Satellite tracking of sea turtles released after prolonged captivity periods

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Post-release wide-ranging movements of sea turtles after prolonged 1

captivity 2

3

Mestre, Frederico1, 2

; Bragança, Marco P.1, 3

; Nunes, Antonieta1; dos 4

Santos, Manuel E.4

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1 Zoomarine - Mundo Aquático S.A., E.N. 125, km 65, Guia, 8201-864 Albufeira, 6

Portugal. 7

2Current affiliation: CIBIO-UE - Centro de Investigação em Biodiversidade e Recursos 8

Genéticos/Universidade de Évora, Departamento de Biologia, Núcleo da Mitra, 7002-9

554-Évora, Portugal. 10

3Corresponding author. Email: [email protected], Telf.: +351289560300.

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4Eco-Ethology Research Unit, ISPA - Instituto Universitário, Rua Jardim do Tabaco, 12

nº34, 1149-041 Lisboa, Portugal. 13

This is a preprint version of the following paper: 14

Mestre, F., Bragança, M. P., Nunes, A., & dos Santos, M. E. (2014). Satellite 15

tracking of sea turtles released after prolonged captivity periods. Marine Biology 16

Research, 10(10), 996-1006. URL: http://dx.doi.org/10.1080/17451000.2013.872801. 17

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http://dx.doi.org/10.1080/17451000.2013.872801

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Post-release wide-ranging movements of sea turtles after 23

prolonged captivity 24

Rehabilitation is an important part of sea turtle conservation efforts, and tracking 25

the animals is both a way of obtaining information on their movements and 26

behaviour, and to monitor, at least temporarily, the success of the rehabilitation 27

process. Two green turtles, Chelonia mydas (Linnaeus, 1758), and one 28

loggerhead turtle, Caretta caretta (Linnaeus, 1758), were rehabilitated after long 29

periods in captivity, and their movements were followed by satellite tracking 30

after their release near the South of Portugal. Location data were obtained for an 31

average of 688 days after release. All three animals showed a directional 32

movement and the last observed locations coincided with known feeding areas 33

for both species, near the coasts of Mauritania and the state of Ceará, Brazil, for 34

the green turtles, and near Cuba, for the loggerhead. Bathymetry, surface 35

currents, wind, sea surface temperature, chlorophyll-a concentration and 36

geomagnetic field were analysed as spatial and environmental variables 37

potentially affecting movement. Only bathymetry, sea surface temperature and 38

geomagnetic variables showed significant association with the path choice. This 39

project supports the notion that sea turtles have the ability to survive in the wild 40

after long periods in captivity and to return to known feeding areas of the species, 41

justifying the effort in their rehabilitation and post-release tracking. 42

Keywords: Sea turtle rehabilitation, satellite tracking, Chelonia mydas, Caretta 43

caretta. 44

45

Introduction 46

Sea turtles are threatened throughout their life cycle by several anthropogenic factors 47

such as bycatch, poaching, modification of nesting beaches, pollution and marine debris 48

(Bolten et al. 2010; Donlan et al. 2010). Although not every sea turtle that is ill, injured 49

or entangled strands ashore (Epperly et al. 1996), beached individuals of such 50

charismatic fauna normally attract more public attention (Feck & Hamann 2013), which 51

may lead to a rehabilitation response. The reasons listed by Moore et al. (2007) for the 52

rehabilitation of marine mammals can also be used to justify sea turtle rehabilitation 53

attempts: conservation of endangered species; care of animals harmed by human 54

3

activities; mitigation of human use of sea turtle nesting beaches; research focused on 55

rehabilitation or wildlife medicine; post-release tracking, as a way to improve 56

knowledge on wild populations and migration; public education campaigns about 57

marine ecosystem health and its importance to sea turtle conservation. Considering the 58

low survival probability of each turtle (from egg to adulthood, e.g. Frazer 1986) but also 59

its potential reproductive output (Broderick et al. 2003), the rehabilitation of a single, or 60

a small number, of individuals becomes demographically relevant. 61

Studies on the post release behaviour of rehabilitated sea turtles are limited and have 62

mostly been restricted to sea turtles accidentally captured by long-liners and released 63

after hook removal on-board the fishing boats (Swimmer et al. 2006 and Sasso & 64

