Bottlenose dolphin's (Tursiops truncatus) potential prey items differences in size distribution and health conditions among habitat type and localities in Bocas del Toro Archipelago

(1)

Biología & Economía

1

Undergraduate Thesis Research Project

1

PROJECT TITLE: 2

Bottlenose dolphin’s (Tursiops truncatus) potential prey items differences in size distribution and

3

health conditions among habitat type and localities in Bocas del Toro Archipelago.

4

5

María Paula Hernández1_*, Dalia C. Barragán-Barrera2, Laura J. May-Collado3, Andrea Luna-Acosta4, 6

Susana Caballero5, and Federico G. Riet-Sapriza6. 7

8

*Corresponding author. Tel: (+57) 317 401 9895, (+57)(1) 3394949 ext. 4769; E-mail address: 9

[email protected] 10

11

1._{Laboratorio de Ecología Molecular de Vertebrados Acuáticos (LEMVA). Facultad de Ciencias Biológicas.} 12

Universidad de Los Andes, Carrera 1 # 18A-12, Bogotá, Colombia. 13

Universidad de Los Andes, Carrera 1 # 18A-12, Bogotá, Colombia. Fundación Macuáticos Colombia. E-mail 15

address: [email protected] 16

3._{Department of Biology, University of Vermont, 109 Carrigan Drive, Burlington, VT 05405, USA. E-mail} 17

address: [email protected] 18

4._{Department of Ecology and Territory, Pontificia Universidad Javeriana, Bogotá, Colombia.} 19

Universidad de Los Andes, Carrera 1 # 18A-12, Bogotá, Colombia. E-mail address: 21

[email protected] 22

Universidad de Los Andes, Carrera 1 # 18A-12, Bogotá, Colombia. E-mail address: [email protected] 24

25

26

27

28

(2)

2

ABSTRACT

30

31

Bottlenose dolphins (Tursiops truncatus) are general and opportunistic top predators, consuming a 32

variety of prey items. Prey preferences differ among populations found around the globe, and are tied 33

with prey species abundance and distribution. In Bocas del Toro Archipelago there is a small and 34

highly phylopatric bottlenose dolphin population. The Archipelago is characterized by its habitat 35

heterogeneity; with some areas presenting high coastal development in relation to others. The aim of 36

this study is to test possible differences in potential bottlenose dolphin prey size distribution and health 37

conditions between habitat type and localities in the Bocas del Toro Archipelago. We found that

38

average length measurements of prey differ between locations and habitats, showing smaller fish

39

(juveniles) in mangroves areas and adults in coral reef and off-shore zones. Fish health assessment 40

indexes indicate a higher well-being of fish found in coral reef habitats when compared with others. 41

We have concerns regarding the possibility of dolphins foraging in highly intervened ecosystems, 42

therefore acquiring pollutants and heavy metals from prey. 43

44

45

46

47

48

49

50

51

(3)

3

INTRODUCTION

53

54

Bottlenose dolphins (Tursiops truncatus) are general and opportunistic top predators, consuming a 55

variety of prey items (Allen et al. 2001; Blanco et al. 2001). Feeding preferences differ among 56

locations and are tied with marine topology, prey availability and abundance (Allen et al. 2001; Ingram 57

& Rogan, 2002). In Galician waters studies show that the local bottlenose dolphin population feeds 58

predominantly on Gadidae and Merlucciidae fish (Santos et al, 2007), meanwhile in the Mid-Atlantic 59

coast of the U.S. bottlenose dolphins are foraging mainly in Sciaenidae fish (Gannon & Waples, 2004). 60

Furthermore, Mead & Potter (1990) concluded that bottlenose dolphin main prey species of fish 61

correspond to the Sciaenidae and Phycidae family, and the main prey species of cephalopods to the 62

Lolinginidae family. The diet of delphinids has been studied primarily via stomach content, fatty acid, 63

DNA and stable isotope analyses (Das et al, 2003; Ford et al, 1998; Hooker et al, 2001; Riccialdelli et 64

al, 2010). As marine top predators, bottlenose dolphins influence and structure aquatic communities 65

(Bowen, 1997); but they are vulnerable to changes in environmental conditions and prey abundance. 66

Moreover, foraging tactics in bottlenose dolphins are strongly associated with habitat heterogeneity and 67

ecosystem characteristics (Torres & Read, 2009). 68

69

Taxonomic and molecular approaches are highly important in determining potential dolphin prey 70

species. Molecular techniques and DNA analyses provide critical information for species identification. 71

