; Killick et al., 2012). A CPA has never been applied to

sea turtle satellite telemetry data and provided the option of consolidating vertical and

horizontal movement metrics into a single analysis.

During the months of June – July of both years, I placed transmitters on turtles

opportunistically during nightly patrols of select sections of the nesting beach near

Rethymno (latitude 35.385o, longitude 24.590

o). Those sections of beach have historically

been patrolled by ARCHELON, and were known to have the highest density of nesting

activity. For each turtle encountered, I waited until egg-laying was completed after which

I measured the straight and curved carapace length and width. The length measurements

were taken from the nuchal notch to the tip of the supercaudal scute and the width

measurements were taken from the widest points of the carapace. Next, I applied two

external flipper tags for the ARCHELON monitoring project as an identifier for each

turtle (Margaritoulis and Rees 2011). I then determined each turtle’s current reproductive

status with a portable real-time ultrasound imaging device (Rostal et al., 1996; Blanco et

al., 2012a). During the 2010 season, I used an Aloka SSD-500 during the 2011 season a

Sonosite 180 Plus. These portable devices allowed me to scan one ovary and oviduct at a

time by placing the ultrasound probe in the inguinal region above the hind flipper while

the turtle was covering the nest (Blanco et al., 2012a). I recorded scans of each oviduct

and ovary using an attached printer for the Aloka SSD-500, and stored digitally when

using the Sonosite 180 Plus. This noninvasive process took approximately 5-7 minutes

for each turtle. Finally, I attached the transmitters using a tethering method, a process that

took 7-10 minutes.

16

Satellite Transmitter Attachment

I obtained location, dive, and temperature data using pop-up archival satellite

transmitters with opportunistic transmissions. I used Wildlife Computers (Redmond,

WA) tag models Mk10-PAT for 19 turtles and Mk10-AF (with Fastloc GPS capabilities)

for 1 individual (table 2.1). All turtles were reproductively active adult female

loggerheads; all transmitters were attached after the turtle had finished depositing eggs.

I followed a modified procedure from Morreale et al. (1996), Morreale (1999) and

Blanco et al. (2012b) to attach a buoyant hydrodynamic satellite transmitter to a sea turtle

via a short tether. First, I cleaned a supracaudal scute with 70% alcohol, then, within this

scute, I made a small circular incision (5.0 mm) using a sterilized drill bit and battery

powered drill. I immediately cleaned the incision with a povidine-iodine topical antiseptic

solution. Next, I inserted sterilized surgical tubing (3.2 mm inside diameter, 6.4 mm

outside diameter and a 1.6 mm wall thickness) into the incision. The surgical tubing

prevented direct contact between the tether and the carapace, ensuring that the movement

of the flexible tether would not abrade the carapace. Then I inserted the tether (181 kg

test monofilament fishing line) through the rubber tubing, through a button on the ventral

side of the carapace and finally back up and through the tubing. The tether also passed

through a button on the dorsal side to inhibit contact between the crimp and the carapace.

The ventral button spread the force of the transmitter pulling on the carapace, thus

reducing its pressure and further limiting the impact of the attachment. The buttons were

made from high-density polyethylene with smoothed and rounded edges. I secured the

tether to both the carapace and transmitter with double barreled copper crimps size 2.2B.

In approximately the middle of the tether I included a 172 kg-test swivel to allow for

17

rotational movement of the tag. These crimps and swivels were corrodible so that they

would break away within a year or less. The length of tether, from transmitter to

carapace, ranged between 15 and 25 cm to ensure that the individual did not entangle

itself with either front or rear flippers. This method yielded a minimal processing time of

7-10 min, minimal hindrance and restraint to the turtle during attachment, and low impact

to the carapace and extremely low level of drag compared to objects directly attached to

the anterior portions of the carapace (Logan and Morreale, 1994; Watson and Granger,

1998, Jones et al., 2011).

Satellite Transmitters

I modified the Mk10-PAT transmitters to increase their buoyancy and to ensure

an upright posture once the turtle slowed forward movement at the surface (Blanco et al.,

2012b). This was achieved by gluing a custom–made, hydrodynamically shaped cone of

syntactic foam to the preexisting float material. The modified transmitters weighed ~115

g and had a buoyancy of ~36 g (Blanco et al., 2012b). Most importantly, the overall

shape of the transmitter was hydrodynamically designed to reduce drag and the

attachment method allowed for the tag to remain in the turtle’s slipstream as it swam

(Logan and Morreale, 1994, Blanco et al., 2012b). The GPS (PAT-Mk10-F) transmitter

was not physically modified.

The transmitters were programmed to compile and transmit dive and temperature

data as histograms summarizing 4-hour periods. In 2010, I set the transmitters to a 6 hour

on: off duty cycle, with a maximum of 75 transmissions per day, with unused transmits

carried over to the next day. For the 2011 season, the programmed duty cycle did not

limit transmissions based on timing of day or year; however I limited the overall number

18

of transmissions to 52 per day in an effort to prolong battery life. I did continue to allow

for transmits to be carried over if unused. All transmitters sampled and summarized

diving data (dive depth, dive duration, and time at depth) in pre-assigned bins. A dive

was classified as reaching below 1 meter and lasting longer than 1 minute. The histogram

bins for dive depth and time at depth were 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 75, 100,

200 and >200 meters of depth. Dive durations were placed into bins of 2, 5, 10, 20, 30,

40, 50, 60, 90 and >90 minutes. In addition, maximum and minimum temperatures were

recorded at the sea surface and at intervals of 8 meters of depth.

Post-nesting Movements and Behaviors

I conducted all spatial referencing, mapping and plotting of spatially referenced

data using ArcGIS 9.3 and 10.0 (ESRI 2011). For turtle locations, I used only Argos

location of classes (LC) 3, 2, 1, 0, A, and the GPS locations. I determined the start of

post-nesting behavior either through ultrasonography that revealed an empty ovary, or

through receiving successive location points from the turtle obviously moving away from

the nesting beach. I measured tortuosity by dividing the straight line distance by the

actual path of the turtle. Tortuosity is measured in a 0 to 1 scale with a value of 1

equaling a straight line and a value of 0 being least straight (Benhamou, 2004).

Switching State-Space Model (SSSM)

To generate daily position estimates, I applied a Bayesian switching state-space

model (Jonsen et al., 2007, Bailey et al., 2008) to all raw location data for each track (n =

19). Location estimates were inferred by coupling a statistical model of the observation

method (measurement equation) with a model of the movement dynamics (transition

equation) (Patterson et al., 2008, Bailey et al., 2008). The measurement equation

19

accounted for errors (published estimates) in observed satellite locations (Vincent et al.,

2002). When satellite positions were missing, linearly interpolated positions were used as

initial values (Bailey et al., 2008). The transition equation was based on a first-difference

correlated random walk model (Jonsen et al., 2005, Bailey et al., 2008). In addition, this

equation included a process model for each of two behavioral modes (Jonsen et al.,

2005). Behavioral mode 1 (bmode 1) was considered to represent transiting (migration)

and behavioral mode 2 (bmode 2) represented area restricted search (foraging and

overwintering) (Bailey et al., 2009). Transiting (bmode 1) was categorized as having a

turn angle of closer to 0 with autocorrelation higher than during area restricted search

(bmode 2) (Jonsen et al., 2007). Calculated values of < 1.25 were categorized as bmode

1, while those > 1.75 were considered bmode 2. All values in-between were regarded as

uncertain behavioral mode.

The model was fitted using the R software package and Winbugs software (Lunn

et al., 2000, Bailey et al., 2012). Two chains were run in parallel, each for a total of

30,000 Markov Chain Monte Carlo Samples, with the first 10,000 samples discarded as

burn-in, and the remaining samples thinned, retaining every fifth sample to reduce

autocorrelation (Blanco et al., 2010).

Changepoint Analysis (CPA)

To include a more comprehensive set of metrics from the transmitters, I applied

changepoint analyses with binary segmentation to incorporate all horizontal and vertical

movement data for each turtle individually. To more fully interpret the at-sea behavior of

these turtles, I used a total of 9 separate measured variables. As with the SSSM analysis, I

calculated turn angle and rate, the two horizontal movement metrics, using the raw

20

location data from ARGOS and algorithms and script generated in dBase Plus software.

In addition, I consolidated dive behavior data into 7 key metrics: percentage of time at

surface (above 5 m of depth), percentage of time above median dive depth, mean dives

per sample period, max dive depth per sample period, mean dive duration per sample

period, max dive duration per sample period, and variance in dive duration per sample

period. All dive metric sample periods were 4 hours in duration. The main strength of the

changepoint analysis was to calculate when a shift in the mean and variance occurred

within each parameter arranged by time. For each selected metric, I calculated a

maximum of 20 changepoints, well above the expected number of behavioral modes

exhibited by a sea turtle. Then I overlaid these changepoints to discover at what date and

time there was a shift in the mean and variance for many metrics simultaneously. I

considered changepoints occurring within a period of 1 day as simultaneous. When there

were simultaneous shifts in several metrics, it was deemed that an individual had changed

overall at-sea behavior. The model was run using the changepoint package for R (Killick

et al., 2012).

I used results from both the switching state-space model and the changepoint

analysis to interpret the horizontal and vertical movement data. Using the combination of

models, I determined with more accuracy the temporal range for the various at-sea

behaviors (migration, foraging and overwintering) and the overall movement and dive

patterns associated with each behavioral mode. I compared dive behavior for each turtle

for foraging and overwintering, as well as the location of residency in the Mediterranean

(One Way ANOVA; statistical significance at a level of 0.05). Statistical analyses were

21

performed in R (Venables and Smith, 2013). I calculated turn angles and net movement

rates with a custom-made program using dBase Plus software.

Results

I obtained data from 19 of the 20 turtles after they finished nesting for the season

and were tracked as they moved away from the beaches of Rethymno (table 2.1; figures

2.1, 2.2, 2.3 and 2.4). Transmitter durations during post-nesting periods ranged from 11

to 250 days (mean ± SD: 136 ± 74.3 days), totaling 2718 days of tracking data. Five

transmitters from 2010 averaged 104 ± 68.3 days, while the 15 transmitters from

2011with the updated duty cycle averaged 147 ± 75.2 days. I received a total of 4066

location points, 2601 dive behavior histograms, and 1065 temperature histograms.

Approximately 24% of the location data were of classes 3, 2, 1, 0, A or GPS.

The switching state-space model calculated that behavior mode 1 (bmode value <

1.25) occurred 11.4% of the time, while behavior mode 2 (bmode value > 1.75) occurred

76.3% of the time. The remaining 12.3% of tracking data were calculated as uncertain

behavior (1.25 < bmode value < 1.75).

Using the changepoint analysis, I calculated a total of 5 behavior modes, with no

uncertain behavior mode. Behavior mode 1 represented migration, and this was only

exhibited by those turtles that traveled away from Crete. Behavior mode 2 was a

transition behavior prior to foraging, coming after either the nesting or migration phases.

Behavior mode 3 was designated as foraging behavior. Behavior mode 4 also represented

a transition phase; however this time between foraging and overwintering and behavior

mode 5 represented overwintering.

22

Of the 20 turtles tracked, 15 were determined to exhibit post-nesting migrations

away from Crete (figures 2.1, 2.2 and 2.3). Nine individuals (Turtles 1 – 9) travelled to

the North African coast, with eight ultimately settling in the Gulf of Gabes, Tunisia, and

one maintaining residency along the northeastern Libyan coast. The remaining six turtles

that migrated (Turtles 10 – 15) travelled north into the Aegean Sea Loggerheads tracked

into the Aegean Sea never went farther north than 38.5o latitude, and those off the waters

of Tunisia never went farther west than 10.4o longitude. The most easterly position of a

tracked turtle in this study was 27.7o longitude. Migration distances for the turtles that

travelled away from Crete, calculated using the raw Argos data, ranged from 237 to 2347

km and exhibited travel speeds from 36.0 to 52.8 km day-1

.

For those turtles that migrated south to the African coast, four established

residency offshore, never coming closer than 40 km from land. The remaining five

loggerheads first travelled to the coasts of Libya, with four of these turtles then slowly

continuing their migrations westward towards the Gulf of Gabes, Tunisia. Turtles 8 and 9

took particularly distinct migrations, travelling first east then southwest around Crete,

while the rest of the turtles all travelled west from Rethymno in a direct path to Africa

(tortuosity mean ± SD of Turtles 1 – 7 = 0.87 ± 0.08; Turtles 8 – 9 = 0.48 ± 0.06). In

comparison the six turtles that migrated to the Aegean Sea (tortuosity Turtles 10 – 15 =

0.75 ± 0.17) ended up residing in three different regions. Two travelled to the Saronikos

Gulf, near Athens; two turtles maintained residency near central Aegean islands, Nisos

Ikaria and Naxos; while the remaining two migrated to the coastal waters of Turkey near

Izmir and Bodrum. Four turtles never left the coastal waters of Crete after they finished

nesting (figure 2.4). Turtles 16 - 19 found separate sites of residency around Crete. Three

23

remained on the north coast, their sites of residency did not overlap, and the fourth

shifted slightly to the island of Gavdos, 35 km south of Crete.

Sites of residency for all individuals were characterized by depths shallower than

200 m and were within 200 km of a coast. The turtles on the expansive Tunisian Shelf

were much farther from land than those in the Aegean Sea and within the waters of Crete,

which stayed much closer to the coasts and resided in much smaller bays.

