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Evaluating the constraints governing activity patterns of a coastal marine top predator

Abstract

How animals partition activity throughout the day is influenced by processes that affect supply and obtainability of resources. However, as resource supply and usability are often entrained by the same diurnal pattern, it has been difficult to disentangle their relative importance. Given the strong influence that tide has on the distribution and accessibility of resources, intertidal systems present opportunities to examine questions surrounding the drivers of activity patterns. Here, we used multisensory biologgers to study the activity patterns of a coastal marine predator, sicklefin lemon sharks (Negaprion acutidens), in a tidally driven environment. Hidden Markov models were used to identify relatively high and low locomotory activity states, which were used as proxies for behavioural–activity states and to examine the factors underpinning variation in activity patterns. Although tide governs the spatial distributions of this species and showed some effect on sharks’ activity, diurnal light patterns were the predominant factor influencing behavioural-activity patterns, with the probability of high activity peaking overnight. Temperature and body size also had minor negative influences on the probability of animals being in the high-activity state. Interestingly, sharks were least likely to be in a high-activity state during high tide, a time of presumed high resource supply, contradicting the common assumption that this species forages during high tide. We suggest that despite the importance of the accessibility of resources, functional constraints, such as sensory (e.g., visual) and mechanical (e.g., swimming) performance ultimately underpin the activity patterns of intertidal marine predators through their influence on foraging success.

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Availability of data and material

The datasets generated and/or analysed during the current study are available from the corresponding author on a reasonable request.

Code availability

The R code used for data analysis in the current study are available from the corresponding author on a reasonable request.

References

  • Adam T, Griffiths CA, Leos-Barajas V, Meese EN, Lowe CG, Blackwell PG, Righton D, Langrock R (2019) Joint modelling of multi-scale animal movement data using hierarchical hidden Markov models. Methods Ecol Evol 10:1536–1550

    Google Scholar 

  • Alexander RM (2005) Models and the scaling of energy costs for locomotion. J Exp Biol 208:1645–1652

    PubMed  Google Scholar 

  • Anderson TL, Semlitsch RD (2016) Top predators and habitat complexity alter an intraguild predation module in pond communities. J Anim Ecol 85:548–558

    PubMed  Google Scholar 

  • Andrzejaczek S, Gleiss AC, Lear KO, Pattiaratchi CB, Chapple TK, Meekan MG (2019) Biologging tags reveal links between fine-scale horizontal and vertical movement behaviors in tiger sharks (Galeocerdo cuvier). Front Marine Sci. https://doi.org/10.3389/fmars.2019.00229

    Article  Google Scholar 

  • Angilletta MJ Jr, Angilletta MJ (2009) Thermal adaptation: a theoretical and empirical synthesis. Oxford University Press, New York

    Google Scholar 

  • Angilletta MJ Jr, Niewiarowski PH, Navas CA (2002) The evolution of thermal physiology in ectotherms. J Therm Biol 27:249–268

    Google Scholar 

  • Baldwin B (1974) Behavioural thermoregulation heat loss from animals and man: assessment and control. Butterworth and Co., London, pp 97–117

    Google Scholar 

  • Bauer S, Klaassen M (2013) Mechanistic models of animal migration behaviour–their diversity, structure and use. J Anim Ecol 82:498–508

    PubMed  PubMed Central  Google Scholar 

  • Berger-Tal O, Polak T, Oron A, Lubin Y, Kotler BP, Saltz D (2011) Integrating animal behavior and conservation biology: a conceptual framework. Behav Ecol 22:236–239

    Google Scholar 

  • Blair C (2009) Daily activity patterns and microhabitat use of a heliothermic lizard, Ameiva exsul (Squamata: Teiidae) in Puerto Rico. South Am J Herpetol 4:179–186

    Google Scholar 

  • Bosiger YJ, McCormick MI (2014) Temporal links in daily activity patterns between coral reef predators and their prey. PLoS ONE 9:e111723

    PubMed  PubMed Central  Google Scholar 

  • Bozinovic F, Catalan TP, Estay SA, Sabat P (2013) Acclimation to daily thermal variability drives the metabolic performance curve. Evol Ecol Res 15:579–587

    Google Scholar 

  • Brewster LR, Dale JJ, Guttridge TL, Gruber SH, Hansell AC, Elliott M, Cowx IG, Whitney NM, Gleiss AC (2018) Development and application of a machine learning algorithm for classification of elasmobranch behaviour from accelerometry data. Mar Biol 165:62