International collaborative initiatives such as The Barcode of Life Database (www.barcodinglife.org) 72

use a DNA-based cataloging system based on a fragment of the mitochondrial cytochrome oxidase 73

subunit I (COI) for species identification. These libraries are based on the concept that DNA sequence 74

diversity provides sufficient information to discriminate between congeneric species (Sevilla et al. 75

(4)

4 2007). Therefore, barcoding is a powerful tool that complements traditional prey species taxonomic 76

identification and aids in diet determination of bottlenose dolphins. 77

78

Ecological and diet information is crucial in establishing local food web structure, consumer evolution, 79

ecological roles and ecosystem dynamics (Dunshea et al, 2013). An organism well-being or fitness can 80

be measured and analyzed through health assessment indexes that consider length-weight comparisons 81

(Bolger & Connolly, 1989). These health assessment indexes can be affected by water quality 82

(pollution levels and trace element concentrations), food availability, and temperature. Moreover, the 83

health status may vary between seasons, locations and throughout time (Adams et al. 1993; Bolger & 84

Connolly, 1989). Hence, they provide valuable information that would reflect local environmental 85

conditions and possible physical condition differences between populations inhabiting ecosystems with 86

dissimilar abiotic factors; meaning they could evidence the health status of prey communities 87

bottlenose dolphins forage on. 88

89

The Bocas del Toro Archipelago is located in the northwestern Caribbean coast of Panama; and holds a 90

year-round population (~80; May-Collado pers. comm.) of bottlenose dolphins, which is target of an 91

uncontrolled dolphin-watching industry (May-Collado et al, 2012; May-Collado et al, 2014). The 92

Archipelago is characterized by its high productivity and habitat heterogeneity; composed by 93

mangroves, sea grass beds, and coral reef habitats (D’Croz et al., 2005; Guzman & Guevara, 1998). 94

The diversified range of ecosystems may lead to a differential use of resources by dolphins, thus 95

prompting individual foraging specialization (Browning et al., 2014a; Rossman et al., 2015). 96

Moreover, in the Archipelago there are some areas with high human coastal development. Human 97

impacts include: overfishing, nutrients and heavy metal inflows from chemicals applied to banana 98

(5)

5 plantations, sedimentation from dredging, heavy metal pollution from shipping traffic, increased human 99

population, among others (Seemann et al., 2013). Anthropic activities alters environmental conditions 100

and endorses local habitat degradation. Furthermore, the health condition of bottlenose dolphin prey 101

communities might be different between undisturbed costal habitat and highly impacted areas. 102

103

Recent studies about the genetic status of this bottlenose dolphin population have shown low genetic 104

diversity and high genetic structure, suggesting high philopatry and limited genetic flow with neighbor 105

populations in the Caribbean (Barragán-Barrera et al., 2013; Barragán-Barrera et al, 2015; May-106

Collado, 2013). Additionally, as mentioned above, the Archipelago presents areas with high anthropic 107

disturbances and detrimental abiotic factors (heavy metal pollution) that are potential risks for the 108

overall condition of the ecosystem. Given that, this population of bottlenose dolphins should be 109

managed as a population at risk and conceivable management plans should be established (Barragán-110

Barrera et al, 2015). I would like to test the hypothesis: there are differences in prey occurrence, 111

diversity and physical conditions between potential bottlenose dolphin foraging areas. In order to test 112

this hypothesis, this study aims to determine the overall health condition of potential prey items of the 113

local population of dolphins, and to assess general condition of prey communities 114

115

116

117

118

119

120

(6)

6 122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

Figure 1.a). Study area. b). Defined “Sub-regions” in the study area, based on previous dolphin

sightings. Black dots correspond to bottlenose dolphin sightings. The Almirante port (yellow) is the

region with high coastal development and environmental degradation. Map retrieved from:

(7)

7

MATERIALS AND METHODS

145

146

Field sampling and locality definition 147

We defined four sub-regions within the study area based on dolphin distribution patterns and their 148

potential foraging areas (see figure 1). The established sub-regions are the following: a). Almirante: 149