SSSM Behavior Mode 1 – Transiting:

The SSSM calculated that 15 turtles exhibited transiting behavior (bmode 1)

(figure 2.1). With the smoothed tracks from the SSSM, calculated distances travelled

throughout bmode 1 ranged from 187 to 2077 km and travel rates ranged from 32.5 to

53.6 km day-1

. The individuals that travelled to the African coast averaged (mean ± SD)

33.8 ± 9.3 days during SSSM bmode 1; while those that settled in the Aegean averaged

far less at only 7.7 ± 2.3 days. The SSSM results for turtles 1, 2 and 9 were inconsistent

with the results for all other individuals. Turtles 1 and 9, according to the SSSM, only

exhibited behavior mode 1, even though both turtles clearly stopped migrating in the Gulf

of Gabes. As a result, a switch to area restricted search (bmode 2) should have been

represented. For turtle 2, on the other hand, the SSSM calculated that it only exhibited

uncertain behavior throughout the tracking duration; while it also clearly exhibited a

directed migration towards Tunisia.

During transiting behavior, as calculated by the SSSM, turtles (n = 15) averaged

(mean ± SD) 11.4 ± 7.7 dives per four hour sample period, with 55.8% of dive time spent

between 1 and 5 meters of depth. Dive durations during SSSM bmode 1 averaged 18.5 ±

17.3 minutes. Individuals that travelled to the coast of Africa averaged 11.5 ± 7.8 dives

24

per sample period, while those migrating north into the Aegean Sea averaged slightly

fewer at 10.3 ± 6.1 dives per sample period. Turtles migrating southwards also took

slightly shorter dives on average (mean ± SD = 18.2 ± 16.9 minutes) than those migrating

north (24.2 ± 21.2 minutes) and spent less time at the surface (Africa: 54.5% of dive time

and Aegean: 71.8% of dive time) (figure 2.6).

SSSM Behavior Mode 2 – Area Restricted Search:

The SSSM bmode 2 (area restricted search) encompassed 76.4% of all dive data

including those turtles that did not migrate away from Crete. Turtles 1, 2, 9, however,

were missing from this analysis due to inconsistent SSSM results and Turtle 11 due to a

lack of data beyond transiting phase. Turtles during area restricted search averaged (±

SD) 10.6 ± 9.6 dives per sample period, 18.6 ± 20.0 minute dives and spent 30.4% of

dive time above 5 meters of depth. There were slight differences in the dive behavior

during SSSM bmode 2 for turtles from the 3 different regions. Individuals that

maintained residency in the Aegean Sea took the most dives on average (Aegean: mean ±

SD = 12.3 ± 9.5 dives; African: 9.88 ± 11.3 dives; Cretan: 8.27 ± 5.9 dives), with the

shortest average dive duration (Aegean: 17.3 ± 18.9 minutes; African: 17.4 ± 20.3

minutes; Cretan: 24.5 ± 21.5 minutes) and there was a significant difference in the

amount of dive time spent closest to the surface (Aegean: 37.1%; African: 25.3%; Cretan:

25.2%; p < 0.001, F = 14.7) (figure 2.7). These regional differences, however, are most

likely due to the duration of available data, as the transmitters on the Cretan turtles lasted

the longest. This skews the Cretan data with a higher amount of overwintering behavior

(i.e. fewest dives per sample period, longest dive durations and shortest amount of time

spent at the surface) compared to the other regions.

25

CPA Behavior Mode 1 – Migration:

Behavioral mode 1, as calculated by changepoint analysis, was categorized as

migration for those 15 turtles that travelled away from Crete (figures 2.2 and 2.3);

however for the turtles that migrated north, this behavioral mode also included several

days during which the turtles had already arrived at its site of residency (figure 2.3).

Turtles overall, during this behavioral mode, averaged more dives (14.1 ± 8.7 dives per

sample) and shorter dive durations (16.0 ± 14.9 minutes) than during the SSSM bmode 1

(figures 2.5 and 2.8). In addition, CPA behavior mode 1 was characterized by 52.3% of

dive time spent above 5 meters of depth. Differences were found in dive behavior based

on region. There was a significant difference in the number of dives per sample period

between region, with the northern migrating turtles averaging the most dives (Aegean:

mean ± SD: 15.4 ± 8.7 dives; African: 10.9 ± 7.8 dives; p < 0.0001; F = 17.4) (figure

2.9). In addition, turtles that migrated into the Aegean Sea averaged shorter dive

durations and spent slightly less time closer to the surface (Aegean: 14.7 ± 13.1 minutes;

51.5% of dive time; African: 20.0 ± 18.9 minutes; 53.8% of dive time).

CPA Behavior Mode 2 – Transition Behavior:

Behavioral mode 2 as calculated by the CPA represented a transition phase

between migration (or nesting) and foraging. Fourteen turtles exhibited such a transition

behavior; but this did not imply that the turtle had arrived at a site of residency. For

several turtles this transition behavior was indeed a slowing of travel rate, but not a

change in turn angle. Three turtles (5, 13 and 16) began what appeared to be foraging

immediately after migration; this included a switch to far more localized movement;

while for two turtles (2 and 11) the transmitter lost contact immediately after migration

26

ended. The transition behavior averaged 20.8 ± 10.8 days with a range of 6 – 39 days.

Turtles that travelled north had the shortest transition period, followed by the African

migrants with the turtles that remained near Crete exhibiting the longest transition phases.

When compared to the CPA identified migration phase, the transition behavior

was characterized by a decrease in mean dives per sample period (mean ± SD = 12.5 ±

8.9) and a slight increase in mean dive duration (16.6 ± 15.6 minutes). There was also a

significant decline in the amount of time spent above 5 meters (43.4% of dive time; p =

0.01, F = 6.11) (figures 2.8 and 2.10). In addition, for the migrant turtles there was a

substantial decline in travel rate to a mean (± SD) of 11.0 ± 5.8 km day-1

between

behaviors 1 and 2.

CPA Behavior Mode 3 – Foraging:

Behavioral mode 3, as calculated by CPA, was categorized as foraging. For the

turtles that exhibited a change in behavior to overwintering (n = 8), foraging lasted on

average 70.3 ± 33.0 days; for the remaining turtles, foraging continued without a distinct

change in behavior (as calculated by the CPA) until the transmitter stopped functioning.

The foraging behavioral mode was characterized by a slight decrease in mean rate of

diving (11.2 ± 9.83 dives/period) and an increase in mean dive durations (19.1 ± 18.5

minutes). Additionally, there was a significant decline in the amount of time spent above

5 meters of depth when compared with migration and the transiting behaviors (32.0%; p

< 0.0001; F = 32.0) (figure 2.8). Regionally dive behavior differed during the foraging

mode. There was a significant difference in the number of dives per sample period (p =

.01, F = 4.50), with turtles migrating to Africa averaging the highest number of dives

(African: 12.5 ± 11.3 dives; Aegean: 10.2 ± 8.4 dives; Cretan: 9.12 ± 6.0 dives). This was

27

associated with turtles residing in African waters taking shorter dives on average (16.0 ±

15.3 minutes) than those remaining in more northern waters (Aegean: 22.8 ± 23.1

minutes; Cretan: 22.7 ± 17.8 minutes) (figure 2.11). There was not a significant

difference in time spent at the surface among foraging sites (African: 35.3% of dive time;

Aegean: 29.6% of dive time; Cretan: 28.0% of dive time; p = 0.14, F = 1.96). Throughout

the foraging months for all regions, sea surface temperatures averaged 25.5o ± 2.2

o C. The

southern waters were considerably warmer during this time, averaging 26.2o ± 2.3

o C,

while the waters of Crete averaged 25.0o ± 2.2

o C and as expected the Aegean Sea

averaged the coldest sea surface temperatures of 24.5o ± 1.8

o C.

CPA Behavior Modes 4 and 5 - Transition Phase and Overwintering:

Two turtles (Turtle 5 and Turtle 16) exhibited a type of transition behavior

between foraging and overwintering (behavior mode 4) and 8 turtles (Turtles 5, 7, 8, 13,

14, 16, 17, and 19) exhibited overwintering behavior or, as calculated by the CPA,

behavior mode 5. The dates when overwintering began varied with no distinct regional

trend (range for overwintering start date: Oct 13 – Jan 22). The overwintering transition

phases also began in October (Oct 3 and Oct 16). The average sea surface temperature

during late October was 21.0o ± 1.5

o C, with the Gulf of Gabes being typically 2

o C

warmer than the Aegean Sea. While the lowest sea surface temperature recorded by the

transmitters during overwintering was 13.4o C. This temperature was recorded in

February in the Gulf of Gabes.

This second transition behavior, between foraging and overwintering, was

characterized by similar mean dives and dive durations as during foraging, however, with

increased standard deviations in both metrics (dives per sample period: mean ± SD: 12.7

28

± 15.7; duration: 16.6 ± 19.7). Additionally, a reduction in the amount of time spent close

to the surface during this behavior was particularly indicative that these turtles were

switching behaviors to a more sedentary phase. The two turtles spent only 21.2% of dive

time above 5 meters of depth and this was significantly different than all previous

behavior modes (p < 0.001, F = 25.5) (figures 2.8 and 2.12).

Overwintering was characterized by only 11.0% of dive time at the surface, mean

dive duration of 64.1 ± 40.7 minutes and a reduction in the mean dives per sample period

to only 2.2 ± 2.6 dives. Both time spent above 5 meters and number of dives per sample

period were significantly different when compared to the previous dive behavior modes

(time at depth: p < 0.001, F = 50.8; dives: p < 0.001, F = 44.2) (figures 2.8 and 2.13).

Mean (± SD) sea surface temperature during behavior mode 5 in the Gulf of Gabes was

15.9o ± 2.3

o C (date range: 3/11 – 30/3, x̄ = 24/1), near Crete was 18.5

o ± 2.1

o C (date

range: 19/10 – 2/3, x̄ = 1/11) and in the Aegean Sea was 17.2o ± 1.4

o C (date range: 2/11

– 26/3, x̄ = 17/12).

Discussion

The results of this study demonstrated three post-nesting strategies for loggerhead

turtles from Rethymno: 1) long distance southward migration to the African coast (n = 9);

2) northward migration into the Aegean Sea (n = 6); and 3) staying resident within the

waters of Crete (n = 4). These various strategies matched results reported in Broderick et

al. (2007), Zbinden et al. (2008; 2011), Margaritoulis and Rees (2011) and Schofield et

al. (2013), when all of these studies are combined. Broderick et al. (2007) found that

loggerheads either migrated or remained near the nesting site; Zbinden et al. (2008; 2011)

and Schofield et al. (2013) identified that nesting females mainly either took a northward

29

or southward migration and Margaritoulis and Rees (2011) and Schofield et al. (2013)

reported that turtles migrated into the Aegean Sea.

Tag return data from ARCHELON for turtles migrating from Rethymno

(Margaritoulis et al., 2003; Zbinden et al., 2008), exhibit some differences in the relative

proportions of turtles ending up in different sites of residency For example, the Gulf of

Gabes is second to the Aegean Sea for number of tag returns (Margaritoulis and Rees,

2011). Another interesting contrast is that tag returns from Peloponnesus and Zakynthos,

Greece, the 2 largest nest sites in the region, show a much lower ratio of turtles migrating

to the Aegean Sea than to Tunisia (Margaritoulis et al., 2003). This pattern was

reinforced by telemetry results of loggerheads from Zakynthos, with only 6 of 65

individuals migrating to the Aegean Sea (Schofield et al., 2013). Thus, the Aegean Sea is

likely an important foraging ground, but maybe more so for turtles nesting in Crete.

The results also indicate different dive strategies associated with turtles that

become resident in different regions. According to the CPA, the Aegean turtles were

more active while migrating, however this changed with the switch to foraging, with the

turtles from African waters becoming the most active (highest number of dives per

sample period). The regional difference in foraging behavior may correspond to the water

temperatures associated with each site of residency. The Aegean and Cretan residents

behaved similarly as their sites of residency were of similar water temperatures; while the

African turtles were far more active in waters on average 2o C warmer. A similar trend

was found by Godley et al. (2003) with 2 satellite tracked loggerheads from Cyprus. The

individual foraging in waters approximately 2o C cooler remained submerged for longer,

30

thus taking fewer dives per sample period than the turtle foraging in warmer waters

(Godley et al., 2003).

The use of changepoint analysis resulted in a more thorough understanding of the

at-sea behavior of these loggerheads. The SSSM provided a clear distinction for most of

the turtles on when migration ended and area restricted search began. However, the

SSSM produced ambiguous results for 3 turtles. For Turtle 2 this could be explained by a

lack of robust data as 87% of location points were of quality B or worse; however for

Turtles 1 and 9 the datasets were comparable to the rest of the individuals. The

changepoint analysis allowed me to incorporate all data acquired through the transmitters

to make a well informed decision as to when behaviors changed as well as what

characterized each behavior type. With this method, a lack of horizontal movement data

did not restrict my ability to interpret the behavior of these animals, thus leading me to

discover when and how each turtle behaved during migration, foraging and

overwintering, plus informing me of new transition behaviors.