Epperly 2007) or to individuals entangled in trammel nets and released after a short 65

period of time (e.g. Snoddy & Southwood 2010). 66

Some sea turtles have been released carrying satellite transmitters, which allowed the 67

study of their subsequent movements and to monitor their rehabilitation success (see 68

Godley et al. 2008). 69

Post-release adaptation to the wild is critical to the rehabilitation process. With a few 70

exceptions (e.g. Bentivegna 2001; Cardona et al. 2012) this has not been studied in 71

depth, particularly for sea turtles that experienced long captivity periods. 72

This study provides new data on sea turtles’ post-release movements after long periods 73

in captivity, through the satellite tracking of two green turtles (Chelonia mydas) and one 74

loggerhead turtle (Caretta caretta). A comprehensive set of potential variables was 75

analysed, building on other studies that assessed only one or a low number of 76

parameters, such as sea surface temperature (Hays et al. 2001 and Hawkes et al. 2007), 77

geomagnetic variables (Benhamou et al. 2011), surface currents (Luschi et al. 2003; 78

Bentivegna et al. 2007 and Hawkes et al. 2007) or chlorophyll-a concentration 79

(Polovina et al. 2001). 80

The main objective of this paper is to obtain information on sea turtle movement and 81

behaviour, assessing the success of the rehabilitation process after prolonged periods of 82

captivity. 83

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4

Materials and Methods 87

Specimen handling and release 88

Two female green turtles and one female loggerhead turtle were released in the Atlantic 89

Ocean, about 20 miles south of Portimão, Portugal (approximately 36°46'48.57"N; 90

8°32'16.54"W) on 30 September 2009, after being rehabilitated at Zoomarine’s 91

Rehabilitation Centre, Porto d’Abrigo (PdAZ). The three turtles tracked in this study 92

came from the following backgrounds: 93

CM1 (green turtle, nicknamed Tartaruga) was transferred from the Funchal Municipal 94

Museum (Madeira, Portugal) on the 22nd

of April 2004, where it was kept for about 30 95

years. On arrival at the rehabilitation center: weight = 32.0 kg, straight carapace length 96

(SCL) = 60.6 cm; On release: weight = 80.4 kg, SCL = 78 cm. 97

CM2 (green turtle, nicknamed Cat) was seized by the Portuguese airport customs on the 98

27th

of August 2001 (on arrival at the rehabilitation center: weight = 4.8 kg, SCL = 33.9 99

cm). It was sent to the PdAZ by the national authority for nature conservation (ICNF – 100

Institute for Nature and Forest Conservation). On March of 2006 the left fore flipper 101

was surgically amputated due to a severe infection but its subsequent swimming ability 102

was apparently not affected. On release: weight = 60.5 kg, SCL = 77.5 cm. 103

CC (loggerhead turtle, nicknamed Calantha) was transferred from the Vasco da Gama 104

Aquarium (Oeiras, Portugal) on the 13th

of October 2005, where it was exhibited for 105

about 25 years (on arrival at the rehabilitation center: weight = 115 kg, SCL = 84 cm; 106

on release: weighted = 125.8 kg, SCL = 84 cm). 107

All specimens had a long history of captivity. During the rehabilitation time at PdAZ, 108

human interaction with these individuals was minimized. 109

Each turtle was considered fit for release when it met certain predefined criteria 110

(Bluvias 2008): 1) no medication for at least two weeks; 2) the ability to capture live 111

prey; 3) good body condition; 4) no diseases or lesions (wounds, tumours, skin 112

irritation, epibionts or endoparasites); 5) normal digestive function; 6) the ability for 113

active movement; 7) the capacity to lift its head and breathe normally; 8) attempts to 114

move when on dry substrate; 9) normal blood parameters for 2 to 4 weeks. 115

The three turtles were fitted with Argos System satellite tags on top of the carapace 116

following the procedure described by Coyne et al. (2008). The KiwiSat 101 117

transmitters (Sirtrack Limited, New Zealand) operated with a 40-second repetition rate 118

