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Using fisheries data to model the oceanic habitats of juvenile silky shark (Carcharhinus falciformis) in the tropical eastern Atlantic Ocean

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Abstract

Investigating the relationship between species and environmental conditions is key for the correct management of highly migratory large pelagic species like silky shark (Carcharhinus falciformis). This species is currently ranked as vulnerable by the International Union for Conservation of Nature and the population trend may be decreasing globally. Tuna fisheries annually catch around 5 million tons worldwide but may have effects on the ecosystem, including impacts on certain sensitive non-target species. We provide the first insights into the environmental preferences of silky shark in the Atlantic Ocean by modelling their presence from tropical tuna purse seine observer data (~ 7500 fishing sets between 2003 and 2015) with a set of biotic and abiotic oceanographic factors, spatial–temporal terms and fishing operation variables. Oceanographic data (sea surface temperature, sea surface temperature change, salinity, sea surface height, chlorophyll-a, chlorophyll-a change, oxygen, and current information such as speed, direction and eddy kinetic energy) were downloaded and processed from the EU Copernicus Marine Environment Monitoring Service. Results provide information on the hotspots dynamics of silky shark as well as its habitat preferences. Models detected a significant relationship between seasonal upwelling events, mesoscale features and silky shark presence and suggested strong interaction between productive systems and the spatial–temporal distribution of the species. The model also highlighted both persistent (i.e. Gabon) and temporary areas (i.e. Guinea and southern-central tropical Atlantic Ocean) for silky shark in the region. This information could be used to assist tuna regional fisheries management organizations in the conservation and management of this vulnerable non-target species.

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Notes

  1. Man-made floating objects usually constructed and deployed at sea as bamboo rafts with an underwater part with the aim of attracting target species.

References

  • Abrahms B, Scales KL, Hazen EL, Bograd SJ, Schick RS, Robinson PW, Costa DP (2018) Mesoscale activity facilitates energy gain in a top predator. Proc R Soc B. https://doi.org/10.1098/rspb.2018.1101

    Article  PubMed  Google Scholar 

  • Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723. https://doi.org/10.1109/tac.1974.1100705

    Article  Google Scholar 

  • Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43:1223–1232. https://doi.org/10.1111/j.1365-2664.2006.01214.x

    Article  Google Scholar 

  • Amandè M, Chassot E, Chavance P, Pianet R (2008) Silky shark (Carcharhinus falciformis) bycatch in the French tuna purse-seine fishery of the Indian Ocean IOTC Proceedings IOTC-2008-WPEB-16: 22p

  • Amandè MJ et al (2010) Bycatch of the European purse seine tuna fishery in the Atlantic Ocean for the 2003–2007 period. Aquat Living Resour 23:353–362

    Article  Google Scholar 

  • Andrade HA (2003) The relationship between the skipjack tuna (Katsuwonus pelamis) fishery and seasonal temperature variability in the south-western Atlantic. Fish Oceanogr 12:10–18. https://doi.org/10.1046/j.1365-2419.2003.00220.x

    Article  Google Scholar 

  • Baker MR, Hollowed AB (2014) Delineating ecological regions in marine systems: Integrating physical structure and community composition toinform spatial management in the eastern Bering Sea. Deep Sea Res Part II Top Stud Oceanogr 109:215–240

    Article  Google Scholar 

  • Bakun A (1996) Patterns in the ocean: ocean processes and marine population dynamics. California Sea Grant College System/NOAA/Centro de Investigaciones Biologicas del Noroeste, La Paz, Mexico. 323 pp, ISBN 1-888691-01-8

  • Belkin IM et al (2014) Fronts, fish, and predators. Deep Sea Res II 107:1–2. https://doi.org/10.1016/j.dsr2.2014.07.009

    Article  Google Scholar 

  • Belkin IM, O'Reilly JE (2009) An algorithm for oceanic front detection in chlorophyll and SST satellite imagery. J Mar Syst 78:319–326. https://doi.org/10.1016/j.jmarsys.2008.11.018

    Article  Google Scholar 

  • Benitez-Nelson CR et al (2007) Mesoscale eddies drive increased silica export in the subtropical Pacific Ocean. Science 316:1017–1021. https://doi.org/10.1126/science.1136221

    Article  CAS  PubMed  Google Scholar 

  • Bigelow KA, Boggs CH, He XI (1999) Environmental effects on swordfish and blue shark catch rates in the US North Pacific longline fishery. Fish Oceanogr 8:178–198. https://doi.org/10.1046/j.1365-2419.1999.00105.x