Where the two analytical methods overlapped, the largest difference found

between SSSM and the CPA was the interpretation of the migration phase. The SSSM

calculated that this first behavior lasted on average 20.8 ± 15.1 days, while behavior

mode 1 according to CPA was on average 36.2 ± 12.9 days. The CPA calculated that the

turtles travelling to Africa had slightly shorter migration durations than determined by the

SSSM; however for those travelling north, CPA behavior mode 1 lasted on average 40

days longer than the SSSM bmode 1. Thus, even though the northern turtles had reached

a site of residency, their dive behavior, according to the CPA, was still characteristic of

migration. Although, the duration of the first CPA behavior mode was particularly long

31

for the Aegean turtles, the CPA transition behavior (CPA bmode 2) between migration

and foraging was much shorter on average than for the turtles that migrated to Africa or

stayed near Crete. As a result and even though the migration distances differed by an

average of 1000 km, the amount of days it took for the Aegean and African turtles to

migrate and complete the transition phase was not significantly different (p = 0.1, F =

2.9), nor when comparing the start dates of the transition phase and the start dates of

foraging between sites (CPA mode 2 start date: p = 0.4, F = 0.747; CPA mode 3 start

date: p = 0.4; F = 0.670). However, there was a significant difference when comparing

these dates to the non-migrants (CPA mode 2 start date: p < 0.001, F = 14.4; CPA mode 3

start date: p = 0.002, F = 9.89) as well as when comparing the number of days between

the end of nesting and the start of foraging (p = 0.02, F = 5.3), as the Cretan turtles,

without the requirement to migrate, could begin foraging much sooner.

Sea surface temperature did not seem to play a role in influencing when these

turtles changed behaviors from migration through foraging, as there was less than a 0.5o

C difference between the mean SST for each individual region during behavior mode 1

and 2 and the start of mode 3. A possible explanation for this delayed shift from

migration to foraging, for those northern turtles, could be sustained hormone levels

associated with migratory behavior. In loggerheads, various hormones drive the behavior

of adult turtles as they migrate from their foraging site to nest; however it is still unclear

which cues are responsible for the return migration (Wibbels et al., 1990; Owens, 1997).

In birds, prolactin and corticosterone work in conjunction to prompt both the vernal and

fall migrations (Martin and Meier, 1973). For those northern turtles, even though they

had arrived at their sites of residency, hormone levels may have remained at positions

32

associated with continued migration. As a result, these turtles maintained diving

behaviors characteristic of migration, eventually switching modes well after arriving at a

site of residency.

In identifying additional behavior modes, it becomes apparent that loggerheads

are far more dynamic animals than previously established. Even though the Eastern

Mediterranean basin is relatively small, loggerheads behaved differently between the 3

sites. This may indicate that the foraging environments at each site differ and also that

loggerheads are able to adjust diving behavior accordingly. Furthermore, by determining

in more detail the temporal and spatial range of each behavior mode, it becomes easier to

identify the possible triggers that may prompt the switch from one behavior to the next.

This is important in gaining a more complete understanding of the ecology of sea turtles.

In terms of conservation and management, governments can use this improved

understanding of at-sea behavior to designate when and how specific fisheries are able to

use certain environments. For example, loggerheads cross the Eastern Mediterranean Sea

annually for the post-nesting migration during August and September. During the

migratory behavior, these turtles take several short dives, spending over 50% of dive time

above 5 meters. As a result, restricting longline fisheries during these months in terms of

number of lines deployed and at which depths hooks are placed could greatly reduce by-

catch. In another example, by determining specifically when overwintering behavior

begins and ends, restrictions to trawling could be implemented during those months to

also limit the interactions with sea turtles. The tracked turtles from this study moved

through the Exclusive Economic Zones of 4 countries: Greece, Libya, Turkey, and

Tunisia. These countries are responsible for 37.8 % of the captures of sea turtles by

33

fishing gear annually in the Mediterranean (Casale, 2011). As is clear in Spotila et al.

(2000), fisheries activities have the potential to lead a sea turtle species to extinction.

Thus it is imperative for the benefit of both fisheries and wildlife to find the optimal

balance between limited by-catch, sustainable harvest and economic gain.

34

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sea for adult loggerhead sea turtles in the Mediterranean Sea: satellite tracking

corroborates findings from potentially biased sources. Marine Biology 153: 899 –

906.





39

Tables and Figures

Table 2.1: Summary data of the 20 satellite tracked loggerhead turtles from Rethymno, Crete.

40

Figure 2.1: Results from the SSSM for the 15 turtles that migrated away from Crete. Each track is colored to represent

a different turtle and each circle represents a location estimate from the SSSM. The circles are colored based on

behavior mode exhibited at each location.

Tunisia

Sicily

Greece

Libya

Egypt

Turkey

Eastern

Mediterranean

Sea

Aegean

Sea

Strait of Sicily

41

Figure 2.2: Raw Argos location data (LC: A, 0, 1, 2, or 3) for the turtles that migrated to Africa. Each track is colored to

represent a different turtle and each circle is colored to represent a CPA behavior mode exhibited by the turtle at that

location.

Aegean

Sea Eastern

Mediterranean

Sea

Gulf of Gabes

Tunisia

Sicily

Libya

Greece

Crete

Egypt

42

Figure 2.3: Raw Argos location data (LC: A, 0, 1, 2, or 3) displaying the turtles that migrated into the Aegean

Sea. Each track is colored to represent a different turtle and each circle is colored to represent a CPA

behavior mode exhibited by the turtle at that location.

Aegean

Sea

Greece

Turkey

Crete Rethymno

43

Figure 2.4: Raw Argos location data (LC: A, 0, 1, 2, or 3) displaying the turtles that remained near Crete. Each

track is colored to represent a different turtle and each circle is colored to represent a CPA behavior mode

exhibited by the turtle at that location.

Rethymno

Chania

Heraklion

Cretan Sea

44

Figure 2.5: Dive behavior during SSSM bmodes 1 and 2 for all turtles. Horizontal bars = median; box =

50%; whiskers = range of observations within 1.5 times the interquartile range from edge of the box;

circles = observations farther than 1.5 times the interquartile range.

45

Figure 2.6: Dive behavior during SSSM bmode 1 for turtles based on migratory strategy (Africa: n = 9;

Aegean: n = 6). Horizontal bars = median; box = 50%; whiskers = range of observations within 1.5 times the

interquartile range from edge of the box; circles = observations farther than 1.5 times the interquartile range.

46

Figure 2.7: Dive behavior during SSSM bmode 2 for turtles based on migratory strategy (Africa: n

= 6; Aegean: n = 5; Crete: n = 4). Horizontal bars = median; box = 50%; whiskers = range of

observations within 1.5 times the interquartile range from edge of the box; circles = observations

farther than 1.5 times the interquartile range.

47

Figure 2.8: Dive behavior during each CPA behavior mode (1-5) for all turtles. Horizontal bars = median; box =

50%; whiskers = range of observations within 1.5 times the interquartile range from edge of the box; circles =

observations farther than 1.5 times the interquartile range.

48

Figure 2.9: Dive behavior during CPA behavior mode 1 for turtles based on migratory strategy (Africa: n = 9;

Aegean: n = 6). Horizontal bars = median; box = 50%; whiskers = range of observations within 1.5 times the


49

Figure 2.10: Dive behavior during CPA behavior mode 2 for turtles based on migratory strategy (Africa:

n = 7; Aegean: n = 4; Crete: n = 3). Horizontal bars = median; box = 50%; whiskers = range of

observations within 1.5 times the interquartile range from edge of the box; circles = observations farther

than 1.5 times the interquartile range.

50

Figure 2.11: Dive behavior during CPA behavior mode 3 for turtles based on migratory strategy (Africa: n

= 8; Aegean: n = 5; Crete: n = 4). Horizontal bars = median; box = 50%; whiskers = range of observations

within 1.5 times the interquartile range from edge of the box; circles = observations farther than 1.5 times

the interquartile range.

51

Figure 2.12: Dive behavior during CPA behavior mode 4 for turtles based on migratory strategy (Africa: n = 1;

Crete: n = 1). Horizontal bars = median; box = 50%; whiskers = range of observations within 1.5 times the


52

Figure 2.13: Dive behavior during CPA behavior mode 5 for turtles based on migratory strategy (Africa: n

= 3; Aegean: n = 2; Crete: n = 3). Horizontal bars = median; box = 50%; whiskers = range of observations

within 1.5 times the interquartile range from edge of the box; circles = observations farther than 1.5 times

the interquartile range.

53

CHAPTER 3: Fitness differences between postnesting loggerhead sea turtles

(Caretta caretta) from Rethymno, Crete, Greece

Abstract

Foraging success can influence reproductive output in sea turtles; and is therefore

an important factor to measure in order to understand population dynamics. During the

2010 and 2011 nesting seasons, I deployed 20 satellite transmitters on postnesting

loggerheads from Rethymno, Crete, Greece to monitor their at-sea behavior. Of these, 19

transmitters provided location and dive date through the migration phase and into

foraging behavior. There were 3 foraging strategies; 1) nine turtles migrated to the North

African coast, with 8 focused in the Gulf of Gabes, Tunisia; 2) six turtles migrated to the

Aegean Sea and 3) four turtles did not take long distance migrations, instead remaining

resident within the waters of Crete. Two fitness proxies were associated with differences

in postnesting strategies. Northern foraging turtles had significantly larger curved and

straight carapace lengths and clutch sizes than turtles foraging near Crete or Africa. This

could be due to the disparity in benthic prey abundances between the 3 regions. The

Aegean has a higher abundance of macrobenthic fauna than the other 2 regions and the

Gulf of Gabes has an increased level of eutrophication. The low level of prey resources

there may be due to the increased presence of harmful algal blooms. As a result, this may

be contributing to the steady decline in clutch size and nests per season at 2 critical

loggerhead nesting beaches in Greece.

54

Introduction

Long distance migrations have evolved as a result of seasonal fluctuations in

resource availability. These resource requirements range from food availability, to

improved climate, to predator avoidance, to increased success of offspring development

(Corkeron and Connor, 1999; Boyle and Conway, 2007; Morreale et al., 2007). Sea

turtles are the only reptiles to exhibit long-distance migrations of over thousands of

kilometers (Plotkin, 2003). Starting as hatchlings, they emerge from the nests and

instinctually swim directly to the open ocean (Carr, 1967; Carr and Meylan, 1980;

Lohmann et al., 1997). After residing in large oceanic gyres, juvenile sea turtles move to

the common foraging grounds of their adult counterparts (Musick and Limpus, 1997). As

adults, sea turtles migrate throughout the remainder of their lives to and from areas of

nesting (Limpus et al., 1992; Shillinger et al., 2008). Availability of resources can also

impact more than the requirement to migrate. Resource availability can constrain energy

budgets, in turn influencing body size (Wikelski and Thom, 2000), reproductive output

(Limpus and Nicholls, 1988; Solow et al., 2002) and population dynamics (Jenouvrier et

al., 2005; Wallace et al., 2006).

Sea turtle reproductive output is influenced by foraging success during the time in

between nesting seasons (Wallace et al., 2006; Saba et al., 2007, 2008). Higher foraging

success in leatherback turtles (Dermochelys coriacea) led to larger clutch sizes and

shorter remigration intervals (Wallace et al., 2006; Saba et al., 2007, 2008). Foraging

success can also influence body size in reptiles, as marine iguanas shrank by as much as

20% within 2 years due to low food abundance (Wikelski and Thoms, 2000). In the

Mediterranean, there is a carapace size and clutch size dichotomy for loggerhead turtles

55

(Caretta caretta) based on foraging area, with turtles feeding in northern waters being

larger and producing large clutch sizes than their southern counterparts (Zbinden et al.,

2011). Loggerheads forage on a wide variety of benthic animals, especially on slow

moving invertebrates (Plotkin et al., 1993; Godley et al., 1997; Casale et al., 2008; Lazar

et al., 2010). Throughout the Eastern Mediterranean Sea, loggerheads forage primarily on

molluscs, crustaceans and echinoderms (Godley, et al., 2007; Casale et al., 2008; Lazar et

al., 2010). I combined these data with the abundance of benthic prey from the common

foraging sites to determine a mechanism for a dichotomy in fitness between loggerheads

that migrate to different feeding areas. I deployed 20 satellite transmitters to track

loggerhead postnesting behavior within the Mediterranean Sea. This allowed me to

identify various migratory pathways and foraging sites for the third largest loggerhead

nesting population in Greece, in Rethymno, Crete (Margaritoulis et al., 2003). I also

compared 2 proxies of fitness, carapace size and clutch size, by groups exhibiting

different postnesting strategies (Wallace et al., 2006; Zbinden et al., 2011).

Methods

I obtained location, dive and temperature data for postnesting female loggerheads

using popup archival satellite transmitters with opportunistic transmissions. I used

Wildlife Computers’ (Redmond, WA) tag models Mk10-PAT for 19 turtles and Mk10-

AF (with Fastloc GPS capabilities) for 1 individual (Table 2.1).

During the 2010 and 2011 loggerhead nesting seasons (June-July), I attached

transmitters on turtles opportunistically during nightly patrols of select sections of nesting

beach within Rethymno, Crete, Greece (latitude 35.385o, longitude 24.590

o). These

sections of beach have historically been patrolled by ARCHELON and they have the

56

highest density of nesting activity. Once a turtle was encountered, I waited for the

completion of egg laying and then measured and examined it for any carapace or flipper

damage. Next, I applied two external flipper tags for the ARCHELON monitoring project

as an identifier for each turtle (Margaritoulis and Rees 2011). I then determined each

turtle’s current reproductive status with a portable real time ultrasound (Rostal et al.,

1996; Blanco et al., 2012b). I used an Aloka SSD-500 during the 2010 season and a

Sonosite 180 Plus during the 2011 season. I scanned one ovary and oviduct at a time by

placing the ultrasound probe in the inguinal region above the hind flipper (Blanco et al.,

2012b). I recorded scans using an attached printer for the Aloka SSD-500 and digitally

when using the Sonosite 180 Plus. This entire noninvasive model took approximately 5-7

minutes for each turtle. Finally, I attached the transmitters using a tethering method

modified from Morreale et al. (1996), Morreale (1999) and Blanco et al. (2012a), a

process that takes 7 – 10 minutes.

