Origins, Movements, and Foraging Behavior of Hawksbill Sea

Home , Hawksbill sea turtle, Spheciospongia vesparium

ORIGINS, MOVEMENTS, AND FORAGING BEHAVIOR OF HAWKSBILL SEA

TURTLES (ERETMOCHELYS IMBRICATA) IN PALM BEACH COUNTY

WATERS, FLORIDA, USA

Lawrence D. Wood

A Thesis Submitted to the Faculty of

The Charles E Schmidt College of Science

In Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

Florida Atlantic University

Boca Raton, FL

December 2014

ACKNOWLEDGEMENTS

The author wishes to thank the many volunteers, interns, dive boat operators, organizations, and funding sources that have made this study possible. Special thanks go to the management and staff of the Palm Beach Zoo and Conservation Society for so graciously hosting this project and providing the critical support needed for its continuation and completion. Critical funding was provided by the Sea Turtle

Conservancy through the Florida Sea Turtle License Plate Grants Program, the National

Save the Sea Turtle Foundation, the Bay and Paul Foundations, Mr. Robert Murtagh, Dr.

Terry Maple, and others. The author is grateful for the technical support provided by Dr.

Barbara Brunnick and Mr. Chris Johnson, and especially grateful to Dr. Terry Maple for his inspiration, advice, and encouragement before and while achieving this degree.

ABSTRACT

Author: Lawrence D. Wood

Title: Origins, movements, and foraging behavior of hawksbill sea turtles (Eretmochelys imbricata) in Palm Beach County waters, Florida, USA

Institution: Florida Atlantic University

Thesis Advisor: Dr. Sarah Milton

Degree: Doctor of Philosophy

Year: 2014

This dissertation examined the natal origins, home-range, and in-situ foraging behavior of an aggregation of sub-adult hawksbill turtles (Eretmochelys imbricata) found off the coast of Palm Beach County, Florida. Surveys were conducted on approximately 30 linear km of reef between 15 and 30 m in depth. Tissue samples were retrieved from 112 turtles for mtDNA haplotype determination. GPS-linked satellite transmitters were deployed on six resident sub-adults, resulting in both minimum convex polygon (MCP) and 95%, 50%, and 25% kernel density estimates (KDE) of home-range size. A foraging ethogram was developed, and sequential analysis performed on thirty videos (141 total minutes) of in-situ foraging behavior. Seventeen total haplotypes were identified in this aggregation, the majority (75%) of which represented rookeries on Mexico’s Yucatan

Peninsula. Other sources, from most to least important, include Barbados, Costa Rica,

Puerto Rico, Antigua, and the U.S. Virgin Islands. Home range estimates ranged from

1.1-19 km2 (mean 10.1 km2) using the MCP method, and 0.01-1.2 km2 (mean 0.49 km2) using the 95% KDE method. Consistent use of core areas within the home range, particularly at night, suggests the repeated use of familiar refuges for shelter. Five behaviors leading to prey ingestion were identified: scan, target, nudge, bite, and chew.

Collectively, these behaviors occurred in decreasing frequency leading to prey ingestion, suggesting a highly discriminatory feeding strategy that focused on a narrow range of poriferan prey through extensive exploration of the benthic environment. These are the first and most detailed behavioral studies to date concerning hawksbill turtles in Florida, and have contributed important baseline information concerning the biogeography and natural history of this species in this part of its range.

ORIGINS, MOVEMENTS, AND FORAGING BEHAVIOR OF HAWKSBILL

TURTLES (ERETMOCHELYS IMBRICATA) IN PALM BEACH COUNTY

WATERS, FLORIDA, USA

TABLES ...... viii FIGURES ...... x INTRODUCTION ...... 1 CHAPTER 1: ORIGINS ...... 3 Introduction ...... 3 Methods ...... 5 Results ...... 10 Discussion ...... 12 CHAPTER 2: MOVEMENTS ...... 18 Introduction ...... 18 Methods ...... 21 Results ...... 29 Discussion ...... 50 CHAPTER 3: FORAGING BEHAVIOR ...... 65 Introduction ...... 65 Methods ...... 68 Results ...... 71 Discussion ...... 76 REFERENCES ...... 83

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TABLES

Table 1.1. Short (380-480 bp) and long (740 bp) haplotypes and their proportions for all and juvenile hawksbills only from three foraging grounds in the western Atlantic: Palm Beach (PB), Mona Island Puerto Rico, and Cayman Island. Data for Mona are from Vélez-Zuazo et al. (2008); data from Cayman Islands are from Blumenthal et al. (2009b)...... 10

Table 1. 2 Pairwise comparisons of haplotype frequencies (FST values) among three aggregations of hawksbill turtles from which 740 base-pair haplotypes are available: Palm Beach (PB), Mona Island Puerto Rico, and Cayman Islands. F-statistics from haplotype frequencies are shown below the diagonal, FST P-values above the diagonal...... 11

Table 1.3. Maximum likelihood estimate for nesting beach origin of juvenile hawksbill turtles from Palm Beach County, Florida, based on 94 of 106 available sequences (12 juveniles had haplotypes that have not been reported from any nesting beach). Estimate is based on 384 bp of control region sequence and was generated using SPAM 3.7b (Alaska Department of Fish and Game, 2003)...... 11

Table 2.1. Search radii and cell size used for 95% kernel density estimates in Arcview 10.1® (ESRI, Inc.)...... 28

Table 2.2. Deployment dates, release locations, capture depths (m), substrate type, deployment duration (days) and straight carapace length (notch of the nuchal scute to the tip of either pygal scute, in cm) for six sampled hawksbills...... 29

Table 2.3. Total, diurnal (8:00 a.m. – 7:59 p.m. EST), and nocturnal (8:00 p.m. -7:59 a.m. EST) home range (HR) estimates for six hawksbill turtles. n= number of GPS coordinates; MCP= minimum convex polygon; KDE95= kernel density estimate, 95% contour...... 30

Table 2.4. Total, diurnal (8:00 a.m. – 7:59 p.m. EST), and nocturnal (8:00 p.m. -7:59 a.m. EST) core-use area estimates for six hawksbill turtles. MCP= minimum convex polygon; KDE50= kernel density estimate, 50% contour, KDE25= kernel density estimate, 25% contour...... 39

Table 2.5. Coordinates per three habitat zones for three turtles (#’s 21-23) residing on the Continental Reef Tract, and the area (extent) of each in km2...... 41

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Table 2.6. Proportionality of coordinates per habitat zone within and between individuals. W=west of the main ledge; L&C=ledge and reef crest; E= east of reef crest. Z-score and p-value are shown for each pair. Pairs that show no significant difference are shown in bold. (Fisher’s pooled 2-sample test for proportionality: Minitab 17™ statistical software) ...... 49

Table 2.7. Estimated foraging home ranges of hawksbill turtles (Ei) in Florida and the Caribbean. MCP= Minimum Convex Polygon method; KDE= Kernel Density Estimate...... 51

Table 3.1. Ethogram of hawksbill turtle foraging behavior...... 70

Table 3.2. Cumulative transition matrix. Numbers in cells represent the number of times a behavior on the y-axis transitioned to a behavior on the x-axis. For example, ‘scan’ transitioned to ‘target’ 247 times (*)...... 71

Table 3.3. Cumulative behavior transition frequencies. These are computed by dividing each cell by the sum (∑) of that row. For example, ‘scan’ transitioned to ‘target’ 247 out of 259 times (from Table 2), resulting in a frequency of 0.95(*), or 95% of the time...... 71

FIGURES

Figure 1.1. Bathymetry of the study site...... 6

Figure 1.2. Source areas of sub-adult hawksbill turtles in the Palm Beach aggregation (n=110)...... 13

Figure 1.3. Size distribution of 146 hawksbills captured between April 2004 and October 2010 on reefs off Palm Beach County, Florida...... 16

Figure 2.1. Habitat delineation at the continental reef tract (CRT). The west zone consists of patch reef and sand; ledges consist of cliff walls; the ridge consists of the reef crest; and the east zone (fore-reef) consists of spur-and- groove formations. Between ledge zones are not found on the CRT...... 24

Figure 2.2. Habitat delineation on the deep ridge complex (DRC). This area includes large artificial reef structures (playground, china barge, Amaryllis, Mizpah, and Spearman’s barge). The west zone consists of patch reef and sand; ledges consist of cliff walls; the ridge consists of the reef crest; and the east zone (fore-reef) consists of spur-and-groove formations. Between ledge zones consist of sandy bottom...... 25

Figure 2.3a-e. Home range estimates for turtle #’s 19 and 24 (deep ridge complex), and 21-23 (continental reef tract). The shaded polygon represents the HRE as calculated by the Minimum Convex Polygon (MCP) method, and the light blue contour as calculated by the 95% Kernel Density Estimate method (KDE95). Core – use areas (KDE50 and KDE25) are represented by bright green and white contours, respectively...... 31

Figure 2.4a-b. (a) Home-range overlap (KDE 95, 50, 25) for turtles 21-23 (continental reef tract). For all three turtles, the 25% core-use areas (KDE25), in white, were located at or near the center of each 50% (KDE50) contour (bright green). (b) Home-range overlap (KDE 95, 50, 25) for turtles 19 and 24. Both were captured at an artificial reef site consisting of scuttled vessels, limerock, and concrete debris. The 50% core-use areas (KDE50 in bright green) overlapped nearly perfectly at this site, and the 25% (KDE25) core-use area (in white) for both animals was located at a shipwreck known as the Amaryllis...... 37

Figure 2.5. Mean proportion (%) of diurnal coordinates located in the area between the KDE50 and KDE95 isopleths, within the KDE50 isopleth, and within the KDE25 isopleth for 5 turtles...... 40

Figure 2.6. Home range size (km2) vs. number of coordinates and straight carapace length (SCL notch-tip (cm)) for six turtles. Open squares (□) = SCL; open diamonds (◊) = total KDE95; crosshairs (×) = nocturnal KDE95; triangles (▲) = nocturnal KDE50...... 41

Figure 2.7. Proportion of day and night coordinates located east of the reef ridge (spur- and-groove); at the ledge/ridge (L & R); and west of the reef ridge (patch reef) for turtle #’s 21-23...... 43

Figure 2.8. Turtle #21. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type. The “Trench” is an east-west cut in the reef created for communication lines that has undercuts and caves...... 44

Figure 2.9a-c. (a) Turtle #22 diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type: north and south portions. Ron’s Reef has undercuts and caves. (b) Turtle #22 northern portion. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type. Coordinates are concentrated near a feature known as “Ron’s Rock”, which is a large boulder that separated from the reef that provides undercuts and caves...... 45

Figure 2.10. Turtle #23. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type...... 48

Figure 2.11. Sub-adult hawksbill sleeping under a ledge at night in Palm Beach. Photo courtesy of Andrea Whitaker...... 55

Figure 2.12. Turtle #19. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type. Mizpah, Amaryllis, and China Barge are scuttled ships...... 56

Figure 2.13. Turtle #24. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type. Mizpah, Amaryllis, and China Barge are scuttled ships...... 57

Figure 2.14. Rates of encounters (sightings/hr. on scuba) with previously tagged study animals vs. encounters with untagged individuals in the study site...... 59

Figure 2.15. Evidence of shark predation on a hawksbill turtle in northern Palm Beach County, Florida. Photo courtesy of Terri Roberts...... 61

Figure 3.1. Search behavior of hawksbill turtles. Scan (top row left); target (top row right); nudge (bottom row left); bite (bottom row right). ‘Chew’ and ‘swallow’ are active behaviors not well represented in still photographs...... 70

Figure 3.2. Cumulative kinematic diagram of sequential hawksbill foraging behavior. “SC”=scan; “TA”=target; “NU”=nudge; “BI”=bite; “CH”=chew; “SW”=swallow. The values (positioned at line origin) represent the frequency with which one behavior directly follows another. Line weight is proportional to frequency...... 72

Figure 3.3. Frequency of six behaviors leading to and including prey ingestion. TA=target; NU=nudge; BI=bite; CH=chew; SW=swallow...... 73

Figure 3.4. Frequency of each behavior leading to the focal act of food ingestion. TA=target; NU=nudge; BI=bite; CH=chew; SW=swallow...... 73

Figure 3.5. Frequency of first (target) and last (swallow) behaviors per video duration… ...... 74

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INTRODUCTION

Marine turtles are globally-distributed, economically valuable animals that have endured a long history of human interaction. Significantly depleted stocks of all species have prompted large-scale conservation measures over the last few decades, including considerable scientific attention. Among the most critically endangered of these is the hawksbill turtle (Eretmochelys imbricata), yet comparatively few studies have addressed its biology. A project originally entitled "An Assessment of the Hawksbill Turtles of

Palm Beach County Waters" is now entering its tenth year under the authorization of

NMFS Permit #’s 1418 (Dec. 23, 2003) and 14272 (Jan. 27, 2009). This effort was initiated in response to the lack of hawksbill data from Florida, and has since explored the population structure, genetic diversity, movements, and foraging ecology of this species in a previously under-appreciated part of their range. These studies are designed to directly address the following important tasks as stated in the Federal Recovery Plan for

Atlantic hawksbills (NMFS, 1998):

1210 Identify important marine habitats.

"...but information on the location of specific foraging areas is extremely limited. These areas need to be: identified. The habitat requirements of smaller hawksbills need to be identified. PRDNR, VIDFW, NMFS, FWS, FDEP, and other interested resource agencies should support this research."