    Article  Google Scholar 

  • Birkmanis CA, Partridge JC, Simmons LW, Heupel MR, Sequeira AMM (2020) Shark conservation hindered by lack of habitat protection. Glob Ecol Conserv 21:e00862. https://doi.org/10.1016/j.gecco.2019.e00862

    Article  Google Scholar 

  • BjØrnstad ON, Falck W (2001) Nonparametric spatial covariance functions: estimation and testing. Environ Ecol Stat 8:53–70. https://doi.org/10.1023/a:1009601932481

    Article  Google Scholar 

  • Bonfil R (1993) Biological paramenters of commercially exploited silky sharks. Carcharhinus falciformis, from the Campeche Bank, Mexico NOAA Tech Rep NMFS 115:73–86

  • Branstetter S (1987) Age, growth and reproductive biology of the silky shark, Carcharhinus falciformis, and the scalloped hammerhead, Sphyrna lewini, from the northwestern Gulf of Mexico. Environ Biol Fishes 19:161–173. https://doi.org/10.1007/BF00005346

    Article  Google Scholar 

  • Brodersen KH, Gallusser F, Koehler J, Remy N, Scott SL (2015) Inferring causal impact using Bayesian structural time-series models. Ann Appl Stat 9:247–274

    Article  Google Scholar 

  • Brodie S, Hobday AJ, Smith JA, Everett JD, Taylor MD, Gray CA, Suthers IM (2015) Modelling the oceanic habitats of two pelagic species using recreational fisheries data. Fish Oceanogr 24:463–477. https://doi.org/10.1111/fog.12122

    Article  Google Scholar 

  • Brodie S et al (2018) Integrating dynamic subsurface habitat metrics into species distribution models. Front Mar Sci. https://doi.org/10.3389/fmars.2018.00219

    Article  Google Scholar 

  • Cabrera-Chávez-Costa AA, Galván-Magaña F, Escobar-Sánchez O (2010) Food habits of the silky shark Carcharhinus falciformis (Müller & Henle, 1839) off the western coast of Baja California Sur, Mexico. J Appl Ichthyol 26:499–503. https://doi.org/10.1111/j.1439-0426.2010.01482.x

    Article  Google Scholar 

  • Cayula J-F, Cornillon P (1992) Edge detection algorithm for SST images. J Atmos Oceanic Technol 9:67–80. https://doi.org/10.1175/1520-0426(1992)009%3c0067:edafsi%3e2.0.co;2

    Article  Google Scholar 

  • Chassot E et al (2011) Satellite remote sensing for an ecosystem approach to fisheries management. ICES J Mar Sci 68:651–666. https://doi.org/10.1093/icesjms/fsq195

    Article  Google Scholar 

  • Clarke S et al (2015) Report of the Pacific shark life history expert panel workshop, 28–30 April 2015 WCPFC-SC11–2015/EB-IP-13

  • Clarke S, Langley A, Lennert-Cody C, Aires-da-Silva A, Maunder M (2018) Pacific-wide silky shark (Carcharhinus falciformis) Stock Status Assessment WCPFC Scientific Committee 14th Regular Session WCPFC-SC14–2018/SA-WP-08, Busan, Republic of Korea:137

  • Coelho R et al (2019) Improving scientific advice for the conservation and management of oceanic sharks and rays: final report-Study European Commission EA-02-19-274-EN-N:658. https://doi.org/10.2826/229340

  • Cortés E, Arocha F, Beerkircher L, Carvalho F, Domingo A, Heuperl M, Holtzhausen H, Santos MN, Ribera M, Simpfendorfer C (2010) Ecological risk assessment of pelagic sharks caught in Atlantic pelagic longline fisheries. Aquat Living Res 23:25–34. https://doi.org/10.1051/alr/2009044

    Article  Google Scholar 

  • Cortés-Avizanda A, Almaraz P, Carrete M, Sánchez-Zapata JA, Delgado A, Hiraldo F, Donázar JA (2011) Spatial heterogeneity in resource distribution promotes facultative sociality in two trans-Saharan migratory birds. PLoS ONE 6:e21016. https://doi.org/10.1371/journal.pone.0021016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cortés E, Brown CA, Beerhircher L (2007) Relative abundance of pelagic sharks in the western north Atlantic Ocean, including the Gulf of Mexico and Caribbean Sea. Gulf Carib Res 19:37–52