5

and a salt water switch (transmitting only when the animal surfaced). The location data 119

time span was from September 2009 to September 2011. 120

121

Environmental data 122

General Bathymetric Chart of the Oceans (GEBCO) bathymetry (in meters) was 123

retrieved through the British Oceanographic Data Centre website (BODC 2012). This 124

dataset has a resolution of 30 arc-seconds, and was generated by combining quality-125

controlled ship depth soundings with interpolation between sounding points, which is 126

estimated by satellite-derived gravity data (GEBCO 2012). Bathymetric data might be 127

an important variable to understand the movement of sea turtles, since these species 128

have continental (nesting) and neritic (feeding) stages in their life history (Kobayashi et 129

al. 2008). 130

Data on surface currents (in ms-1

) were downloaded from the Ocean Surface Current 131

Analysis (OSCAR) website (Bonjean & Lagerloef 2002; OSCAR 2012). These data 132

consisted of information about the East-West (u) and North-South (v) components of 133

the surface currents which were transformed to speed ( 22 vuS , in ms-1

) and water 134

flow direction (D = arctan(u/v); in degrees). 135

Chlorophyll-a data (in mg m-3

) and Sea Surface Temperature (SST), (in ºC) were 136

downloaded from the NASA Earth Observations website (http://neo.sci.gsfc.nasa.gov) 137

and were obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS) 138

instrument in the NASA's satellite Aqua, with a resolution of 1 km. The chlorophyll-a 139

data provide information on the concentration of surface phytoplankton, and the SST is 140

the temperature of the top millimetre of the ocean, accurate to a half a degree Celsius. 141

Both chlorophyll-a and SST were considered by previous studies (e.g., Kobayashi et al. 142

2008) as important variables in loggerhead movement. 143

Geomagnetic variables were based on the World Magnetic Model for 2010/2015 and 144

were downloaded from NOAA’s National Geophysical Data Center website 145

(ftp://ftp.ngdc.noaa.gov/geomag/wmm/wmm2010/shapefiles/). Three geomagnetic 146

variables were considered for analysis: declination (in degrees), inclination (in degrees) 147

and intensity (in nanoTeslas). The spatial representation of the geomagnetic isolines 148

will depend on the orientation strategy followed by the turtles in relation to these 149

variables, as discussed by Lohmann et al. (2007). Here, we interpolated the isolines in 150

6

order to obtain continuous surfaces, as these gradients might be the best way to identify 151

any influence of the magnetic field. Geomagnetic variables are important navigation 152

cues at intermediate scales to green turtles (Benhamou et al. 2011) and also to the 153

movements of loggerheads (Lohmann et al. 2004 and Kobayashi et al. 2008). 154

Surface winds were also considered as a relevant variable. East-West (u) and North-155

South (v) components were obtained from NOAA’s Multiple-Satellite Blended Sea 156

Surface Winds, downloaded from the NOAA-NOMADS Live Access Server 157

(http://nomads.ncdc.noaa.gov/las/), and speed (in ms-1

) and direction (in degrees) were 158

subsequently computed. Collard & Ogren (1990) found that surface winds are important 159

to dispersal patterns of post-hatching Kemp’s ridley turtles (Lepidochelys kempii); 160

Hochscheid et al. (2010), on the other hand, reported that loggerheads may remain at the 161

surface for extended periods to absorb solar radiation or to recover from anaerobic 162

activity, and therefore may be significantly affected by winds; the effect of the drag 163

caused by the satellite transmitter on the movements of the sea turtles has been noted by 164

Watson & Granger (1998). All these factors highlight the potential influence of surface 165

winds on sea turtle paths. 166

Shoreline data were downloaded from the GSHHS (Global Self-consistent Hierarchical 167

High-resolution Shoreline) website (GSHHS 2012) (Wessel & Smith 1996). The highest 168

resolution data available were used. 169

All the ecogeographical variables (with the exception of bathymetry geomagnetic 170

variables) were averaged monthly in the considered time period. The wind direction and 171

current flow values follow the oceanographic convention (angles are measured 172

clockwise from North). 173

All GIS analysis and plotting was carried out using Quantum GIS, version “Lisboa” 174

