10.5061/DRYAD.WWPZGMSKM
Berti, Emilio
0000-0001-9286-011X
German Center for Integrative Biodiversity Research
Davoli, Marco
Aarhus University
Buitenwerf, Robert
Aarhus University
Dyer, Alexander
German Center for Integrative Biodiversity Research
Hansen, Oskar
Aarhus University
Hirt, Myriam
German Center for Integrative Biodiversity Research
Svenning, Jens-Christian
Aarhus University
Terlau, Jördis
German Center for Integrative Biodiversity Research
Brose, Ulrich
German Center for Integrative Biodiversity Research
Vollrath, Fritz
University of Oxford
The R package enerscape: A general energy landscape framework for
terrestrial movement ecology
Dryad
dataset
2021
energy landscape
movement ecology
locomotory performance
enerscape
marsican bear
animal movement
Deutsche Forschungsgemeinschaft
https://ror.org/018mejw64
FZT 118
Deutsche Forschungsgemeinschaft
https://ror.org/018mejw64
BR 2315/21-1
The Velux Foundations
https://ror.org/007ww2d15
16549
Research Fund Denmark: Natural Sciences project MegaComplexity*
0135-00225B
2021-10-20T00:00:00Z
2021-10-20T00:00:00Z
en
https://doi.org/10.5281/zenodo.5532100
3096 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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 that have high landscape connectivity based on
movement efficiency, highlighting potential corridors. It also identifies
areas where high energy costs may prevent movement and dispersal,
potentially exacerbating human-wildlife conflicts in the park. A major
strength of enerscape is that it requires only widely available
topographic and body size data. As such, enerscape permits a first
cost-effective way to estimate landscape use and movement corridors even
when telemetry data is not readily available, such as for the example with
the bear. Enerscape is built in a modular way and other movement modes and
ecosystem types can be implemented when appropriate locomotory models are
available. In summary, enerscape is a new general tool that quantifies,
using minimal and widely available data, the energy costs of moving
through a landscape. This can clarify how and why animals move in real
landscapes and inform practical conservation and restoration decisions.
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. GPS records of horses and cattle are under embargo for one year. For more information contact emilio.berti@idiv.de.
This readme.txt file was generated on 2021-10-20 by Emilio Berti GENERAL
INFORMATION 1. Title of Dataset: The R package enerscape: A general energy
landscape framework for terrestrial movement ecology 2. Author Information
A. Corresponding author Name: Emilio Berti
Institution: German Center for Integrative Biodiversity Research (iDiv)
Address: Puschstrasse 4, Leipzig, Germany Email:
emilio.berti@idiv.de 3. Date of data collection: 2016-2017 4. Geographic
location of data collection: A. Rewilding site in Mols-Bjerge, Denmark
SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on the data:
CC0 "No Rights Reserved" 2. Links to publications that cite or
use the data: A. "The r package enerscape: A general energy
landscape framework for terrestrial movement ecology. Berti et al. (2021).
Methods in Ecology and Evolution (in press)" DATA & FILE
OVERVIEW 1. Directory tree: . ├── enerscape_0.1.3.tar.gz ├── mols-bjerge
│ ├── Mols.dbf │ ├── Mols.prj │ ├── Mols.shp │ └── Mols.shx ├──
monthly-ndvi.js └── readme.txt 1 directory, 7 files 1.1
enerscape_0.1.3.tar.gz is the last version of the R package ENERSCAPE
1.2 mols-bjerge contains the shapefiels (Mols.*) of the rewilding site in
Mols-Bjerge 1.3 monthly-ndvi.js is the javascript code to get NDVI
from Sentinel-2 imagery using Google Earth Engine. . Additional related
data collected that was not included in the current data package: 4. Are
there multiple versions of the dataset? no METHODOLOGICAL INFORMATION
1. Description of methods used for collection/generation of data:
Shapefiles for the Mols Bjerge rewilding site were obtained from GPS
localization of electric fences where all studied animals lived. 2.
Methods for processing the data: Shapefile data was not processed.
DATA-SPECIFIC INFORMATION FOR: enerscape_0.1.3.tar.gz This is the current
version of the enerscape package in CRAN. A version in active development
can be found at: https://github.com/emilio-berti/enerscape