    Google Scholar 

  • Dagorn L, Holland KN, Restrepo V, Moreno G (2012) Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems? Fish Fish. https://doi.org/10.1111/j.1467-2979.2012.00478.x

    Article  Google Scholar 

  • Dell J, Wilcox C, Hobday AJ (2011) Estimation of yellowfin tuna (Thunnus albacares) habitat in waters adjacent to Australia’s East Coast: making the most of commercial catch data. Fish Oceanogr 20:383–396. https://doi.org/10.1111/j.1365-2419.2011.00591.x

    Article  Google Scholar 

  • Dewar H et al (2018) Basking shark (Cetorhinus maximus) movements in the eastern north Pacific determined using satellite telemetry. Front Mar Sci. https://doi.org/10.3389/fmars.2018.00163

    Article  Google Scholar 

  • Dobson AJ (1983) Introduction to statistical modelling. Chapman and Hall, London

    Book  Google Scholar 

  • Dormann CF et al (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46. https://doi.org/10.1111/j.1600-0587.2012.07348.x

    Article  Google Scholar 

  • Druon J-N, Chassot E, Murua H, Lopez J (2017) Skipjack tuna availability for purse seine fisheries is driven by suitable feeding habitat dynamics in the Atlantic and Indian Oceans. Front Mar Sci. https://doi.org/10.3389/fmars.2017.00315

    Article  Google Scholar 

  • Duffy LM, Lennert-Cody CE, Olson RJ, Minte-Vera CV, Griffiths SP (2019) Assessing vulnerability of bycatch species in the tuna purse-seine fisheries of the eastern Pacific Ocean. Fish Res 219:105316. https://doi.org/10.1016/j.fishres.2019.105316

    Article  Google Scholar 

  • Eddy C, Brill R, Bernal D (2016) Rates of at-vessel mortality and post-release survival of pelagic sharks captured with tuna purse seines around drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean. Fish Res 174:109–117. https://doi.org/10.1016/j.fishres.2015.09.008

    Article  Google Scholar 

  • Elith J et al (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151. https://doi.org/10.1111/j.2006.0906-7590.04596.x

    Article  Google Scholar 

  • Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159

    Article  Google Scholar 

  • Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24:38–49

    Article  Google Scholar 

  • Filmalter JD, Capello M, Deneubourg J-L, Cowley PD, Dagorn L (2013) Looking behind the curtain: quantifying massive shark mortality in fish aggregating devices. Front Ecol Environ 11:291–296. https://doi.org/10.1890/130045

    Article  Google Scholar 

  • Filmalter JD, Cowley PD, Forget F, Dagorn L (2015) Fine-scale 3-dimensional movement behaviour of silky sharks Carcharhinus falciformis associated with fish aggregating devices (FADs). Mar Ecol Prog Ser 539:207–223. https://doi.org/10.3354/meps11514

    Article  Google Scholar 

  • Filmalter JD, Cowley PD, Potier M, Ménard F, Smale MJ, Cherel Y, Dagorn L (2016) Feeding ecology of silky sharks Carcharhinus falciformis associated with floating objects in the western Indian Ocean. J Fish Biol. https://doi.org/10.1111/jfb.13241

    Article  PubMed  Google Scholar 

  • Foundation PS (2016) Python Language Reference, version 2.7. https://www.python.org

  • Franco J, Moreno G, Lopez J, Sancristobal I (2012) Testing new designs of drifting fish aggregating device (DFAD) in the eastern Atlantic to reduce turtle and shark mortality. Collect Vol Sci Pap ICCAT 68:1754–1762

    Google Scholar 

  • Freeman EA, Moisen G (2008) PresenceAbsence: an R package for presence absence analysis. J Stat Softw 23:31. https://doi.org/10.18637/jss.v023.i11

    Article  Google Scholar 

  • Froese R, Pauly D (2008) Fishbase 2008. https://www.fishbase.org

  • Giannoulaki M et al (2013) Characterizing the potential habitat of European anchovy Engraulis encrasicolus in the Mediterranean Sea, at different life stages. Fish Oceanogr 22:69–89. https://doi.org/10.1111/fog.12005

    Article  Google Scholar 

  • Goñi N et al (2015) System of verification of the code of good practices on board ANABAC and OPAGAC tuna purse seiners and preliminary results for the Atlantic Ocean IOTC–2015–WPEB11–INF09

  • Goujon M, Vernet AL, Dagorn L (2012) Preliminary results of the Orthongel program “eco-FAD” as June 30th 2012 IOTC–2012–WPEB08–INF21

