Stochastic simulations reveal few green wave surfing populations among spring migrating herbivorous waterfowl

Xin Wang, Lei Cao (Corresponding author), Anthony D. Fox, Richard Fuller, Larry Griffin, Carl Mitchell, Yunlin Zhao, Oun-Kyong Moon, David Cabot, Zhenggang Xu, Nyambayar Batbayar, Andrea Kölzsch, Henk P. van der Jeugd, Jesper Madsen, Liding Chen, Ran Nathan (Corresponding author)

Research output: Contribution to journal/periodicalArticleScientificpeer-review

35 Citations (Scopus)
76 Downloads (Pure)

Abstract

Tracking seasonally changing resources is regarded as a widespread proximate mechanism underpinning animal migration. Migrating herbivores, for example, are hypothesized to track seasonal foliage dynamics over large spatial scales. Previous investigations of this green wave hypothesis involved few species and limited geographical extent, and used conventional correlation that cannot disentangle alternative correlated effects. Here, we introduce stochastic simulations to test this hypothesis using 222 individual spring migration episodes of 14 populations of ten species of geese, swans and dabbling ducks throughout Europe, East Asia, and North America. We find that the green wave cannot be considered a ubiquitous driver of herbivorous waterfowl spring migration, as it explains observed migration patterns of only a few grazing populations in specific regions. We suggest that ecological barriers and particularly human disturbance likely constrain the capacity of herbivorous waterfowl to track the green wave in some regions, highlighting key challenges in conserving migratory birds.
Original languageEnglish
Pages (from-to)2187
JournalNature Communications
Volume10
Issue number1
DOIs
Publication statusPublished - 16 May 2019

Keywords

  • international
  • Animals
  • Stochastic Processes
  • Models, Biological
  • Europe
  • Animal Migration/physiology
  • Geese/physiology
  • Seasons
  • Ducks/physiology
  • Far East
  • North America
  • Herbivory/physiology

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