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 (R2
adj 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.
Abundance patterns of mammals across Russia explained by remotely sensed vegetation productivity and snow indices
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