    CAS  PubMed  PubMed Central  Google Scholar 

  • Bullock RW, Guttridge TL, Cowx IG, Elliott M, Gruber SH (2015) The behaviour and recovery of juvenile lemon sharks Negaprion brevirostris in response to external accelerometer tag attachment. J Fish Biol 87:1342–1354

    CAS  PubMed  Google Scholar 

  • Carlisle AB, Starr RM (2009) Habitat use, residency, and seasonal distribution of female leopard sharks Triakis semifasciata in Elkhorn Slough, California. Mar Ecol Prog Ser 380:213–228

    Google Scholar 

  • Carter N, Jasny M, Gurung B, Liu J (2015) Impacts of people and tigers on leopard spatiotemporal activity patterns in a global biodiversity hotspot. Global Ecol Conserv 3:149–162

    Google Scholar 

  • Chivers LS, Hatch SA, Elliott KH (2015) Accelerometry reveals an impact of short-term tagging on seabird activity budgets. Condor Ornitholl Appl 118:159–168

    Google Scholar 

  • Ciechanowski M, Zając T, Biłas A, Dunajski R (2007) Spatiotemporal variation in activity of bat species differing in hunting tactics: effects of weather, moonlight, food abundance, and structural clutter. Can J Zool 85:1249–1263

    Google Scholar 

  • Clarke A (2004) Is there a universal temperature dependence of metabolism? Funct Ecol 18:252–256

    Google Scholar 

  • Cozzi G, Broekhuis F, McNutt JW, Turnbull LA, Macdonald DW, Schmid B (2012) Fear of the dark or dinner by moonlight? Reduced temporal partitioning among Africa’s large carnivores. Ecology 93:2590–2599

    PubMed  Google Scholar 

  • Cresswell W, Lind J, Quinn JL (2010) Predator-hunting success and prey vulnerability: quantifying the spatial scale over which lethal and non-lethal effects of predation occur. J Anim Ecol 79:556–562

    PubMed  Google Scholar 

  • Dean B, Freeman R, Kirk H, Leonard K, Phillips RA, Perrins CM, Guilford T (2013) Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviour. J R Soc Interf. https://doi.org/10.1098/rsif.2012.0570

    Article  Google Scholar 

  • Dill LM, Heithaus MR, Walters CJ (2003) Behaviorally mediated indirect interactions in marine communities and their conservation implications. Ecology 84:1151–1157. https://doi.org/10.1890/0012-9658

    Article  Google Scholar 

  • Diosdado JAV, Barker ZE, Hodges HR, Amory JR, Croft DP, Bell NJ, Codling EA (2015) Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system. Animal Biotele 3:15

    Google Scholar 

  • Egbert GD, Erofeeva SY (2002) Efficient inverse modeling of barotropic ocean tides. J Atmosph Oceanic Technol 19:183–204

    Google Scholar 

  • Elliott KH, Gaston AJ (2015) Diel vertical migration of prey and light availability constrain foraging in an Arctic seabird. Mar Biol 162:1739–1748

    Google Scholar 

  • Filmalter JD, Dagorn L, Cowley PD (2013) Spatial behaviour and site fidelity of the sicklefin lemon shark Negaprion acutidens in a remote Indian Ocean atoll. Mar Biol 160:2425–2436

    Google Scholar 

  • Funston P, Mills M, Biggs H (2001) Factors affecting the hunting success of male and female lions in the Kruger National Park. J Zool 253:419–431

    Google Scholar 

  • Gardiner JM, Atema J (2014) Flow sensing in sharks: lateral line contributions to navigation and prey capture Flow sensing in air and water. Springer, Lodone

    Google Scholar 

  • Garrity SD (1984) Some adaptations of gastropods to physical stress on a tropical rocky shore. Ecology 65:559–574

    Google Scholar 

  • Glanville E, Seebacher F (2006) Compensation for environmental change by complementary shifts of thermal sensitivity and thermoregulatory behaviour in an ectotherm. J Exp Biol 209:4869–4877

    CAS  PubMed  Google Scholar 

  • Glazier DS (2005) Beyond the ‘3/4-power law’: variation in the intra-and interspecific scaling of metabolic rate in animals. Biol Rev 80:611–662

    PubMed  Google Scholar 

  • Gleiss AC, Wilson RP, Shepard ELC (2011) Making overall dynamic body acceleration work: on the theory of acceleration as a proxy for energy expenditure. Methods Ecol Evol 2:23–33

