Spatio-Temporal Distribution of Juvenile Oceanic Whitetip Shark Incidental Catch in the Western Indian Ocean

Abstract

Oceanic whitetip shark (Carcharhinus longimanus) is an important top predator in pelagic ecosystems currently classified as globally Critically Endangered by the International Union for the Conservation of Nature. This species is incidentally caught by fisheries targeting highly migratory tunas and billfishes throughout the Indian Ocean. Understanding the temporal, spatial and environmental factors influencing the capture of this species is essential to reduce incidental catches. In this study, we used generalized additive models to analyze the spatio-temporal distributions of the juvenile oceanic whitetip shark catches and the environmental conditions in the western Indian Ocean using observer data from 2010 to 2020 of the European Union and associated flags purse seine fishery. We found sea surface temperature and nitrate concentration to be the most important environmental variables predicting the probability of catching an oceanic whitetip shark. A higher probability of capture was predicted in areas where sea surface temperature was below 24°C and with low nitrate concentrations close to zero and intermediate values (1.5-2.5 mmol.m-3). We also found a higher probability of capture in sets on fish aggregating devices than in sets on free schools of tuna. The Kenya and Somalia basin was identified to have higher probabilities of capture during the summer monsoon (June to September) when upwelling of deep cold waters occurs. We provide the first prediction maps of capture probabilities and insights into the environmental preferences of oceanic whitetip shark in the western Indian Ocean. However, the causal mechanisms behind these insights should be explored in future studies before they can be used to design spatial management and conservation strategies, such as time-area closures, for bycatch avoidance.

Evidence to inform spatial management of a western Pacific Ocean tuna purse seine fishery

“…ABMTs hold substantial potential to balance socioeconomic benefits derived from fisheries and costs to at-risk species exposed to bycatch fishing mortality (Gilman et al, 2019a;Mannocci et al, 2020;Lopetegui-Eguren et al, 2022). Mean field prediction surfaces defined catch rate hotspots for principal market tunas, silky sharks, rays and whale sharks, informing the development of candidate static spatial management strategies that reduce catch risk of at-risk species without causing unacceptable costs to catch rates of target species.…”

“…Industrial purse seine fisheries targeting mainly skipjack and yellowfin tunas, as well as bigeye tuna, occur primarily in the tropics of the eastern Atlantic Ocean, western Indian Ocean and eastern and western Pacific Ocean (Hall & Roman, 2013). Pelagic predator distributions, local abundance and aggregating behavior are defined by environmental variables such as temperature and dissolved oxygen, depth of the thermocline, and availability of their prey (Musyl et al 2003(Musyl et al , 2011Lopetegui-Eguren et al, 2022). Pelagic predators have different environmental preferences and tolerances (Lehodey et al, 2011;Muhling et al, 2011;Brodziak and Walsh, 2013).…”

“…Relative to free-swimming tuna schools chasing prey, sets on relatively slower-moving drifting FADs and logs catch a larger number and weight of nontarget species per set and per unit weight of target tunas (Hall & Roman 2013;Torres-Irineo et al 2014;Gaertner et al 2016;Peatman et al 2017;Lezama-Ochoa et al 2017;Pons et al, 2023). Shark catch rates, in number or weight of captures per set, are higher in drifting FAD and log sets than in free school sets (Amande et al 2008(Amande et al , 2010Clarke et al, 2011;Lopetegui-Eguren et al, 2022). However, when applying a catch rate of the weight of caught sharks per weight of principal market tunas, shark catch rates in school and associated sets are the same order of magnitude (ISSF, 2017).…”