Could the biggest movers be the biggest losers – clues from ecosystem modelling of whale-krill interactions
Vivitskaia J. D. Tulloch (1,2), Éva E. Plagányi (2), Christopher Brown (3), Richard Matear (4), Anthony Richardson (2), Hugh P. Possingham (1)
1 ARC Centre of Excellence in Environmental Decisions, University of Queensland, St Lucia, Brisbane, Queensland, 4072
2 CSIRO Oceans and Atmosphere Flagship, Queensland BioSciences Precinct (QBP), St Lucia, Brisbane, Queensland, 4072
3 Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia
4 CSIRO Oceans and Atmosphere Flagship, GPO Box 1538, Hobart, Tasmania 7004
Reliable predictions of climate change impacts on harvested marine species such as krill and their dependent predators are crucial for effective ecosystem-‐based fisheries management. In the Southern Hemisphere, altered productivity regimes are expected due to climate-‐induced changes in the oceans. Highly migratory baleen whales may be particularly susceptible to these changes, due to the close synchrony between their life history and water temperature, and productivity. There is currently limited understanding of the complex trophic interactions between these species, and their responses to changes in the marine environment. We developed a focused forage fish ‘Model of Intermediate Complexity for Ecosystem Assessments’ (MICE) for phytoplankton, krill and five baleen whales (Blue, Fin, Humpback, Minke, Right whales), including predator-‐prey feeding interactions. We fitted the model to available catch and survey data, and account for key uncertainties to increase robustness. We included environmental forcing using outputs of existing global climate models to predict primary-‐productivity shifts under climate change for the southern hemisphere, and used the predicted patterns to evaluate how krill perform under alternate oceanographic conditions. We found spatial and temporal variability in productivity-‐driven changes in krill across the southern oceans, with consequences for future fisheries management. By modeling interactions between whales and changes in their prey, we found differences between whale species in bottom-‐up forcing of spatial distribution and abundance. With many of the large whale populations severely impacted by historic whaling, this improved understanding of their response to changes in their prey from multiple could have important implications for conservation.