1.8.0 (Quantum GIS Development Team, 2013) and two R packages: “raster” (Hijmans 175

& van Etten 2012) and “maptools” (Lewin-Koh et al. 2012). The software R version 176

was x64 2.15.1 (R Core Team 2012). 177

178

Track analysis 179

Data were received from the Argos system through the STAT (Satellite Tracking and 180

Analysis Tool) platform, which is a web-based tool that facilitates the reception and 181

7

filtration of Argos data (Coyne & Godley 2005). The specimen’s location, in near real-182

time display, may be sent to a website, allowing the sharing of this information with the 183

general public. 184

The Argos data are classified according to the location accuracy of each point, which 185

mainly depends on the geometrical conditions of the satellite pass at the time it receives 186

the uplinks, and on the stability of the transmitter frequency (Argos, 2011). In the 187

particular case of marine species, the limited time spent at the surface restricts the 188

number of uplinks received by the satellite, so these data are particularly prone to 189

location error (Freitas et al. 2008). The Argos data locations are classified according to 190

an error estimate, and only those in the error classes 1(<1500 m), 2 (<500 m) and 3 191

(<250 m) were retained for further analysis. Locations on land, as well as those that 192

imply an unrealistically high swimming speed of more than 6 km.h-1

for the loggerhead 193

turtle (Bentivegna et al. 2007) and 5 km.h-1

for the green turtles (Luschi et al. 1998) 194

were also discarded. 195

Defining resource use and availability is a fundamental stage in resource selection 196

studies. Resource use can be defined in several ways, such as time spent and distance 197

travelled within the used area (Buskirk & Millspaugh 2006). The availability of 198

resources was defined for each turtle by considering a kernel 99% to avoid the exclusion 199

of data from paths actually used. This was calculated using the fixed kernel with the 200

smoothing parameter computed by the reference bandwidth method (Powell 2000), 201

using the R package “adehabitatHR” (Calenge 2006). The used resources are those 202

within a buffer with a width of 60 km (considering that the maximum daily average 203

distance travelled was just less than 30 km). 204

To identify variables accounting for the turtle path choice (departing from resource 205

availability) a Kolmogorov-Smirnov test (KS) was performed highlighting deviations 206

between availability and actual use of space. Subsequently, for each of the variables for 207

which significant differences were found, a Strauss’ Linear Index (SLI) (Strauss 1979) 208

was computed: 209

iiOSLI ̂ (1) 210

211

8

Where uuO ii / (sample proportion of used units in category i) and mmii /̂212

(sample proportion of available units in category i). 213

The analysis of current and surface winds significance (speed and direction in both 214

cases) was performed using a different strategy, pairing movement direction and speed 215

with the underlying variables. For wind and current direction, the circular correlation 216

statistic was used, running the R package “CircStats” (Agostinelli 2012), while for wind 217

and current speed a linear model was adopted. The analyses were performed separately 218

for each of the turtles. 219

220

Results 221

Location data were obtained for an average of 688 days after release (CC=653 d; 222

CM1=675 d; CM2=736 d). The tracking data from the three turtles are plotted on Figure 223

1, showing that all three animals followed a targeted movement (rather than random) 224

and, most importantly, that the last observed locations coincided with known feeding 225

areas for each species (Marcovaldi & Marcovaldi 1999; Fretey 2001; Dodd & Byles 226

2003; Santos et al. 2011). In the beginning of this study, both of the C. mydas turtles 227

followed a path along the coast, with CM2 crossing the Atlantic to Brazil after reaching 228