Port Almirante is a highly disturbed area that contributes to local ecosystem degradation; b). Cayo 150

coral; the outer most region of the Archipelago; c). Dolphin bay: the central part of the Archipelago 151

where sightings often occur; and d). Popa 1: an area where dolphins usually forage (based on 152

observations of interactions with fish) and social interactions happen. Furthermore, we discriminated 153

also by the environmental characteristics of each sampling locality. Habitat type was divided in three 154

groups: coral reef, mangrove and sea grass beds, and offshore ecosystems. Fish samples (n = 164) were 155

collected in the defined “sub-regions” along the Archipelago during February-March 2016. In most 156

sub-regions fish traps were used to capture live fish; however, in Cayo coral besides employing fish 157

traps local fishermen captured free-ranging fish using fishing nets. The previous allowed sampling in 158

the benthic and pelagic zone. At each sampling location we registered date, GPS position, water depth 159

and temperature. When collected, fish were directly immersed in an ice-cold water bath (-4ºC) for 160

sacrifice (Barker et al, 2002; Blessing et al, 2010) and transported in an ice-filled cooler to the 161

Smithsonian Tropical Research Institution (STRI). 162

163

Fish health assessment indexes 164

At the STRI facilities weight and length measures were taken for each sampled fish. We measured fork 165

length (FL), standard length (SL), wet weight (WW), liver weight (LW), stomach and intestine weight 166

(IW), and gonads weight (GW). We decided to analyze the hepatosomatic index (HIS), gonadosomatic 167

(8)

8 index (GSI), fullness index (FI) and Fulton’s condition factor (CF); since they are suitable indicators of 168

fish general health conditions. 169

The health assessment indexes were estimated using the following formulas: 170

Gonadosomatic index (GSI) Hepatosomatic index (HSI)

171

172

173

Fullness index (FI) Fulton’s Condition Factor (CF) 174

175

176

DNA analyses for prey identification 177

Tissue subsamples (approx. 400mg each) were isolated from fragments of dorsal white muscle and 178

liver. These were preserved in 2ml eppendorf tubes with ethanol (70%) and transported to Universidad 179

de Los Andes (Colombia) for molecular analyses at the Laboratory LEMVA (Laboratorio de Ecología 180

Molecular de Vertebrados Acuáticos). The whole white muscle genomic DNA was extractions were 181

performed using the STRATEC Molecular DNA extraction kit. Thereafter, a NanoDrop protocol was 182

conducted in order to quantitate the micro-volume (ng/𝜇l) of DNA for each the sample. PCR protocols 183

of the COI gene region from mtDNA were amplified using universal fish primers. The 25𝜇l PCR 184

reaction mix included 18.75𝜇l of ultrapure water, 2.25𝜇l of 10xPCR Buffer, 1.25𝜇l of MgCl2 (50mM), 185

0.25𝜇l of each primer (Forward (F) – Reverse (R)), 0.5𝜇l of dNTP’s and 0.625𝑈 of Taq polymerase 186

and 0.5-2.0𝜇l of DNA template. The thermal regime was conducted following Ward et al. (2005). PCR 187

products were visualized in 1.5% agarose gels and the samples with proper bands were selected for 188

sequencing. Final products were sequenced using the ABI-3500 Sanger sequencer of Universidad de 189

Los Andes. Sequences were cleaned and aligned using ARLEQUIN version 3.5.1.2. The resulting 190

𝑮𝑺𝑰=𝐺𝑜𝑛𝑎𝑑𝑠 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔)

𝑊𝑒𝑡 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔) ∗100 𝑯𝑺𝑰=

𝐿𝑖𝑣𝑒𝑟 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔)

𝑊𝑒𝑡 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔) ∗100

𝑭𝑰=𝐼𝑛𝑡𝑒𝑠𝑡𝑖𝑛𝑒 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔)

𝑊𝑒𝑡 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔) ∗100 𝑪𝑭=

𝑊𝑒𝑡 𝑤𝑒𝑖𝑔ℎ𝑡(𝑔)

(9)

9

FASTA sequence was introduced for a BLAST on NCBI database

191

(https://blast.ncbi.nlm.nih.gov/Blast.cgi), and the suggested matches were compared with in-situ data 192

(traditional taxonomic information) in order to classify the organism. 193

194

Statistical analyses 195

All statistical tests were conducted using R-Studio (https://www.rstudio.com/). We conducted Shapiro-196

Wilk test in order to test the normality of the data. Moreover, we performed correlations plots between 197

length and weight variables, which were tested with the Pearson correlation test. Finally, to test the data 198

we employed ANOVA models to analyze possible differences among group means and their variation. 199

200

201

202

203

204

205

206

207

208

209

210

211

212

(10)

10

RESULTS

214

Potential prey size distribution and health condition indexes 215

A total of 113 samples (out of n = 164) were evaluated, the 51 remaining samples were excluded from

216

the analyses for as they were juvenile sardines found in shallow mangrove waters were dolphins are not

217

likely to forage. These residual samples will be employed for forthcoming isotopic and heavy metal

218

analyses in the study area. Data analysis was centered in conducting comparisons between habitat types

219

and the defined sub-regions. In the Popa 1 sub-region the data was limited due a low density capture

220

rate; in addition, all samples from this area were juveniles which had not a complete development and

221

we could not obtain the measures for determining health assessment indexes.

