Vegetation productivity summarized by the Dynamic Habitat Indices explains broad-scale patterns of moose abundance across Russia

Elena Razenkova (Corresponding author), Volker C. Radeloff, Maxim Dubinin, Eugenia V. Bragina, Andrew M. Allen, Murray K. Clayton, Anna M. Pidgeon, Leonid M. Baskin, Nicholas C. Coops, Martina L. Hobi

Research output: Contribution to journal/periodicalArticleScientificpeer-review

Abstract

Identifying the factors that determine habitat suitability and hence patterns of wildlife abundances over broad spatial scales is important for conservation. Ecosystem productivity is a key aspect of habitat suitability, especially for large mammals. Our goals were to a) explain patterns of moose (Alces alces) abundance across Russia based on remotely sensed measures of vegetation productivity using Dynamic Habitat Indices (DHIs), and b) examine if patterns of moose abundance and productivity differed before and after the collapse of the Soviet Union. We evaluated the utility of the DHIs using multiple regression models predicting moose abundance by administrative regions. Univariate models of the individual DHIs had lower predictive power than all three combined. The three DHIs together with environmental variables, explained 79% of variation in moose abundance. Interestingly, the predictive power of the models was highest for the 1980s, and decreased for the two subsequent decades. We speculate that the lower predictive power of our environmental variables in the later decades may be due to increasing human influence on moose densities. Overall, we were able to explain patterns in moose abundance in Russia well, which can inform wildlife managers on the long-term patterns of habitat use of the species.

Original languageEnglish
Article number836
JournalScientific Reports
Volume10
Issue number1
DOIs
Publication statusPublished - 01 Dec 2020
Externally publishedYes

Keywords

  • international

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