Western Sahara, and the CM1 staying near the African coast. The third turtle, the C. 229

caretta, crossed the Atlantic shortly after being released, passing between the Madeira 230

and Canary Islands until it reached the coastal waters of Cuba. 231

FIGURE 1 232

In studies of this nature, data quality can be assessed by evaluating the percentage of 233

locations within each of the error classes, as seen in Table 1. CC had more accurate 234

locations, probably due to longer or more frequent surfacing periods. CM1’s satellite 235

data were the least accurate, with more than 80% of the locations having no error 236

estimation, although it is the specimen with the largest time span of data (Figure 2). For 237

unknown reasons, locations from specimen CM2 were interrupted for over a year, 238

during which the animal stayed in the same general area (see Hays et al. 2007 for a 239

discussion of transmission problems). 240

9

TABLE 1 241

FIGURE 2 242

The last recorded locations for each of the turtles were: East coast of Cuba (CC); Banc 243

d’Arguin National Park, off the coast of Mauritania (CM1) and north-eastern coast of 244

Brazil (CM2). 245

The average daily speed of each specimen was: 0.191 km.h-1

(CM1), 1.15 km.h-1

(CC) 246

and 0.995 km.h-1

(CM2). CM1 has a lower average speed because the animal’s 247

movement was reduced upon arriving at the coastal region of the Banc d’Arguin 248

National Park. Ignoring these last locations, speed values were similar to those of the 249

other turtles. 250

251

Track analysis 252

Tables 2 to 4 show the main results of the statistical analysis on the influence of 253

environmental variables in the paths chosen by each sea turtle. 254

TABLE 2 255

TABLE 3 256

TABLE 4 257

The following analysis, using the Strauss Linear Index, evaluates the relation between 258

each turtle and the environmental variables. The curves representing the SLI values are 259

presented in Figure 3. 260

FIGURE 3 261

These results highlight the importance of the geomagnetic variables in the sea turtles’ 262

navigation. 263

In the case of CM1, all three geomagnetic variables were significant to the path 264

followed. Nevertheless there seems to be no particular preference within each variable. 265

That is explained by the isoline layout, which is fairly perpendicular to CM1’s path 266

(Figure 4). Bathymetry was also important to this specimen’s movement, which showed 267

a strong preference for shallow areas. Surface currents and winds had no significant 268

impact on space use. 269

To CM2, inclination and declination had a more important effect. Regarding 270

geomagnetic field inclination there is a strong selection of values between -12º and -271

10

7.89º, explained by the final part of the path where the turtle moves parallel to the 272

isolines. Geomagnetic field declination is basically perpendicular to this turtle’s path, 273

explaining the variation in the SLI. The coastal path followed indicates a strong 274

selection of shallow areas (and a strong avoidance of depths over 3830 m). Wind 275

direction was also significant. However, it had a residual importance in path choice, 276

considering that the correlation coefficient was very low (r = 0.134). 277

CC was also influenced by the geomagnetic variables. It followed a path parallel to 278

some inclination isolines with a selection of values between 33.1º and 35.3º. 279

Geomagnetic field intensity also shows a degree of selection between 38760 nT and 280

39369 nT, for the same reason. CC moves in a perpendicular path to the declination 281

isolines. In what regards field declination, there was an avoidance of values between –282

20.26º and –19.88º, with no particular selection for values above, as shown by the SLI. 283

Bathymetry was an important variable for this turtle, with a positive selection of depths 284

between 6140 m and 5620 m, and between 5010 m and 3980 m. Contrary to the green 285

turtles, this specimen approached and departed the coast perpendicularly, which is 286

expressed in a negative selection of shallower areas. Finally, SST was also a significant 287

variable to CC. This specimen selected values under 22.4ºC, according to the SLI. 288

Surface currents and wind direction were also significant. 289

290

FIGURE 4 291

292

Discussion 293

Three turtles, of various and unknown origins, spent a long time in captivity, and were 294

finally brought to a rehabilitation centre in the South of Portugal, where their condition 295

was much improved. Considered fit to return to the ocean, they were released after 296

being tagged with satellite transmitters for an opportunistic study of their movements. It 297

was hoped that this effort would produce some insights concerning their preferences 298

and a notion about the survival chances of animals in such circumstances. All three 299

turtles were tracked for a significant time and showed non-random displacements that 300

interestingly brought the animals to traditional feeding regions of both species. The 301

extension of the post-release movements is remarkable (CC = 9709 km, CM1 = 3053 302

11

km and CM2 = 6806 km), but see Hays & Scott (2013) for context. It can be compared 303

to those in a previous study carried out in the Pacific (Luschi et al. 2003). 304

