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Abundance patterns of mammals across Russia explained by remotely sensed vegetation productivity and snow indices

  • Elena Razenkova*
  • , Maxim Dubinin
  • , Anna M. Pidgeon
  • , Martina L. Hobi
  • , Likai Zhu
  • , Eugenia V. Bragina
  • , Andrew M. Allen
  • , Murray K. Clayton
  • , Leonid M. Baskin
  • , Nicholas C. Coops
  • , Volker C. Radeloff
  • *此作品的通讯作者
  • University of Wisconsin-Madison
  • NextGIS
  • Swiss Federal Institute for Forest, Snow and Landscape Research
  • Radboud University Nijmegen
  • University of Wisconsin-Madison
  • Russian Academy of Sciences
  • University of British Columbia

科研成果: 期刊稿件文章同行评审

摘要

Aim: Predicting biodiversity responses to global changes requires good models of species' distributions. Both environmental conditions and human activities determine population density patterns. However, quantifying the relationship between wildlife population densities and their underlying environmental conditions across large geographical scales has remained challenging. Our goal was to explain the abundances of mammal species based on their response to several remotely sensed indices including the Dynamic Habitat Indices (DHIs) and the novel Winter Habitat Indices (WHIs). Location: Russia, the majority of regions. Taxon: Eight mammal species. Methods: We estimated average population densities for each species across Russia from 1981 to 2010 from winter track counts. The DHIs measure vegetative productivity, a proxy for food availability. Our WHIs included the duration of snow-free ground, duration of snow-covered ground and the start, end and length of frozen season. In models, we included elevation, climate conditions, human footprint index. We parameterized multiple linear regression and applied best-subset model selection to determine the main factors influencing population density. Results: The DHIs were included in some of the top-twelve models of every species, and in the top model for moose, wild boar, red fox and wolf, so they were important for species at all trophic levels. The WHIs were included in top models for all species except roe deer, demonstrating the importance of winter conditions. The duration of frozen ground without snow and the end of frozen season were particularly important. Our top models performed well for all the species (R2adj 0.43–0.87). Main Conclusions: The combination of the DHIs and the WHIs with climate and human-related variables resulted in high explanatory power. We show that vegetation productivity and winter conditions are key drivers of variation in population density of eight species across Russia.

源语言英语
页(从-至)932-946
页数15
期刊Journal of Biogeography
50
5
DOI
出版状态已出版 - 5月 2023

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