Satellite Transmitter Attachment

I followed a modified procedure from Morreale et al. (1996), Morreale (1999) and

Blanco et al. (2012a) to attach a satellite transmitter to a sea turtle via tether. First, I

cleaned a supracaudal scute with 70% alcohol, then, within this scute, I made a small

circular incision (5.0 mm) using a sterilized drill bit and battery powered drill. I

immediately cleaned the incision with a povidine-iodine topical antiseptic solution. Next,

I inserted sterilized surgical tubing (3.2 mm inside diameter, 6.4 mm outside diameter

and a 1.6 mm wall size) into the incision. The surgical tubing prevented direct contact

from the tether to the incision ensuring that the movement of the tether would not abrade

the carapace. Then I inserted the tether (181 kg test monofilament fishing line) through

57

the rubber tubing, then through a button on the ventral side of the carapace and finally

back through the tubing. The tether also passed through a button on the dorsal side to

inhibit contact between the crimp and the carapace. The ventral button spread the force of

the transmitter pulling on the carapace, thus reducing its pressure and further limiting the

impact of the attachment. The buttons were made from strong high-density soft plastics. I

secured the tether to both the carapace and transmitter with double barreled copper

crimps size 2.2B. In approximately the middle of the tether, I included a 172 kg test

swivel to allow for rotational movement of the tag. These crimps and swivels were

corrodible so that they would break away within a year or less. The length of tether, from

transmitter to carapace, ranged between 15 and 25 cm to ensure that the individual did

not entangle itself with either front or rear flippers. This method provided a rapid

processing time, extremely low hindrance and restraint to the turtle, low impact to the

carapace and extremely low level of drag compared to any direct attachment methods to

the carapace (Logan and Morreale, 1994; Watson and Granger, 1998, Jones et al., 2011).

Fitness Proxies

I measured curved carapace length (CCL) from the nuchal notch to the tip of the

supracaudal scute and curved widths (CCW) were measured form the widest points of the

carapace. To take the straight carapace length and width (SCL and SCW respectively)

measurements, I used calipers and measured from the same locations as done for the

curved measurements. These measurements were made to the nearest 0.5 cm. I also

checked for scars and lesions on the carapace and flippers.

Clutch sizes were determined by excavating each identified nest, laid by turtles

with transmitters attached, 10 days after the emergence of the first hatchling. Excavations

58

were performed in accordance with guidelines set forth by ARCHELON, the Sea Turtle

Protection Society of Greece (Margaritoulis et al., 2005). Each excavation was performed

by hand with nest contents sorted into categories of hatched eggs, unhatched eggs and

hatchlings. Clutch size was calculated as the sum of the hatched and unhatched eggs.

I compared clutch sizes and carapace sizes of turtles foraging in each region using

a generalized linear model and a one way ANOVA (statistical significance at a level of

0.05). I performed all statistical analyses in R (Venables and Smith, 2013).

Benthic Assessments

I compiled benthic assessments of the Aegean Sea, Crete and the Gulf of Gabes

from Karakassis and Eleftheriou, 1997, El Lakhrach et al., 2012 and Karakassis

unpublished data. El Lakhrach et al. (2012) sampled the Gulf of Gabes from 36 stations

between depths of 20 and 260 m. Twenty-one stations were < 60 m and 15 stations were

> 60 m (El Lakhrach et al., 2012). For sampling in the < 60 m stations, a “shrimp” type

trawl with a horizontal opening of 23 m was used and in the > 60 m stations a vertical

opening trawl with a horizontal opening of 15 m was used; both trawls had a mesh

diameter of 20 mm (El Lakhrach et al., 2012).

The benthic environment of Crete was sampled from 148 stations, ranging in

depth from 40 – 200 m (Karakassis unpublished data). Sixty-seven stations were < 40 m;

42 stations were between 40 and 100 m and 39 stations were between 100 and 200 m

(Karakassis unpublished data). In the Aegean Sea, samples were taken from 21 stations

at < 50 m (Karakassis unpublished data). At each station, the benthic environment was

sampled using a 0.1 m2 top-opening Smith-McIntyre grab (Karakassis and Eleftheriou,

59

1997). Samples were then sieved over a 0.5 mm mesh (Karakassis and Eleftheriou,

1997).

From the results of these benthic assessments, I calculated abundances

(individuals/hectare) of molluscs, crustaceans and echinoderms. I selected species based

on loggerhead diet studies in the Mediterranean Sea conducted by Godley, et al., 2007,

Casale et al., 2008 and Lazar et al., 2010.

Results

I received data from 19 of the 20 transmitters through the postnesting migrations

of the turtles (table 3.1). These turtles exhibited unique postnesting strategies. 1) Nine

individuals (Turtles 1 – 9) travelled to the North African coast with 8 settling in the Gulf

of Gabes, Tunisia and 1 maintaining residency along the northeast Libyan coast. 2) Six

turtles (Turtles 10 – 15) travelled north into the Aegean Sea and 3) four turtles (Turtles 16

- 19) remained within the waters of Crete. Turtle 11 was not included in carapace length

or clutch size comparisons due to a lack of comparable data. This turtle had healed

injuries to posterior marginal scutes making length measurements impossible and its

monitored nest was partially lost to the sea prior to being excavated.

There were significant differences (one way ANOVA) between curved carapace

lengths (CCL) (F = 6.9, p = 0.007, df = 17) and straight carapace lengths (SCL) (F = 6.0,

p = 0.01, df = 17) of the turtles from each postnesting strategy (figure 3.1), however not

when comparing the curved (CCW) (F = 2.7, p = .09, df = 18) and straight (SCW) (F =

3.5, p = .05, df = 18) carapace widths. Turtles (n = 5) that migrated to the Aegean Sea

were the longest, turtles (n = 9) that migrated to the African coast were the second

longest, and turtles (n = 4) that resided within the waters of Crete were the shortest

60

(Aegean Sea: mean ± SD CCL: 86.0 ± 5.00 cm, SCL: 82.2 ± 6.00 cm; African coast:

CCL: 82.4 ± 2.23 cm, SCL: 78.6 ± 2.04 cm; Crete: CCL: 77.6 ± 3.20 cm, SCL: 73.5 ±

3.32 cm). The overall average CCL for the 18 turtles was 82.3 ± 4.36 cm, ranging from

75.0 to 91.0 cm, and the average SCL was 78.4 ± 4.72 cm with a range of 71.0 to 87.0

cm. Regional body size differences also corresponded to clutch sizes, with a significant

difference (F = 6.4, p = 0.005, df = 32) between clutches laid by turtles exhibiting each

migratory strategy. The largest clutch sizes on average (n = 9, x̄ = 127 ± 12.3 eggs)

occurred for turtles that travelled to the Aegean Sea, while those that stayed near Crete (n

= 6, x̄ = 99.2 ± 25.8 eggs) or travelled to the African coast (n = 18, x̄ = 99.9 ± 19.1 eggs)

had much smaller clutch sizes. The overall mean clutch size for all known nests of these

monitored turtles (n = 33) was (mean ± SD) 107 ± 22.1 eggs with a range of 67 – 150

eggs.

A generalized linear model indicated that the clutch size trend was not simply an

artifact of body size differences between regions and curved and straight carapace lengths

did not significantly impact clutch size (SCL: p = 0.8, df = 31; CCL: p = 1.0, df = 31).

In the Gulf of Gabes, El Lakhrach et al. (2012) found a total of 131 species of

echinoderms, molluscs and crustaceans; however an abundance of only 1700 inds/ha in

the < 50 m stations, 350 inds/ha in the 50 to 100 m stations and 200 inds/ha in the

stations between 100 and 200 m. From the Karakassis unpublished data, I counted a total

of 75 species of prey items for loggerheads in Crete and the Aegean Sea. In Crete, the

abundance these 75 species was 6245 inds/ha in the < 50 m stations, 1832 inds/ha in the

50 to 100 m stations and 631 inds/ha in the 100 to 200 m stations (Karakassis

unpublished data). In the Aegean Sea, sampling stations did not reach beyond 50 m, and

61

the abundance was 10110 inds/ha within the < 50 m depth range (Karakassis unpublished

data).

Discussion

Loggerhead turtles that migrated to 3 areas of the Eastern Mediterranean Sea

differed in size and reproductive output. The fitness comparisons for turtles of varying

migratory strategies were similar to results from a study on Zakynthos Island (Zbinden et

al., 2011). On Zakynthos, loggerheads that foraged in northern waters (Adriatic Sea) were

on average 2.9 cm longer and produced clutches of 11.6 more eggs than those that

migrated south to Tunisia. However, they did not propose a mechanism for this. I found

that turtles in the Aegean Sea were also larger than their southern foraging counterparts,

and in addition, turtles remaining near Crete were the smallest. Furthermore, mean

curved carapace lengths and mean clutch sizes for Aegean migrants were similar to the

Adriatic turtles (Zbinden et al., 2011). I hypothesize that the trend in fitness differences

for turtles from Crete and Zakynthos reflect the different prey resources of each foraging

ground (figures 3.2, 3.3 and 3.4). In Japan, the adult female loggerheads foraging in the

nutrient poor oceanic environments are in fact not only smaller, but also have 2.4 times

less cumulative reproductive output than the benthic foragers (Hatase et al., 2013). I also

propose that since adult loggerheads throughout the Eastern Mediterranean forage from

the benthic environment, the differences in fitness parameters of subpopulations residing

in different foraging grounds may be a proxy for nutrient value and abundance of benthic

species from those regions.

The Eastern Mediterranean basin is one of the most oligotrophic areas in the

world (Lampadariou and Tselepides, 2006) and Greek loggerheads are much smaller than

62

their Atlantic and Pacific counterparts (Margaritoulis et al., 2003). However, net primary

productivity is unusually high on the eastern coasts of Tunisia (Drira et al., 2008). The

high level of primary productivity is not reflected in the benthic prey abundance. Instead,

it is due to high levels of anthropogenic inputs from major coastal cities like Gabes and

Sfax that have led to a constant state of eutrophication in these waters (Drira et al., 2008).

Eutrophication may be reducing the prey abundance for loggerheads (Turki et al., 2006;

Ben Brahim et al., 2010). Macrobenthic assessments from 0 - 50 m indicate that the

Aegean Sea has ~5.9 times more individuals of molluscs, crustaceans and echinoderms

per hectare than the Gulf of Gabes and ~1.6 times more individuals per hectare than Crete

(Tselepides et al., 2000; El Lakhrach et al., 2012; Karakassis unpublished data). In turn,

such a lack of food could be limiting the overall growth and clutch sizes of loggerheads

residing near Africa and Crete.

Indeed, foraging strategies have been linked to body sizes in turtle populations

(Hawkes et al., 2006; Saba et al., 2008; Hatase et al., 2010, 2013; Reich et al., 2010) and

typically, loggerheads that forage further offshore tend to be smaller than their nearshore

counterparts. However, in the Gulf of Gabes this seems to be the opposite. When

comparing the sizes of the 8 turtles that travelled to this region, the 4 that foraged >40 km

from shore (CCL mean ± SD: 83.9 ± 2.39 cm; SCL: 79.9 ± 2.25 cm) were longer on

average than the turtles that resided close to shore (CCL: 80.8 ± 0.500 cm; SCL: 77.3 ±

1.19 cm). In addition, mean clutch sizes for those foraging offshore (n = 11, x̄ ± SD = 101

± 19.0 eggs) were larger than those remaining nearshore (n = 6, x̄ ± SD = 92.0 ± 15.2

eggs). This may be due to the relatively higher levels of Chl-α found nearshore (130 ng l-

1) than found further offshore (30 ng l

-1), along with a higher presence of harmful algal

63

blooms along the coastline (Bel Hassan et al., 2008; Drira et al., 2008). In addition, this

region is characterized as having a very large continental shelf, thus the offshore residents

can still forage in the benthic environment, unlike the smaller loggerheads described in

previous studies as they are pelagic foragers (Hawkes et al., 2006; Hatase et al., 2010,

2013; Reich et al., 2010). Indeed, the offshore turtles primarily foraged in waters with a

max depth of 50 m (~80% of dives were within 50 m of depth and ~90% were within 75

m of depth) and stayed within a much smaller horizontal range than oceanic foragers

(Hawkes et al., 2006). In addition, these turtles foraged much closer to the Strait of Sicily,

waters which are more directly affected by currents travelling west to east. This may help

to maintain a more mixed and less eutrophic environment. Trawl studies indicate that the

waters of the Gulf of Gabes with a max depth of 60 m have a much higher megabenthic

species abundance than the deeper waters (< 60 m: 1700 inds/ha; > 60 m: 350 inds/ha)

and this corresponds to the presence of the Posidonia beds (El Lakhrach et al., 2012).