Interestingly, the final locations determined are close to known feeding grounds for both 305

species. Banc d’Arguin National Park (Fretey 2001; Godley et al. 2010) and the coast of 306

Ceará, Brazil (Marcovaldi & Marcovaldi 1999; Santos et al. 2011) for green turtles and 307

the Great Bahamas Bank, near the north coast of Cuba, for the loggerheads (Dodd & 308

Byles 2003). Having no detailed information on the pre-capture background of these 309

specimens, it is impossible to know to what extent any previous migration experience 310

was relevant (CC and CM1 were probably captured as adults, while CM2 was likely 311

collected as a juvenile). 312

The observed effect of bathymetry, which was significant to both C. mydas turtles, 313

might be explained by the extension of their path following the coast of Africa. These 314

coastal movements have been reported in previous works (such as Godley et al. 2002 315

and Troëng et al. 2005) and were considered an optimum strategy regarding feeding. So, 316

it can also be hypothesized that this option might maximize post-release food intake, by 317

moving along the coast and thus increasing the chance of finding food. 318

Geomagnetic variables (intensity, inclination and declination) were the most significant 319

variables explaining the use of space by the turtles. Studies with magnetically disturbed 320

sea turtles and with displaced animals (e.g. Luschi et al. 2007 and Benhamou et al. 321

2011) have supported the notion that sea turtles perceive the magnetic field and navigate 322

using this information. The ability of sea turtles to use geomagnetic inclination as an 323

approximation of latitude (Lohmann & Lohmann 1994) combined with the detection of 324

geomagnetic intensity (Lohmann & Lohmann 1996) might allow navigation with a bi-325

coordinate magnetic map as has been previously proposed and is considered to be 326

possible in some regions of the world (Putman et al. 2011 and Boström et al. 2012). 327

Additionally, as mentioned by Monzón-Argüello et al. (2009), juvenile loggerheads are 328

most frequently found in geomagnetic inclination isolines common to their natal 329

rookeries (between 34º and 46º). Given that CC selected a mean inclination of 37.013º, 330

we might presume that this was an important factor in path choice, although it is an 331

adult. Overall, our data support the notion of geomagnetic navigation abilities for these 332

animals. 333

SST was only significant to CC, which selected values between 20ºC and 22.4º C. The 334

12

initial portion of CC’s path is consistent with an avoidance of lower SST on the 335

northernmost part of the available area. Following this, CC’s path reveals a preference 336

for intermediate SST values, avoiding the warmer southern temperatures. This might be 337

due to other factors, namely the magnetic inclination. The values of the SST selected 338

are comparable to those found in previous works, such as 14.45 °C to 19.95 °C for 339

loggerheads in the Pacific (Kobayashi et al. 2008), 10.21ºC to 28.4ºC for juvenile 340

loggerheads in the South-western Atlantic (Barceló 2011) and 20.20ºC to 29.50ºC for 341

green turtles in the Gulf of California (McDermott et al. 2003). However it has been 342

reported that, in some areas, SST is a variable of minor importance in regard to the path 343

choice by green turtles (Hays et al. 2001). 344

Chlorophyll concentration did not have any significant effect on the path chosen by any 345

of the turtles. Nevertheless, the values of chlorophyll in the area used are similar to 346

those from previous studies, such as 0.458 ± 1.012 mg/m3 for juvenile loggerheads in 347

the South-western Atlantic (Barceló 2011) or between 0.11 mg/m3 and 0.31 mg/m

3 for 348

loggerheads, in the Pacific Ocean (Kobayashi et al. 2008). The lower mean chlorophyll 349

concentration in the area used by CC was probably due to the open ocean path chosen 350

by this specimen. The higher concentration in the area used by CM1 was due to the fact 351

that this turtle spent a considerable proportion of the time in an area with high 352

chlorophyll concentration, at the Banc d’Arguin National Park, Mauritania. 353

Current speed had no significant effect on the turtles’ paths, suggesting that neither of 354

the turtles used the current to assist their movement. This is expected since flow 355

direction assessment can be very difficult in the ocean (Chapman et al. 2011). Only the 356

specimen CC (which spent more time at the surface) was significantly affected by 357

surface current direction. Previous works had confirmed the relevance of ocean currents 358

to loggerheads (Bentivegna et al. 2007) and green turtles (Girard et al. 2006). A recent 359

review on the behaviour of animals in flows, whether air or water (Chapman et al. 2011) 360

has suggested that sea turtles follow a strategy of “Full Drift – Constant Compass 361

