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Animals follow specific movement patterns and search strategies to maximize encounters with essential resources (e.g. prey, favourable habitat) while minimizing exposures to suboptimal conditions (e.g. competitors, predators). While describing spatiotemporal patterns in animal movement from tracking data is common, understanding the associated search strategies employed continues to be a key challenge in ecology. Moreover, studies in marine ecology commonly focus on singular aspects of species' movements, however using multiple analytical approaches can further enable researchers to identify ecological phenomena and resolve fundamental ecological questions relating to movement. Here, we used a set of statistical physics-based methods to analyze satellite tracking data from three co-occurring apex predators (tiger, great hammerhead and bull sharks) that predominantly inhabit productive coastal regions of the northwest Atlantic Ocean and Gulf of Mexico. We analyzed data from 96 sharks and calculated a range of metrics, including each species' displacements, turning angles, dispersion, space-use and community-wide movement patterns to characterize each species' movements and identify potential search strategies. Our comprehensive approach revealed high interspecific variability in shark movement patterns and search strategies. Tiger sharks displayed near-random movements consistent with a Brownian strategy commonly associated with movements through resource-rich habitats. Great hammerheads showed a mixed-movement strategy including Brownian and resident-type movements, suggesting adaptation to widespread and localized high resource availability. Bull sharks followed a resident movement strategy with restricted movements indicating localized high resource availability. We hypothesize that the species-specific search strategies identified here may help foster the co-existence of these sympatric apex predators. Following this comprehensive approach provided novel insights into spatial ecology and assisted with identifying unique movement and search strategies. Similar future studies of animal movement will help characterize movement patterns and also enable the identification of search strategies to help elucidate the ecological drivers of movement and to understand species' responses to environmental change.
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