221. Determine distribution, abundance, and status in the marine environment.

"...To recover the hawksbill, it is critical for resource managers to know when, where, and in what abundance hawksbills may occur during the various stages of their life cycles."

The data obtained so far have significant regional importance as the effort continues to improve the status of hawksbills and other sea turtles in the Wider Caribbean region.

Due to their close association with coral reef habitats and their status as a critically endangered species, hawksbill turtles are also emerging as an important flagship species for coral reef conservation, and are currently benefiting from renewed attention within the scientific community.

The three primary objectives of the following studies are to determine the source rookeries of hawksbill turtles captured in Palm Beach County waters, to examine the spatial and temporal patterns of habitat use among long-term residents, and to describe details of hawksbill foraging behavior via direct in-situ observation. The results of these studies provide the first answers to bio-geographical questions on both coarse- and fine- scales, and shed light on how the hawksbills’ role as long- term, residential mega- spongivores influences their patterns of habitat use. In addition, these results underscore the value of complimenting remote-sensing technologies with direct observation, as each has their own inherent limitations. When combined, data from “close-up” and “far away” are capable of providing a much more realistic picture of marine turtle ecology, and can provide a new and valuable platform for many future studies on this and other marine chelonians.

CHAPTER 1: ORIGINS

Introduction

The hawksbill turtle (Eretmochelys imbricata) is a highly specialized marine turtle associated with coral reefs and other hard-bottom habitats in tropical and subtropical seas world-wide, and currently listed as Critically Endangered by the International Union for the Conservation of Nature (IUCN ) (Mortimer and Donnelly 2007). In the western

Atlantic Ocean, hawksbills occur from the southern United States south to Brazil and east throughout the Greater and Lesser Antilles. In the continental USA, nesting is rare; only one nest has been documented in Texas, and four or fewer were recorded annually in

Florida between 1979 and 2003 (Meylan and Redlow 2006). However, hawksbills occur with regularity in Florida waters, particularly along the southeastern and central Gulf of

Mexico coasts and in the Florida Keys (Meylan and Redlow 2006). These authors confirmed the presence of all life stages in the state and described their distributions based on observations of live turtles at sea, in-water capture programs, incidental captures, museum records, and stranding data. However, few studies have focused on this species in Florida waters (Eaton et al. 2008), and relatively little is known about its biology or habitat use in continental U.S. waters.

This study focused on the reefs adjacent to Palm Beach County, Florida (26°45′N,

80°01′W), which represent one of the most northerly sites in the western Atlantic Ocean

3 at which a hawksbill foraging aggregation has been identified. The existence of hawksbills at this site may be due, in part, to the proximity of an offshoot of the Gulf

Stream known as the Florida Current. The current passes near the southeastern Florida coastline and brings warm tropical water from the Gulf of Mexico and Caribbean. It continues northeast toward Bermuda and may similarly account for the presence of a hawksbill foraging aggregation there (Meylan et al. 2011). Meylan and Redlow (2006) hypothesized that the convergence of currents from a wide area of the Gulf of Mexico and the Caribbean into the Florida Current may serve to concentrate pelagic-sized hawksbills along the coast of southeastern Florida, and would help to explain observed stranding patterns. The hypothesis of a dispersal corridor in this area was supported by the results of Blumenthal et al. (2009), who used ocean current data and models of passively drifting particles to predict the dispersal patterns of Caribbean hawksbills.

The reefs off Palm Beach County are part of the Southeast Florida Continental Reef

Tract, which has been described as a high-latitude reef system (Moyer et al. 2003; Banks et al. 2007, 2008; Riegl et al. 2007). The reef supports a fauna similar to that of the

Florida Keys, Bahamas, and Caribbean but with a different community structure, lacking the major reef-building coral, Acropora palmata; it is characterized by low coral cover

(1–13%) and a dominance of sponges and octocorals (Jaap and Hallock 1990; Moyer et al. 2003; Banks et al. 2008).

The discovery of a substantial foraging aggregation of hawksbills at this high- latitude site broadens the understanding of habitat use of this Critically Endangered species. Coral reefs appear to be its primary habitat, although the use of other rocky, high-energy environments such as cliff walls, shoals, and limestone and volcanic

4 outcrops has also been documented (Meylan and Redlow 2006 and references therein).

These observations are consistent with the spongivorous feeding habits of the species

(Meylan 1988). Seagrass beds are also used to some extent (Diez et al. 2003; Bjorndal and Bolten 2010), as are mangrove-fringed bays, lagoons, and estuaries in the eastern

Pacific (Carr 1952). These habitats face numerous threats in Florida (Collier et al. 2008) and world-wide (Jackson et al. 2001; Wilkinson 2004).

Due to the broad geographic scales over which sea turtles disperse, understanding the mixture of origins (and probable destinations) of sub-adult aggregations throughout their range is necessary to linking critical habitat at formative life stages with critical habitat later in adulthood. In this study, the nesting beach origins of hawksbill turtles found in Palm Beach County (Florida, USA) waters were determined and compared with similar aggregations elsewhere in the Caribbean region.

Methods

Hawksbills were hand-captured during 435 year-round drift-dives on 30-km stretch

(N26°55′ to N26°37′) of the nearshore reefs off the coast of central and northern Palm

Beach County, Florida between April 2004 and October 2010. Commercial dive charter operators provided access to 40+ dive initiation sites, which traverse the majority of the

15-30 m colonized hardbottom habitats that line the coast approximately 2.5 km from shore (Figure 1.1).

Figure 1.1. Bathymetry of the study site.

The dive sites most readily accessed by local dive charters to the north and south of the Lake worth Inlet framed the extent of the study site. Sampling days were avoided when sea swells exceeded 1.5 m. Sampling sessions consisted of 2–3 drift dives that averaged 32.3 min. each, the location of which were decided upon by the charter operator prior to each departure based on a number of factors, including local sea conditions, diver certification levels, and/or client preference. Once at the destination, the dive path often

6 followed ridges that served as landmarks to help orient the recreational-client divers, thereby reducing access to adjacent areas that feature less-dramatic bathymetry. These biases in sampling were a necessary compromise in order to use the commercial diving firms for logistical support.

The research team typically began dives adjacent to or downstream from the client group to minimize interference with study animals. The course taken and distance traveled by the team were determined by current direction and velocity, with adjustments made to avoid high turbidity. Based on 16 dives for which dive times and GPS coordinates for start and stop points were available, the average speed of travel of the divers was 0.42 m s–1 (range 0.1–1.3, SD = 0.329). Thus, a typical drift dive traversed approximately 816 m of reef (estimated total linear distance 355 km).

Each turtle captured was brought to the surface at a safe ascent rate by a pair of divers, and transferred to the dive boat. A small tissue sample was obtained from the trailing edge of either rear flipper with a 4 mm sterile biopsy punch and fixed in a sodium chloride-saturated DMSO solution. The biopsy site was disinfected with injection-site alcohol and/or betadine swabs both before and after the sample was taken.

Maximum straight carapace length (notch-tip), minimum carapace length (notch- notch), maximum carapace width, and straight plastral length were recorded with standard 100cm tree calipers. A flexible measuring tape was used to record the curved measurements of the same parameters of the carapace and plastron, plus anterior and posterior scute width and tail length (plastron-tip of tail). These measurements are described in detail in van Dam and Diez (1998b). Photographs were taken of the

7 carapace, plastron, all angles of the head, tail, and any additional features of interest such as wounds, physical anomalies, and epibiota.

One self-piercing, self-locking inconel steel ear tag (Style 681; National Band and

Tag Co. Newport, KY) was placed (with the clamping tool provided) into the 1st or 2nd large trailing scale distal to the base of each front flipper. The tag was checked to ensure proper locking. The turtles were scanned for existing transponders with a Biomark, Inc.

(Boise, Idaho) "Pocket Reader" 125/ 134.2 KHz tag scanner. If none were found, a

Passive Integrated Transponder (PIT) tag (Item TX1406L; Digital Angel Co, St. Paul,

MN) was injected (with the tool provided) into the musculature at the base of either front flipper, usually on the right side.

Sequence data were generated by the ICBR Genetic Analysis Core, University of

Florida, USA. DNA was extracted using Qiagen DNeasy Tissue Kits and manufacturer’s protocols. A 740 base pair segment of mtDNA control region was amplified using primers LTEi9 and H950 (Abreu-Grobois et al. 2006; Browne et al. 2010) and sequenced on an Applied Biosystems model AB3730xl sequencer at the ICBR DNA Sequencing

Core, University of Florida, USA.

Sequences were aligned with published Atlantic and Caribbean 380–480 bp (short) sequences (Bass et al. 1996; Bowen et al. 1996, 2007; Díaz-Fernández et al. 1999) and longer (740 bp), unpublished sequences (Abreu-Grobois et al. 2006; Vélez-Zuazo et al.

2008) using MULTALIN (Corpet 1988) and assigned a three-part haplotype name following Vélez-Zuazo et al. (2008) and Browne et al. (2010); e.g., Q/MX1 (EiA41). To compare foraging aggregations for which long (740 bp) sequence data are available

(Palm Beach, Mona Island, and Cayman Islands), an AMOVA was performed in

Arlequin 3.01 (Excoffier et al. 2005). To estimate source populations for the Palm Beach foraging aggregation, it was necessary to truncate sequences to the 384 bp segment used by Bass et al. (1996), Bowen et al. (2007), Blumenthal et al. (2009b), and Browne et al.

(2010) because data on the frequencies of the longer sequence are not yet available from most nesting beaches. An estimate of the sources for the Palm Beach aggregation was generated using SPAM 3.7b (Alaska Department of Fish and Game 2003) with baseline nesting data from Bass et al. (1996), Díaz-Fernández et al. (1999), Troëng et al. (2005),

Bowen et al. (2007), Vélez-Zuazo et al. (2008), and Browne et al. (2010). Seven presumed adults (>74.1 SCLn-t) were removed from the Palm Beach sample before this estimate was generated.

Results

A 740 bp sequence was generated for 110 individuals (Table 1.1).

