The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
virtualspecies, an R package to generate virtual species distributions
Open accessAbstract
virtualspecies is a freely available package for R designed to generate virtual species distributions, a procedure increasingly used in ecology to improve species distribution models. This package combines the existing methodological approaches with the objective of generating virtual species distributions with increased ecological realism. The package includes 1) generating the probability of occurrence of a virtual species from a spatial set of environmental conditions (i.e. environmental suitability), with two different approaches; 2) converting the environmental suitability into presence–absence with a probabilistic approach; 3) introducing dispersal limitations in the realised virtual species distributions and 4) sampling occurrences with different biases in the sampling procedure. The package was designed to be extremely flexible, to allow users to simulate their own defined species–environment relationships, as well as to provide a fine control over every simulation parameter. The package also includes a function to generate random virtual species distributions. We provide a simple example in this paper showing how increasing ecological realism of the virtual species impacts the predictive performance of species distribution models. We expect that this new package will be valuable to researchers willing to test techniques and protocols of species distribution models as well as various biogeographical hypotheses.
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Cites
A review of methods for the assessment of prediction errors in conservation presence/absence models
FIELDING, A. H., & BELL, J. F. (1997) · Environmental Conservation · doi:10.1017/s0376892997000088 · Cited by 6,956
The art of modelling range-shifting species: The art of modelling range-shifting species
Elith, J., Kearney, M., & Phillips, S. (2010) · Methods in Ecology and Evolution · doi:10.1111/j.2041-210x.2010.00036.x · Cited by 2,813
Varela, S., Anderson, R. P., García‐Valdés, R., & Fernández‐González, F. (2014) · Ecography · doi:10.1111/j.1600-0587.2013.00441.x · Cited by 433
Cited by
Predicting into unknown space? Estimating the area of applicability of spatial prediction models
Meyer, H., & Pebesma, E. (2021) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13650 · Cited by 662
Collinearity in ecological niche modeling: Confusions and challenges
Feng, X., Park, D. S., Liang, Y., Pandey, R., & Papeş, M. (2019) · Ecology and Evolution · doi:10.1002/ece3.5555 · Cited by 438
The area under the precision‐recall curve as a performance metric for rare binary events
Sofaer, H. R., Hoeting, J. A., & Jarnevich, C. S. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13140 · Cited by 375
Modelling species presence‐only data with random forests
Valavi, R., Elith, J., Lahoz‐Monfort, J. J., & Guillera‐Arroita, G. (2021) · Ecography · doi:10.1111/ecog.05615 · Cited by 307
Nearest neighbour distance matching Leave‐One‐Out Cross‐Validation for map validation
Milà, C., Mateu, J., Pebesma, E., & Meyer, H. (2022) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13851 · Cited by 119
Metadata
- Authors
- Leroy, B., Meynard, C. N., Bellard, C., & Courchamp, F.
- Venue
- Ecography
- Publisher
- Wiley
- Published
- 2015-06-15
- Volume
- 39
- Issue
- 6
- Pages
- 599-607
- ISSN
- 0906-7590 (ISSN-L)
- 1600-0587
- OpenAlex
- W1602238219
- Cited by
- 300
- References
- 3
- FWCI
- 5.08
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Leroy, B., Meynard, C. N., Bellard, C., & Courchamp, F. (2016). virtualspecies, an R package to generate virtual species distributions. Ecography. https://doi.org/10.1111/ecog.01388
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