Inter-Research >  > Prepress Abstract

MEPS prepress abstract   -  DOI:

Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes

Dawn R. Barlow*, Kim S. Bernard, Pablo Escobar-Flores, Daniel M. Palacios, Leigh G. Torres

*Corresponding author:

ABSTRACT: The response of marine predators to global climate change and shifting ocean conditions is tightly linked with their environment and prey. Environmental data are frequently used as proxies for prey availability in marine predator distribution models as the ephemeral nature of prey makes sampling difficult. For this reason, the functional, ecological links between environment, prey, and predator are rarely described or explicitly tested. This study utilizes three years of vessel-based whale survey data paired with oceanographic sampling and hydroacoustic backscatter to model trophic relationships between water column structure, krill availability, and blue whale distribution in New Zealand’s South Taranaki Bight region under typical (2014 and 2017) and warm (2016) austral summer oceanographic regimes. The warm regime was characterized by a shallower mixed layer, and a stronger, thicker, and warmer thermocline. Boosted regression tree models showed that krill metrics predicted blue whale distribution (typical regime = 36% versus warm regime = 64% cross-validated deviance explained) better than oceanography (typical regime = 19% versus warm regime = 31% cross-validated deviance explained). However, oceanographic features that predicted more krill aggregations (typical regime) and higher krill density (warm regime) aligned closely with the features that predicted higher probability of blue whale presence in each regime. Therefore, this study confirms that environmental drivers of prey availability can serve as suitable proxies for blue whale distribution. Considering changing ocean conditions that may influence the distribution of marine predators, these findings emphasize the need for models based on functional relationships and calibrated across a broad range of conditions to inform effective conservation management.