PB PB Mona Cayman PB PB Mona Cayman 740 bp (all) (Juv.) (Juv.) (Juv.) (all) (Juv.) (Juv.) (Juv.) prop. prop. prop. prop. A/Cu1 Ei-A01 3 0.027 2 0.019 15 0.268 44 0.478 Alpha/g Ei-A02 1 0.009 1 0.010 1 0.018 2 0.022 B/e Ei-A03 1 0.009 1 0.010 1 0.018 1 0.011 F/e Ei-A09 4 0.036 4 0.038 6 0.107 8 0.087 F/PR1 Ei-A11 14 0.126 12 0.114 17 0.304 17 0.185 G/i Ei-A12 1 0.009 1 0.010 L Ei-A18 N/PR2 Ei-A20 1 0.009 1 0.010 2 0.036 P/MX3 Ei-A22 6 0.054 6 0.057 2 0.036 Q/MX1 Ei-A23 50 0.450 48 0.457 2 0.036 Q/MX2 Ei-A24 11 0.120 A Ei-A27 1 0.009 1 0.010 Ei-A28 4 0.043 CU3 Ei-A29 2 0.036 1 0.011 M Ei-A35 1 0.009 1 0.010 N Ei-A36 1 0.009 1 0.018 Q Ei-A39 10 0.090 10 0.095 Q/MX1 Ei-A41 12 0.108 12 0.114 1 0.018 Q/MX2 Ei-A43 3 0.027 3 0.029 1 0.018 F/PR1 Ei-A45 2 0.036 A/CU1 Ei-A51 1 0.018 Ei-A59 1 0.018 Ei-A60 1 0.018 F/PR1 Ei-A63 1 0.009 1 0.010 A Ei-A68 1 0.018 Ei-A72 2 0.022 Q/MX2 Ei-A83 2 0.018 2 0.019

Total 110 104 56 92

Seventeen “long sequences” were represented, all assignable to known haplotypes

(Abreu-Grobois et al. 2006). Mexican haplotypes (P and Q) made up 65.1% of the sample. One haplotype, n (Ei-A36), currently known only from foraging grounds in

Cuba, is represented by the largest of three possible adult females captured during the study. The genetic diversity of the Palm Beach aggregation is comparable to that at

Mona and Cayman (Table 1.2), but these sites differ significantly in haplotype frequencies, with a unique bias toward Mexican haplotypes in the Palm Beach aggregation (Table 1.3).

PB (all) PB (Juv.) Mona (Juv.) Cayman (Juv.) PB (all) 0.00000 0.99967 0.00000 0.00000 PB (juv.) 0.00000 0.00000 0.00000 0.00000 Mona (juv.) 0.14517 0.15281 0.00000 0.00529 Cayman (juv.) 0.22715 0.23468 0.03794 0.00000

90% Confidence Intervals Population Estimate Lower Upper Antigua, Jumby Bay 0.0201 0.000 0.059 Barbados – Leeward side 0.1351 0.000 0.228 Barbados –Windward side 0.0000 — — Belize, Gales Point 0.0000 — — Costa Rica, Tortuguero 0.0521 0.008 0.134 Cuba, Doce Leguas 0.0000 — — Mexico, Yucatán 0.7547 0.677 0.822 Puerto Rico, Mona Island 0.0320 0.003 0.112 U.S. Virgin Island, Buck Island 0.0061 — —

The preliminary estimate of source areas suggests that Mexican beaches are the predominant source of individuals in the Palm Beach aggregation, and that other likely contributors from most to least important include the leeward side of Barbados, Costa

Rica, Mona Island, Antigua, and the US Virgin Islands.

Discussion

This study provides the first description of the origins of a significant foraging aggregation of the Critically Endangered hawksbill turtle within the waters of the continental United States. The hawksbills that use the Palm Beach reefs as benthic developmental habitat represent a temporary assemblage of individuals from multiple nesting beach populations. The concept of “mixed stocks” on foraging grounds is well established for sea turtles in general (Bowen 1995) and for hawksbills specifically

(Blumenthal 2009b and references therein). The results suggest that this foraging aggregation is a mixture of contributions from three to six nesting areas (Figure 1.2).

Mexico- 75.6%

Barbados-Leeward- 13.6% Costa Rica- 5.2%

Mona Island, P.R.- 3.2%

Antigua- 2.0%

USVI- 0.6%

Figure 1.2. Source areas of sub-adult hawksbill turtles in the Palm Beach aggregation (n=110).

However, it is unusual in that it is largely derived from a single source, Mexican nesting beaches on the Yucatan Peninsula (75.5%, 90% CI = 67.7–82.2%).

At least one haplotype, q (EiA-39), which could not be included in the Maximum

Likelihood Analysis (MLA), is known only from Mexican beaches (F. Alberto Abreu-

Grobois, pers. comm.). It represents about 9% of the foraging sample and suggests that the Mexican contribution to the Palm Beach aggregation is actually greater (close to

85%) than the preliminary estimate. Thus, this aggregation was similar to that reported from Río Lagartos, Mexico, in being dominated by Mexican haplotypes (at least 71% in the case of Río Lagartos) (Díaz-Fernández et al. 1999). The Texas aggregation reported by Bowen et al. (2007) was also dominated by Mexican haplotypes, but it represented

13 individuals stranded from the epipelagic stage and not from a benthic foraging aggregation.

One other foraging area, Cuba A of Bowen et al. (2007), was dominated by a single source (72% Cuba). For other benthic foraging aggregations so far examined (Puerto

Rico and Cayman Islands), no single nesting area is the source for more than 50% of the individuals observed (Bowen et al. 2007; Vélez-Zuazo et al. 2008; Blumenthal et al.

2009b).

In the western Atlantic, hawksbill nesting rookeries are split between the insular

Caribbean island chain and the western Caribbean mainland. Hatchlings from the insular rookeries, which span the Caribbean Archipelago from Cuba to the tip of South America, likely disperse into the central Caribbean basin and eventually into the North Atlantic gyre upon departing their natal beaches. After the completion of this epipelagic stage, young juveniles typically return to the expansive Caribbean basin seeking neritic developmental habitat, where considerable mixing of genetic stocks could be expected among juvenile aggregations (Blumenthal et al 2009).

On the Central and South American mainland, hawksbill rookeries exist from the

Yucatan Peninsula of Mexico to the Northern coast of Brazil, the largest two of these at both ends of this range, respectively, with moderate contributions coming from the coasts of Nicaragua, Costa Rica, and Panama (NMFS 2013). The regionally-significant number of hatchlings leaving the beaches of northern Yucatan could easily substitute the gyre system in the Gulf of Mexico for the one in the North Atlantic, where Witherington et al.

(2012) recently confirmed their presence. Upon the completion of this stage, the Loop

Current system in the Eastern Gulf of Mexico could facilitate their arrival in the Dry

Tortugas and Marquesas Islands, then to northern Cuba and the Florida Keys, and eventually, further downstream, to the SE coast of the Florida Peninsula. Indeed, the trajectories of modelled particles released from hawksbill index nesting beaches in the

Caribbean made it through the straights of Florida to eventually arrive in South Florida via the Gulf Stream (Blumenthal et al. 2009). If the hatchlings remain entrained in the currents of the Gulf of Mexico for a sufficient amount of time, they could become segregated from individuals from other regions, and relatively easily disperse to neritic foraging grounds in southern Florida. Oceanic currents play an important role in the dispersal of many pelagic larvae (Mora and Sale 2002), and have been shown to facilitate considerable genetic mixing in marine crustaceans, resulting in locally genetically unstructured populations in shrimp (Benzie et al 2002; McMillen-Jackson and Bert 2004) and spiny lobster (Silberman et al 1994; Naro-Maciel et al 2011). Likewise, hawksbill turtles from various genetic stocks also become mixed during their own ‘planktonic’ stage. Nonetheless, current patterns may play an important role in composing the mixtures, and result in increased genetic structure among aggregations at certain neritic foraging grounds (Blumenthal et al. 2009). The bias toward Mexican stocks found in the

Palm Beach aggregation has likely been influenced by these large-scale oceanographic processes.

The mean straight carapace length (56.6±9.7 cm) of this aggregation of hawksbills is representative of a later benthic developmental stage (Fig. 1.3).

Figure 1.3. Size distribution of 146 hawksbills captured between April 2004 and October 2010 on reefs off Palm Beach County, Florida.

Based on an average recruitment size of 20–26 cm SCL for Atlantic benthic developmental sites (Meylan and Redlow 2006; Meylan et al. 2011: table 11), it is likely that the hawksbills that recruit to the Palm Beach reefs have already spent time in benthic developmental habitat elsewhere. The work of Blumenthal et al. (2009b) suggests that for the majority of individuals (those from Mexican nesting beaches), this site or sites should be in the Gulf of Mexico or more southerly parts of the Southeast Florida

Continental Reef Tract. Arrival at the Palm Beach reefs is almost certainly facilitated by the prevailing surface currents, including the Yucatan, Loop, and Florida Currents.

The Palm Beach developmental aggregation appears to overlap with adults in the internesting habitat and/or migratory corridor. The rarity of adults at the site, their

16 infrequent subsequent observation, and occurrence only during the reproductive season suggest that they were not resident but rather were involved in some aspect of reproductive behavior. Overlap of this nature has been described for Barbados (Horrocks et al. 2011) and Panama (Meylan et al. 2011) and likely occurs at several other benthic developmental sites (Meylan et al. 2011: table 11). The largest of 3 possible adult females had haplotype n (Ei-A36), which is not yet known from any nesting beach. This haplotype has only been identified from foraging areas in Cuba and Puerto Rico (Díaz-

Fernández 1999; Vélez-Zuazo et al. 2008).

With the exception of Bermuda, Palm Beach County is the northernmost location in the greater Atlantic known to serve as benthic developmental habitat for hawksbills. This reef system extends north at least as far as northern Palm Beach County and south to the

Florida Keys, and thus the possibility exists that Florida’s east coast in its entirety supports large numbers of immature hawksbills. Furthermore, the turtles in the Palm

Beach aggregation are in the later part of their benthic developmental stage and have survived the earliest stages of the life cycle during which survivorship is expected to be low. They are thus of high demographic value, and the reef system off southeastern

Florida that supports them merits consideration as critical habitat for hawksbills.

Appropriate management of these reefs will be important to the long-term survival of this critically endangered species.

CHAPTER 2: MOVEMENTS

Introduction

Hawksbill turtles (Eretmochelys imbricata) are migratory marine turtles that are widely distributed throughout the Caribbean Sea, west to the Gulf of Mexico, and south along both the eastern and western coasts of Central and Northern South America

(Witzell, 1983). Though nesting is rare on the U.S. mainland, juvenile, sub-adult, and adult hawksbill turtles have been reported in waters near the Florida Keys northward along Florida’s east coast to the reefs adjacent to Palm Beach County (Lund 1985,

Meylan and Redlow, 2006, Wood, et.al. 2013). As large spongivores, hawksbills are considered important apex predators that may influence reef ecosystem structure and dynamics (Hill, 1998; Leon and Bjorndal, 2002), but as a result of long-term over- exploitation, are listed as Critically Endangered worldwide by the IUCN (Baille and

Groombridge, 1996).

Hawksbill distribution in southeast Florida remains largely unknown, and a number of authors have recognized the need for expanded in-water research on this species here and elsewhere (Eaton, et. al., 2008; Hayes, 2008; Hawkes et. al. 2012; Hart et. al. 2012). Several foraging areas have been identified in continental U. S. waters, including the Dry Tortugas, and Florida Keys (Hart et. al. 2012; In-water Research Group

2009). Recently, Wood et. al. (2013) found the abundance and growth rates among a

Palm Beach County aggregation comparable to those measured elsewhere in the

Caribbean. After originating from Caribbean rookeries, the dispersal of post-pelagic juvenile hawksbills to southeast Florida is likely facilitated by the Gulf Stream current

(Blumenthal et al., 2009a). Indeed, both the Palm Beach County and Florida Keys aggregations are represented by multiple regional haplotypes, the former being strongly represented by Mexico’s Yucatan rookeries (Wood et. al., 2013; In-water Research

Group, 2009). Still, however, little is known of their movements or patterns of habitat use.

