NSF Award
2307754
A rapid climate shift in the Gulf of Maine in 2010 caused an abrupt redistribution in the endangered North Atlantic right whale (Eubalaena glacialis), leading to changing foraging patterns, higher mortality rates due to vessel collisions and entanglement in fishing gear, as well as a drop in the calving rate. This decline in population size and health has triggered the International Union for Conservation of Nature to re-classify right whale conservation status from endangered to critically endangered. The case of the right whale illustrates the ecological and socio-economic consequences of a lack of understanding of how an organism responds to climate change. Such rapid redistributions have previously been unpredictable, as right whale monitoring and modeling efforts are focused on known and accessible historic habitats. This project develops a new modeling framework to integrate novel right whale data with trans-boundary prey surveys to understand adaptation, identify potential habitats outside regular monitoring regions, and predict changes to right whale distribution in future decades. Model results will guide the development and implementation of protective policies administered by federal agencies and provide theoretical support for expanding dynamic management efforts. Project synthesis will be applied in organizations including the Atlantic Large Whale Take Reduction Team and the Regional Wildlife Science Collaborative for Offshore Wind. A publicly-available data science lesson plan will be developed to teach spatial analysis techniques and engender discussion on conservation management. <br/><br/>This proposal seeks to utilize robust right whale and zooplankton monitoring data to build a next-generation species distribution model to explain and predict right whale foraging decisions and spatial distribution patterns. The research will test the hypothesis that there are measurable thresholds of prey density that cause individual animals to utilize or abandon a foraging site. However, these prey density thresholds may vary depending on environmental factors such as prey species, site, and season, or by demographic factors such as right whale age and reproductive status. Using consecutive sightings of identified individuals, an individual movement model will be developed to understand foraging decision-making and estimate prey density thresholds across this range of environmental and demographic variables. This model will be coupled with genetic analysis of right whale fecal samples to identify prey taxa and prey ratios in distinct habitats and foraging seasons. Prey thresholds will be incorporated into a prey patch model spanning the North Atlantic to characterize the spatial and temporal occurrence of suitable foraging habitat. Then a next-generation species distribution modeling framework will be used that draws on behavioral thresholds resolved from the individual movement model and prey patch occurrence models parameterized by prey content in the fecal samples. This modeling framework will provide new predictive capacity for determining when right whales may shift foraging patterns and which habitats are suitable for becoming a novel foraging hot spot. Model results will be used to quantify the bioenergetic and anthropogenic components of the climate change effect on right whale populations.<br/><br/>This award was co-funded through the GEO/OCE Biological Oceanography Program and the BIO/IOS Organismal Responses to Climate Change Program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
