reindeer_rsf | R Documentation |
An data set where GPS positions of wild reindeer (Rangifer tarandus tarandus) Hardangervidda management area, southern Norway, were organized in a use-availability design for point resource-selection analysis (RSA) and annotated with environmental data. It includes data from 115 female individuals collected between 2001 and 2019. The data set was regularized with 3h data and 9 random locations were created for each used location. It was then annotated with rasters on the zone of influence of private cabins and public resorts with exponential decay shape and radii varying from 100m to 10km, as well as land cover and bio-geo-climatic variables. Geographical coordinates of the used and random positions were omitted after data annotation.
This is part of the data set used for analysis in Niebuhr et al. (2023). ZOI variables with shapes other than the exponential decay were omitted.
data(reindeer_rsf)
A data frame with 31,735 rows and 28 variables:
Case in the use-availability setup; 1 represents a used location, 0 represents a random locations.
Components 1 to 4 from a principal component analysis representing bio-geo-climatic variation in Norway, from Bakkestuen et al. 2008. PCAs 1 to 4 represent, respectively, continentality, altitude, terrain ruggedness, and solar radiation. More information in Niebuhr et al. 2023.
Squared value for components 1 and 2 to from a principal component analysis representing bio-geo-climatic variation in Norway, from Bakkestuen et al. 2008.
Land use and land cover classes from NORUT, reclassified as in Niebuhr et al. 2023.
Cumulative zone of influence of private cabins at each location, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Zone of influence of the nearest private cabin at each location, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Cumulative zone of influence of public resorts at each location, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Zone of influence of the nearest public resort at each location, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Cumulative zone of influence of private, low traffic roads, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Zone of influence of the nearest private, low traffic road with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Cumulative zone of influence of public, high traffic roads, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Zone of influence of the nearest public, high traffic road with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Cumulative zone of influence of trails, weighted by the number of tourists in each trail, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Zone of influence of the nearest trail, weighted by the number of tourists in the trail, with exponential decay shape, and radii defined by XXX (from 100 to 20000m).
Niebuhr, B. B., Van Moorter, B., Stien, A., Tveraa, T., Strand, O., Langeland, K., Sandström, P., Alam, M., Skarin, A., & Panzacchi, M. (2023). Estimating the cumulative impact and zone of influence of anthropogenic features on biodiversity. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.14133
Bakkestuen, V., Erikstad, L., & Halvorsen, R. (2008). Step-less models for regional environmental variation in Norway. Journal of Biogeography, 35(10), 1906–1922. https://doi.org/10.1111/j.1365-2699.2008.01941.x
library(tibble)
data("reindeer_rsf")
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