Areas of normal daily activity among animals are often referred to as “home ranges” (Burt 1943; Bailey 1984), and are sometimes maintained at some or all life stages by otherwise highly vagile species (Burt, 1943; Borger et. al. 2008). Once established, the geographical extent of the home range is typically determined by a combination of resource availability, energy expenditure, competition, and predator/prey interactions

(Rincon-Diaz et. al. 2011; Barraquand 2012). Where studied in the Caribbean, sub-adult hawksbills demonstrate fidelity to relatively small areas of reef (van Dam and Diez

1998a; Cuevas, et. al, 2007; Blumenthal et al., 2009a; Hart et. al 2012; Hawkes et. al.

2012; 2014). Likewise, in Palm Beach County, Florida, volunteer SCUBA divers have repeatedly identified dozens of uniquely identifiable hawksbill turtles within 2 linear kilometers of each’s original tagging/observation site over a span of several years (Wood, et. al., 2013). These observations suggest that some may restrict their movements to a home range for extended periods of time, perhaps even throughout the majority of their juvenile and sub-adult life stages (Hart. et. al., 2013; Wood et. al., 2013). Currently, no information exists concerning the spatial extent of hawksbill movements in SE Florida.

This basic information is fundamental to our understanding of the life history of this species, and critical for the effective management of its recovery (NMFS/USFWS, 1998).

Until recently, the use of satellite telemetry to study movement patterns in sea turtles has been limited to research encompassing relatively large geographic scales, typically addressing questions of migration and/or long-range dispersal. Due to short surface-times and positional inaccuracies inherent in remote sensing technology, satellite telemetry has not been very suitable for fine-scale assessments of marine turtles

(Bradshaw et al., 2007, Witt et al., 2010). The relatively small spatial scale over which typical sub-adult hawksbill turtles are suspected to move precludes the use of most standard, ARGOS-based transmitters. However, new technologies such as GPS-linked

Fastloc® (Wildlife Telemetry Systems, Ltd., Leeds, UK) have improved positioning accuracy by incorporating data from the global positioning system (GPS), even when communication (surface) times are limited (Moen et al., 1996, 1997; Witt et al., 2010).

This technology can more reliably estimate the extent of the turtle’s home range, and provide the additional resolution required to explore intra-range patterns of habitat use.

Animal habitat use estimates can be determined with various spatial analyses such as the traditional “minimum convex polygon” (MCP) and more recent non-parametric

“kernel density” (KDE) methods (Seminoff, et. al., 2002; Cuevas et. al. 2007). Because certain locations within the subject’s home range may be visited more or less frequently, the concept of the “habitat utilization distribution” (UD) (Worton 1987) was introduced to better describe areas of within-range core-use that may be linked to important behavioral needs such as foraging, resting, or predator avoidance. Understandably, an animals’ presence may not always be evenly distributed throughout its entire range, and

20 may change its UD patterns on various temporal and spatial scales. This is particularly applicable in cases where animals exhibit central-place foraging or repeatedly return to a focal point of activity, such as a den or nest (Orians and Pearson 1979; Barraquand,

2011). MCP area estimates cannot detect within-range subtleties, if present, because they calculate the total polygonal area surrounding all observations, including unusual, but potentially relevant outliers (Burt 1943). Alternatively, KDE’s provide a more realistic estimate of the home range by scaling the boundaries to the areas most frequently visited by the subject, thereby creating a UD (reviews by Worton, 1987, 1989; White and Garrot

1990). By excluding the outliers and recognizing clusters, UD frequency contours reveal areas of disproportionately high or low use within the overall home range, which can be used to link specific environmental features to important life-history traits. In this study, home-range estimates were generated for sub-adult hawksbill turtles in Palm Beach

County, Florida, and UD’s were developed to examine the fine-scale, within-range patterns of habitat use.

Methods

Study site

This study was conducted on the northernmost section of the Southeast Florida

Continental Reef Tract (see Banks et. al. 2007, 2008; Riegl et. al., 2007), located in the waters of northern Palm Beach County, Florida, USA (Figure 1.1). This non-accreting, shore-parallel reef system is located approximately 2 km offshore, forming a narrow ridge that features a 2-3 m tall landward ledge or cliff, a central plateau that rises to 16 m, and a gradual seaward slope that descends to the seafloor at approximately 21 m. To the

21 north and east of the reef tract’s terminus, the hardbottom consists of what are believed to be cemented sand dunes known as the “deep ridge complex” (Riegle et. al. 2007) that form a series of shore-parallel ridges featuring similar physical characteristics in slightly deeper water (21-27 m).

In addition to the natural reefs of the area, various ‘artificial’ reef structures

(vessels, concrete, limerock rubble) have been intentionally scuttled for ecological and recreational enhancement by the Palm Beach County Department of Environmental

Resources Management. One of these sites, known locally as the “Corridor” consists of series of ships and rock rubble that lie in close proximity to the deep ridge complex, in approximately 24 m of water. These structures have been in the water for over 45 years, resulting in thorough biotic encrustation.

Collectively, the reef-associated biota of Palm Beach County exist at a relatively high latitude, and survive due to the warm waters of the Gulf Stream Current. Still however, several important environmental constraints have helped shape the community structure. The meandering Gulf Stream results in comparatively wide water temperature variations, both seasonally (21-290 C) and episodically (temporary upwellings as low as

150 C). Persistent currents average 1.3 m s-1, but occasionally exceed 3 m s-1 (Banks et. al.,

2008). Additionally, the east coast of Florida is subject to periodic hurricanes and tropical storms, which can generate scouring wave surges and large-scale substrate redistribution.

As a result, any exposed hardbottom can be considered ephemeral, and favors the recruitment of those organisms that can most quickly colonize a newly exposed spot.

These conditions have resulted in a heterogeneous patchwork of benthic communities

22 dominated by macroalgae, alcyonian corals, and poriferans; rounded out by zooanthids, tunicates, hydroids, and a relatively small (≃12%) proportion of scleractinian corals

(Moyer et. al. 2003; Jaap, 2006). For the purposes of this study, the bathymetry of the reef complex has been divided into three zones at the reef tract site, and five zones at the deep ridge complex site: (1) ledges (includes artificial reefs); (2) ridges; (3) fore-reef

(east of ridge line), and (4) patch reef (west of the ledges), and (5) between ledges

(Figures 2.1, 2.2).

Figure 2.1. Habitat delineation at the continental reef tract (CRT). The west zone consists of patch reef and sand; ledges consist of cliff walls; the ridge consists of the reef crest; and the east zone (fore-reef) consists of spur-and-groove formations. Between ledge zones are not found on the CRT.

Figure 2.2. Habitat delineation on the deep ridge complex (DRC). This area includes large artificial reef structures (playground, china barge, Amaryllis, Mizpah, and Spearman’s barge). The west zone consists of patch reef and sand; ledges consist of cliff walls; the ridge consists of the reef crest; and the east zone (fore-reef) consists of spur- and-groove formations. Between ledge zones consist of sandy bottom.

The ledges are typically found on the landward (west) edge of the reef ridge, and are characterized by steep (1-4 m) cliffs that form numerous overhangs, vertical surfaces, and small caves. The artificial reefs at the Corridor site are included in this category due to their similar vertical/enclosed features. The reef ridge is the shallowest part of the

25 reef, and is characterized by a low-relief landscape pocked with craters, mounds, and small discontinuous ledges. From the eastern edge of the reef ridge, the fore-reef gently slopes seaward, and features numerous prominent, shore-perpendicular hills and valleys

(a.k.a. “spur-and-groove” formations) that descend to sandy bottom. Generally, the ledge/artificial habitats host a high-density of encrusting biota, perhaps due to extended substrate exposure, while the reef top and fore-reef are dominated by soft corals, seafans, and poriferans such as the giant barrel sponge (Xestospongia muta) that can better tolerate strong currents and shifting substrate.

Sampling

Six (n=6) sub-adult hawksbill turtles were hand-captured during SCUBA diving surveys on the nearshore reefs of north-central Palm Beach County, Florida, USA between 1-06-09 and 9-23-13. Previously-tagged turtles were specifically sought due to their increased likelihood of extended local residency. After thoroughly cleaning and drying the apex of each turtle’s carapace, a combination of T308 adhesive epoxy (Powers

Fasteners, Inc., New Rochelle, NY) and sonic- weldTM putty was used to attach a Mk10-

AF GPS-linked multi-sensor satellite transmitter (Wildlife Computers, Inc., Redmond,

WA). The turtles were retained on a boat for at least 45 minutes to allow the adhesives to dry, then released at the surface above the capture site. Four (n=4) turtles were captured and released near the northern terminus of the continental reef tract, and two (n=2) at the shipwreck site known as the “Corridor”. The turtles were assigned sequential numerical

ID’s corresponding to each transmitter’s ID (19-24).

The satellite tags were programmed to calculate Argos and GPS coordinates at each surfacing event (approximately 20 per 24 hour period), and to transmit data daily.

Based on battery-life estimates provided by the manufacturer, this configuration maximized data recovery while providing at least one year of expected functionality.

Four tags were retrieved (#‘s 21-24) upon re-capture of the turtles. One was re-deployed after manufacturer rebuild (#24). Data were retrieved via the Argos system through CLS

America, Inc. (Largo, MD) and/or directly downloaded (#’s 21-24) and decoded with

DAP Processor version 3.0 software (Wildlife Computers, Inc., Redmond, WA).

Only GPS coordinates were used for the home range estimates. As suggested by the tag manufacturer, positions assigned a DAP software quality indicator, a.k.a

‘residual’ value higher than 20 were excluded from the analysis. The remaining coordinates were georectified and imported into the appropriate projection using Arcview

10.1 GIS (ESRI, Inc.) software. Once projected, data points were visually inspected, and those deemed impossible or highly unlikely (on land, 10+km away from the study site) were manually removed. The coordinates were grouped by hour, and classified as either

‘diurnal’ (8:00 a.m. - 7:59 p.m. EST) or ‘nocturnal’ (8:00 p.m. - 7:59-a.m. EST). The

Spatial Analyst extension of Arcview 10.1 (ESRI, Inc.) was used to create minimum convex polygons (MCP) and kernel density home range estimates (KDE; 95, 50, and

25% contours) of both the 24 hr data set and the 12 hr day/night data sets individually

(per MacLeod, 2014). By estimating the probability of an animal’s presence or absence within its home range, the 95%, 50%, and 25% contours represent where the turtle is likely to be 95, 50, and 25% of the time, respectively.

The ‘extent’ for each sample was set as the extent of each individual data set, and the search radius (h) or ‘smoothing factor’ for each turtle were calculated by Arcview

10.1 using the quadratic kernel function described in Silverman (1986). The h-values and cell sizes generated for each analysis are shown in Table 2.1.

Table 2.1. Search radii and cell size used for 95% kernel density estimates in Arcview 10.1® (ESRI, Inc.).

Search radii (smoothing factor)/cell size

Turtle All (95%) Diurnal (95%) Nocturnal (95%)

19 84.318/10 53.852/8 69.544/8 20 37.531/4 n/a n/a 21 95.314/11 41.348/5 95.314/11 22 134.748/16 132.825/16 127.706/15 23 113.854/13 113.854/14 57.350/6 24 124.498/15 103.091/12 109.742/13

The contours of the 50 and 95% KDE isopleths were manually traced for 5 turtles

(19, 21-24), and the number of diurnal and nocturnal positions located within and outside the 50% ‘core-use’ isopleth were recorded. LIDAR images of the site’s bathymetry

(Palm Beach County Env. Resources Management) were used to delineate 5 habitat types: east (fore -reef/spur-and groove dominated); reef ridge; ledge, between ledges

(sand), and west (patch reef dominated). The number of positions (total and diurnal) located in each habitat zone were tested for proportional differences within and between individuals using pooled 2-sample Fisher’s exact tests (95% confidence level) using

Minitab 17™ statistical software.

