Latitudinal gradient and species traits determine bat distributions
across Europe
Abstract
Climatic and anthropogenic impacts have determined the extinction of
species in the past and are also the main factors shaping their present
distribution ranges. Geographic range size – a biogeographic variable
commonly used to assess population abundance, survival, and conservation
status – varies with latitude. According to Rapoport’s rule, range size
typically increases with latitude in mammals. Bats differ from other
groups of mammals with regards to numerous morphological, physiological,
and behavioral adaptations of sensory and motor systems. Nevertheless,
bats are a suitable group for evaluating the rule because they show a
strong latitudinal gradient in species richness. Our aim was to
investigate the distribution patterns of European bat fauna based on two
biogeographic variables 1) geographical range size and 2) average
latitude of their distribution range, and investigate whether species
traits characteristic to bats, mobility and hibernation, are associated
with variation in range size and latitudinal distribution. We collected
geographical data and species trait data on 44 European bat species from
the literature. We discovered that range size and average latitude of
distribution range follows Rapoport’s rule to a high degree in bats.
Additionally, traits related to hibernation and movement behavior, more
specifically hibernation breadth (indicating how widely a species
utilizes different types of hibernacula) and mobility (based on seasonal
movements), are associated with large distribution ranges and could
affect northerly ranges in European bats. Range size does not only
assist in directing conservation of threatened species, but it also
provides insights into fundamental processes such as dispersal and
adaptation. Our results emphasize that knowledge on the relationship
between traits and species distribution is important for understanding
current distribution patterns and could work as background information
for predictive models on the effect of future landscape changes.