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Dynamic Lake Ice Conditions Shape Caribou Water-Crossing Behavior in the Arctic
Qianru Liao1, Eliezer Gurarie2, William F Fagan1
1Department of Biology, University of Maryland, College Park, Maryland, USA.
Global Change Biology
|April 13, 2026
Summary
Caribou migration is affected by changing lake ice conditions. Spring crossings depend on ice stability, while fall movements are influenced by route efficiency, impacting Arctic wildlife connectivity.
Area of Science:
- Ecology
- Animal Behavior
- Climate Change Science
Background:
- Animal migration relies on navigation and decision-making in changing environments.
- Understanding responses to transient barriers like seasonal ice is crucial for predicting migration under global change.
- Arctic warming alters ice cover, impacting overland migrants like barren-ground caribou (Rangifer tarandus).
Purpose of the Study:
- To quantitatively assess caribou behavioral responses to changing lake ice conditions.
- To analyze lake-crossing decisions in relation to ice conditions and movement factors.
- To develop a framework for predicting climate-driven shifts in migratory behavior.
Main Methods:
- Analyzed 20 years of GPS data from 406 caribou and daily MODIS land surface albedo data.
- Classified transit events (crossing vs. circumnavigation) based on GPS trajectories.
- Linked behavioral decisions to spatially and temporally resolved ice conditions using statistical models.
Main Results:
- Spring crossing decisions were influenced by intermediate ice conditions, with a threshold identified at a specific albedo percentile rank.
- Fall behavior was better explained by movement-related factors like relative speeds along alternative routes when the lake was ice-free.
- Ice acts as a seasonal filter, shaping functional connectivity through perceptual and energetic constraints.
Conclusions:
- Caribou exhibit distinct seasonal strategies for navigating lake ice, influenced by ice stability in spring and route efficiency in fall.
- The study provides a transferable framework for linking remote sensing to individual behavior to identify thresholds in response to dynamic landscape features.
- This approach supports predictive monitoring of climate-driven changes in migratory behavior and movement constraints.
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