    Google Scholar 

  • Gleiss AC, Wright S, Liebsch N, Wilson RP, Norman B (2013) Contrasting diel patterns in vertical movement and locomotor activity of whale sharks at Ningaloo Reef. Mar Biol 160:2981–2992

    CAS  Google Scholar 

  • Gruber S (1984) Bioenergetics of the captive and free-ranging lemon shark AAZPA. Ann Conf Proc pp 340–373

  • Guttridge TL, Gruber SH, Franks BR, Kessel ST, Gledhill KS, Uphill J, Krause J, Sims DW (2012) Deep danger: intra-specific predation risk influences habitat use and aggregation formation of juvenile lemon sharks Negaprion brevirostris. Mar Ecol Prog Ser 445:279–291

    Google Scholar 

  • Hammerschlag N, Skubel RA, Calich H, Nelson ER, Shiffman DS, Wester J, Macdonald CC, Cain S, Jennings L, Enchelmaier A (2017) Nocturnal and crepuscular behavior in elasmobranchs: a review of movement, habitat use, foraging, and reproduction in the dark. Bull Mar Sci 93:355–374

    Google Scholar 

  • Heithaus MR, Wirsing AJ, Burkholder D, Thomson J, Dill LM (2009) Towards a predictive framework for predator risk effects: the interaction of landscape features and prey escape tactics. J Anim Ecol 78:556–562

    PubMed  Google Scholar 

  • Heithaus MR, Wirsing AJ, Dill LM (2012) The ecological importance of intact top-predator populations: a synthesis of 15 years of research in a seagrass ecosystem. Marine Freshwater Res 63:1039–1050

    Google Scholar 

  • Hirzel AH, Le Lay G (2008) Habitat suitability modelling and niche theory. J Appl Ecol 45:1372–1381

    Google Scholar 

  • Hopcraft JGC, Sinclair A, Packer C (2005) Planning for success: serengeti lions seek prey accessibility rather than abundance. J Anim Ecol 74:559–566

    Google Scholar 

  • Hounslow JL, Brewster LR, Lear KO, Guttridge TL, Daly R, Whitney NM, Gleiss AC (2019) Assessing the effects of sampling frequency on behavioural classification of accelerometer data. J Exp Mar Biol Ecol 512:22–30

    Google Scholar 

  • Houston AI, McNamara JM (2014) Foraging currencies, metabolism and behavioural routines. J Anim Ecol 83:30–40

    PubMed  Google Scholar 

  • Huey RB, Kingsolver JG (1989) Evolution of thermal sensitivity of ectotherm performance. Trends Ecol Evol 4:131–135

    CAS  PubMed  Google Scholar 

  • Kim D (2007) Prey detection mechanism of elasmobranchs. Biosystems 87:322–331

    PubMed  Google Scholar 

  • Kleiber M (1973) Body size, conductance for animal heat flow and Newton’s law of cooling. Read Animal Energy 37:226–239

    Google Scholar 

  • Krebs JR, Inman AJ (1992) Learning and foraging: individuals, groups, and populations. Am Nat 140:S63–S84

    PubMed  Google Scholar 

  • Kronfeld-Schor N, Dayan T (2003) Partitioning of time as an ecological resource. Annu Rev Ecol Evol Syst 34:153–181

    Google Scholar 

  • Kunkel KE, Pletscher DH, Boyd DK, Ream RR, Fairchild MW (2004) Factors correlated with foraging behavior of wolves in and near Glacier National Park, Montana. J Wildl Manag 68:167–178

    Google Scholar 

  • Ladds MA, Thompson AP, Kadar J-P, Slip DJ, Hocking DP, Harcourt RG (2017) Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry. Animal Biotele 5:9

    Google Scholar 

  • Lea JSE, Humphries NE, von Brandis RG, Clarke CR, Sims DW (2016) Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design. Proc Royal Soc B 1:283

    Google Scholar 

  • Lea JS, Humphries NE, Bortoluzzi J, Daly R, von Brandis RG, Patel E, Patel E, Clarke CR, Sims DW (2020) At the turn of the tide: space use and habitat partitioning in two sympatric shark species is driven by tidal phase. Front Marine Sci 7:624

    Google Scholar 

  • Lear KO, Gleiss AC, Whitney NM (2018) Metabolic rates and the energetic cost of external tag attachment in juvenile blacktip sharks Carcharhinus limbatus. J Fish Biol 93:391–395