Results

GPS location data were gathered from six (n=6) sub-adult hawksbill turtles (SCL(n-t):

50.0 - 70.6 cm; mean: 59.0±9.1; median 58.2) between August of 2010 and May 2014

(Table 2.2). Deployment duration ranged from 102 - 429 days (mean 286±121), providing between 33 and 2116 (mean 1005, SD±6782) acceptable coordinates (Tables

2.2 and 2.3). Turtle #20 ceased transmitting 102 days after deployment, and provided only 33 positions that met the standards for inclusion, limiting its contribution to the study and the reliability of the home range estimate for this individual.

turtle deploy release location capture substrate deployment SCL(n-t) i.d. date lat/lon depth type duration (cm) (m) (days) 19 9/06/10 26’48’201N 24.4 ship 369 67.7 80’00’961W 20 8/04/10 26’42’250N 18.3 reef 102 70.6 80’00’990W 21 7/31/12 26’42’573N 15.2 reef 357 49.1 80’00’960W 22 7/31/12 26’41’784N 15.2 reef 429 50.0 80’01’112W 23 9/28/12 26’42’940N 16.5 reef 232 61.6 80’01’460W 24 9/23/13 26’47’302N 19.8 ship 226 54.7 80’00’970W mean± 18.2±3.5 286±121 59.0±9.1 SD

total HR (km2) diurnal HR (km2) nocturnal HR (km2)

turtle n MCP KDE95 n MCP KDE95 n MCP KDE95 i.d.

19 637 4.7 0.49 356 2.32 0.23 281 3.09 0.17

20 33 1.1 0.01 13 0.20 n/a 20 0.98 n/a

21 624 5.5 0.51 361 1.97 0.96 263 4.66 0.35

22 2116 19.0 1.12 1126 18.57 1.11 961 8.99 0.67

23 858 13.4 0.46 486 6.77 0.55 401 6.61 0.17

24 1764 16.8 0.35 971 12.6 0.21 793 7.42 0.29

mean± 1005± 10.1± 0.49± 552± 7.1± 0.61± 453± 5.3± 0.33± SD 782 7.3 0.36 418 7.2 0.41 354 3.0 0.21

The home ranges (HRE) estimated by the Minimum Convex Polygon (MCP) method ranged from 1.10 - 19.04 km2 (mean 10.1±7.3). Diurnal HRE’s ranged from 0.2

- 18.57 km2 (mean 7.1±7.2), and nocturnal HRE’s ranged from 0.98 - 8.99 km2 (mean

5.3±3.0) (Table 2.3, Figures 2.3a-e). Though this method did not illustrate the details of within-range habitat use, it included what could have been occasional exploratory movements to nearshore, offshore, or adjacent areas, and had enough resolution to detect a nearly 50% reduction in activity (movement) at night (Table 2.2).

Figure 2.3a.

Figure 2.3b.

Figure 2.3c.

Figure 2.3d.

Figure 2.3e.

The home range size calculated by the kernel density method (KDE95) ranged from 0.01 -

1.12 km2 (mean 0.49±0.36), and largely confined the turtles’ movements to the study site’s 15 - 20 m offshore hardbottom habitats (Table 2.2, Figures 2.3a-e). The 95%

kernel density estimates (KDE95) reduced the MCP HRE’s by an average of 93% (Table

2.2). Turtles 22 and 24 had one continuous 95% isopleth (Figures 2.3b, 2.3e); while turtles 19, 21, and 23 had smaller additional 95% isopleth ‘islands’ adjacent to the primary area of use (Figures 2.3a, c, and d). Turtle #20 is not represented due to the low sample size for this animal. When the coordinates were temporally segregated, the

2 diurnal and nocturnal KDE95 HRE’s ranged from 0.23 -1.11 km (mean 0.61±0.41), and

0.17 - 0.67 km2 (mean 0.33±0.21) respectively (Table 2.2), again showing a nearly 50% reduction in the area occupied by the turtles at night.

The turtles tracked on the continental reef tract (CRT) showed similarly shaped home ranges that tightly outlined the reef ridge (Figures 2.3c, d, and e). The northern half of turtle #21’s home range overlapped with the southern half of turtle #23’s home range, and also overlapped, though to a lesser degree, with turtle #22’s range to its south

(Figure 2.4a). Conversely, the two turtles that were captured at the off-reef shipwreck site (a.k.a the “Corridor”) to the north of the Inlet (turtle #‘s 19 and 24) showed very differently shaped home ranges, but extremely high overlap near the capture site itself

(Figure 2.4b). In this case, turtle #19 had a 30% larger home range than #24 and exhibited considerably more extensive use of the natural reefs to the north and east of the artificial reef site

Figure 2.4a.

Figure 2.4b.

2 Core-use areas (KDE50 and KDE25) averaged 0.03±0.03 and 0.01±0.004 km respectively, and were roughly centered within each turtles’ home range. (Table 2.4;

Figures 2.3a-e). Turtle #21 had two KDE50 isopleths, the southern of which was considerably more populated (312 coordinates vs. 54) and used for comparison

core-use area (km2)

turtle i.d. KDE50 total KDE50 diurnal KDE50 nocturnal KDE25

19 0.02 0.03 0.005 0.002

20 0.004 ------

21 0.07 0.12 0.03 0.01

22 0.06 0.09 0.02 0.01

23 0.04 0.05 0.02 0.01

24 0.01 0.01 0.01 0.003

mean± 0.03±0.03 0.06±0.04 0.02±0.01 0.01±0.004 SD

with the other turtles (Figure 2.3d). The areas within the KDE50 isopleths were populated by a roughly equal number of day vs. night positions (46.1±2.1% and 53.9±2.1% respectively), however there was a bias toward daytime positions (68.1±2.7%) in the

areas contained between the 50% and 95% contour lines (Figure 2.5). The KDE25

isopleths were centered within the KDE50 isopleths, and located very near sites that can provide shelter, e.g. shipwrecks and ledges (Figures 2.3a-e). Approximately 40%

(41.0±3.1) of the coordinates within these very small core-use areas were diurnal (Figure

2.5).

proportionof diurnal coordinates (%) 0 50-95 50 25 KDE contours

Figure 2.5. Mean proportion (%) of diurnal coordinates located in the area between the KDE50 and KDE95 isopleths, within the KDE50 isopleth, and within the KDE25 isopleth for 5 turtles.

Overall, the size of the home ranges increased with deployment duration and number of coordinates. However, home range did not increase with straight carapace length (Figure 2.6). It is evident that the low number of coordinates available for the analysis underestimated turtle #20’s home range. Unlike the other HRE’s, the 50% nocturnal kernel density estimates did not increase with deployment duration nor number of coordinates (Figure 2.6).

2500 80

70 R2 = 0.4446 2000 60

50 1500

R2 = 0.8984 40

1000

SCL(n-t)(CM) # coordinates #

20 500 10

0 0 0 0.2 0.4 0.6 0.8 1 1.2 Home range (KDE) (km2)

Coordinates per three habitat “zones” (east of ledge, ledge and ridge, and west of ledge) were determined for the turtles (#’s 21-23) residing on the Continental Reef Tract.

The extent and number of coordinates found in these zones in each turtle’s ‘range’ are shown in Table 2.5.

Table 2.5. Coordinates per three habitat zones for three turtles (#’s 21-23) residing on the Continental Reef Tract, and the area (extent) of each in km2.

Turtle 21 22 23 # positions (km2) # positions (km2) # positions (km2) East 254 4.62 998 5.44 211 3.61 L&C 290 0.29 845 0.29 497 0.17 West 79 6.71 338 8.43 177 5.41

There was a disproportionately high number of coordinates per area found in the ledge and ridge zone; it contained 46.5, 38.7, and 56.2% (mean 47.1%) of coordinates for turtles 21-23 respectively, though it constituted an average of only 2.0% of the total area covered by each turtle.

Approximately half of the diurnal coordinates for turtle #’s 21 and 22 (46.8 and

49.7% respectively) and a quarter of turtle # 23’s coordinates (25.1%) were located above the eastern portion of the reef ridge in the spur-and-groove formations (Figures 2.7; 2.8;

2.9a-c; 2.10).

east 11.1 14.8 L & R w est 32.3

46.8

42.1

Turtle #21 day 52.3 Turtle #21 night

east 16.7 L & R 13.8 w est

40.5 49.7

33.2 Turtle #22 day 45.5 Turtle #22 night

east L & R 16.7 22.7 25.1 22.3 w est

Turtle # 23 day Turtle #23 night 52.1 60.8

Figure 2.7. Proportion of day and night coordinates located east of the reef ridge (spur-and-groove); at the ledge/ridge (L & R); and west of the reef ridge (patch reef) for turtle #’s 21-23.

Figure 2.9a.

Figure 2.9b.

Figure 2.9c.

Figure 2.10. Turtle #23. Diurnal (8:00 a.m. - 7:59 p.m. EST - yellow dots) and nocturnal (8:00p.m. – 7:59 a.m. EST – blue dots) coordinates per habitat type.

The smallest proportion of diurnal coordinates for turtles 21 and 22 were located in the patch reef zone west of the main ledge (11.1 and 16.7%, respectively), but nearly evenly split between the patch reef (22.7%) and the spur-and-groove (25.1%) zones for

48 turtle # 23 (Figure 2.10). The remainder of the diurnal coordinates for each turtle were associated with the high-relief ledge/ridge zone, including just over half for turtle #23

(52.1%) (Figure 2.10). Pair-wise comparisons revealed significant differences within and among turtles in their use of these habitat zones (Table 2.6).

turtle 21 22 23

W L&C E W L&C E W L&E E

21 W ±1.72/ ±3.72/ 0.085 0.000 L&C ±13.09/ ±3.52/ ±3.66/ 0.000 0.001 0.000 E ±11.20/ ±2.06/ ±2.18/ ±7.01/ 0.000 0.046 0.032 0.000 22 W ±3.03/ 0.003 L&C ±17.26/ ±8.81/ 0.000 0.000 E ±21.67/ ±4.69/ ±11.23/ 0.000 0.000 0.000 23 W

L&C ±15.65/ 0.000 E ±1.97/ ±13.87/ 0.058 0.000

During the nighttime hours, the proportion of locations increased in the ledge/ride zone 10.2%, 12.3%, and 8.7% (mean 10.4%) for turtles 21, 22, and 23, respectively, and decreased in the fore-reef zone by 14.5% (turtle #21) and 9.2% (turtle #22), and 2.8%

(turtle #23) (mean 8.3%) (Figure 2.7).

Discussion

Over the years, various methodologies have been applied to estimate hawksbill home ranges, but none with data generated from GPS-quality satellite telemetry. The results of this study mirror previous estimates that suggest sub-adult hawksbills heavily utilize small areas of reef habitat (≃ 1 km2), indicating this is a fairly ubiquitous natural history trait for this species (Table 2.7).

Table 2.7. Estimated foraging home ranges of hawksbill turtles (Ei) in Florida and the Caribbean. MCP= Minimum Convex Polygon method; KDE= Kernel Density Estimate.