Casale et al. (2008) also commonly found sea grass within the gut and feces of benthic

foraging loggerheads from Tunisia. However, due to the influx of anthropogenic waste,

these sea grass beds are quickly degrading, with a decline in shoot density and an

increased presence of large areas of dead meadows (Ben Brahim et al., 2010; El Lakhrach

et al., 2012). Furthermore, nearshore benthic assessments north and south of Gabes city

have found that species abundances tend to be higher the further away from the direct

anthropogenic inputs (Tlig-Zouari et al., 2009; Rabaoui et al., 2010; Derbali et al., 2012).

As a result, the inshore prey quality may be far worse than offshore due to the increased

levels of industrial runoff.

64

The turtles that remained near Crete were also smaller than the Aegean group, and

this may also be due to a general lack of prey resources in the area. The waters of Crete

are more oligotrophic than the Aegean, and have lower benthic macrofaunal density and

biomass than do ecosystems at comparable depths throughout the world, including

environments with sea turtle foraging (Karakassis and Eleftheriou, 1997). Specifically,

the Cretan benthos (from 0 – 50 m of depth) contains only ~62% of the amount of prey

items per m2 as does the Aegean Sea (Karakassis unpublished results). Also the benthic

environment around Crete is more limited, as the continental shelf is particularly narrow

extending at most only 13 km from shore, while in the Gulf of Gabes the shelf reaches

over 200 km from shore and in the Adriatic over 300 km (Karakassis and Eleftheriou,

1997). This was also indicated in the dive data, as the Cretan turtles spent more dive time

below 50 m than the migrants (Crete: 15.5% of dives and 20.9% of dive time deeper than

50 m; Africa: 6.5% of dives and 5.8% of dive time; Aegean: 3.9% of dives and 6.2% of

dive time). In addition, the macrobenthic fauna abundance around Crete drops by

approximately 75% and 85% respectively as the depth increases from <50 m to 100 m

and to 200 m (the tracked turtles from all regions never dove beyond 200 m of depth)

(Tselepides et al., 2000; Karakassis unpublished results). Furthermore, the Cretan turtles

were significantly less active during foraging behavior (fewer dives per sample period)

than both the Tunisan and Aegean turtles (one way ANOVA: p = .01, F = 4.50), another

potential indication of a lack of food availability; as a reduction in foraging activity has

been found in marine animals during times of reduced food availability (Sograd and Olla,

1996; Wikelski and Thom, 2000).

65

Overall, it seems that the prey quality and abundance of the northern

Mediterranean waters, Aegean and Adriatic, plays a critical role in maintaining larger

more fecund individuals. Zakynthos Island, in western Greece, houses the largest nesting

population in the region, with turtles migrating from the Gulf of Gabes as well as the

Adriatic and Aegean Seas (Margaritoulis, 2005; Zbinden et al., 2008). Considering the

increasingly eutrophic conditions of the Gulf of Gabes, it may therefore be expected that

overall clutch sizes are decreasing. As of 2002, there was no trend of decreasing average

clutch size for Zakynthos Island (Margaritoulis, 2005), even though the Gulf of Gabes is

home to 28 – 44.4% of the nesting females from western Greece (Margaritoulis et al.,

2003; Zbinden et al., 2011). However, since 2003, clutch sizes have begun to decline,

with the average clutch size from 2003 to 2009 (106.7 eggs) falling below the minimum

average clutch size from between 1982 and 2002 (111.4 eggs) (nest monitoring in

Zakynthos began in 1982) (Margaritoulis et al., 2011). Rethymno also has a similar

percentage of turtles (28.6 – 47.4%) foraging in the southern waters and nest numbers

continue to steadily decline (Margaritoulis et al., 2009). In the Gulf of Gabes, the influx

of industrial runoff began in the 1970s and the first occurrence of harmful algal blooms

occurred in 1989 (Turki et al., 2006). As a result, the turtles currently nesting may be the

first to be showing signs of reduced reproductive output and this may be the beginning of

a trend of decreasing reproductive fitness, as sea turtles do show signs of decreased

reproductive fitness during times of limited food availability (Wallace et al., 2006; Saba

et al., 2007; Chaloupka et al., 2008). Furthermore, in an environment characterized by sea

grass meadows, a rise in sea temperature will not only exacerbate the already declining

presence of Posidonia, but will also increase the level of eutrophication, as seen in a

66

similar coastal lagoon within the Mediterranean (Lloret et al., 2008). In turn, the reduced

reproductive output may translate to fewer nests per season as well as longer remigration

intervals between nesting seasons; a combination which could severely reduce the overall

population of Mediterranean loggerheads.

Finally, it is important to understand why the Aegean Sea is home to the most

fecund turtles. Although this Sea is considered oligotrophic, there is a constant input of

cold, low salinity and high nutrient water from the Black Sea that displaces the warm,

hypersaline waters travelling north along the Turkish coast (Lampadariou and Tselepides,

2006). With this increased level of mixing, this region supports some of the highest

species richness of fish and invertebrates for the entire Eastern Mediterranean (Coll et al.,

2010). Furthermore, the Aegean Sea is characterized as having a much higher

macrobenthic species abundance (specifically inds/ha of molluscs, crustaceans and

echinoderms) than Cretan waters and the Gulf of Gabes (Abello et al., 2002; Belcari et

al., 2002; Karakassis and Eleftheriou, 2007; El Lakhrach et al., 2012; Karakassis

unpublished results).

Several steps should be taken to ensure the survival of the loggerhead nesting

population of Greece. For example, the reduction of anthropogenic inputs (industrial

runoff, sewage and fertilizer) in the Gulf of Gabes could help improve the quality of the

benthic environment in an area where close to 40% of nesting females from Greece

forage. As global temperatures climb, the impacts of eutrophication are expected to

advance, with harmful algal blooms occurring at higher rates (Edwards et al., 2006).

Furthermore, an increase in light attenuation caused by algal blooms will severely reduce

the presence of the sea grass beds critical for the survival of benthic invertebrates (Lloret

67

et al., 2008). Another conservation concern is the improved protection of the northern

foraging turtles as they are important in helping sustain higher reproductive outputs. The

northern turtles, regardless of size, were able to produce larger clutches on average. As a

result, this population could help balance the reduced reproductive output of the non-

migrants and the southern foragers.

Further research is also required to help improve our understanding of this fitness

dichotomy. A more complete assessment of fitness parameters (remigration intervals and

nests per season) would be useful in determining if the turtles with the various migratory

strategies are in fact nesting at different frequencies depending on clutch size or

migration distance. This increased understanding could be used to focus conservation

efforts. For example, if the Cretan turtles, with their lack of migration, are in fact nesting

yearly, their lifetime reproductive output may match that of the northern foragers.

Furthermore, the Aegean turtles are on average ~1000 km closer to the nesting beach

than the long distance migrants, thus they may return to nest more often as well. This in

turn focuses the reason for the reduction in nesting output in Rethymno to the reduced

foraging success of the turtles residing along the North African coast.

68

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Tables and Figures

Table 3.1: Summary data of the 20 satellite tracked loggerhead turtles from Rethymno, Crete.

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Figure 3.1: Relationship between fitness proxies and foraging sites. Boxplots of CCL, SCL and clutch sizes for

the 3 migratory strategies. Horizontal bars = median; box = 50%; whiskers = range of observations within 1.5

times the interquartile range from the edge of the box; circles = observation farther than 1.5 times the

interquartile range.

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Figure 3.2: Abundance (inds/ha) of loggerhead prey within the Gulf of Gabes, Tunisia (El Lakhrach et al.,

2012) and locations of foraging loggerhead turtles. The yellow circles represent the location data of the

nearshore resident turtles (n = 4), while the red circles represent the location data of the offshore residents (n =

4).

Tunisia

Gulf of Gabes

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Figure 3.3: Abundance (inds/ha) of loggerhead prey within the Aegean Sea (Karakassis unpublished data) and

locations of foraging loggerhead turtles. The pink circles represent the location data for the resident turtles within

this region (n = 6).

Greece Turkey Aegean

Sea

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Figure 3.4: Abundance (inds/ha) of loggerhead prey within the waters of Crete (Karakassis unpublished data) and

locations of foraging loggerhead turtles. The orange circles represent the location data for the resident turtles

within this region (n = 4).

Crete Rethymno

Cretan Sea

79

CHAPTER 4: Potential impacts of global warming on loggerhead turtles in the

Mediterranean Sea

Abstract

Climate change will likely have substantial impacts on marine ecosystems. Sea

turtles can be affected by climate change impacts in both their terrestrial (nesting beach)

and oceanic habitats. Over the past 30 years, temperatures at foraging and breeding sites

of loggerhead turtles (Caretta caretta) in the Mediterranean Sea have steadily increased.

These increases have been linked to declines in clutch sizes (eggs per nest) and total

number of nests produced per season at the major nesting site on Zakynthos Island. In

addition, phenological shifts have occurred, with nesting seasons starting earlier.

According to my calculations, a 3° - 5° C rise in air and ocean temperature at the

Zakynthos nesting site will cause the nesting season in this important rookery to shift

earlier by as much as 50 – 74 days. Furthermore, in aquatic habitats, warmer than average

ocean temperatures are causing a loss of sea grass beds; critical habitats for prey items of

loggerheads in the region. Based on statistically downscaled outputs of 14 climate

models, assessed by the Intergovernmental Panel on Climate Change (IPCC), temperature

at key foraging and breeding sites for loggerhead turtles in the Mediterranean Sea will

continue to rise over the next 88 years. With the slow rate of recovery of sea grasses and

the multitude of direct anthropogenic impacts, a rise in ocean temperature only

exacerbates the decline of these marine plants, potentially causing a severe reduction in

this population of loggerhead turtles.

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Introduction

Although the warming of the oceans is three times slower than air temperature on

land, marine species are shifting distributions and phenology at a greater rate than those

in terrestrial systems (Poloczanska et al., 2013). The Mediterranean Sea is a diverse

system, with subtropical species residing in southern waters and temperate species

thriving in the north (Bianchi and Morri, 2000). In addition, several species are able to

inhabit the entire basin and may be considered well adapted to a broad range of

environmental variability (Lejeusne et al., 2009). Compared to the rest of the world’s

oceans, the Mediterranean Sea is also home to a particularly high diversity of species ,

with 4 – 18% of the earth’s marine species permanently residing in this relatively small

basin (0.82% surface area and 0.32% volume of the world ocean) (Bianchi and Morri,

2000). In addition, over a quarter of the species are endemic to the Mediterranean,

including a sea grass species, Posidonia oceanica, which is critical in maintaining such

high levels of biodiversity (Bianchi and Morri, 2000). High levels of biodiversity

notwithstanding, anthropogenic impacts (pollution, overfishing, habitat destruction, and

species introductions) are reaching a climax in the Mediterranean region, causing

extensive environmental damage (Lejeusne et al., 2009). Coupled with these direct

impacts are the projections of a continuously changing climate, which means more

biodiversity loss is to be expected.

Sea surface temperature (SST), air temperature (Ta) and precipitation are major

driving forces in sea turtle ecology, both in key aquatic and terrestrial habitats (Sato et

al., 1998; Hays et al., 2002, 2003; Mazaris et al., 2004, 2008, 2009; Weishampel et al.,

2004; McMahon and Hays, 2006; Pike et al., 2006; Hawkes et al., 2007; Houghton et al.,

81

2007; Saba et al., 2007, 2012; Chaloupka et al., 2008; Santidrián Tomillo et al., 2012;

Luschi et al., 2013). Although loggerhead turtles (Caretta caretta) in the Eastern

Mediterranean are found within a broad latitudinal range, over 25% of all recorded

annual nesting activity in the region occurs on just 5.5 km of beach, and foraging is

localized to the benthic environments of only 5 primary regions (Margaritoulis et al.,

2003; 2005; Schofield et al., 2013). As a result, shifts in environmental conditions at the

regional scale, or even that of a single nesting beach, can have a severe impact on the

overall survival of this species (Witt et al., 2010).

In the Mediterranean Sea, Greece is home to the largest population of nesting

loggerheads, with Zakynthos Island, Kyparissia Bay and Rethymno, Crete ranked in

order of nests per season (Margaritoulis et al., 2003). At Zakynthos Island, it has been

reported that higher SSTs at the breeding sites have caused an earlier date of first adult

female emergence, reduced clutch sizes, and increased hatching success (Mazaris et al.,

2008). However, there does not appear to be a logical and direct mechanism to account

for the reduction in clutch size or the increase in hatching success, and thus other

variables may have influenced these trends. It also has been reported that rising SSTs at

foraging sites of loggerhead turtles nesting on Zakynthos related to a phenological shift in

the nesting season and a reduction in nests per season (Mazaris et al., 2009). Furthermore,

loggerheads residing in the Mediterranean are thought to be more susceptible than their

subtropical counterparts in Florida to shifts in nesting behavior, as SST at the breeding

site rises (Mazaris et al., 2013). In addition, because sea turtle sex is determined by the

temperature of incubation (Morreale et al., 1982; Standora and Spotila, 1985; Mrosovsky

82

et al., 2000), increasing air and sand temperatures will maintain and exacerbate the

already highly female biased hatchling sex ratio (Zbinden et al., 2011).

Also critical to the success of sea turtle reproduction is the availability of prey

resources in their foraging habitats (Wallace et al., 2006; Saba et al., 2008). Females

depend on food resources for vitellogenesis prior to migrating to the nesting beach and

less food could result in a delayed return; thus, sea turtles will nest less frequently if food

availability is limited (Wallace et al., 2006). An alteration in primary and secondary

production in the foraging areas also has been noted to contribute substantially to nesting

success (Limpus and Nicholls, 2000; Saba et al., 2007; Chaloupka et al., 2008).