  • Graham N, Ferro RST, Karp WA, MacMullen P (2007) Fishing practice, gear design, and the ecosystem approach—three case studies demonstrating the effect of management strategy on gear selectivity and discards. ICES J Mar Sci 64:744–750. https://doi.org/10.1093/icesjms/fsm059

    Article  Google Scholar 

  • Grant MI, Smart JJ, White WT, Chin A, Baje L, Simpfendorfer CA (2018) Life history characteristics of the silky shark Carcharhinus falciformis from the central west Pacific. Mar Freshw Res 69:562–573. https://doi.org/10.1071/MF17163

    Article  Google Scholar 

  • Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29–36

    Article  CAS  Google Scholar 

  • Hassrick JL et al (2016) Early ocean distribution of juvenile Chinook salmon in an upwelling ecosystem. Fish Oceanogr 25:133–146. https://doi.org/10.1111/fog.12141

    Article  Google Scholar 

  • Hastie T, Tibshirani R (1986) Generalized additive models. Statistical science. Routledge, London, pp 297–310

    Google Scholar 

  • Hazen EL et al (2018) A dynamic ocean management tool to reduce bycatch and support sustainable fisheries. Sci Adv. https://doi.org/10.1126/sciadv.aar3001

    Article  PubMed  PubMed Central  Google Scholar 

  • Hazin F, Oliveira PG, Macena BC (2007) Aspects of the reproductive biology of the silky shark, Carcharhinus falciformis (Nardo, 1827), in the vicinity of Archipelago of Saint Peter and Saint Paul, in the equatorial Atlantic Ocean Collective Volume of Scientific Papers: ICCAT 60:648–651

  • Hobday AJ, Hartog JR (2014) Derived ocean features for dynamic ocean management. Oceanography 27:134–145. https://doi.org/10.5670/oceanog.2014.92

    Article  Google Scholar 

  • Hobday AJ, Hartog JR, Timmiss T, Fielding J (2010) Dynamic spatial zoning to manage southern bluefin tuna (Thunnus maccoyii) capture in amulti-species longline fishery. Fish Oceanogr 19(3):243–253

    Article  Google Scholar 

  • Hobday AJ, Hartog JR, Spillman CM, Alves O (2011) Seasonal forecasting of tuna habitat for dynamic spatial management. Can J Fish Aquat Sci 68:898–911. https://doi.org/10.1139/f2011-031

    Article  Google Scholar 

  • Hobday AJ, Maxwell SM, Forgie J, McDonald J (2013) Dynamic ocean management: integrating scientific and technological capacity with law, policy, and management. Stan Envtl LJ 33:125

    Google Scholar 

  • Hothorn T, Hornik K, Strobl C, Zeileis A (2015) Party: a laboratory for recursive partitioning. R package version 10-23

  • Humphries NE et al (2010) Environmental context explains Lévy and Brownian movement patterns of marine predators. Nature 465:1066–1069

    Article  CAS  Google Scholar 

  • Hutchinson M et al (2019) Movements and habitat use of juvenile silky sharks in the Pacific Ocean inform conservation strategies. Fish Res 210:131–142. https://doi.org/10.1016/j.fishres.2018.10.016

    Article  Google Scholar 

  • Hutchinson MR, Itano DG, Muir JA, Holland KN (2015) Post-release survival of juvenile silky sharks captured in a tropical tuna purse seine fishery. Mar Ecol Prog Ser 521:143–154

    Article  Google Scholar 

  • ICCAT (2011) Recommendation by ICCAT on the conservation of silky sharks caught in association with ICCAT fisheries. Rec 11-08

  • Jacoby DMP, Croft DP, Sims DW (2012) Social behaviour in sharks and rays: analysis, patterns and implications for conservation. Fish Fish 13:399–417. https://doi.org/10.1111/j.1467-2979.2011.00436.x

    Article  Google Scholar 

  • Jiménez-Valverde A, Lobo JM (2007) Threshold criteria for conversion of probability of species presence to either–or presence–absence. Acta Oecologica 31(3):361–369

    Article  Google Scholar 

  • Jones AR, Hosegood P, Wynn RB, De Boer MN, Butler-Cowdry S, Embling CB (2014) Fine-scale hydrodynamics influence the spatio-temporal distribution of harbour porpoises at a coastal hotspot. Prog Oceanogr 128:30–48. https://doi.org/10.1016/j.pocean.2014.08.002