Location sample estimated method reference notes size foraging home range Dom n=3 2,455-10,071 satellite Hawkes et. adult/ Republic km2 tracking/ al. 2012 internesting MCP Ei Cayman n=57 2-2080 m linear dist. Blumenthal sub-adult Ei Is. mean 545; SD bet. captures et.al. 2009 ±514 Puerto Rico n=87 0.00-5.22 km linear dist. van Dam sub-adult Ei mean 0.45 km bet. captures and Diez, 1998 Puerto Rico n=3 0.07-0.14 km2 sonic van Dam sub-adult Ei tracking and Diez, 1998 Mexico n=1 0.021-0.124 MCP/KDE Cuevas and sub-adult Ei km2 Maldonado 1999 Dry Tortugas n=3 9.2-21.5 km2 satellite/ Hart et. al., sub-adult Ei acoustic 2012 tracking/ KDE Dom n=34 0.06-1.55 km linear dist. Leon and sub-adult Ei Republic (0.36 mean; bet. captures Diez 1999 SD ±0.32) BVI n=45 mean 0.5 km linear dist. Hawkes et. juvenile/sub (SD±1.1) bet. captures al. 2014 adult Ei

Palm Beach n=73 0-9308 m linear dist. Wood et. al. sub-adult Ei County, USA (mean 1345; bet. captures 2013 SD±2302)

Palm Beach n=6 0.00-1.12 km2 satellite THIS sub-adult Ei County, USA (mean 0.52, tracking/ STUDY SD±0.40) MCP, KDE

Aside from the possibility of occasional forays to inshore and offshore waters, the turtles studied in Palm Beach remained very closely associated with the study site’s 15-

25 m hard-bottom reef habitats. This underscores the value of supplementing minimum convex polygons with kernel density estimates to acquire a more meaningful assessment of habitat use. Care should be taken, however, to recognize differences in home-range estimates that can result from the varying derivations of the “smoothing factor” (h) during the kernel density calculations. Known also as the “search radius”, or

“bandwidth”, this variable may have a profound effect on the resulting home range estimates. Each point in the dataset is assigned a three-dimensional volume which is highest at the point itself, then diminishes to zero at some circular distance, known as the search radius for that point. The ‘volumes’ of all the points within a certain area, or raster cell, are then summed where they overlap at the cell center. The resulting kernel calculation can depend on how ‘smoothly’ the volume of the cells account for areas of higher or lower point densities. In this study, where a large number of positions were mostly clumped together, a search radius was chosen that resulted in one or few, rather than multiple and fragmented 95% isopleths. Because the turtles are traveling throughout the area between surface times, the areas between the fragments should, realistically, be included in the home range calculations. Alternatively, a smaller search radius that produces multiple 95% isopleths may reduce overall home-range size estimates, but be more useful in answering fine-scale habitat use questions.

As sub-adults, the extent of the turtles’ daily movements should primarily reflect food availability (Rincon-Diaz et. al. 2011), rather than courtship and/or reproductive behavior. Spongivory is common in Caribbean hawksbills (reviewed by Bjorndal, 1997), and seems to dominate the diet of those in Palm Beach as well (L. Wood, unpub data).

Though a complete list of dietary items is unavailable from this site, known prey items

52 such as the loggerhead sponge Spheciospongia vesparium, the chicken liver sponge

Chondrilla caribensis, the giant barrel sponge Xestospongia muta, and the leathery barrel sponge Geodia sp. are commonly found at these depths.

Collectively, the home ranges increased proportionately with the number of coordinates acquired for each turtle, suggesting that data volume may have influenced the resulting home range estimates. This trend has occurred in other studies as well (Hart et. al 2012; Seminoff, et.al. 2002). In this study, this relationship was strongly influenced by the two turtles that provided the smallest and largest datasets (#‘s 20 and 22 respectively).

The other four turtles had very similar HRE’s, though one of them (# 24) collected at least twice the number of coordinates of the other two (#‘s 21 and 23). However, the home range estimates among all six turtles did not increase with carapace length, indicating that increased residency time does not coincide with continual spatial expansion. If it had, larger turtles (presumably residents of the site longer) would be expected to have proportionately larger areas of activity. It is likely that the HRE’s for the turtles with fewer coordinates would gradually increase to more closely match those with larger data sets as the gaps between 95% contour ‘islands’, as seen with turtles

19,21, and 23, become filled in with additional coordinates, which represent surfacing events, and become subsequently more strongly represented in the overall area calculation. Conversely, the increased HRE generated from larger data sets could result from an overshadowing of small pockets of within-range core-use, and become exaggerated by the accumulation of coordinates that meet the reported accuracy requirements for inclusion, but still contain moderate to low positional error. To ensure the reliability of the study’s HRE’s based on deployment duration, Seminoff et.al. (2002)

53 determined that juvenile green turtles (n=12) took less than 100 days to occupy 100% of each’s calculated home range, based on between 16 and 61 (mean 37) coordinates per turtle. Therefore, it is likely that the home ranges reported for the deployments exceeding

200 days (600+ coordinates) in this study are reasonably accurate (turtle #’s 19, 21, 23, and 24), and perhaps even over-estimated in turtle #22 (429 days; 2116 coordinates), given the particular smoothing factor ‘h’ used in the analysis.

This trend, however, was not seen in the nocturnal 50% kernel density (KDE50) estimates; all turtles (with the exception of turtle #20), occupied areas measuring less than .03 km2 at night, regardless of the number of positions in the analysis (Figure 2.6).

Moreover, the KDE25 isopleth for each turtle was nearly centered within the KDE50 contours, further shrinking the size of the core-use areas to less than .01 km2. This consistency reflects the remarkably high fidelity these turtles have to specific sites within their overall range.

Hawksbills are known to become largely inactive at night (Hart, et. al. 2012,

Blumenthal, et. al. 2009, van Dam and Diez 1997), and to retreat to refuges (rock outcroppings, coral heads, etc.) during times of diurnal inactivity (Blumenthal, et. al.

2009, Houghton et. al., 2003, Proetti et. al. 2012) (Figure 2.11).

Figure 2.11. Sub-adult hawksbill sleeping under a ledge at night in Palm Beach. Photo courtesy of Andrea Whitaker.

The cover of underwater structures creates low-light, multi-dimensional micro- habitats, provides refuge from currents and predators, and potentially extends turtle dive times by counteracting mild positive buoyancy at depth, a.k.a. “assisted resting”

(Houghton et. al 2003). This study site lacks coral heads, and relatively few sizable caves/caverns are found on the crest, patch reef, or seaward “spur-and groove” slope of the reef. The hawksbills tracked in this study consistently returned to structurally complex, cave-forming core-use areas throughout both the day and night hours. Two turtles (# 19 and 24) centered their activity around an artificial reef site known locally as the “Corridor”; which consists of several shipwrecks and rubble piles (Figures 2.12;

2.13).

Turtle # 21‘s area of core use centered around an east-west cut in the reef known locally as the “Trench”, which was created many years ago to accommodate communication cables (Figure 2.8). Turtle #22‘s core-use area centered around a prominent landmark

57 known as “Ron’s Rock”, which features a large boulder that separated from the western facing edge of the reef, and turtle #23 centered its activity around a large overhang near the northern end of the Breakers Reef tract (Figures 2.9; 2.10a and b). The fidelity these turtles maintain to these particular sites may strongly influence their daily movement patterns, and significantly frame the shape and extent of individual foraging ranges.

Aside from the six turtles tracked in this study, dozens of additional individuals have also been tagged and repeatedly encountered in the study site (Wood et. al, 2013).

Through 2012, twenty- one other hawksbills were captured on the Corridor wreck site itself, and fifty-six on the Breakers reef tract. Overall, the rates of encounters with previously-tagged individuals increased between 2004 and 2012, while those with untagged hawksbills decreased crossing over at the midpoint in 2008, suggesting that the majority of the individuals likely to be residing in the area have been identified (Figure

2.14).

tagged hawksbills 1.2 untagged hawksbills Linear (tagged hawksbills) 1 Linear (untagged hawksbills)

0.8

0.6

0.4

0.2 sightings/hr. (SCUBA only) sightings/hr.

0 2004 2005 2006 2007 2008 2009 2010 2011 2012 year

Figure 2.14. Rates of encounters (sightings/hr. on scuba) with previously tagged study animals vs. encounters with untagged individuals in the study site.

Given similar behavior among the others in the study site, any given hawksbill in the area may directly share resources with at least 10-20 other individuals.

The considerable range-overlap among members of this aggregation suggests that foraging areas are not very strongly defended. Still, aggression among individuals has been documented in both captive and wild settings, indicating some sort of mild territoriality (Sanches and Bellini 1999; van dam and Diez 2000; Blumenthal et. al. 2009;

Wood, pers. obs.). For hawksbills, the extent of the defensible territory may simply be the distance from which a conspecific can be detected, or perhaps ‘tolerated’. Resident turtles are much more likely to encounter one another at or near preferred refuge sites, particularly at night, leading to some degree of either cooperative or defensive action.

Either way, as a space becomes more crowded, some individuals, especially latecomers,

59 will find themselves unable to find the desired cover, and will likely be compelled to move on by more aggressive individuals. Over time, it may be advantageous for the turtles to choose a reliable and familiar ‘home base’ that is shared with conspecifics

(including those of other species) only to the extent that physical space and competition

(tolerance) allow.

In a number of species, including various birds (Eiserer, 1984; Beauchamp, 1999), bats (Lewis, 1995), insects (Finkbeiner et.al. 2012; Pearson and Anderson, 1985), and primates (Anderson, 1998), individuals regularly congregate in a quiescent state known as ‘communal roosting’ (Devries et. al, 1987). The drivers behind this behavior are hypothesized to include thermoregulation (Yom-Tov, 1977; du Plessus et.al. 1994), information sharing (Ward and Zahavi, 1973), foraging efficiency (Caccamise and

Morrison, 1988), and prey dilution/predator confusion (Turner, 1975; Gillette et. al. 1979;

Eiserer, 1984; Finkbeiner et. al. 2012). In the case of ectothermic and otherwise non- social hawksbill turtles, predator avoidance/prey dilution emerges as the most likely benefit for individuals seeking nightly refuge in common areas, leading to some level of competition for the most protective locations within them. Southeast Florida is known as a foraging ground and migratory corridor for numerous shark species, including tiger sharks (Galeocerdo cuvier) which are known predators of marine turtles (Figure 2.15).

Figure 2.15. Evidence of shark predation on a hawksbill turtle in northern Palm Beach County, Florida. Photo courtesy of Terri Roberts.

During times of inactivity, especially at night, the more quickly a turtle can return to refuge after each surfacing requirement, which occurs roughly hourly (Wood, unpub data), the presumably less exposed it would be to predation. Given the persistent and often strong northerly current in the study site, a quick return to an established location would be advantageous over repeatedly seeking out unfamiliar, potentially already- occupied refuges.

It is evident that the turtles extend their range during the day into the patch reef and spur-and-groove formations, likely reflecting foraging expeditions. Still, however, the near- equal proportion of diurnal and nocturnal coordinates that occur within the core-use

areas (both KDE50 and KDE25) (Figure 2.5) suggests that the turtles make repeated diurnal visits to these areas, which may be for food (foraging is commonly observed at wrecks,

61 rubble, and ledge walls) but may also serve to reinforce some level of dominance over each turtle’s preferred ‘roost’, all located within each turtles the ‘ledge and ridge’ habitat zone. Even though the ledge and ridge portion of the reef constitutes only a tiny fraction

(2%) of the area covered by the turtles, the turtles showed a disproportionately strong presence in these areas based on the number of coordinates located per habitat zone

(Table 2.4), further reflecting the importance of areas most likely to provide refuge.

Consistent patterns of movement within a home range imply spatial learning and memory

(Shettleworth, 2001), and repeated behaviors are likely to reflect prior experiences.

Coincidentally, among the three turtles tracked on the Breakers reef (21-23), each’s

KDE95 isopleth terminated at another’s core-use area, where a higher probability of interaction between them would be expected. Though perhaps for other reasons, there is a conspicuous lack of hawksbill turtles under 40 cm SCL in this study site (Wood et. al,

2013), which could be a competitive disadvantage if alternative refuges are unavailable.

The home range sizes among this hawksbill aggregation are comparable to those reported from other Caribbean sites (Table 2.6), as are their abundance and growth rates

(Wood et.al., 2013), further suggesting that the reefs of Palm Beach, though not formerly considered important hawksbill habitat, are strongly supportive of their development, and worthy of continued study and targeted conservation measures. Understanding where hawksbills are most likely to be found can greatly streamline management strategies in a number of ways. Though direct harvest is strictly prohibited in U.S. waters, these turtles are impacted by a number of anthropogenic effects such as discarded fishing line, boat propeller strikes, and the pervasive degradation of the reef habitat resulting from rapid coastal development. Their consistent presence on the 15-25’ deep reef complex

62 underscores their reliance on it for both food and shelter. Since covered refuges have emerged as important environmental features that may strongly influence their abundance and distribution, a carefully planned artificial reef program, similar to Palm Beach

County’s, may augment hawksbill recruitment in areas where similar features are lacking.