In the Mediterranean there is a fitness dichotomy in which northern turtles are

larger and produce larger clutch sizes than their southern counterparts (Zbinden et al.,

2011). Indeed, this fitness difference may be attributed to the higher availability of prey

resources in the northern foraging grounds (chapter 3). Loggerheads in the Mediterranean

Sea tend to feed on slow-moving benthic organisms associated with sea grass beds

(Casale et al., 2008; Lazar et al., 2010). These sea grass beds, specifically composed of

Posidonia oceanica, an endemic species of the Mediterranean, are critical habitats for the

overall biodiversity of the region (Borum et al., 2004). Unquestionably, water

temperature plays a role in the physiology and overall survival of these species, and mass

sea grass shoot mortality is associated with rising temperatures (Duarte, 2002; Marbá and

Duarte, 2010).

Here I examine the effects of a continuously warming environment on loggerhead

turtles residing in the Eastern Mediterranean Sea. The objective of this study was to

identify key climatic variables influencing nesting success and behavior of loggerhead

83

turtles in the Mediterranean Sea. To that end, I used SST, Ta and precipitation to

investigate correlations with trends in the Greek nesting data from Margaritoulis and

Rees (2001), Margaritoulis et al. (2003; 2009; 2011), and Margaritoulis (2005). To assess

likely future nesting success, I then used global climate change models which also were

related to future foraging success and behavior of Mediterranean loggerhead turtles.

Methods

To determine the relationships between selected climate conditions (SST, Ta and

precipitation) and nesting and foraging success, I took measurements of sand

temperatures at the nesting beach of Rethymno, Crete, and obtained historic climate data

from the 5 high-usage areas for the nesting loggerhead turtles of Greece (Adriatic,

Aegean, Crete, Gulf of Gabes and Zakynthos Island/Kyparissia Bay) I then extracted and

statistically downscaled IPCC climate change models for the 21st century, to assess the

effects of climate change on projections of future survival of this population.

During the 2012 nesting season in Rethymno, Crete I measured beach

temperatures using 6 iButtons (Maxim Integrated, San Jose, CA). The iButtons have a

temperature resolution of 0.5° C. At each location along this predominantly north-facing

beach, I placed one iButton at the surface of the sand and another at a depth of 50 cm, to

measure sand temperatures at the surface and at nest depths. Each iButton measured the

temperature every 60 minutes during the majority of the 2012 nesting season (May 21 –

Aug 1). The iButton was encased in a film canister punctured with several holes to

protect the device from outside elements. I placed iButtons at three sites of high nesting

activity (Location 1: Lat: 35.3697o Lon: 24.51518

o, Location 2: Lat: 35.3821

o Lon:

24.5818o, Location 3: Lat: 35.3911

o Lon: 24.6085

o). Location 1, the farthest west, was

84

6.2 km from location 2 and 8.8 km from location 3. Location 2 was 2.6 km from location

3, the farthest east. Locations 2 and 3 were on beaches patrolled at night and the beaches

at all three locations were patrolled during the morning, in order to mark and characterize

the previous night’s nesting activity.

Based on results of telemetry studies conducted by Schofield et al. (2010; 2013),

Zbinden at el. (2011), Panagopoulou et al. (2012), Backof et al. (2013) and satellite tracks

from this study (Ch 1), I selected 5 high usage regions for loggerheads in the

Mediterranean Sea (Adriatic Sea, Zakynthos Island/Kyparissia Bay, Gulf of Gabes,

Island of Crete and the Aegean Sea) (figure 4.1). For these regions, I extracted monthly

SST values from 1982 to 2012 from the NOAA NCEP EMC CMB Global Reynolds and

Smith OI version 1 dataset (Reynolds and Smith, 1994). I also obtained historic

precipitation data from the Global Precipitation Climatology Centre (GPCC) and historic

air temperature data from weather stations at the international airports of Laganas, on

Zakynthos, Heraklion, on Crete and Kalamata, in the Peloponnese. The Laganas airport is

~3 km from the nesting beaches of Zakynthos; Heraklion airport is ~60 km from the

nesting beaches of Rethymno; and the Kalamata airport is ~40 km from the nesting

beaches of Kyparissia Bay. To test the significance of change in SST, Ta and

precipitation through time, I performed a simple linear regression (statistical significance

set at a level of 0.05).

I obtained climate change projections for the 5 high-usage regions from global

climate models developed for the Intergovernmental Panel on Climate Change (IPCC)

fifth assessment report (AR5) and for the World Climate Research Programme’s Coupled

Model Intercomparison Project phase 5 (CMIP5) under the RCP 8.5 greenhouse gas

85

emissions scenario (table 4.1). RCP 8.5 is the highest expected level of greenhouse gas

emissions. For SST, I used 13 ocean models: ACCESS1.0, BCC-CSM1.1, CCSM4,

CMCC-CMS, CNRM-CM5, CSIRO-Mk3.6.0, GFDL-CM3, GISS-E2, HadGEM2-AO,

INM-CM4, IPSL-CM5B-LR, MIROC5 and MRI-CGCM3. For Ta and precipitation, I

used 14 atmospheric models: ACCESS1.0, BCC-CSM1.1, CCSM4, CMCC-CMS,

CNRM-CM5, CSIRO-Mk3.6.0, FGOALS-g2, GFDL-CM3, GISS-E2, HadGEM2-AO,

INM-CM4, IPSL-CM5A-MR, MIROC5 and MRI-CGCM3.

To downscale the models from a global to regional scale, I bias corrected all

climate model data using the delta method; which is performed by subtracting the mean

annual value of the future projection of a model for a specified region (from 2006 – 2100)

from the overall mean of the historical data from the same model and region (from 1982

– 2005) (Hay et al., 2000). Using this process, I determined an annual change in

temperature/precipitation for that model for that region. Similarly, I bias corrected Ta and

SST during the breeding months at Zakynthos to account for variability based on

observed data (Saba et al, 2012). In this method, first I calculated the mean and standard

deviations of the monthly means of both the observed data and the historical climate

model data for the years 1984 – 2005. Then, I calculated a mean bias correction factor by

dividing the average monthly mean of the observed data by the average monthly mean of

the same month from the historical climate model data. I calculated an SD bias correction

factor by dividing the corresponding SD values. Next, I multiplied the mean bias

correction factor for each month by the corresponding monthly mean from the historical

and future climate model projections on an annual basis. Then, I subtracted this mean

bias-corrected value from the corresponding average monthly mean from the observed

86

data. I multiplied this new value by the SD bias correction factor of the corresponding

month, and finally I added this value to the average monthly mean from the observed

data. This resulted in the bias-corrected future climate model projection data having the

same mean and SD as the observed data for the same time period. This bias correction

method yielded more accurate projections of the change in nesting phenology for

Zakynthos Island.

Nesting data for Greece was provided from Margaritoulis and Rees (2001),

Margaritoulis et al. (2003; 2009; 2011) and Margaritoulis (2005). I used generalized

linear models to test statistical significance of the relationship between environmental

variables (precipitation, Ta and SST) and patterns in nesting data. Statistical significance

was set at 0.05. I used models calculated from the linear trend lines of relationships

between SST and Ta and day of first female emergence at Zakynthos to make projections

on how the start of the nesting season would shift as SST and Ta changed.

Results

Beach temperatures for Rethymno, Crete varied slightly between the three sites in

2012 (figure 4.2). Location 1 had the lowest sand surface temperature (x̄ ± SD = 31.8° ±

9.9° C), but the highest temperature at nest depth (28.4° ± 1.9° C). Location 2 had the

highest sand surface temperature (33.6° ± 10.7° C) and a lower nest depth temperature

(27.1° ± 1.9° C) than at location 1. Sand surface temperature (32.0° ± 9.5° C) at location

3 was similar to that at location 1 and temperature at nest depth (27.1° ± 1.8° C) was the

same as at location 2. Location 1 had the smallest average difference between surface

temperature and temperature at nest depth of 3.4° C, while locations 2 and 3 had mean

differences of 6.6° C and 4.9° C respectively. Sand surface temperatures reached a high

87

of 61.5° C and a low of 13.0° C, while nest depth temperatures were much less variable

(range = 23.5° to 31.0° C). Temperature at nest depth at location 1 remained consistently

above 29.5o C (loggerhead pivotal temperature Kyparissia Bay: 29.3

o C; Mrosovsky et

al., 2002) beginning on July 7 well before the end of the nesting season. Locations 2 and

3 did not reach that high temperature consistently until July 27.

Over three decades, there was a steady and statistically significant increase in SST

at Crete during consecutive breeding seasons (April – June), from x̄ = 19.0o C in 1982, to

20.2o C in 2012 (R

2 = 0.477, p < 0.01) (figure 4.3a). The lowest SST during those months

occurred in 1987 (18.2o C), and the highest occurred in 2012. Mean SST over the 30 year

period at Crete was slightly warmer (0.4° C) than at Zakynthos and Kyparissia. However,

there was a similar rise (1.2o C) in SST over the course of the same time period at both

Zakynthos Island and Kyparissia Bay (R2 = 0.370, p < 0.01). The coldest month during

the nesting season occurred in 1991 (17.9° C) and the warmest month during nesting

occurred in 2003 (20.0° C). Using Zakynthos nesting data from 1984 – 2002, Mazaris et

al. (2008) found a significant relationship between the rise in SST and the earlier onset in

day of first female emergence. Using updated nesting data from Zakynthos (1984 –

2009), I calculated that this relationship remains significant (p < 0.001, R2 = 0.830, y = -

12.157(x) + 378.97), with females continuing to emerge to nest earlier in the season

(figure 4.3b).

Future nesting patterns were predicted using statistically downscaled climate

change models. From these, I calculated that mean SST during the breeding season will

rise by between 2.4o – 6.0

o C in all three regions by 2100 (figures 4.3d and 4.3e). Using

the bias-corrected data of climate projections based on the mean and SD of the observed

88

data, I also calculated that the start of the nesting season in Zakynthos will shift to an

earlier date by (mean ± SD) 52.5 ± 12.0 days (range = 39.6 – 74.8 days) by 2100 (figure

4.3c). This will advance the day of first female emergence from late May, to as early as

mid-March.

Overall, the mean annual SST at the foraging grounds from 1982 - 2012 varied by

region, with the Adriatic Sea being the coldest (x̄ = 18.6o C, range = 17.9

o – 19.4

o C) and

the Gulf of Gabes the warmest (x̄ = 20.8o C, range = 19.9

o – 21.4

o C) (figure 4.4a). There

was a significant steady increase in mean annual SST from 1982 – 2012. SST increased

0.6o C (R

2 = 0.311, p = 0.04) in the Adriatic, 1.4

o C (R

2 = 0.560, p < 0.01) in the Aegean,

1.3o C (R

2 = 0.674, p < 0.01) around Crete, 0.6

o C (R

2 = 0.474, p < 0.01) in the Gulf of

Gabes, and 1.0o C (R

2 = 0.393, p < 0.01) around Zakynthos and Kyparissia. The bias-

corrected climate models projected a steady increase in the mean annual SST for all

regions of 2.1o – 6.5

o C for the years 2013-2100 (figures 4.4b, c, d, e, f). Mazaris et al.

(2009), using nesting data from 1984 – 2007, found a significant relationship between the

temperature at the foraging site 2 years prior to the nesting season and the decline in nests

per season in Zakynthos. Using up to date nesting date (1984 – 2009), I calculated that

this correlation continued for the next several years (p = 0.03, df = 25) (figure 4.8a). I

also calculated a similar trend in Rethymno, from 1990 - 2004, with a 1.2o C increase in

temperature at the foraging sites (Aegean Sea, Crete, and Gulf of Gabes), corresponding

to a decrease in nest numbers by 260 nests per season (p < 0.01, df = 14) (figure 4.8b). In

Kyparissia, however, I calculated that the correlation between foraging site SST and nests

per season was not significant (p = 0.7; df = 16).

89

There was an increase in mean SST over the course of the past 30 years in all

regions (Adriatic: 1.6o C, R

2 = 0.046, p = 0.25; Aegean: 1.8

o C, R

2 = 0.555, p < 0.01;

Crete: 1.5o C, R

2 = 0.499, p < 0.01; Gabes: 1.4

o C, R

2 = 0.190, p = 0.01; Zak/Kyp: 1.3

o C,

R2 = 0.251, p < 0.01). The mean SST during the hottest month, August, from 1982 - 2012

varied by region, with the Gulf of Gabes, the southernmost area, being the warmest (x̄ =

27.1o C, range = 25.9

o – 28.6

o C) and the Aegean Sea the coldest (x̄ = 24.7

o C, range =

23.2o – 26.3

o C) (figure 4.5a). In the next 88 years, August SSTs in each region are

expected to increase by (mean ± SD) 4.4o ± 1.3

o C (figure 4.5b). This projected increase

in temperature has severe implications for the survival of sea grass in the key foraging

sites for loggerheads in the Mediterranean.

According to the GPCC, monthly average precipitation from 1982 – 2000 for all 5

regions was 64.6 mm month-1

(± 56.6). November was the wettest monthand June was

the driest. In all regions, there was no significant change in mean annual precipitation

from 1982 – 2000 (p = 0.5, df = 18). At Zakynthos, Kyparissia, and Crete during the

nesting season, June – August, rainfall averaged between 0.13 – 10.4 mm month-1

.