222

223

Habitat type size distribution of prey in the study area is shown in Figure 2. Standard length (SL)

224

values for potential prey items are encompassed in a 6.0 – 31.0cm range. When contemplating size

225

dispersal based on habitat type we found that in coral reef prey size range is 6.0 – 31.0cm with a mean

226

value of 14.21cm; in mangroves and sea grass beds range is 10.0 – 16.6cm with a mean value of

227

13.23cm; finally in off-shore areas size range is 17.7 – 26.0 (cm with a mean value of 20.06cm.

228

Statistical tests were conducted to determine possible measurement dissimilarities between habitat

229

types. ANOVA results had a p-value=0.006 (𝛼=0.05) indicating significant differences in potential

230

dolphin prey size amongst habitat type. Equivalent results were obtained for fork length (FL)

231

comparisons between habitat type with an ANOVA p-value = 2.25e-06.

232

233

We conducted the same approach considering divisions by sub-regions or localities (figure 2).

234

Almirante had a mean size value of 19.30cm, Cayo coral of 22.82cm, Dolphin Bay of 14.55cm,

235

together with a value of 8.0cm for Popa 1. This shows that prey items collected from the Popa 1

(11)

11

locality display smaller measurements in relation to the remaining areas of the Archipelago. ANOVA

237

results had a p-value<0.05 indicating significant differences in potential prey size amongst habitat type.

238

Equivalent results were obtained for fork length (FL) comparisons within habitat type with a significant

239

ANOVA p-value.

240

241

242

243

244

245

246

247

248

249

Figure 2. Frequency size distribution of standard length (SL, cm) of potential prey by habitat type (coral reef, mangrove 250

and sea grass beds and other) and locality (based on sub-regions in figure 1). Habitat and localities are divided as defined in 251

the methods section. 252

253

We performed Pearson correlation functions in R Studio to determine interdependence within length 254

and weight variables. We found strong positive correlations among the standard length (SL) variable 255

liver weight (LW) (p-value=1.04e-19), intestine and stomach weight (IW) (p-value=1.37e-11) and 256

gonads weight (GW) (p-value=0.007). Similar results were obtained when tested with the fork length 257

(FL) of fish; we found strong positive correlations between FL and, LW value=3.91e-11), IW (p-258

Coral reef Sea grass beds Offshore

(12)

12 value=5.21e-11) and GW (p-value=0.006) (see figure 3). The previous means variables move in 259

tandem, implicating an increase in an organism’s weight at of its respective organs (liver, intestine and 260

gonads) as length increases. However when performing the correlation test between the SL and the wet 261

weight (WW) we evidenced no strong correlation value=0.2075), as for FL and WW (p-262

value=0.1562). 263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

Figure 3. Correlation plots of length-measure variables taken from sampled fish. WW: wet weigth. LW: liver

weigth. IW: stomach and intestine weigth. GW: gonads weigth. The WW variable had to be transformed using

the log function in order to fit the data into a known distribution. The first row of the figure correspond to

(13)

Biología & Economía 13 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 Figu re 4 . D is tr ib ut io n of th e F ul to n’ s c on di ti on f ac to r ( C F ) b y ha bi ta t t yp e ( co ra l r ee f, m an gr ov e a nd s ea g ra ss b ed s a nd o th er ) an d loc ality ( ba se d on sub -re gi on s in fi gure 1 ).

(14)

14 Health indexes for fish were estimated for habitat type and locality (exact values for the health 297

assessment indexes are displayed in Table 2 from the supplementary data section). When executing 298

comparisons of the HSI, GSI, FI, and CF among localities we found no significant differences 299

(ANOVA p-value > 0.05). Moreover, we found significant statistical differences in all the indexes 300

when comparing among habitat types (ANOVA p-value > 0.05) (table 1). The previous means coral 301

reef specimens had a higher condition factor and HSI indexes when compared with the remaining sites 302

