spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models
University of Connecticut · Stony Brook University · +6 more institutions
Abstract
Spatial thinning of species occurrence records can help address problems associated with spatial sampling biases. Ideally, thinning removes the fewest records necessary to substantially reduce the effects of sampling bias, while simultaneously retaining the greatest amount of useful information. Spatial thinning can be done manually; however, this is prohibitively time consuming for large datasets. Using a randomization approach, the ‘thin’ function in the spThin R package returns a dataset with the maximum number of records for a given thinning distance, when run for sufficient iterations. We here provide a worked example for the Caribbean spiny pocket mouse, where the results obtained match those of manual…
Citation impact
- FWCI
- 45.68
- Percentile
- 100%
- References
- 35
Authors
5- MEMatthew E. Aiello‐LammensCorresponding
University of Connecticut, Stony Brook University
- RARobert A. Boria
City College of New York
- ARAleksandar Radosavljević
City College of New York
- BVBruno Vilela
Universidad de Alcalá, Universidade Federal de Goiás
- RPRobert P. Anderson
The Graduate Center, CUNY, City College of New York, American Museum of Natural History, City University of New York
Topics & keywords
- Thinning
- Sampling (signal processing)
- Ecological niche
- Ecology
- Niche
- Spatial analysis
- Computer science
- Spatial ecology
- Life below water