Predicting global seasonal distributions and population exchange routes of a Critically Endangered shark

Abstract

Oceanic sharks are of great importance to marine ecosystems but among the most endangered taxa in the world. Their conservation requires spatially and temporally explicit knowledge about distributions and migrations across oceanic basins, which are often challenging to monitor and thus little is known at the global scale. The present study addressed this challenge for the scalloped hammerhead (Sphyrna lewini) which is Critically Endangered. I gathered geo-referenced occurrences of this species from online biogeographic databases, catch data, and peer-reviewed literature. I built seasonal species distribution models (SSDMs) based on these occurrences and 11 environmental variables to predict their suitable habitats. I then predicted their seasonal migration routes for population exchanges with two connectivity analysis techniques (Circuitscape, least-cost path analysis). All SSDMs performed well and showed that there were prominent divergences in seasonal distributions driven by the species' ecological niches. Generally, sea surface temperature was the most important predictor, followed by depth, salinity, primary productivity, distance to macrohabitats, and distance to shoreline. Seasonal suitable habitats were mainly found in tropical continental shelves and deep seas. Possible seasonal migration corridors for population exchanges across ocean basins were identified and some were commonly used by oceanic sharks. The present study highlights (i) the utility of integrating SDMs and connectivity-analysis techniques to predict migration routes for oceanic sharks, and (ii) seasonal and regional changes in their habitat uses, suggesting dynamic, ocean-based conservation measures are needed to conserve these marine apex predators.