The R package enerscape: A general energy landscape framework for terrestrial movement ecology ...
Ecological processes and biodiversity patterns are strongly affected by how animals move through the landscape. However, it remains challenging to predict animal movement and space use. Here we present our new R package enerscape to quantify and predict animal movement in real landscapes based on en...
| Main Authors: | , , , , , , , , , |
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| Format: | Dataset |
| Language: | English |
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Dryad
2021
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.wwpzgmskm https://datadryad.org/stash/dataset/doi:10.5061/dryad.wwpzgmskm |
| Summary: | Ecological processes and biodiversity patterns are strongly affected by how animals move through the landscape. However, it remains challenging to predict animal movement and space use. Here we present our new R package enerscape to quantify and predict animal movement in real landscapes based on energy expenditure. Enerscape integrates a general locomotory model for terrestrial animals with GIS tools in order to map energy costs of movement in a given environment, resulting in energy landscapes that reflect how energy expenditures may shape habitat use. Enerscape only requires topographic data (elevation) and the body mass of the studied animal. To illustrate the potential of enerscape, we analyze the energy landscape for the Marsican bear (Ursus arctos marsicanus) in a protected area in central Italy in order to identify least-cost paths and high-connectivity areas with low energy costs of travel. Enerscape allowed us to identify travel routes for the bear that minimize energy costs of movement and regions ... : This data repository contains only the shapefiles and javascript code that were not publicly available, but needed to reproduce the analysis of the linked article. All other publicly available data sources, which were not included in this data repository, were: Digital elevation model (DEM) for Italy was obtained from TINITALY (http://tinitaly.pi.ingv.it/). Sirente-Velino shapefile from Protected Planet (https://www.protectedplanet.net/en/search-areas?search_term=sirente-velino+regional+park&geo_type=site). DEM and Tree cover density for Denmark was obtained from the Danish National database: https://download.kortforsyningen.dk/content/dhm-2007terr%C3%A6n-10-m-grid and https://download.kortforsyningen.dk/content/treecoverdensity-tcd. NDVI was obtained from Sentinel-2 imagery accessed through Google Eearth Engine: https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2. L'Eroica shapefile was obtained from the official website of the event: https://eroica.cc/en/gaiole/permanent-route. ... |
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