(see figure 4); meanwhile mangrove ecosystems had a higher GSI index. 303

304

Table 1. Statistical results for the health assessment indexes by habitat type and locality. (* indicates a 305

significant statistical value) 306

Indexes P-value Anova by Habitat

P-value Anova by Locality GSI <2e-16 * 0.592

HIS <2e-16 * 0.0918

FI 0.00664 * 0.126

CF 2.25e-06 * 0.656

307

Potential prey DNA analyses 308

Sequence read lengths were about 655pb, which coincides with the COI gene region. When refining 309

and analyzing the sequences we did not find any insertions, deletions or stop codons. The lack of stop 310

codons in the DNA sequence corroborates the functionality of the gene. When employing the BLAST 311

on NCBI to the similarity results were not accurate; therefore, we decided to limit the identification to 312

family level. We found a total of eight fish families in the study area. The resulting families are: 313

Carangidae, Chaetodontidae, Haemulidae, Lutjanidae, Scaridae, Scarinae, Scombridae and Sparidae. 314

There are differences in the species of fish found in coral-reef, mangrove and off-shore habitats (Figure 315

5). Furthermore, in coral-reef habitats we found a higher family diversity (six out of eight) in 316

comparison with the other types of habitat. Individuals from the Caragidae family were found mostly in 317

(15)

15 offshore (other) areas; this corresponds to the pelagic nature of fish species belonging to the family. At 318

locality level we found a high number of fish families (five out of eight) in the Dolphin Bay and Cayo 319

coral sub-regions; and the lowest (one out of eight) in the Popa 1 area (Figure 5). 320

321

322

323

324

325

326

327

328

329

330

331

332

333

(16)

Biología & Economía 16 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 Figu re 5. Dist ri bution of f am il ie s by ha bita t type a nd loc at tie s in the stu dy ar ea . Co ra l r ee f Se a gr as s be ds Of fs ho re Al m ir an te C ay o co ra l Do lp hi n B ay Po pa 1

(17)

17

DISCUSSION

351

352

In the latest field trips conducted in the Archipelago, researchers have witnessed shifts in the nursery 353

areas of the bottlenose dolphins. Presently the “sub-region” comprising Popa 1, Shark Hole and Cerro 354

Brujo (figure 1) is considered as the nursery for preference over the Dolphin Bay area. The Dolphin 355

Bay sub-region has a higher diversity of fish families when compared with Popa1 (figure 5); this would 356

be beneficial for dolphins when foraging. However, anthropic impact in the area is high due the dolphin 357

watching industry pressure; in occasions more than forty dolphin-watching (DW) boats were 358

interacting with a pod of dolphins in the Dolphin Bay area. The previous may have driven bottlenose 359

dolphins, specially lactating females, to change their distribution. Moreover, this would be consistent 360

with results showing smaller prey size in Popa1; since, it would be easier for juvenile dolphins to catch 361

and forage on smaller fish (Barragán-Barrera personal comm.). 362

363

We found significant statistical differences in the health assessment indexes when comparing between 364

habitat types. This would indicate dissimilar physical conditions between fish found in coral reefs, 365

mangroves and offshore areas along the Archipelago. The condition factor reflects the physical 366

condition of fish, and is related to the feeding regime, abiotic and biotic pressures in an ecosystem. Fish 367

inhabiting coral reef ecosystems had a higher condition factor, meaning heavier individuals for a 368

specific length. Foregoing, this would indicate a better general fish condition in coral reef habitats; this 369

would be favorable for dolphins foraging in this type of habitat. Consequently, dolphin distribution can 370

be influenced by the presence/absence of well-conditioned fish; dolphins would rather forage in coral 371

reef areas were fish are greater in size and robustness. In addition, we found a higher GSI for fish 372

inhabiting mangrove areas; meaning, a relative high reproductive development in fish occupying this 373

(18)

18 ecosystem. This result is inconsistent with the size distribution of fish among the Archipelago; since the 374

comparative study showed larger fish in offshore and coral reef habitats, implicating more juveniles in 375

the mangrove and sea grass beds ecosystem. Health condition indexes can fluctuate along seasons and 376

can be influenced by food availability. Therefore, sampling should be conducted along the year in order 377

to reduce bias related to external factors. For instance, condition factor, GSI and HSI tend to decrease 378

when fish are spawning. Moreover, we need to sample a higher number of fish per family in order to 379

establish if either a general or family level index analysis is more appropriate. 380

