Tue, Aug 16, 2022: 10:00 AM-10:15 AM
513B
Background/Question/Methods
Long-distance wildlife migration is driven by biogeographic factors including resource distribution and seasonality. In the rapidly changing Arctic marine environment, shifting sea ice extent and prey availability impact the annual movement of an ice-dependent top predator, the Eastern Beaufort Sea beluga. Belugas exhibit flexible responses to environmental drivers, as well as varied diets and migratory patterns across ecotypes, which may increase their resilience to climate change. We tested the hypothesis that the EBS beluga, will exhibit increasingly varied migratory strategies in a changing environment by comparing summer and fall movement from three decadal telemetry studies conducted in the 1990s (n=27), 2000s (n=7) and 2010s (n=17). We used correlated random walk models to reconcile disparities in sampling regimes across historical datasets, then applied a hidden Markov model to classify location observations into two behavioral states (transiting and foraging). We characterized the migration of each individual beluga on a seasonal scale using the duration of migration from summer to late fall foraging areas, and the number, duration, and area of foraging stops. On a weekly scale, we evaluated spatial distribution and average swimming speed. We used k-means clustering to test for similarities in migratory strategies by sex, year, and decade.
Results/Conclusions
This study presents a novel approach to establish seasonal foraging areas and migration timing for a long-distance migrant, using behavioral data from hidden Markov models. We show a method to compare historical datasets with considerable disparities in temporal resolution and tag duration by applying clustering algorithms to weekly movement parameters.Our hypothesis is supported by k-means clustering of weekly swimming speeds and spatial distribution, which revealed distinct migration strategies that were especially prominent in late August and September. Whales tagged in the most recent decadal study (2010s) generally traveled further north during their fall migration and made more foraging stops. Most females (6/7) employed a migratory strategy which consisted of extended foraging east and north of the tagging site, followed by highly directional westward movement through shallow coastal waters. Summer and late fall foraging hotspots, which were delineated using utilization distributions of foraging observations from the hidden Markov model, showed surprising congruence across decadal groups.This study presents evidence of a species with broad distribution and high phenological plasticity demonstrating increased variation in migratory strategies in the face of a changing environment.
Long-distance wildlife migration is driven by biogeographic factors including resource distribution and seasonality. In the rapidly changing Arctic marine environment, shifting sea ice extent and prey availability impact the annual movement of an ice-dependent top predator, the Eastern Beaufort Sea beluga. Belugas exhibit flexible responses to environmental drivers, as well as varied diets and migratory patterns across ecotypes, which may increase their resilience to climate change. We tested the hypothesis that the EBS beluga, will exhibit increasingly varied migratory strategies in a changing environment by comparing summer and fall movement from three decadal telemetry studies conducted in the 1990s (n=27), 2000s (n=7) and 2010s (n=17). We used correlated random walk models to reconcile disparities in sampling regimes across historical datasets, then applied a hidden Markov model to classify location observations into two behavioral states (transiting and foraging). We characterized the migration of each individual beluga on a seasonal scale using the duration of migration from summer to late fall foraging areas, and the number, duration, and area of foraging stops. On a weekly scale, we evaluated spatial distribution and average swimming speed. We used k-means clustering to test for similarities in migratory strategies by sex, year, and decade.
Results/Conclusions
This study presents a novel approach to establish seasonal foraging areas and migration timing for a long-distance migrant, using behavioral data from hidden Markov models. We show a method to compare historical datasets with considerable disparities in temporal resolution and tag duration by applying clustering algorithms to weekly movement parameters.Our hypothesis is supported by k-means clustering of weekly swimming speeds and spatial distribution, which revealed distinct migration strategies that were especially prominent in late August and September. Whales tagged in the most recent decadal study (2010s) generally traveled further north during their fall migration and made more foraging stops. Most females (6/7) employed a migratory strategy which consisted of extended foraging east and north of the tagging site, followed by highly directional westward movement through shallow coastal waters. Summer and late fall foraging hotspots, which were delineated using utilization distributions of foraging observations from the hidden Markov model, showed surprising congruence across decadal groups.This study presents evidence of a species with broad distribution and high phenological plasticity demonstrating increased variation in migratory strategies in the face of a changing environment.