Against the Spring Wave: Ungulate Migration Phenology in a Changing Arctic

Open Access
John, Christian Lee
Graduate Program:
Master of Science
Document Type:
Master Thesis
Date of Defense:
October 26, 2016
Committee Members:
  • Eric Post, Thesis Advisor/Co-Advisor
  • Douglas Alan Miller, Committee Member
  • Erica A H Smithwick, Committee Member
  • Migration
  • Phenology
  • Arctic
  • Climate Change
  • Caribou
  • Remote Sensing
Migration is a widespread adaptation to seasonal variability in resource distribution and availability. Through effects on resource phenology, composition, and abundance, climate change may disrupt the predictability of seasonal patterns of resource availability, with consequences for migratory timing and resource tracking by consumers. These impacts may be especially pronounced in the Arctic, where recent climatic warming is in excess of twice the global average. For long-distance migrants, the Green Wave Hypothesis has served as a broadly applicable framework for understanding the role of spatially propagating resource phenology in spring migration departure from wintering grounds, migratory rate, and timing of arrival at summer breeding grounds. While avian migrants and subarctic ungulates have been the focus of previous research on this topic, little focus has been placed to date on the impacts of climate change on ungulate migration phenology in the Arctic. Here, I use a framework based on the predictions of the Green Wave Hypothesis to investigate climatic effects on caribou (Rangifer tarandus) migration in a low-Arctic system. I begin in Chapter 2 by quantifying the spring wave in vegetation green-up phenology, finding that an unexpected trend in its direction of propagation is related to a suite of abiotic conditions including temperature, precipitation, and sea ice extent. Chapter 3 is an examination of caribou migration phenology, and the results presented therein suggest that the timing of arrival on the calving grounds is entrained by photoperiod, but is influenced secondarily by population density and timing of green-up.