381

Results showed no statistical differences in the physical condition of fish sampled in the defined sub-382

regions. However, in the Almirante area communities are subject of high anthropic pressures and 383

ecosystem degradation. An homogeneous physical condition of fish among locations does not indicate 384

an uniform physiological state. Research studies have found bioaccumulation of mercury in corals 385

inhabiting the sub-region. Consequently, fish and dolphins foraging in the area exposed to pollution 386

and might be bioaccumulating heavy metals. 387

388

It must be taken into account that the fishing method may have contributed to prey size bias. The 389

tendency of capturing smaller fish in some sub-regions in our study might be linked to the fishing 390

technique, since within the inmost region of the Archipelago sampling was conducted using fishing 391

traps instead of fishing nets. Fishing traps were designed in a way they would reside in the benthic area 392

and the dimensions of the trap entrance could not allow larger fish to enter. Moreover, the barcoding 393

approach generated some taxonomic uncertainty perhaps due hybridization among fish species; further, 394

when realizing matches on NCBI we were only introducing the COI gene portion when this database 395

(19)

19 contains entire genomes. Thence, the COI gene amplified portion could attach to any part of a species 396

genome. 397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

(20)

20

CONCLUSIONS

419

Average fish length measurements differ between locations and habitats, showing smaller fish 420

(juveniles) in mangroves areas and adults in coral reef and off-shore zones. The later might be 421

influencing dolphin distribution in the study area. The “sub-region” Popa 1 is now considered as the 422

nursery for preference over Dolphin Bay. This shift might be related to pressures from the dolphin 423

watching industry, or to unknown related factors. Health assesment index results also indicate 424

differential physical conditions of fish communities along the Archipelago vary between habitats. 425

Moreover, we have concerns regarding the Almirante locality; hence dolphins could be foraging in this 426

intervened ecosystem and acquiring pollutants and heavy metals from prey. It is crucial to conduct 427

stable isotope and heavy metal concentration analyses in prey and predator to determine the overall 428

status of the local food web, and conceive plausible conservation plans. 429

430

431

432

433

AKNOWLEDGMENTS

434

We thank The Rufford Foundation and The Society for Marine Mammalogy for their financial support; 435

The Smithsonian Tropical Institution for Research (STRI) for facility and material assistance; 436

researchers Carlos Polo Silva, Mónica Gamboa, and Betzi Perez for their collaboration and 437

participation on the project.; and student Camila Martinez who helped with the R-Studio analyses. 438

439

(21)

21

SUPPLEMENTARY DATA

441

442

Table 1.Potential prey items of bottlenose dolphins (T. truncatus) in Bocas del Toro Archipelago 443

grouped by habitat type. 444

Locality Family Number of

samples

Percentage of occurrence Mangrove – Sea

grass bed

Haemulidae Lutjanidae Unknown

3 14 17

34

8.82 41.18 50.00

100 Coral reef Chaetodontidae

Lutjanidae Scarinae Scombridae Sparidae Unknown

12 4 3 1 1 22

43

27.91 9.30 6.98 2.32 2.32 51.16

99.99

Unknown Carangidae

Haemulidae Unkown

30 1 5

36

83.33 2.78 13.89

100 (n = 113)

445

446

447

448

449

450

451

452

(22)

22

Table 2.Potential prey items of bottlenose dolphins (T. truncatus) in Bocas del Toro Archipelago 454

grouped by locality. 455

Locality Family Number of

samples

Percentage of occurrence

ALMIRANTE Carangidae

Haemulidae Unknown

23 1 11

35

65.71 2.86 31.43

100 BOCAS TORITO Haemulidae

Lutjanidae Unknown

2 11

6 19

10.53 57.89 31.58

100 BUENA

ESPERANZA

Haemulidae Lutjanidae Unknown

1 3 11

15

6.67 20.00 73.33

100 CAYO CORAL Lutjanidae

Scarinae Scombridae Sparidae Unknown

4 2 1 1 2

10

40.00 20.00 10.00 10.00 20.00

100 DOLPHIN BAY Chaetodontidae

Scarinae Unknown

7 1 14

22

31.82 4.54 63.54

100

POPA 1 Chaetodontidae 5

5

100 100

SAN CRISTOBAL Carangidae 7

7

100 100

(23)