Additionally, focusing on areas where cover is available, particularly after dark, could considerably increase the efficiency of future in-water surveys and/or mark-recapture studies. This study provides the most detailed assessment to date concerning the home range and movements of sub-adult hawksbill turtles, and underscores the value of increasingly accurate remote sensing for marine turtle research. Though comparatively costly, transmitters equipped with GPS capabilities can provide the levels of detail that wildlife managers need to assign critical habitat and target conservation resources. In the case of sub-adult hawksbills, the small home ranges they appear to occupy facilitates transmitter retrieval/refurbishment/re-use, potentially providing a less-costly approach to increasing sample sizes through turtle recapture.

Though the sample size used for this study was relatively small, the turtles tracked showed considerable consistency in their patterns of movement. As randomly-chosen individuals among a resident population, their behavior was likely representative of most of the sub-adults residing the area. The results are further strengthened by the large data sets retrieved from the transmitters, enabling an unusually high-resolution analysis of the finer details of within-range core-use behavior, which were also quite consistent among these individuals. Still, however, the results of this study are limited to a small geographic area on SE coast of Florida, and to just a few turtles. The extent of hawksbill distribution in the rest of the region remains unknown, and there could be considerable

63 differences in home range size and shape among aggregations elsewhere along the SE

Florida coast. This study is also limited in that it only broadly categorized habitat types by tracing visible bathymetric features, which do not reflect the corresponding benthic community structure. In the future, turtle movement data can be integrated with increasingly refined benthic habitat maps to provide more detail on how additional biotic and abiotic features may influence the resulting spatial and temporal patterns of movement in this study site and elsewhere. Hawksbills, like other marine turtle species, have complex life cycles that are not always easily interpreted to students, conservationists, and vital stakeholders, especially at the less familiar juvenile and sub- adult life stages. The continued and expanded use of modern remote sensing tools and the geo-rectified maps they create have dual value as both effective research techniques and powerful outreach tools.

CHAPTER 3: FORAGING BEHAVIOR

Introduction

Direct observations of organisms in wild settings are fundamental to behavioral research. However, ethological studies of marine vertebrates, particularly at depths exceeding 15 meters, are hindered by a host of logistical challenges (Hooker and Baird,

2001). Wide-ranging, fast-moving, and/or deep-diving marine animals are often difficult to find, and even more difficult to observe for extended periods of time, leaving large gaps in our understanding of many basic natural history traits.

In the case of marine turtles, researchers have relied on various remote sensing technologies such as time depth recorders (TDR), ultra-sonic tracking, multi-sensor archival tags, and even inter-mandibular angle sensors to infer in-situ sea turtle habitat use and behavior (Blumenthal, 2009; Wilson et al., 2008; Hochscheid et al., 2005;

Houghton et al., 2008). As revealing as the data are, direct observation remains the only certain way to obtain the details of important in-situ behavioral patterns and environmental interactions, and can potentially provide a much stronger basis for behavioral research and conservation measures (Seminoff, et. al. 2002, Houghton et. al.

2003, Schofield et. al. 2006, Dunbar et. al. 2008).

Hawksbill turtles (Eretmochelys imbricata) are globally-distributed apex coral reef predators that are known to feed primarily on sponges (Meylan, 1988; Hill, 1998; Leon

65 and Bjorndal, 2002). They occur throughout the Caribbean region, the east and west coasts of Central and northern South America, and northward to the Gulf of Mexico,

Florida, and Bermuda (Witzell, 1983; Lund 1985; Meylan and Redlow, 2006). They are listed as an Endangered Species under the United States Endangered Species Act, and

Critically Endangered worldwide by the IUCN (Baille and Groombridge, 1996). Still, however, basic behavioral data are lacking for this species throughout its range

(Blumenthal et al., 2009; Cuevas, 2007), especially in Florida (Meylan and Redlow,

2006).

In response, a number of studies on movements, dive profiles, diet selection, and in-water behavior have improved our understanding of Caribbean hawksbill ecology

(Leon and Bjorndal, 2002; Cuevas et. al. 2007; Velez-Zuazo et. al. 2008; Blumenthal et. al., 2008, 2009; Rincon-Diaz et. al. 2011), and several others have assigned broad behavioral categories such as swimming, feeding, resting, and surfacing to quantify in- situ sea turtle activity (van Dam and Diez 1997, Houghton et. al. 2003, Schofield et. al.

2006, Dunbar et. al. 2008, Blumenthal et. al 2009b, Proietti et. al. 2012). However, none have focused on the process of prey acquisition itself, which for hawksbills, appears to be focused on a fairly narrow range of marine sponges (Leon and Bjorndal 2002, Rincon-

Diaz et. al. 2011).

Spongivory is highly unusual among vertebrates (Burns and Ilan, 2003), and further, though hundreds of sponge species are found in the Caribbean region, only a few are chosen by hawksbills as food (Meylan, 1988; van Dam and Diez, 1997; Leon and

Bjorndal, 2002, Rincon-Diaz et. al. 2011). Though empirical techniques such as stomach lavage and fecal analysis can reveal prey choice, they do not address search

66 behavior/effort, prey recognition, capture rate, or incidental effects the foraging activity may have on the surrounding community. Poriferans can be dangerously well-protected by chemical and physical defenses (Sara and Vacelet, 1973), potentially requiring the turtles to carefully discriminate among the many species they encounter.

In order to establish direct links between what appear to be “appetitive” behaviors

(Tinbergen 1951) with the actual act of prey consumption, the relative frequency of each behavior leading to the focal act of ingestion can be measured and scored (Bakeman and

Gottman 1986, Nowacek 2002). The more closely linked a behavior is to the end result should be inverse to its frequency, and increasingly dependent on the occurrence of the prior behavior in the sequence (Nowacek 2002). A generalist, for example, might employ a relatively short sequence of behaviors leading to a higher rate of acceptance, while a specialist might employ a longer sequence of behaviors leading to a higher rate of rejection per area or item explored. Preliminary observations suggest that hawksbills in

Southeast Florida waters (USA) are discriminating feeders that utilize a predictable series of exploratory behaviors prior to prey ingestion.

Advances in SCUBA technology such as enriched air mixes and closed-circuit breathing devices now allow for considerably more efficient and extended access to moderate depths (15-40 m), and the decreased size and increased resolution/data capacity of underwater video cameras have greatly enhanced the practicality of recording in-water behavior. Though all daily activities are important to the animal in one way or another, no other routine daily behavior involves more direct physical interaction with the micro- environment than foraging, which in the case of hawksbill turtles, is reputedly playing an important role in reef ecology (Leon and Bjorndal 2002). In this study, an ethogram was

67 developed to explore the relationships between the behaviors that lead to prey consumption among wild hawksbill turtles within the contexts of their natural surroundings. This study was possible due to an unusual complacency toward humans among resident hawksbill turtles (presumably a side-effect of repeated encounters with recreational divers), resulting in numerous mid- to close-range recordings of a suite of behaviors, particularly those related to foraging. These recordings have begun to reveal insights concerning search behavior, prey choice, and habitat use, which, can fill important gaps in our overall understanding of this species, and facilitate urgently needed regional recovery efforts (Mortimer and Donnelly 2007, Blumenthal et al., 2009, Foley

2010).

Methods

Hawksbill turtles were filmed on the reefs (15-25m in depth) of central and northern Palm Beach County (Florida, USA) during daytime SCUBA dives. Though various camera makes and models were used, the majority of the footage was recorded with a Canon Powershot SD960 IS Digital ELPH in an Ikelite, Inc. (Indianapolis Indiana,

USA) underwater housing. No lights were used during the filming. Observers not accompanying the PI were carefully instructed to be cognizant of any turtle’s reaction to their presence, and avoid individuals that exhibited defensive or evasive behavior.

Once filming, the observer adjusted his or her distance from the turtle based on its reaction to their presence, i.e. backing away by several meters when the turtle was swimming, and moving closer when it became engaged in foraging activity. When uninterrupted foraging behavior was observed, the camera was positioned as close to the

68 point of prey consumption as possible. Tag numbers, if present, were recorded. Filming sequences were terminated when either the observer was required to continue or terminate his/her dive, or when the turtle actively swam off. Small samples of prey items were opportunistically photographed, collected, and identified by general appearance and/or microscopic spicule morphology.

Videos were viewed frame by frame using Quicktime Player (Apple, Inc.), during which behavioral transitions were scored as pairs from the y-axis behaviors (rows) to the x-axis behaviors (columns) of a transition matrix (appendix 1). The biotic and abiotic features of the turtles’ surroundings, the characteristics of targeted prey items, and various behavioral subtleties not revealed within transition matrices were noted by time code for each sequence. Behavior categories were defined as follows (see Table 3.1):

Scan: slow swimming or ‘walking’ (flippers in contact with substrate); side-to-side head movement close to the substrate; rapid ocular movement; generally continuous forward momentum (Figure 3.1). Target: forward motion stopped; head often sharply angled down when on horizontal surfaces; rhamphotheca pointed directly at object (Figure 3.1).

Nudge: rhamphothecal (closed-mouth) contact with item or substrate (Figure 3.1). Bite: open mouth contact with item, not necessarily resulting in detachment of item (Figure

3.1). Chew: detachment of item, followed by at least two mastications (Figure 3.1).

Swallow: item ingested; ventral throat contraction observed. Transition matrices were summarized and lag sequential analysis (Friendly, 2001, McElroy et. al. 2011) was used to calculate the frequency of defined behaviors at each stage in a series of behavioral transitions, or “lags” prior to a focal act, which in this case was swallowing the food.

Table 3.1. Ethogram of hawksbill turtle foraging behavior.

Behavior Description

Scan slow swim or crawl at or near substrate with forward movement; side-to-side head motion focused on substrate

target forward momentum stopped; head angled to focus on object nudge closed mouth, rhamphothecal contact with object

Bite open-mouthed contact with object

chew item separated from substrate; at least 2 mastications

swallow ingestion of masticated material; throat contraction

Results

Thirty videos totaling 8469 seconds (range 30-1304 sec) were evaluated. A total of

1242 behavioral transitions were recorded (Table 3.2). Sequential transition frequencies are shown in Table 3.3 and Figure 3.2.

scan target nudge bite chew swallow total scan 0 247* 11 1 0 0 259 target 99 0 95 216 0 0 410 nudge 64 5 0 38 0 0 107 bite 65 62 1 0 133 0 261 chew 13 34 2 0 0 78 127 swallow 20 57 1 0 0 0 78 1242

scan target nudge bite chew swallow scan 0 0.95* 0.043 0.0039 0 0

target 0.24 0 0.23 0.53 0 0

nudge 0.60 0.047 0 0.36 0 0

bite 0.2 0.2 0 0 0.51 0

chew 0.10 0.27 0.016 0 0 0.61 swallow 0.26 0.73 0.019 0 0 0

Aside from the onset of the feeding sequence where ‘target’ is the primary activity that follows ‘scan’ (95%), no other consistent step-wise sequence leading to prey consumption was found. Target led to any of three options; returning to scanning (24%), investigating further with nudging (27%), or transitioning straight to a bite (47%).

Nudging occasionally led to a bite (36%), but usually transitioned back to scanning

(60%), and bites only resulted in chewing about half (51%) of the time. Once the item was separated from the substrate and in the turtles’ mouth, chewing resulted in ingestion a slight majority of the time (61%), but otherwise mostly transitioned back to targeting

(27%). After swallowing the item, the turtles usually transitioned back to targeting

(73%), often the same item, or moved on to continue scanning (26%).

The cumulative proportion of each behavior performed is shown in Figure 3.3 and

3.4.

% Occurrence % 10

0 TA NU BI CH SW Behavior

Figure 3.3. Frequency of six behaviors leading to and including prey ingestion. TA=target; NU=nudge; BI=bite; CH=chew; SW=swallow.

80 70 60 50 40

30 injestion (%) injestion 20 10

Frequency of behaviors leading to to leading behaviors of Frequency 0 TA NU BI CH Behavior

Figure 3.4. Frequency of each behavior leading to the focal act of food ingestion. TA=target; NU=nudge; BI=bite; CH=chew; SW=swallow.

