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Balkenhol, N.

Publications and source records attributed to Balkenhol, N..

3 recordsLinked to original sources

Human footprint and forest disturbance reduce space use of brown bears across Europe.

Three-quarters of the planets land surface has been altered by humans, with consequences for animal ecology, movements and related ecosystem functioning. Species often occupy wide geographical ranges with contrasting human disturbance and environmental conditions, yet, limited data availability across species ranges has constrained our understanding of how human impact and resource availability jointly shape intraspecific variation of animal space use. Leveraging a unique dataset of 752 annual GPS movement trajectories from 370 brown bears (Ursus arctos) across the species range in Europe, we investigated the effects of human impact (i.e., human footprint index), resource availability, forest cover and disturbance, and area-based conservation measures on brown bear space use. We quantified space use at different spatio-temporal scales during the growing season (May - September): home range size; representing general space requirements, 10-day long-distance displacement distances, and routine 1-day displacement distances. We found large intraspecific variation in brown bear space use across all scales, which was profoundly affected by human footprint index, vegetation productivity, and recent forest disturbances creating opportunity for resource pulses. Bears occupied smaller home ranges and moved less in more anthropized landscapes and in areas of higher resource availability. Forest disturbances reduced space use while contiguous forest cover promoted longer daily movements. The amount of strictly protected and roadless areas within bear home ranges were too small to affect space use. Anthropized landscapes may hinder the expansion of small and isolated populations, such as the Apennine and Pyrenean, and obstruct population connectivity, for example between the Alpine or Carpathian with the Dinaric Pindos populations. Our findings call for actions to maintain bear movements across landscapes with high human footprint, for example by maintaining forest integrity, to support viable bear populations and their ecosystem functions.

ecology↗

Simulating animal space use from fitted integrated Step-Selection Functions (iSSF)

O_LIA standing challenge in the study of animal movement ecology is the capacity to predict where and when an individual animal might occur on the landscape, the so-called, Utilization Distribution (UD). Under certain assumptions, the steady-state UD can be predicted from a fitted exponential habitat selection function. However, these assumptions are rarely met. Furthermore, there are many applications that require the estimation of transient dynamics rather than steady-state UDs (e.g. when modeling migration or dispersal). Thus, there is a clear need for computational tools capable of predicting UDs based on observed animal movement data. C_LIO_LIIntegrated Step-Selection Analyses (iSSAs) are widely used to study habitat selection and movement of wild animals, and result in a fully parametrized individual-based model of animal movement, which we refer to as an integrated Step Selection Function (iSSF). An iSSF can be used to generate stochastic animal paths based on random draws from a series of Markovian redistribution kernels, each consisting of a selection-free, but possibly habitat-influenced, movement kernel and a movement-free selection function. The UD can be approximated by a sufficiently large set of such stochastic paths. C_LIO_LIHere, we present a set of functions in R to facilitate the simulation of animal space use from fitted iSSFs. Our goal is to provide a general purpose simulator that is easy to use and is part of an existing workflow for iSSAs (within the amt R package). C_LIO_LIWe demonstrate through a series of applications how the simulator can be used to address a variety of questions in applied movement ecology. By providing functions in amt and coded examples, we hope to encourage ecologists using iSSFs to explore their predictions and model goodness-of-fit using simulations, and to further explore mechanistic approaches to modeling landscape connectivity. C_LI

ecology↗

Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe

Biotic interactions are expected to influence species responses to climate change, but they are usually not included when predicting future range shifts. We assessed the importance of biotic interactions to understand future consequences of climate and land use change for biodiversity using as a model system the brown bear (Ursus arctos) in Europe. By including biotic interactions using the spatial variation of energy contribution and habitat models of each food species, we showed that the use of biotic factors considerably improves our understanding of the distribution of brown bears. Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, warning about future indirect climate change effects. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future scenarios of biodiversity change, which is key for conserving biodiversity and ecosystem services.

ecology↗