Biología & Economía 23 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 T ab le 3 . H eal th inde xe s gr oupe d by loc al it y, habi tat ty pe , f is h fam il y and si ze ( M V : M ean val ue , SD : St andar d de vi at ion) . Me an v al ue Me an v al ue Lo ca lit y GS I HS I FI CF Ha bi ta t ty pe GS I HS I FI CF Al m ir an te Bo ca s T or ito Bu en a Es pe ra nz a Ca yo c or al Do lp hi n B ay Po pa 1 Sa n C ris to ba l 0. 644 7 0. 933 1 0. 969 0 0. 727 0 0. 933 5 na na 0. 744 1 0. 940 4 0. 558 4 1. 448 0 1. 013 5 na na 3. 319 3 2. 692 4 1. 461 5 2. 415 2 2. 512 9 na na 0. 026 6 0. 023 1 0. 021 2 0. 025 3 0. 034 8 0. 048 4* Ma ng ro ve – Se a gr as s be d Co ra l re ef 0. 864 3 0. 828 6 0. 800 2 1. 058 9 2. 727 3 2. 385 5 0. 024 1 0. 031 3 MV 0. 841 5 0. 940 9 2. 480 3 0. 029 9 MV 0. 846 4 0. 929 6 2. 556 4 0. 027 7 SD 0. 145 7 0. 334 5 0. 669 4 0. 010 2 SD 0. 025 2 0. 182 9 0. 241 7 0. 005 1 *T he re w as on ly one s am pl e hav in g thi s val ue . T he re m ai ni ng sa m pl ed fi sh in th e ca te go ry h ad n o in de x va lu es. Me an v al ue Fi sh f am ily GS I HS I FI CF Ca ra ng id ae Ch ae to do nt id ae Ha em ul id ae Lu tja ni da e Sc ar in ae Sc om br id ae Sp ar id ae na na 0. 955 9 0. 728 7 1. 611 0 0. 130 0 0. 122 6 0. 953 0 0. 951 5 0. 550 0 0. 700 3 2. 253 6 0. 962 0 0. 516 6 4. 584 1 3. 940 7 1. 768 7 1. 260 6 3. 007 3 1. 474 6 3. 598 0 0. 025 9 0. 048 6 0. 021 3 0. 023 5 0. 029 6 0. 012 1 0. 028 8 MV 0. 709 6 0. 983 8 2. 804 8 0. 027 1 SD 0. 623 3 0. 591 8 1. 313 6 0. 011 1

(24)

24

LITERATURE CITED

472

473

Adams. S. M., Brown. A. M., & Goede. R. W. (1993). A quantitative health assessment index for rapid 474

evaluation of fish condition in the field. Transactions of the American Fisheries Society. 122: 475

63-73. 476

Allen, M. C., Read, a. J., Gaudet, J., & Sayigh, L. S. (2001). Fine-scale habitat selection of foraging 477

bottlenose dolphins Tursiops truncatus near Clearwater, Florida. Mar Ecol Prog Ser 222: 253– 478

264. 479

Barker D., Allan G.L., Rowland S.J. & Pickles J.M. (2002) A Guide to Acceptable Procedures 480

and Practices for Aquaculture and Fisheries Research. Port Stephens, NSW: NSW 481

Fisheries Animal Care and Ethics Committee, Port Stephens Fisheries Centre, New 482

South Wales. 61 pp. 483

Barragán-Barrera, D. C. ; May-Collado, L. J. ; Quiñones-Lebrón, S. G. & S. Caballero. (2013) 484

Population at risk: low genetic diversity in bottlenose dolphins of Bocas del Toro, Panama. 485

International Whaling Commission. SC/65a/SM15: 1–11. 486

Barragán-Barrera, D. C., Islas-Villanueva, V., May-Collado, L. & Caballero S. (2015) Isolated in the 487

Caribbean: Low genetic diversity of bottlenose dolphin population in Bocas del Toro, 488

Caribbean Panama. International Whaling Commission. SC/66a/SM13: 1–12. 489

Berry, K.L.E., Seemann, J., Dellwig, O., Struck, U., Wild, C., & Leinfelder, R.R. (2013). Sources and 490

spatial distribution of heavy metals in scleractinian coral tissues and sediments from the Bocas 491

del Toro Archipelago, Panama. Environ Monit Assess. 185: 9089–9099. 492

Blanco, C., Salomón, O., & Raga, J. A. (2001). Diet of the bottlenose dolphin (Tursiops truncatus) in 493

the Western Mediterranean Sea. J. Mar. Biol. Ass. U.K. 81: 1053–1058. 494

(25)

25 Blessing, J. J., Marshall, J. C., & Balcombe, S. R. (2010). Humane killing of fishes for scientific

495

research: a comparison of two methods. Journal of Fish Biology. 76 (10): 2571-2577. 496