    CAS  PubMed  Google Scholar 

  • Lear KO, Whitney NM, Morgan DL, Brewster LR, Whitty JM, Poulakis GR, Scharer RM, Guttridge TL, Gleiss AC (2019) Thermal performance responses in free-ranging elasmobranchs depend on habitat use and body size. Oecologia 191:829–842

    PubMed  Google Scholar 

  • Leos-Barajas V, Photopoulou T, Langrock R, Patterson TA, Watanabe YY, Murgatroyd M, Papastamatiou YP (2016) Analysis of animal accelerometer data using hidden Markov models. Methods Ecol Evol 8:161–173. https://doi.org/10.1111/2041-210X.12657

    Article  Google Scholar 

  • Lima SL, Dill LM (1990) Behavioral decisions made under the risk of predation: a review and prospectus. Can J Zool 68:619–640

    Google Scholar 

  • Loarie SR, Tambling CJ, Asner GP (2013) Lion hunting behaviour and vegetation structure in an African savanna. Anim Behav 85:899–906

    Google Scholar 

  • Luo J, Serafy JE, Sponaugle S, Teare PB, Kieckbusch D (2009) Movement of gray snapper Lutjanus griseus among subtropical seagrass, mangrove, and coral reef habitats. Mar Ecol Prog Ser 380:255–269

    Google Scholar 

  • Martins A, Heupel M, Bierwagen S, Chin A, Simpfendorfer C (2020) Diurnal activity patterns and habitat use of juvenile Pastinachus ater in a coral reef flat environment. PLoS ONE 15:e0228280

    CAS  PubMed  PubMed Central  Google Scholar 

  • Matern SA, Cech JJ, Hopkins TE (2000) Diel movements of bat rays, Myliobatis californica, in Tomales Bay, California: evidence for behavioral thermoregulation? Environ Biol Fishes 58:173–182

    Google Scholar 

  • McConkey KR, Bell BD (2005) Activity and habitat use of waders are influenced by tide, time and weather. Emu-Austral Ornithol 105:331–340

    Google Scholar 

  • McMahon TE, Matter WJ (2006) Linking habitat selection, emigration and population dynamics of freshwater fishes: a synthesis of ideas and approaches. Ecol Freshw Fish 15:200–210

    Google Scholar 

  • Michelot T, Langrock R, Patterson TA (2016) moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models. Methods Ecol Evol 7:1308–1315

    Google Scholar 

  • Mysterud A, Ims RA (1998) Functional responses in habitat use: availability influences relative use in trade-off situations. Ecology 79:1435–1441

    Google Scholar 

  • Naef-Daenzer L, Naef-Daenzer B, Nager RG (2000) Prey selection and foraging performance of breeding Great Tits Parus major in relation to food availability. J Avian Biol 31:206–214

    Google Scholar 

  • Nakamura I, Matsumoto R, Sato K (2020) Body temperature stability observed in the whale sharks, the world’s largest fish. J Exp Biol 1:223

    Google Scholar 

  • Ollivier F, Samuelson D, Brooks D, Lewis P, Kallberg M, Komáromy A (2004) Comparative morphology of the tapetum lucidum (among selected species). Vet Ophthalmol 7:11–22

    CAS  PubMed  Google Scholar 

  • Papastamatiou YP, Watanabe YY, Bradley D, Dee LE, Weng K, Lowe CG, Caselle JE (2015) Drivers of daily routines in an ectothermic marine predator: hunt warm, rest warmer? PLoS ONE 10:e0127807

    PubMed  PubMed Central  Google Scholar 

  • Papastamatiou YP, Watanabe YY, Demšar U, Leos-Barajas V, Bradley D, Langrock R, Weng K, Lowe CG, Friedlander AM, Caselle JE (2018) Activity seascapes highlight central place foraging strategies in marine predators that never stop swimming. Move Ecol 6:9

    Google Scholar 

  • Patterson TA, Basson M, Bravington MV, Gunn JS (2009) Classifying movement behaviour in relation to environmental conditions using hidden Markov models. J Anim Ecol 78:1113–1123

    PubMed  Google Scholar 

  • Patterson TA, Hobday AJ, Evans K, Eveson JP, Davies CR (2018) Southern bluefin tuna habitat use and residence patterns in the Great Australia Bight. Deep Sea Res Part II 157:169–178