    Article  Google Scholar 

  • Kahru M, Fiedler PC, Gille ST, Manzano M, Mitchell BG (2007) Sea level anomalies control phytoplankton biomass in the Costa Rica Dome area geophysical. Res Lett 34:L22601. https://doi.org/10.1029/2007gl031631

    Article  Google Scholar 

  • Killick R, Eckley IA (2014) Changepoint: an R package for changepoint analysis. J Stat Softw 58:19. https://doi.org/10.18637/jss.v058.i03

    Article  Google Scholar 

  • Killick R, Fearnhead P, Eckley IA (2012) Optimal detection of changepoints with a linear computational cost. J Am Stat Assoc 107:1590–1598

    Article  CAS  Google Scholar 

  • Last PR, Stevens JD (2009) Sharks and rays of Australia. CSIRO Division of Fisheries, Hobart

    Google Scholar 

  • Lennert-Cody C, Aires-da-Silva A, Maunder M, Román M, Hinton M (2016) Updated stock status indicators for silky sharks in the eastern Pacific Ocean (1994–2015) Technical Report SAC-07-06b. Inter-American Tropical Tuna Commission Scientific Advisory Committee Seventh Meeting, La Jolla, California

  • Lennert-Cody CE et al (2018) The importance of environment and life stage on interpretation of silky shark relative abundance indices for the equatorial Pacific Ocean. Fish Oceanogr. https://doi.org/10.1111/fog.12385

    Article  Google Scholar 

  • Lezama-Ochoa N et al (2015) Biodiversity in the by-catch communities of the pelagic ecosystem in the Western Indian Ocean. Biodivers Conserv 24:2647–2671. https://doi.org/10.1007/s10531-015-0951-3

    Article  Google Scholar 

  • Lezama-Ochoa N, Murua H, Ruiz J, Chavance P, Delgado de Molina A, Caballero A, Sancristobal I (2018) Biodiversity and environmental characteristics of the bycatch assemblages from the tropical tuna purse seine fisheries in the eastern Atlantic Ocean. Mar Ecol. https://doi.org/10.1111/maec.12504

    Article  Google Scholar 

  • Lezama Ochoa N et al (2016) Present and future potential habitat distribution of Carcharhinus falciformis and Canthidermis maculata by-catch species in the tropical tuna purse-seine fishery under climate change. Front Mar Sci. https://doi.org/10.3389/fmars.2016.00034

    Article  Google Scholar 

  • Lopez-Calderon J, Manzo-Monroy H, Santamaria-del-Angel E, Castro R, Gonzalez-Silvera A, Millan-Nunez R (2006) Mesoscale variability of the Mexican Tropical Pacific using TOPEX and SeaWiFS data Ciencias marinas 32

  • Lopez J et al. (2017a) Main results of the Spanish Best Practices program: evolution of the use of Non-entangling FADs, interaction with entangled animals, and fauna release operations IOTC–2017–WGFAD01–11

  • Lopez J et al. (2017b) Taking another step forward: system of verification of the code of good practices in the Spanish tropical tuna purse seiner fleet operating in the Atlantic, Indian and Pacific Oceans IOTC–2017–WGFAD01–12

  • Lopez J, Lennert-Cody CE, Maunder MN, Xu H, Brodie S, Jacox M, Hartog J (2019) Developing alternative conservation measures for bigeye tuna in the eastern Pacific Ocean: a dynamic ocean management approach document SAC-10 INF-D

  • Marsac F, Barlow R, Ternon JF, Ménard F, Roberts M (2014) Ecosystem functioning in the Mozambique Channel: synthesis and future research. Deep Sea Res II 100:212–220. https://doi.org/10.1016/j.dsr2.2013.10.028

    Article  Google Scholar 

  • McGlade JM, Cury P, Koranteng KA, Hardman-Mountford N (2002) The Gulf of Guinea large marine ecosystem: environmental forcing and sustainable development of marine resources. Newnes, Amsterdam

    Google Scholar 

  • Miller PI, Scales KL, Ingram SN, Southall EJ, Sims DW (2015) Basking sharks and oceanographic fronts: quantifying associations in the north-east Atlantic. Funct Ecol 29:1099–1109. https://doi.org/10.1111/1365-2435.12423

    Article  Google Scholar 

  • Minami M, Lennert-Cody CE, Gao W, Román-Verdesoto M (2007) Modeling shark bycatch: the zero-inflated negative binomial regression model with smoothing. Fish Res 84:210–221. https://doi.org/10.1016/j.fishres.2006.10.019