Bolver, T., & Connolly, P. L. (1989). The selection of suitable indices for the measurement and 497

analysis of fish condition. J. Fish Biol. 34: 171-182. 498

Bowen, W. D. (1997). Role of marine mammals in aquatic ecosystems. Mar Ecol Prog Ser, 158: 499

267-274. 500

Browning, N. E., Cockcroft, V. G., & Worthy, G. A. J. (2014). Resource partitioning among South 501

African delphinids. Journal of Experimental Marine Biology and Ecology 457:15–21. 502

D’Croz, L., Del Rosario, J. B., & Góndola, P. (2005). The effect of fresh water runoff on the 503

distribution of dissolved inorganic nutrients and plankton in the Bocas del Toro Archipelago, 504

Caribbean Panama. Caribbean Journal of Science 41(3):414–429. 505

Das, K., Lepoint, G., Leroy, Y., & Bouquegneau, J. M. (2003). Marine mammals from the southern 506

North Sea: feeding ecology data from δ13C and δ15N measurements. Mar Ecol Prog Ser 263: 507

287–298. 508

Ford, J. K., Ellis, G. M., Barrett-Lennard, L. G., Morton, A. B., Palm, R. S., & Balcomb, K. C. (1998). 509

Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal 510

British Columbia and adjacent waters. Can. J. Zool. 76(8): 1456–1471. 511

Guzmán, H. M., & Guevara, C. A. (1998). Arrecifes coralinos de Bocas del Toro, Panama: I. 512

Distribución, estructura y estado de conservación de los arrecifes continentales de la Laguna 513

de Chiriqui y la Bahia Almirante. Rev. Biol. Trop. 46(3): 601–623. 514

Hooker, S. K., Iverson, S. J., Ostrom, P., & Smith, S. C. (2001). Diet of northern bottlenose whales 515

inferred from fatty-acid and stable-isotope analyses of biopsy samples. Can. J. Zool. 79(8): 516

1442–1454. 517

(26)

26 Ingram, S. N., & Rogan, E. (2002). Identifying critical areas and habitat preferences of bottlenose 518

dolphins Tursiops truncatus. Marine Ecology Progress Series, 244, 247–255. 519

May-Collado, L. J. (2013). Conservation status of the dolphins of Bocas del Toro: 2004–2012. 520

May-Collado, L., Barragán-Barrera, D., Quiñones, S., & Aquino-Reynoso, W. (2012). Dolphin 521

watching boats impact on habitat use and communication of bottlenose dolphins of Bocas del 522

Toro, Panama during 2004, 2006–2010. International Whaling Commission, SC/64/WW2. 523

May-Collado, L. J., Quiñones-Lebrón, S. G., Barragán-Barrera, D. C., Palacios, J. D., & Gamboa-524

Poveda, M. (2014). The dolphin watching industry of Bocas del Toro continues impacting the 525

resident bottlenose dolphin population. International Whaling Comission, Slovenia. 526

SC/65b/WW06. 527

Riccialdelli, L., Newsome, S. D., Fogel, M. L., & Goodall, R. N. P. (2010). Isotopic assessment of prey 528

and habitat preferences of a cetacean community in the southwestern South Atlantic Ocean. 529

Mar Ecol Prog Ser 418: 235–248. 530

Rossman, S., Ostrom, P. H., Stolen, M., Barros, N. B., Gandhi, H., Stricker, C. A., & Wells, R. S. 531

(2015). Individual specialization in the foraging habits of female bottlenose dolphins living in 532

a trophically diverse and habitat rich estuary. Oecologia 178(2): 415–425. 533

Seemann, J., González, C.T., Carballo-Bolaños, R., Berry, K., Heiss, G.A. Struck, U., & Leinfelder, 534

R.R. (2013). Assessing the ecological effects of human impacts on coral reefs in Bocas del 535

Toro, Panama. Envion Monit Assess. 536

Tezanos-Pinto, G. & Baker, C. S. 2011. Short-term reactions and long-term responses of bottlenose 537

dolphins (Tursiops truncatus) to remote biopsy. New Zealand Journal of Marine and 538

Freshwater Research. 1: 1–17. 539

(27)

27 Trejos L., L. & May-Collado, L. J. (2015). Bottlenose dolphins Tursiops truncatus strandings in Bocas 540

del Toro caused by boat strikes and fishing entanglement. International Whaling Commission 541

2015. SC/66a/WW7: 1-5. 542

Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R., & Hebert, P. D. N. (2005). DNA barcoding 543

Australia’s fish species. Phil. Trans. R. Soc. B, 360: 1847-1857. 544