    Google Scholar 

  • Penteriani V, Kuparinen A, del Mar DM, Palomares F, López-Bao JV, Fedriani JM, Calzada J, Moreno S, Villafuerte R, Campioni L (2013) Responses of a top and a meso predator and their prey to moon phases. Oecologia 173:753–766

    PubMed  Google Scholar 

  • Pihl L, Cattrijsse A, Codling I, Mathieson S, McLusky D, Roberts C (2002) Habitat use by fishes in estuaries and other brackish areas. In: Elliot M, Hemingway K (eds) Fishes in Estuaries. Blackwell Science Ltd, Unitd Kingdom, pp 10–53

    Google Scholar 

  • Pohle J, Langrock R, van Beest FM, Schmidt NM (2017) Selecting the number of states in hidden Markov models: pragmatic solutions illustrated using animal movement. J Agri Biol Environ Stat 22:270–293

    Google Scholar 

  • Puckett KJ, Dill L (1985) The energetics of feeding territoriality in juvenile coho salmon (Oncorhynchus kisutch). Behaviour 92:97–111

    Google Scholar 

  • Pulliam HR (1974) On the theory of optimal diets. Am Nat 108:59–74

    Google Scholar 

  • Puttick GM (1979) Foraging behaviour and activity budgets of Curlew Sandpipers. Ardea 67:111–122

    Google Scholar 

  • Qasem L, Cardew A, Wilson A, Griffiths I, Halsey LG, Shepard ELC, Gleiss AC, Wilson R (2012) Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector? PLoS ONE 7:e31187

    CAS  PubMed  PubMed Central  Google Scholar 

  • Quinn J, Cresswell W (2004) Predator hunting behaviour and prey vulnerability. J Anim Ecol 73:143–154

    Google Scholar 

  • R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; https://www.r-project.org/.

  • Rooker J, Dennis G (1991) Diel, lunar and seasonal changes in a mangrove fish assemblage off southwestern Puerto Rico. Bull Mar Sci 49:684–698

    Google Scholar 

  • Sabando MA, Rieucau G, Bradley D, Caselle JE, Papastamatiou YP (2020) Habitat-specific inter and intraspecific behavioral interactions among reef sharks. Oecologia. https://doi.org/10.1007/s00442-020-04676-y

    Article  PubMed  Google Scholar 

  • Sakamoto KQ, Sato K, Ishizuka M, Watanuki Y, Takahashi A, Daunt F, Wanless S (2009) Can ethograms be automatically generated using body acceleration data from free-ranging birds? PLoS ONE 4:e5379

    PubMed  PubMed Central  Google Scholar 

  • Šálek M, Kreisinger J, Sedláček F, Albrecht T (2010) Do prey densities determine preferences of mammalian predators for habitat edges in an agricultural landscape? Landscape Urban Plan 98:86–91

    Google Scholar 

  • Sato K, Shiomi K, Watanabe Y, Watanuki Y, Takahashi A, Ponganis PJ (2009) Scaling of swim speed and stroke frequency in geometrically similar penguins: they swim optimally to minimize cost of transport. Proc Royal Soc B Biol Sci 277:707–714

    Google Scholar 

  • Shepard EL, Wilson RP, Quintana F, Laich AG, Liebsch N, Albareda DA, Halsey LG, Gleiss A, Morgan DT, Myers AE (2008) Identification of animal movement patterns using tri-axial accelerometry. Endangered Sp Res 10:47–60

    Google Scholar 

  • Sims DW (2000) Can threshold foraging responses of basking sharks be used to estimate their metabolic rate? Mar Ecol Prog Ser 200:289–296

    Google Scholar 

  • Sims D, Nash J, Morritt D (2001) Movements and activity of male and female dogfish in a tidal sea lough: alternative behavioural strategies and apparent sexual segregation. Mar Biol 139:1165–1175

    Google Scholar 

  • Speed CW, Meekan MG, Field IC, McMahon CR, Bradshaw CJA (2012) Heat-seeking sharks: support for behavioural thermoregulation in reef sharks. Mar Ecol Prog Ser 463:231–244

    Google Scholar 

  • Stephens DW, Krebs JR (1986) Foraging theory. Princeton University Press, Princeton

    Google Scholar 

  • Stillman J, Barnwell F (2004) Relationship of daily and circatidal activity rhythms of the fiddler crab, Uca princeps, to the harmonic structure of semidiurnal and mixed tides. Mar Biol 144:473–482