    Article  Google Scholar 

  • Molony B (2008) Fisheries biology and ecology of highly migratory species that commonly interact with industrialised longline and purse-seine fisheries. In: in the western and central Pacific Ocean. Fourth Scientific Committee Meeting of the Western and Central Pacific Fisheries Commission, Port Moresby, Papua New Guinea. Citeseer

  • Mugo RM, Saitoh S-I, Takahashi F, Nihira A, Kuroyama T (2014) Evaluating the role of fronts in habitat overlaps between cold and warm water species in the western North Pacific: a proof of concept. Deep Sea Res II 107:29–39. https://doi.org/10.1016/j.dsr2.2013.11.005

    Article  CAS  Google Scholar 

  • Murase H, Nagashima H, Yonezaki S, Matsukura R, Kitakado T (2009) Application of a generalized additive model (GAM) to reveal relationships between environmental factors and distributions of pelagic fish and krill: a case study in Sendai Bay, Japan. ICES J Mar Sci 66:1417–1424. https://doi.org/10.1093/icesjms/fsp105

    Article  Google Scholar 

  • Murua H, Arrizabalaga H, Huang J, Romanov E, Bach P, de Bruyn P (2009) Ecological Risk Assessment (ERA) for species caught in fisheries managed by the Indian Ocean Tuna Commission (IOTC): a first attempt. IOTC-2009-WPEB-20. Indian Ocean Tuna Commission, Mahé, Seychelles

  • Murua H et al. (2018) Updated Ecological Risk Assessment (ERA) for shark species caught in fisheries managed by the Indian Ocean Tuna Commission (IOTC). IOTC-2018-SC21-14. 28 pp

  • Musyl MK, Gilman EL (2018) Post-release fishing mortality of blue (Prionace glauca) and silky shark (Carcharhinus falciformes) from a Palauan-based commercial longline fishery. Rev Fish Biol Fish. https://doi.org/10.1007/s11160-018-9517-2

    Article  Google Scholar 

  • Musyl MK, Gilman EL (2019) Meta-analysis of post-release fishing mortality in apex predatory pelagic sharks and white marlin. Fish Fish. https://doi.org/10.1111/faf.12358

    Article  Google Scholar 

  • Naimi B (2015) usdm: uncertainty analysis for species distribution models, R package version 1.1-12.

  • Naimi B, Hamm NAS, Groen TA, Skidmore AK, Toxopeus AG (2014) Where is positional uncertainty a problem for species distribution modelling? Ecography 37:191–203. https://doi.org/10.1111/j.1600-0587.2013.00205.x

    Article  Google Scholar 

  • Nieto K, Xu Y, Teo SLH, McClatchie S, Holmes J (2015) How important are coastal fronts to albacore tuna (Thunnus alalunga) habitat in the Northeast Pacific Ocean? Prog Oceanogr. https://doi.org/10.1016/j.pocean.2015.05.004

    Article  Google Scholar 

  • Oliver S, Braccini M, Newman SJ, Harvey ES (2015) Global patterns in the bycatch of sharks and rays. Mar Policy 54:86–97. https://doi.org/10.1016/j.marpol.2014.12.017

    Article  Google Scholar 

  • Ortiz de Urbina J et al. (2018) A preliminary stock assessment for the silky shark in the Indian Ocean using a data-limited approach IOTC WPEB14-33

  • Pearce J, Ferrier S (2000) Evaluating the predictive performance of habitat models developed using logistic regression. Ecol Model 133:225–245. https://doi.org/10.1016/S0304-3800(00)00322-7

    Article  Google Scholar 

  • Pearson RG (2007) Species’ distribution modeling for conservation educators and practitioners. Am Museum Nat Hist 50:54–89

    Google Scholar 

  • Pearson RG et al (2006) Model-based uncertainty in species range prediction. J Biogeogr 33:1704–1711. https://doi.org/10.1111/j.1365-2699.2006.01460.x

    Article  Google Scholar 

  • Pikitch EK et al (2004) Ecosystem-based fishery management. Science 305:346–347. https://doi.org/10.1126/science.1098222

    Article  CAS  PubMed  Google Scholar 

  • Poisson F et al (2016) Technical mitigation measures for sharks and rays in fisheries for tuna and tuna-like species: turning possibility into reality. Aquat Living Resour 29:402

    Article  Google Scholar 

  • Poisson F, Filmalter J-D, Vernet A-L, Laurent D (2014) Mortality rate of silky sharks (Carcharhinus falciformis) caught in the tropical tuna purse seine fishery in the Indian Ocean. Can J Fish Aquat Sci. https://doi.org/10.1139/cjfas-2013-0561