During the breeding months (April, May and June) rainfall averaged between 2.0 – 51.9

mm month-1

. I calculated that annual rainfall at the foraging sites 2 years prior to the

nesting season did not have a significant impact on the number of nests at each site

(Zakynthos: p = 0.5, df = 18; Kyparissia: p = 0.6, df = 16; Rethymno: p = 0.1, df = 12). In

Zakynthos specifically, I calculated that annual rainfall at the foraging sites 2 years prior

to the nesting season did not have a significant impact on clutch size or the start of the

nesting season (clutch size: p = 0.5, df = 18; phenology: p = 0.06; df = 18); and rainfall

during the nesting season did not have a significant impact on hatchling success or

90

hatchling emergence success (hatchling success: p = 0.2, df = 16; hatchling emergence

success: p = 0.2; df = 16). The bias corrected climate models project that rainfall will

decline at Crete by as much a 20.3 mm month-1

and at Zakynthos and Kyparissia by 28.4

mm month-1

(figured 4.7a, b).

At the nesting sites during the breeding months, Ta rose significantly in Zakynthos

(R2 = 0.467; p < 0.01) and Kyparissia Bay (R

2 = 0.252; p < 0.01) between 1982 and

2009, but not in Rethymno (R2 = 0.133; p = 0.06) (figure 4.6a). I calculated that there

was no significant relationship between Ta and nest numbers within the same season

(Zakynthos: p = 0.3, df = 25; Kyparissia: p = 0.5, df = 16; Rethymno: p = 1.0, df = 14).

The bias corrected climate models project that Ta at the nesting sites during the breeding

months will increase by (mean ± SD) 4.1o ± 1.3

o C by 2100 (figure 4.6d, e). There was a

significant relationship between Ta during the breeding season and the date of first female

emergence in Zakynthos (p < 0.01, df = 25, R2 = 0.705; y = -6.8327(x) + 286.35) (figure

4.6b). Based on this equation and the projected increase in Ta, the date of first female

emergence will shift earlier by (mean ± SD) 35.5 ± 11.7 days (range = 16.8 – 50.6 days)

by 2100 (figure 4.6c).

Discussion

Sea Surface Temperatures and air temperatures over land in the Mediterranean

region are steadily rising. An increase in temperature at the breeding sites and foraging

sites has a significant effect on the timing, quantity, and quality of loggerhead nesting in

the Mediterranean Sea (Mazaris et al., 2008; 2009; 2013). In Crete, the third most

important nesting site for loggerheads in Greece, there is already a steady decline in nests

per season, even with consistent conservation efforts for the past 23 years (Margaritoulis

91

et al., 2008). According to Mazaris et al. (2008; 2009) this may partially be due to the

continuously increasing SST during both the breeding and foraging months in all regions

typically occupied by loggerheads. When comparing the SST of Crete to that of the major

nesting areas at Zakynthos and Kyparissia during the breeding months, temperatures in

Crete were typically higher and have exhibited a smaller range of fluctuation. However, I

did not find a significant correlation between the decrease in nests per season in

Rethymno and the increase in SST at the breeding site (p = 0.5, df = 14); nor when

comparing the nests per season to the SST at the breeding sites of Zakynthos and

Kyparissia (Zakynthos nesting: p = 0.7, df = 25; Kyparissia nesting: p = 0.1, df = 16). In

contrast, Mazaris et al. (2008) found that an increase in SST at the breeding site of only

1.5o C during April led to a reduction in mean clutch size by approximately 10 eggs per

clutch in Zakynthos. Over the last 30 years, the waters of Crete in April were, on average,

0.8o C warmer than Zakynthos and Kyparissia Bay. According to Mazaris et al., 2008, it

is then expected that Crete would have higher hatching and hatchling emergence success;

but an earlier date of first and last emergences of adult females, along with smaller clutch

sizes. Typically, Crete does have smaller clutch sizes than both Zakynthos and Kyparissia

Bay (mean clutch size min and max as of 2002: Zakynthos: 111.4 – 130.4 eggs;

Kyparissia: 105.2 – 126.8 eggs; Crete: 102.0 – 124.6) (Margaritoulis et al., 2003).

However, it is difficult to devise a mechanism for this relationship between breeding site

SST and smaller clutch sizes.

Global climate models project that the SST at the breeding sites during April,

May and June will become warmer by an average of 3.7o C. As a result, and if the

relationships established by Mazaris et al. (2008) hold true, the mean clutch sizes at these

92

nesting beaches may fall substantially. Indeed, recent results indicate the numbers are

already declining (clutch size mean ± SD 2003 – 2009: Zakynthos: 106.7 ± 26.1 eggs)

(Margaritoulis et al., 2011). Based on models run by Mazaris et al. (2008), the current

SST at the breeding site of Zakynthos is just above the optimal condition to ensure a

balance between smaller clutch sizes and a higher hatching success. Near Crete, the SST

may already be above this optimal range, as the waters of Crete are warmer than

Zakynthos and clutch sizes already are smaller. A shift in phenology expected for

Zakynthos as temperatures increase, may help to offset the potential decline in clutch

size. With the continued rise in SST potentially resulting in turtles nesting earlier by as

much as 74 days by 2100, the temperature during the nesting season could remain within

the optimal range.

Beach conditions also play a role in the survival of sea turtles (Wallace et al.,

2004; Honarvar et al., 2011; Saba et al., 2012; Santidrián Tomillo et al., 2012; Suss,

2012). In a previous study, however, sand temperatures in Zakynthos and Kyparissia did

not have a significant impact on hatching success (Suss 2012). This corresponds to results

found in Japan on loggerhead nesting as well (Matsuzawa et al., 2002); however not in

leatherback turtles (Dermochelys coriacea), whose hatching success is compromised by

higher temperatures (Santidrián Tomillo et al., 2012).

Nests on Greek beaches had a particularly high hatching success (70 – 92%)

compared to other loggerhead beaches throughout the world (Maragaritoulis et al., 2011;

Suss, 2012). This may be due to the improved abiotic and biotic conditions of the beach

environment facilitating gas exchange in the nests (Wallace et al., 2004; Suss, 2012).

Beach temperatures in Greece may also not reach the thermal maximum for egg

93

incubation (34o C; Moran et al., 1999) nor hatchling emergence (32.4

o C; Miller et al.,

2003). On the 7 beaches of Zakynthos monitored by Suss (2012), nest temperature never

exceeded 34o C throughout the entire nesting and hatching seasons of 2010 and 2011.

However, as global temperatures rise, this thermal maximum may be reached quite soon,

as the highest nest temperature measured by Suss (2012) was 33.8o C.

Extensive assessments of the abiotic and biotic conditions on Crete have not been

conducted, and maybe important in determining the value of the beach environment for

the future of loggerheads in the Mediterranean Sea. However, within the sample period

for sand temperatures from Crete for this study, nest depth sand temperatures remained

above the pivotal temperature for loggerheads in the region beginning a month prior to

the end of the nesting season. This corresponds with the trend for the Eastern

Mediterranean of a strong skew towards a female bias in loggerhead hatchling sex ratios

within many of the critical nesting beaches (Godley et al., 2001a; 2001b; Houghton and

Hays, 2001; Rees and Margaritoulis, 2004; Casale et al., 2005; 2006; Kaska et al., 2006;

Zbinden et al., 2007; Fuller et al., 2013). As sand temperatures warm in the future,

demographics likely will remained skewed towards a more female bias. This skew,

coupled with changes in hatching success rates, can play a strong role in reducing the

overall nesting population for loggerheads in the region, as demonstrated in leatherbacks

from the eastern Pacific (Saba et al., 2012).

Precipitation, air temperature, bacterial load and proximity to vegetation also play

key roles in the survival of hatchlings (Honarvar et al., 2011; Santidrián Tomillo et al.,

2012) and climate change impacts on beach conditions has the potential to cause a 7 %

decline per decade in the nesting population as projected for leatherbacks in Playa

94

Grande, Costa Rica (Saba et al., 2012). Precipitation, historically, has not had a

significant impact on nest success in Greece; however climate models project a

substantial reduction in annual precipitation at the nesting beaches. This may result in

sand temperatures reaching the thermal maxima sooner as well as sand moisture levels

becoming too low for nesting.

Similar to breeding site SST, rise in Ta at the breeding sites during the breeding

months corresponded to an earlier start to the nesting season in Zakynthos. It is unclear

whether SST or Ta plays the stronger role in prompting nesting, as sea turtles demonstrate

many behavioral strategies, for example residing in warmer spots within the water

(Backof, 2013) or breaching the surface to bask (Spotila and Standora, 1985), in order to

find an optimal temperature. Regardless, it is apparent that warmer temperatures, both air

and sea, result in earlier nesting seasons, however this may not improve nest success, but

rather, may sustain current conditions. Beach temperatures are expected to rise and

precipitation is projected to decline during the months prior to the current nesting season

(figures 4.6d, e; 4.7c). As a result, even though loggerheads may shift nesting to earlier in

the year, the climate conditions during nesting and hatching may remain the same.

In previous studies (Chaloupka et al. 2008; Mazaris et al. 2009), warmer SSTs at

the foraging sites for loggerheads led to a reduction in nesting numbers. Similar trends

were also found in green turtles (Chelonia mydas) and leatherbacks (Limpus and

Nicholls, 2000; Chaloupka, 2001; Saba et al., 2007). In the Mediterranean, Mazaris et al.

(2009) found that only a 1.5o C increase in SST at the foraging grounds corresponded to a

decline of almost 500 nests per season in Zakynthos. I also calculated a similar trend in

Rethymno and found that the trend continued in Zakynthos when including more up-to-

95

date nesting data. However, this trend did not hold true for the nesting activity in

Kyparissia Bay, indicating that the correlation and connecting mechanisms may be far

more complicated.

Greek loggerheads forage in regions typically characterized by shallow benthic

environments with large areas of sea grass beds (Schofield et al., 2013). These sea grass

meadows are habitats for a very diverse set of species, including invertebrate prey items

for loggerheads (Godley et al., 1997; Casale et al., 2008; Lazar et al., 2010; El Lakhrach

et al., 2012). SST plays a crucial role in the survival of these sea grasses, specifically

Posidonea oceanica, the most common sea grass in the Mediterranean (Marba et al.,

1996; Marba et al., 2005; Marba and Duarte, 2010). Sea grass meadows already are

steadily declining due to direct and indirect anthropogenic effects (Duarte, 2002).

Furthermore, sea grasses are slow to recover from disturbances, and on the Spanish coast

in the Western Mediterranean there is a negative net population growth rate of Posidonea

oceanica (Marba et al., 2005). A strong correlation also exists between the annual max

SST and shoot mortality near the Balearic Islands, with an increase of 3o C causing shoot

density to decline by approximately 13 – 40% along with an increase in mortality rate

from 0.05 to 0.15 (Marba and Duarte, 2010). In addition, an increase of only 1o C caused

a decline in shoot density by as much as 20% at one site (Marba and Duarte, 2010). Over

the last 30 years, at loggerhead foraging sites, the SST during August increased by

between 1.3o – 1.8

o C (figure 4.5a). Future projections of SST in August suggest a

warming by another (mean ± SD) 4.4o ± 1.3

o C by 2100 (figure 4.5b). As a result, the sea

grass meadows loggerheads depend upon for much of their foraging may decline by well

over 40%.

96

Abiotic conditions play a critical role in the survival of sea turtles both on the

beach and at sea. As Ta and SST continue to rise and precipitation declines, loggerheads

in the Mediterranean Sea may be able to compensate by nesting earlier in the season;

however with the extreme skew in sex ratio, the decrease in precipitation and likely soil

moisture, and the projected deterioration of the foraging grounds, these phenological

adjustments may not be enough to sustain the population. As a result, stronger efforts are

needed to maintain the nesting beaches to accommodate for the changes that are expected

to occur regarding nesting phenology and potentially reduced clutch sizes and fewer nests

per season. Furthermore, a severe reduction in the anthropogenic impacts on sea grasses

is not only necessary for the survival of sea turtles, but also essential for the overall

survival of the benthic environment throughout the Mediterranean Sea.

97

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Tables and Figures

Table 4.1: Summary information and references for the climate change models used in this study.

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Table 4.1: Continued

110


111


112

Figure 4.1: Map of the Mediterranean Sea indicating the 5 high usage sites for loggerheads.

Italy

Greece

Turkey

Tunisia

Libya

Adriatic

Sea

Gulf

Of

Gabes

Zakynthos

Island

Kyparissia Bay

Aegean

Sea

Crete

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Figure 4.2: Mean daily sand temperatures from May 21—Aug 1 at the surface (0 cm) and at nest depth (50

cm) at 3 monitored nesting locations on the beaches of Rethymno.

114

a b

c d

115

Figure 4.3: a) Mean annual SST during the breeding months at the nesting sites of Crete and Zakynthos/Kyparissia.