    Google Scholar 

  • Stoddart DR, Coe MJ, Fosberg FR (1979) D’Arros and St Joseph, Amirante Islands. Atoll Res Bull, Islands

    Google Scholar 

  • Strang K, Steudel K (1990) Explaining the scaling of transport costs: the role of stride frequency and stride length. J Zool 221:343–358

    Google Scholar 

  • Sunday JM, Bates AE, Kearney MR, Colwell RK, Dulvy NK, Longino JT, Huey RB (2014) Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation. Proc Natl Acad Sci 111:5610–5615

    CAS  PubMed  PubMed Central  Google Scholar 

  • Vianna GM, Meekan MG, Meeuwig JJ, Speed CW (2013) Environmental influences on patterns of vertical movement and site fidelity of grey reef sharks (Carcharhinus amblyrhynchos) at aggregation sites. PLoS ONE 8:e60331

    CAS  PubMed  PubMed Central  Google Scholar 

  • Weng KC, O’Sullivan JB, Lowe CG, Winkler CE, Dewar H, Block BA (2007) Movements, behavior and habitat preferences of juvenile white sharks Carcharodon carcharias in the eastern Pacific. Mar Ecol Prog Ser 338:211–224

    Google Scholar 

  • West GB, Brown JH, Enquist BJ (1997) A general model for the origin of allometric scaling laws in biology. Science 276:122–126

    CAS  PubMed  Google Scholar 

  • White CR, Seymour RS (2003) Mammalian basal metabolic rate is proportional to body mass2/3. Proc Natl Acad Sci 100:4046–4049

    CAS  PubMed  PubMed Central  Google Scholar 

  • White W, Platell M, Potter I (2004) Comparisons between the diets of four abundant species of elasmobranchs in a subtropical embayment: implications for resource partitioning. Mar Biol 144:439–448

    Google Scholar 

  • Whitmore BM, White CF, Gleiss AC, Whitney NM (2016) A float-release package for recovering data-loggers from wild sharks. J Exp Mar Biol Ecol 475:49–53

    Google Scholar 

  • Wilson RP, White CR, Quintana F, Halsey LG, Liebsch N, Martin GR, Butler PJ (2006) Moving towards acceleration for estimates of activity-specific metabolic rate in free-living animals: the case of the cormorant. J Anim Ecol 75:1081–1090

    PubMed  Google Scholar 

  • Wilson RP, Liebsch N, Davies IM, Quintana F, Weimerskirch H, Storch S, Lucke K, Siebert U, Zankl S, Müller G (2007) All at sea with animal tracks; methodological and analytical solutions for the resolution of movement. Deep Sea Res Part II 54:193–210

    Google Scholar 

  • Zucchini W, MacDonald IL, Langrock R (2016) Hidden Markov models for time series: an introduction using R. Chapman and Hall/CRC, Cleveland

    Google Scholar 

  • Sundström LF, Gruber SH (1998) Using speed-sensing transmitters to construct a bioenergetics model for subadult lemon sharks, Negaprion brevirostris (Poey), in the field. Hydrobiologia 371:241–247. https://doi.org/10.1023/A:1017031406947

    Article  Google Scholar 

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Acknowledgements

We would like to thank C. Keating-Daly and J. Hounslow for assitance in tagging and data collection. We thank J. Lea for modelled tidal data and T. Adam, J. Pohle, M. Ötting, and S. Mews for assistance in data analysis. Additionally, we thank reviewers for their valuable comments which helped to improve the quality of this manuscript. We thank Save Our Seas Foundation for supporting and accomodating our stay at D’Arros Research Centre.

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This work was supported by Save Our Seas Foundation. E. Byrnes was supported under the Murdoch University IPRS funding scheme.

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EEB, RD, ACG conceived the study and planned fieldwork. EEB and RD conducted fieldwork. EEB, VL-B, and RL conducted data analysis and interpretation. The first draft of the manuscript was written by EEB and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Evan E. Byrnes.

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All research was approved by and conducted with the knowledge of the Seychelles Ministry of Environment, Energy and Climate Change and animal use was conducted under a Murdoch University Animal Ethics permit (R2927/17).

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Byrnes, E.E., Daly, R., Leos-Barajas, V. et al. Evaluating the constraints governing activity patterns of a coastal marine top predator. Mar Biol 168, 11 (2021). https://doi.org/10.1007/s00227-020-03803-w

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