    Article  Google Scholar 

  • Potier M, Bach P, Ménard F, Marsac F (2014) Influence of mesoscale features on micronekton and large pelagic fish communities in the Mozambique Channel. Deep Sea Res II 100:184–199. https://doi.org/10.1016/j.dsr2.2013.10.026

    Article  CAS  Google Scholar 

  • Queiroz N et al (2016) Ocean-wide tracking of pelagic sharks reveals extent of overlap with longline fishing hotspots. Proc Natl Acad Sci 113:1582–1587. https://doi.org/10.1073/pnas.1510090113

    Article  CAS  PubMed  Google Scholar 

  • Queiroz N, Humphries NE, Noble LR, Santos AM, Sims DW (2012) Spatial dynamics and expanded vertical niche of blue sharks in oceanographic fronts reveal habitat targets for conservation. PLoS ONE 7:e32374. https://doi.org/10.1371/journal.pone.0032374

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Queiroz N, Vila-Pouca C, Couto A, Southall EJ, Mucientes G, Humphries NE, Sims DW (2017) Convergent foraging tactics of marine predators with different feeding strategies across heterogeneous ocean environments. Front Mar Sci. https://doi.org/10.3389/fmars.2017.00239

    Article  Google Scholar 

  • Reglero P et al (2017) Environmental and biological characteristics of Atlantic bluefin tuna and albacore spawning habitats based on their egg distributions. Deep Sea Res II 140:105–116. https://doi.org/10.1016/j.dsr2.2017.03.013

    Article  CAS  Google Scholar 

  • Restrepo V, Dagorn L, Moreno G (2016) Mitigation of silky shark bycatch in tropical tuna purse seine fisheries ISSF technical report 2016–2017. International Seafood Sustainability Foundation, Washington, DC

    Google Scholar 

  • Restrepo V et al (2018) Compendium of ISSF at-sea bycatch mitigation research activities as of September 2018 ISSF technical report 2018–2020. International Seafood Sustainability Foundation, Washington DC

    Google Scholar 

  • Rice J, Harley S (2013) Updated stock assessment of silky sharks in the western and central Pacific Ocean Scientific Committee Ninth Regular Session:6-14

  • Rice J, Tremblay-Boyer L, Scott R, Hare S, Tidd A (2015) Analysis of stock status and related indicators for key shark species of the Western Central Pacific Fisheries Commission. In: Western and Central Pacific Fisheries Commission 11th Regular Session, pp 1–146

  • Rigby CL, Sherman CS, Chin A, Simpfendorfer C (2017) Carcharhinus falciformis. The IUCN red list of threatened species. https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T39370A117721799.en

  • Sagarminaga Y, Arrizabalaga H (2014) Relationship of Northeast Atlantic albacore juveniles with upper surface thermal and Chlorophyll-a fronts. Deep Sea Res II. https://doi.org/10.1016/j.dsr2.2013.11.006

    Article  Google Scholar 

  • Scales KL, Hazen EL, Jacox MG, Castruccio F, Maxwell SM, Lewison RL, Bograd SJ (2018) Fisheries bycatch risk to marine megafauna is intensified in Lagrangian coherent structures. Proc Natl Acad Sci. https://doi.org/10.1073/pnas.1801270115

    Article  PubMed  Google Scholar 

  • Scales KL, Hazen EL, Jacox MG, Edwards CA, Boustany AM, Oliver MJ, Bograd SJ (2016) Scales of inference: on the sensitivity of habitat models for wide-ranging marine predators to the resolution of environmental data. Ecography. https://doi.org/10.1111/ecog.02272

    Article  Google Scholar 

  • Snyder S, Franks PJS, Talley LD, Xu Y, Kohin S (2017) Crossing the line: tunas actively exploit submesoscale fronts to enhance foraging success. Limnol Oceanogr Lett 2:187–194. https://doi.org/10.1002/lol2.10049

    Article  Google Scholar 

  • Springer S (1967) Social organization of shark population. In: Gilbert PW, Mathewson RF, Rall DP (eds) Sharks, skates and rays. John Hopkins Press, Baltimore, pp p149–174

    Google Scholar 

  • Strobl C, Hothorn T, Zeileis A (2009) Party on! a new, conditional variable-importance measure for random forests available in the party package. R J Anim Ecol 1(2):14–17

    Google Scholar 

  • Team RDC (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. https://www.r-project.org/