Overall, a gradual decrease in the frequency of behaviors was observed over the progression of the sequence leading to ingestion. ‘Scan’ is not included because ‘target’ is the behavior that initiates the feeding sequence.

When plotted against video duration, the number of ‘targeting’ and ‘swallowing’ behaviors both increased, but at much different rates. As would be expected of sequences that only record foraging behavior, the near-linear relationship (R2=0.772) between video duration and targeting behavior reflects a fairly steady and continuous search effort during foraging bouts. In contrast, the number of items swallowed increased only slightly among the same video sequences (R2=0.201), demonstrating a low rate of return on foraging effort (Figure 3.5).

80 R2 = 0.7719 70 swallow target 60 50 40 30 2 20 R = 0.2006

frequency of behavior frequency 10 0 0 200 400 600 800 1000 1200 1400 video duration (sec)

Figure 3.5. Frequency of first (target) and last (swallow) behaviors per video duration.

In situ Observations

Aside from surfacing ascents, the hawksbills observed did not appear to exploit any part of the mid-water column. The turtles maintained neutral- to slightly- positive buoyancy at the bottom, and often used the tips of all four flippers to gently push off of the substrate in an alternating ‘walking’ gait when moving slowly over the reef. In exposed areas such as the reef top and slope, there was a preference (75% of the foraging sequences) for facing into the prevailing current while searching for prey. Fish were associated with hawksbill foraging in a minority of the videos (7 of 30), and were represented by Spanish hogfish (Bodianus rufus), queen angelfish, (Holocanthus ciliaris), and juvenile wrasses of the Family Labridae.

When engaged in uninterrupted searching behavior, the turtles typically kept their heads angled down with the eyes focused forward, mouth slightly opening and closing, and the rhamphotheca within inches of, and often making contact with, the substrate

(a.k.a. “nudging”). Considerable effort went in to searching for concealed or semi- concealed prey, which required relatively slow forward movement and the close inspection of holes, small crevices/depressions, and small patches of accumulated sand.

In patches dominated by a high-density of tall (0.5+ m) octocorals (e.g. sea rods and whips, sea fans, etc.), the turtles remained close to the substrate by pushing through and over the dense coral cover, apparently not deterred by the stinging cells of the various benthic anthozoans and hydrozoans they made contact with. The turtles often paused to inspect around the bases of vase (Callispongia sp.) and barrel (Xestospongia sp.) sponges. Open-mouthed scraping of rock surfaces was common. In some cases, the turtles used their mouths to deliberately grasp and overturn rocks to gain access to their

75 underside or the substrate beneath. Small patches of the reef with thin (2-6 cm) layers of sand were closely examined, and often bites reaching several cm deep into the substrate resulted in mouthfuls of well-concealed prey, which in many cases appeared to be (by color and oscular arrangement) young encrusting forms of the loggerhead sponge S. vesparium. Pushing upward away from the substrate with the front flippers was often required to separate mouthfuls of leathery-textured sponges. Mouthfuls were thoroughly masticated using multi-directional lower mandible movements during which sponge fragments and biotic and abiotic debris (e.g. sand, pebbles, algae, hydroids) were separated and rejected. Often, if an item was eventually ingested, it was only a small proportion of the original mouthful. It was common for the turtles to take several bites into the prey’s newly exposed inner tissue before moving on; and though some were fragmented or displaced, no one individual sponge was fully consumed. On reef ledges and artificial reefs (e.g. scuttled vessels, concrete debris etc.), turtles were seen actively seeking prey and scraping small bites from vertical and underside surfaces.

Hawksbills were observed consuming the chicken-liver sponge Chondrilla caribensis (Demospongiae:Chondrosida: Chondrillidae); encrusting forms of the loggerhead sponge Spheciospongia vesparium (Demospongiae: Hadromeridae:

Clionaidae); and the giant barrel sponge Xestospongia muta (Demospongiae:

Haplosclerida:Petrosiidae).

Discussion

The dominance of sponges in the diet of Caribbean hawksbills has been well- described (Meylan, 1988; Bjorndal, 1997; Blumenthal, 2009; Rincon-Diaz, 2011), and

76 though this study did not seek to compile a complete list of prey items consumed by hawksbills throughout the study site, a narrow selection of poriferans of the class

Demospongiae were the only items ingested during the observations. Although poriferan diversity and abundance is quite high in this area (100+ species), most sponge taxa were ignored or rejected as food sources, suggesting they likely have some lesser degree of palatability.

During foraging bouts, the behaviors that led to prey ingestion were typical for grazers seeking sedentary food. However, the close scrutiny of the substrate and each item prior to ingestion suggests that the turtles were using a highly exploratory strategy to identify and consume specific prey items, many of which were fully or partially concealed by sand, epibiota, rocks, or within crevices. As opposed to what would be expected of a non-discriminate feeder, a very small proportion (<10%) of the items initially investigated by the turtles ended up being consumed. Overall, there was close to a 50/50 chance that an item was rejected at each lag leading to the focal act of swallowing; i.e. about half (53%) of the items they targeted received a bite, about half of those bites (51%) resulted in something to be chewed, and only a little better than half

(61%) of those items were swallowed (Table 3.3). It was common, however, for the turtles to take multiple bites at the same item as evidenced by the high rate (73%) of

‘target’ behavior that immediately followed swallowing (Table 3.3), and the weight of the

‘swallow-target-bite-chew-swallow’ loop that largely excluded a return to the exploratory nudge (Figure 3.2). The evidence suggests that the turtles, through multiple stages of scrutiny, ensure the dietary inclusion of only a narrow range of prey items, and once identified, take repeated bites of the chosen item before moving on, leaving it damaged,

77 but not necessarily fatally. Differentiation was found between ectosomal and choanosomal tissue layers in the sponges A. varians and Geodia ssp, (known Caribbean hawksbill prey items), creating non-random distribution of chemical and structural defenses (Hill 1999, Hill and Hill 2002). Presumably, the best defenses would be allocated to parts of the sponge most likely to be encountered by predators (Rohde and

Schupp 2012). Indeed, the hawksbills observed in this study did appear to seek exposed choanosome of target species, including the giant barrel sponge X. muta, and were frequently seen feeding on irregularly-shaped, encrusting/concealed forms of S. vesparium, which may have been subject to repeat hawksbill cropping. Recent satellite tracking data from hawksbills in the area reveal small (≃1 km2), long-term overlapping home-ranges, in which certain preferred specimens could be re-encountered fairly frequently, or perhaps even specifically sought for some measure of increased nutritional value.

It is well-established that marine turtles are equipped with complex optic visual systems that include the capacity to discriminate colors (Levenson et. al, 2004; Eckert et. al. 2006), as well as olfactory systems to perceive chemical cues (Manton et. al, 1972,

Grassman and Owens, 1982). Though currently not believed to be involved in foraging, evidence also suggests that sea turtles perceive sound underwater, particularly in low frequencies (O’Hara and Wilcox, 1990; Martin et. al., 2012). Hawksbill sensory systems are not well-studied, but their close phylogenetic relationship with other hard-shelled marine turtles likely provides them with similar sensory capabilities. Though it is impossible to ascertain exactly how an animal processes information in the wild, various

78 behavioral cues can reveal what senses are likely being used for what purpose, and to what extent each may be involved in prey recognition.

Foraging sequences began (i.e. “scan” to “target”) under two general circumstances. When swimming above the bottom by a meter or two, eye movements made it apparent that their attention was alternating between the observer, other divers

(when present), and the bottom itself. When something on the bottom caught their attention, they would often abruptly stop, sharply angle downward, and begin to inspect a patch of substrate more closely. Alternatively, when the turtles were already in contact with and closely inspecting the bottom, both eyes would remain focused forward as the head was moving over the substrate, occasionally turning their attention to the observer or larger surroundings. Both eyes would always remain focused on any item chosen for further investigation (i.e. nudge or bite).

Though these observations strongly imply that hawksbills were visualizing their surroundings at multiple scales, several lines of evidence suggest that olfaction was also playing an important role in finding food. Most striking was the turtle’s ability to locate concealed prey. While the turtles were closely inspecting the substrate (frequently facing into the prevailing current), they continuously performed small jaw movements known as buccal oscillations (Walker, 1959). Common in reptiles and amphibians, variations on these movements are known to increase nasal ventilation without involving the lungs, and likely aid in olfaction (Jorgensen, 2000). Hochscheid et. al. (2005) found similar jaw movements ceased during rest and amplified just prior to feeding in captive loggerhead turtles, and suggested they function in chemoreception during foraging. Several sponge

79 taxa are known to produce odors, some pungent, making olfaction a potentially effective tool for locating concealed items among the rich benthic community.

Once separated from the substrate, considerable time was spent masticating each mouthful, often resulting in the rejection of the majority of its contents. Though perhaps located elsewhere within the buccal cavity, juvenile hawksbill turtles lack taste buds on their tongues (Iwasaki et. al., 1996), so thorough chewing may help detect unwanted items via their texture and further expose the olfactory receptors to chemical signatures associated with preferred prey species.

The frequent “nudging” behavior observed in the hawksbills is similar to the

“touch with muzzle” behavior observed in the four-eyed turtle (Sacalia quadriocellata)

(Liu et.al., 2009), “nose explore” in the desert tortoise (Gopherus agassizii) (Ruby and

Niblick, 1994), and “nose” behavior in various Emydid turtles (Davis, 2009), and probably further facilitates chemoreception. Additionally, applying pressure with the rhamphotheca may serve an additional tactile function for hawksbills by providing information on the consistency or compaction (a.k.a. “hardness”) of an item or area of substrate. Further, applying pressure directly to a sponge could potentially facilitate a surge of oscular flow, perhaps aiding in its identification.

It is likely that some of the turtles being filmed became distracted from foraging by the presence of the observer and other nearby divers. And, since the turtles were filmed only during foraging bouts, it is difficult to estimate the overall intake-per-unit-time spent searching. Nonetheless, close scrutiny of the substrate while searching for food is by nature time consuming, and the small differences in food ingestion observed between short and long video sequences suggests that the turtles probably forage fairly

80 consistently throughout the day to acquire sufficient caloric intake. The long-term use of small areas inevitably results in a familiarity with the terrain, and it is very likely that the turtles become aware of the location of the most productive patches on multiple scales, even to the point of purposefully overturning loose rocks to seek prey underneath or returning to previously-damaged sponges. In the Red Sea, relatively undefended sponges are likely to be found in the nooks, cracks, and slits of structurally complex habitats

(Richter 2001), and Pawlik (1997) proposed that the rapid growth of some chemically- undefended Caribbean sponges compensates for the effects of predation. In Palm Beach, it is apparent that turtles find sufficient populations of suitable prey species within a small, repeatedly-patrolled area, but invest a considerable amount of time and energy to locate and positively identify those they deem most desirable.

In this study, only small ‘snapshots’ of turtle foraging activities were captured on video, and very likely missed important behavioral traits involved in searching and/or choosing food items. Still, detailed in-water behavioral observations hold considerable potential to better understand the basic survival strategies of sea turtles and the species with which they interact (Houghton et. al., 2001; Schofield et.al.. 2006 and 2007;

Blumenthal et.al., 2009). Where possible, researchers should seek opportunities to collect photos and video footage of turtles in their natural environment, which are becoming easier to obtain as small hand-held underwater cameras become increasingly available. These data will broaden our understanding of sea turtle behavior, and in the case of hawksbills, accommodate researchers examining the effects of spongivory on coral reef community structure and/or the adaptations of both the turtles and sponges that have fostered this unusual ecological relationship. Further studies are needed, particularly

81 with longer video sequences, that compare behavior among individuals, and integrate the frequency and/or sequence of behaviors to various biotic and/or abiotic features of the micro-environments in which the turtles are searching. Given standardized methodologies among study sites, foraging strategies, diet, habitat preferences, and social interaction could be compared and contrasted between individuals and locations, leading to a clearer understanding of the role this species plays in the various community types found throughout its range.

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