Orientation”, which means that sea turtles keep constantly heading towards their goal 362

regardless of the flow, resulting in some lateral displacement. In fact, at least for green 363

turtles, currents have a negative effect on navigation ability, as the turtles cannot 364

compensate the deflecting action of currents (Girard et al. 2006). 365

Surface wind speed and current speed had no significant effect on the paths. 366

13

Nevertheless, the direction of surface winds was considered significantly correlated 367

with the directions followed by CC and CM2. Given that sea turtles are air breathing 368

animals, and spend a portion of their time at the water surface, they might be subjected 369

to wind driven circulation of the water column, as well as wind drag on their carapace, 370

as also suggested by Watson & Granger (1998). 371

In the case of CC, the influence of surface currents and wind direction might be 372

explained by more frequent or extended surfacing periods, therefore with higher 373

exposure to surface winds and currents. This is supported by two sources of 374

information: our own observations (when at the rehabilitation centre this specimen spent 375

more time at the surface than the other two) and the number and quality of locations 376

received. CC had more location data (until transmissions stopped) and the locations 377

were more accurate, which was due to the more frequent presence of the transmitter at 378

the surface. 379

Rehabilitation of stranded or confiscated specimens is an important component of 380

conservation efforts, particularly in species that are facing conservation challenges, such 381

as climate change (Witt et al. 2010; Wallace et al. 2011 and Pike 2013), poaching 382

(eggs), fisheries bycatch, pollution and coastal urban development (Wallace et al. 2011). 383

Additionally, each adult is particularly valuable since few embryos survive to 384

adulthood, (approximately 1/1000 in loggerheads (Frazer 1986) and given that sexual 385

maturity is reached relatively late in life (42 to 44 years in green turtles and 23.5 to 29.3 386

years in loggerheads) (Goshe et al. 2010 and Casale et al. 2011). So, every 387

reproductively active adult is of major importance to the species’ conservation. 388

The main purpose of this study was to evaluate the ability of these sea turtles to survive 389

in the wild after long periods in captivity. Overall, we note that their return to the wild 390

was apparently successful, considering that these animals swam to known feeding areas 391

of their species. 392

The rehabilitation process does not end with the release of the individuals to their 393

natural habitat. Tracking the animals is both a way of obtaining information on their 394

movements and behaviour, and to monitor, at least temporarily, the success of the 395

rehabilitation effort. 396

Acknowledgements 397

The administration board of Zoomarine Portugal funded the spatial analysis, and Élio 398

14

Vicente was instrumental to this study in many ways. We are grateful to the Portuguese 399

Navy for the continuous collaboration in turtle release operations. We thank Michael 400

Coyne (seaturtle.org) for help in data collection, Paulo Relvas (CCMAR/FCT, 401

University of Algarve) for assistance in the interpretation and treatment of some 402

variables, and José Matos (Instituto Nacional de Investigação Agrária e Veterinária, 403

I.P.) for the very useful comments on the manuscript. 404

405

406

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672

673

674

675

676

677

678

679

680

23

Table 1 - Number of locations for each animal (% percentage) (CC – Caretta caretta; 681

CM1 and CM2 - Chelonia mydas) and error class: 3 (<250 m); 2 (250-500 m); 1 (500-682

1500 m); 0 (>1500 m); A (no error estimation, 3 uplinks); B (no error estimation, 1-2 683

uplinks) and Z (invalid locations). 684

Error Class CC (%) CM1 (%) CM2 (%)

3 659 (11,69) 57 (2,52) 295 (11,20)

2 1313 (23,28) 112 (4,96) 419 (15,91)

1 887 (15,73) 125 (5,53) 360 (13,67)