Solid lines are the linear trend lines (Crete R2 = 0.477; Zak/Kyp R2 = 0.370). b) Relationship between day of first

female emergence and mean SST during the breeding months in Zakynthos Island (R2 = 0.830). c) Projections of the

day of first female emergence through 2100 based on 13 climate model estimations of the increase in SST during the

breeding months at Zakynthos Island. d) Projected change in mean SST during the breeding months for Crete based

on results from 13 climate change models. e) Projected change in mean SST during the breeding months for

Zakynthos and Kyparissia based on results from 13 climate change models.

e

116

a b

c d

117

Figure 4.4: a) Mean annual SST at the 5 high usage areas for loggerheads in the Mediterranean. Solid lines are the

linear trend lines (Adriatic R2 = 0.311; Aegean R2 = 0.560; Crete R2 = 0.674; Gabes R2 = 0.474; Zak/Kyp R2 = 0.393).

b) Projected change in mean annual SST for the Adriatic Sea based on results from 13 climate change models. c)

Projected change in mean annual SST for the Aegean Sea based on results from 13 climate change models. d)

Projected change in mean annual SST for the waters of Crete based on results from 13 climate change models. e)

Projected change in mean annual SST for the Gulf of Gabes based on results from 13 climate change models. f)

Projected change in mean annual SST for Zakynthos Island and Kyparissia Bay based on results from 13 climate

change models.

e f

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Figure 4.5: a) August SST at the 5 high usage areas for loggerheads in the Mediterranean. Solid lines are the linear

trend lines (Adriatic R2 = 0.046; Aegean R2 = 0.555; Crete R2 = 0.499; Gabes R2 = 0.190; Zak/Kyp R2 = 0.251). b)

Means of the projectd changes in August SST for all 5 regions based on results from 13 climate change models.

a b

119

a b

c d

120

Figure 4.6: a) Mean Ta during the breeding months at 3 nesting site for loggerheads in Greece. Solid lines are the linear

trend lines (Crete R2 = 0.133; Kyparissia R2 = 0.252; Zakynthos R2 = 0.467). b) Relationship between day of first

female emergence and mean Ta during the breeding months in Zakynthos Island (R2 = 0.705). c) Projections of the day

of first female emergence through 2100 based on climate model (n = 14) estimations on the increase in Ta during the

breeding months at Zakynthos Island. d) Projected change in Ta for Crete during the breeding months based on results

from 14 climate change models. e) Projected change in Ta for Zakynthos/Kyparissia during the breeding months based

on results from 14 climate change models.

e

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Figure 4.7: a) Projected change in precipitation rate for Crete based on results from 14 climate change

models. b) Projected change in precipitation rate for Zakynthos/Kyparissia based on results from 14

climate change models. c) Mean of the projectd changes in precipitation rates for Crete and Zak/Kyp

during the breeding months based on results from 14 climate change models.

a b

c

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Figure 4.8: a) Relationship between number of nests per season at Zakynthos and the mean annual SST at the 5

foraging sites 2 years prior. Solid line is the linear trend line (R2 = 0.190). b) Relationship between number of nests

per season at Rethymno and the mean annual SST at the foraging sites (Gulf of Gabes, Aegean Sea and Crete) 2 years

prior. Solid line is the linear trend line (R2 = 0.572).

a b

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CHAPTER 5: Conclusions and Conservation Implications

Changepoint Analysis

The 19 satellite tracked loggerhead turtles from Rethymno, Crete, Greece

exhibited 3 unique post-nesting behavioral patterns. First, 9 turtles migrated south to the

North African coast; second, 6 turtles migrated directly north into the Aegean Sea; and

third, 4 turtles did not migrate and remained resident within the waters of Crete. Due to

the use of an improved analytical for interpreting telemetry data, changepoint analysis, I

obtained a more complete spatial and temporal designation of loggerhead at-sea behavior.

All told, I distinguished five unique behavioral modes for loggerheads in the Eastern

Mediterranean Sea. These included migration, foraging, and overwintering, along with 2

newly discovered transition phases; the first occurring prior to foraging and the second

prior to overwintering. The discovery of the transition phases helps broaden our

understanding of loggerhead at-sea behavior and contributes to improving conservation

and management decisions.

Regional Fitness Differences

Because most adult loggerheads forage from the benthic environment, some

fitness measures are a good proxy for the overall value and abundance of benthic fauna

from their foraging areas. The turtles foraging in the Aegean Sea had greater carapace

lengths and larger clutch sizes than the turtles foraging in the coastal waters near Crete or

Africa. Based on benthic surveys, the Aegean Sea had the highest abundance and species

richness of molluscs and crustaceans of the three general foraging areas. Crete had 40 %

less species abundance within the same depth range and the benthic environment for

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foraging was far more limited. In the Gulf of Gabes, the benthic prey abundance was very

low due to the continuous influx of industrial runoff from the developing cities of

Tunisia. The nearshore foraging turtles from this region were smaller than the turtles

foraging offshore further out on the Tunisian shelf, where the negative effects of the

eutrophication and harmful algal blooms may not be as strong. The benthic environment

in this region is also very large, and thus provides foraging grounds for a larger

percentage of nesting turtles from Greece. However, with an increasing level of

eutrophication and frequency of harmful algal blooms, this region may not be able to

continue sustaining populations of loggerheads into the future.

Climate Change Impacts

The SST at critical regions for loggerhead foraging and nesting in the Eastern

Mediterranean Sea is expected to increase by between 2.1o – 6.5

o C by 2100.

Simultaneously at the nesting sites, Ta is expected to rise by 2.1o – 8.0

o C, while

precipitation is expected to decrease by as much as 20 – 30 mm/month. This dramatic and

rapid shift in climate has the potential to greatly impact nesting and foraging success.

Based on the rise in SST and Ta at Zakynthos Island, I projected that loggerheads will

shift the nesting season earlier by as much as 74 days by 2100. However, beach

temperatures are expected to rise and precipitation is projected to decline during these

earlier weeks prior to the current nesting season. As a result, the shift to nesting earlier in

the year will result in the continuation of a heavily female biased hatchling sex ratio and

the annual reduction in precipitation may limit hatching success entirely. Furthermore,

foraging success may be greatly reduced by the increase in SST, as the sea grass beds that

support loggerhead prey are already showing signs of deterioration due to increasing

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temperatures and high levels of eutrophication, particularly in the Gulf of Gabes. As a

result, a reduction in fitness associated with reduced foraging success coupled with the

already highly female biased sex ratio in Greek loggerheads may cause steep declines in

this already imperiled nesting population.

Further Conservation Concerns

The 19 successfully tracked turtles in this study moved through the Exclusive

Economic Zones of 4 countries: Greece, Libya, Turkey, and Tunisia. These countries are

responsible for 37.8 % of the captures of sea turtles by fishing gear annually in the

Mediterranean (Casale, 2011). As is clear in Spotila et al. (2000), fisheries activities have

the potential to drive a sea turtle species to extinction. Therefore, with the improved

assessment of loggerhead behavioral patterns in the Mediterranean Sea gained through

CPA, decisions regarding the opening and closing of regions for fisheries can become

more precise.

Within the Mediterranean Sea, bottom trawling is responsible for 39,000 captures

annually, and also has the lowest mortality rate of 20 % (Casale, 2011). This method is

found at a higher frequency in Libya and Tunisia, with trawl fisheries in the Gulf of

Gabes responsible for close to 15 % of the total annual by-catch in the entire

Mediterranean (Jribi et al., 2007). The mortality rate is particularly low in the Gulf of

Gabes (3.3 %) due to the short duration of each trawl and this has convinced fishermen

that turtle excluder devices are not necessary (Jribi et al., 2007). However, with the

overfishing of the benthic environment, prey availability might be substantially reduced

and may pose a larger threat (Jribi et al., 2007).

126

Demersal and pelagic longline fisheries are responsible for an estimated 60,000 –

80,000 turtle captures annually in the Mediterranean and these methods have a mortality

rate of 30 – 40 % (Casale 2011; Lewison et al., 2004). Longline fishing is more common

in the Aegean Sea; however also found often amongst Libyan fishermen (Casale, 2011).

The hooks of longlines are the largest threat, with 91 – 96 % of the longline turtle bycatch

in the Gulf of Gabes captured via hook, the remaining turtles were caught due to line

entanglement (Jribi et al., 2008). A transition to circle hooks may greatly reduce this by-

catch, as was seen in experiments conducted throughout the world (Read, 2007).

Set nets are responsible for the fewest annual captures; however have the highest

mortality rate of 60 % (Casale, 2011). Greece, Turkey, Tunisia and Libya are responsible

for 50 % of the annual captures using set nets in the Mediterranean, with the Gulf of

Gabes having a mortality rate of close to 70 % (Casale, 2011; Echwikhi et al., 2010). As

a result, regardless of the amount of beach protection and monitoring of nests, without a

serious reduction in the fishing effort from these 4 countries, this Mediterranean

population of loggerheads may not continue to survive.

It is imperative that serious efforts, especially in the foraging and overwintering

areas and along the migration paths identified in this study, are taken to reduce the overall

impact of humans on wildlife. The clear indication from this study is that human

activities are particularly impacting the survival of loggerheads in the Mediterranean Sea.

From direct effects like tourist activity and development on critical nesting beaches and

dangerous fishing practices at the foraging grounds to indirect effects like the influx of

industrial waste in the Gulf of Gabes and climate change, loggerheads in the

Mediterranean Sea cannot be expected to thrive with conservation efforts only geared

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towards nest protection. These are dynamic animals that exhibit a range of behaviors to

take advantage of the variety of environments they interact with. Without a cooperative

effort from the various countries of the region to adjust their behaviors, we will lose

Mediterranean loggerheads along with their ecosystems.

128

References

Casale, P. 2011. Sea turtle by-catch in the Mediterranean. Fish and Fisheries 12: 299 –

316.

Echwikhi, K., I. Jribi, M.N. Bradai and A. Bouain. 2010. Gillnet fishery-loggerhead turtle

interactions in the Gulf of Gabes, Tunisia. Herpetological Journal 20: 25 – 30.

Jribi, I., M.N. Bradai and A. Bouain. 2007. Impact of trawl fishery on marine turtles in

the Gulf of Gabes, Tunisia. Herpetological Journal 17: 110 – 114.

Lewison, R.L., S.A. Sloan and L.B. Crowder. 2004. Quantifying the effects of fisheries

on threatened species. the impacts of pelagic longlines on loggerhead and

leatherback sea turtles. Ecology Letter 7: 221 – 231.

Read, A.J. 2007. Do circle hooks reduce the mortality of sea turtles in pelagic longlines?

A review of recent experiments. Biological Conservation 135: 155 – 169.

Spotila, J.R., R.D. Reina, A.C. Steyermark, P.T. Plotkin and F.V. Paladino. 2000. Pacific

leatherback turtles face extinction. Nature 405: 529 – 530.

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APPENDIX A: Projected changes in man SST for August at the five high usage sites

a b

a) Projected change in mean SST (oC) during August for the Adriatic Sea based on results from 13 climate change

models. b) Projected change in mean SST (oC) during August for the Aegean Sea based on results from 13 climate

change models. c) Projected change in mean SST (oC) during August for Crete based on results from 13 climate

change models. d) Projected change in mean SST (oC) during August for the Gulf of Gabes based on results from

13 climate change models. e) Projected change in mean SST (oC) during August for Zakynthos and Kyparissia Bay

based on results from 13 climate change models.

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e

c d

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APPENDIX B: Projected change in precipitation during the breeding months at the breeding sites

a b

a) Projected change in mean precipitation (mm/month) during April, May and June for Crete based on results from

14 climate change models. b) Projected change in mean precipitation (mm/month) during April, May and June for

Zakynthos and Kyparissia based on results from 14 climate change models.

132

VITA

Samir H. Patel

[email protected]

EDUCATION

Ph.D., Environmental Science, Drexel University, Philadelphia, PA 2013

B.A. Biological Sciences, Minor in Film Studies, 2005

The George Washington University, Washington, DC

PROFESSIONAL EXPERIENCE

Reviewer, Marine Turtle Newsletter 2012 – 2013

Teaching Assistant, Drexel University 2009 – 2010

Research Assistant, Drexel University 2009

Upper School Biology Teacher, Tabor Academy, Marion, MA 2007 – 2008

Upper School Science Teacher, Saint Edward’s School, Vero Beach, FL 2005 – 2007

FUNDING AND AWARDS

Travel Grant, International Sea Turtle Symposium 2011 – 2013

Travel Subsidy, Office of Graduate Studies, Drexel University 2011 and 2013

Travel Grant, Department of Biology, Drexel University 2012

Research Grant, The Leatherback Trust 2012

PROFESSIONAL SOCIETIES

International Sea Turtle Society 2011 – present

SELECT PUBLICATIONS AND ABSTRACTS

Patel, S.H., A. Panagopoulou, S.J. Morreale, D. Margaritoulis and J.R. Spotila. 2011.

Post-nesting behavior of loggerheads from Crete revealed by satellite telemetry.

International Sea Turtle Symposium, San Diego, CA.

Patel, S.H., A. Panagopoulou, S.J. Morreale, F.V. Paladino, D. Margaritoulis and J.R.

Spotila. 2012. Post-reproductive migration of an adult male loggerhead from

Crete revealed by satellite telemetry. International Sea Turtle Symposium,

Huatulco, Mexico.

Patel, S.H., A. Panagopoulou, S.J. Morreale, F.V. Paladino, D. Margaritoulis and J.R.

Spotila. 2012. Post-nesting strategies of loggerheads from Crete revealed by

satellite telemetry. International Sea Turtle Symposium, Huatulco, Mexico.

Patel, S.H., A. Panagopoulou, H. Bailey, S.J. Morreale, F.V. Paladino, D. Margaritoulis

and J.R. Spotila. 2013. Identifying behavioral states in loggerhead turtles using

satellite telemetry data. International Sea Turtle Symposium, Baltimore, MD.

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