  • Tew Kai E, Marsac F (2010) Influence of mesoscale eddies on spatial structuring of top predators’ communities in the Mozambique Channel. Prog Oceanogr 86:214–223. https://doi.org/10.1016/j.pocean.2010.04.010

    Article  Google Scholar 

  • Tseng C-T, Sun C-L, Belkin IM, Yeh S-Z, Kuo C-L, Liu D-C (2014) Sea surface temperature fronts affect distribution of Pacific saury (Cololabis saira) in the Northwestern Pacific Ocean. Deep Sea Res II 107:15–21. https://doi.org/10.1016/j.dsr2.2014.06.001

    Article  Google Scholar 

  • Villarino E, Chust G, Licandro P, Butenschön M, Ibaibarriaga L, Larrañaga A, Irigoien X (2015) Modelling the future biogeography of North Atlantic zooplankton communities in response to climate change. Mar Ecol Prog Ser 531:121–142

    Article  CAS  Google Scholar 

  • Welch H et al (2018) Practical considerations for operationalizing dynamic management tools. J Appl Ecol. https://doi.org/10.1111/1365-2664.13281

    Article  Google Scholar 

  • Williamson MJ, Tebbs EJ, Dawson TP, Jacoby DMP (2019) Satellite remote sensing in shark and ray ecology, conservation and management. Front Mar Sci. https://doi.org/10.3389/fmars.2019.00135

    Article  Google Scholar 

  • Wood S (2006) Generalized additive models: an introduction with R, vol 66. Chapman & Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Wood S (2014) Package ‘mgcv’ R package version17-29

  • Woodman SM, Forney KA, Becker EA, DeAngelis ML, Hazen EL, Palacios DM, Redfern JV (2019) eSDM: a tool for creating and exploring ensembles of predictions from species distribution and abundance models. Methods Ecol Evol. https://doi.org/10.1111/2041-210X.13283

    Article  Google Scholar 

  • Xu Y, Nieto K, Teo SLH, McClatchie S, Holmes J (2015) Influence of fronts on the spatial distribution of albacore tuna (Thunnus alalunga) in the Northeast Pacific over the past 30 years (1982–2011). Prog Oceanogr. https://doi.org/10.1016/j.pocean.2015.04.013

    Article  Google Scholar 

  • Young JW et al (2014) The trophodynamics of marine top predators: current knowledge, recent advances and challenges. Deep Sea Res II. https://doi.org/10.1016/j.dsr2.2014.05.015

    Article  Google Scholar 

  • Zuur AF, Mira A, Carvalho F, Ieno EN, Saveliev AA, Smith GM, Walker NJ (2009) Negative binomial GAM and GAMM to analyse amphibian roadkills. Mixed effects models and extensions in ecology with R. Springer, New York, NY, pp 383–397. https://doi.org/10.1007/978-0-387-87458-6_16

    Chapter  Google Scholar 

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Acknowledgements

The authors sincerely thank Dr. Maite Louzao and Igor Arregi for their useful comments, suggestion and assistance while developing the study. We also thank the comments of the 2 anonymous reviewers that considerably improved the manuscript. This is paper 961 from AZTI-tecnalia.

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Correspondence to Jon Lopez.

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Communicated by Angus Jackson.

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Supplementary material 1

Histogram of size frequency of the silky sharks included in this study showing the 95% (red dashed line) and 99% (pink dashed line) percentiles. Size data was dominated by individuals of 80–150 cm TL (TIFF 28601 kb)

Supplementary material 2

(GIF 122690 kb)

Supplementary material 3

(GIF 21179 kb)

Supplementary material 4

Averaged predictions of silky shark probability standard error for the three environmental regimes identified in this study: stable (day of the year 290–154), cool (day of the year 155–239) and warming season (day of the year 240–289) (TIFF 98070 kb)

Supplementary material 5

Monthly averaged predictions of silky shark probability (TIFF 147104 kb)

Supplementary material 6

Monthly simplified predictions of silky shark probability (TIFF 147104 kb)

Supplementary material 7

Monthly averaged predictions of silky shark probability standard error (TIFF 147104 kb)

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Lopez, J., Alvarez-Berastegui, D., Soto, M. et al. Using fisheries data to model the oceanic habitats of juvenile silky shark (Carcharhinus falciformis) in the tropical eastern Atlantic Ocean. Biodivers Conserv 29, 2377–2397 (2020). https://doi.org/10.1007/s10531-020-01979-7

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