0 509 (9,03) 87 (3,85) 190 (7,21)

A 856 (15,18) 461 (20,41) 562 (21,34)

B 1367 (24,24) 1386 (61,35) 783 (29,73)

Z 48 (0,85) 31 (1,37) 25 (0,95)

685

686

687

688

689

690

691

692

693

694

695

696

697

698

24

Table 2 – Influence of environmental variables in the paths followed by CM1; Mean 699

(±SD); Range – range of values in the used area; coefficient of the Linear Model (LM); 700

Kolmogorov-Smirnov's D (KS-D); Circular correlation coefficient (corr - r); NS - non 701

significant relation; * - significant relation (p<0.05). 702

Variable Mean (±SD) Range Statistic

Significance LM KS-D corr – r

Bathymetry -986.919 m

(± 1328.181)

-4388.0 m to -

1.0 m - 0,588 - *

SST 21.691ºC (±

1.482)

17.61ºC to

27.05ºC - 0,500 - NS

Chlorophyll 2.498 mg m-3

(± 4.303)

0.0 mg m-3 to

56.110 mg m-

3

- 0,194 - NS

Inclination 31.671º (±

6.775)

16.93º to

46.12º - 0,628 - *

Declination -20.372º (±

0.081)

-20.54º to -

20.26º - 0,929 - *

Intensity 39757.960 nT

(± 1898.371)

36440 nT to

42440 nT - 0,714 - *

Current speed 0.100 ms-1 0.027 to 0.204

ms-1 0.025 - - NS

Current direction - - - - 0.061 NS

Surface wind

speed 5.267 ms-1

1.400 to 7.657

ms-1 -0.021 - - NS

Surface wind

direction - - - - 0.133 NS

703

704

705

706

707

708

709

710

711

712

25

Table 3 – Influence of environmental variables in the paths followed by CM2; Mean 713







(± 1656.854)

-5612 m to -2

m - 0,424 - *

SST 25.185ºC (±

2.894)

19.46ºC to

30.20ºC - 0,200 - NS


(± 1.060)

0.0 mg m-3

to 12.850 mg

m-3

- 0,095 - NS


17.960)

-15.770º to

46.280º - 0,293 - *


0.205)

-21.24º to -

20.05º - 0,462 - NS


(± 3939.630)

27300 nT to

42980 nT - 0,293 - *

Current speed 0.114 ms-1 0.026 to

0.392 ms-1 -0.207 - - NS

Current direction - - - - 0.012 NS

Surface wind

speed 6.170 ms-1

4.394 to

8.118 ms-1 -0.045 - - NS

Surface wind

direction - - - - 0.134 *

717

718

719

720

721

722

723

724

26

Table 4 – Influence of environmental variables in the paths followed by CC; Mean 725







(± 1052.146)

-6539 m to -2

m - 0,382 - *

SST 24.141ºC (±

3.267)

19.09ºC to

30.75ºC - 0,391 - *


(± 0.037)

0.0 mg m-3 to

0.427 mg m-3 - 0,333 - NS


3.331)

31.35º to

48.69º - 0,775 - *


0.912)

-20.36º to -

16.84º - 0,325 - *


(± 1146.686)

38090 nT to

42790 nT - 0,436 - *

Current speed 0.080 ms-1 0.006 to 0.328

ms-1 -0.138 - - NS

Current direction - - - - 0.328 *

Surface wind

speed 6.748 ms-1

4.564 to 8.605

ms-1 0.011 - - NS

Surface wind

direction - - - - 0.094 *

729

730

731

732

733

734

735

736

27

Figure 1 - Track of the three specimens followed in this study. 737

738

739

740

741

742

743

744

745

746

747

748

749

750

751

752

753

754

28

Figure 2 – Monthly number of locations for each turtle. CC , CM1 and CM2. 755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

29

Figure 3 - Strauss' Linear Index for the significant variables. 773

774

775

30

Figure 4 - Geomagnetic Field (A) Inclination, (B) Intensity and (C) Declination (World 776

Magnetic Model for 2010/2015). 777

778

Satellite tracking of sea turtles released after prolonged captivity periods

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