Abstract

AbstractHistorically, ungulate migrations occurred in most grassland and boreal woodland ecosystems, but many have been lost due to increasing habitat loss and fragmentation. With the rate of environmental change increasing, identifying and prioritizing migration routes for conservation has taken on a new urgency. Understanding the cues that drive long‐distance animal movements is critical to predicting the fate of migrations under different environmental change scenarios and how large migratory herbivores will respond to increasing resource heterogeneity and anthropogenic influences. We used an individual‐based modeling approach to investigate the influence of environmental conditions, monitored using satellite data, on departure date and movement speed of migrating zebras in Botswana. Daily zebra movements between dry and rainy season ranges were annotated with coincident observations of precipitation from the Tropical Rainfall Measuring Mission data set and Moderate Resolution Imaging Spectroradiometer‐derived normalized difference vegetation index (NDVI). An array of increasingly complex movement models representing alternative hypotheses regarding the environmental cues and controls for movement was parameterized and tested. The best and most justified model predicted daily zebra movement as two linear functions of precipitation rate and NDVI and included a modeled departure date as a function of cumulative precipitation. The model was highly successful at replicating both the timing and pace of seven actual migrations observed using GPS telemetry (R2 = 0.914). It shows how zebras rapidly adjust their movement to changing environmental conditions during migration and are able to reverse migration to avoid adverse conditions or exploit renewed resource availability, a nomadic behavior which should lend them a degree of resilience to climate and environmental change. Our results demonstrate how competing individual‐based migration models, informed by freely available satellite data, can be used to evaluate the weight of evidence for multiple hypotheses regarding the use of environmental cues in animal movement. This modeling framework can be applied to quantify how animals adapt the timing and pace of their movements to prevailing environmental conditions and to forecast migrations in near real time or under alternative environmental scenarios.

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