rSPACE: spatially based power analysis for conservation and ecology
Item Metadata
Dublin Core
Title
rSPACE: spatially based power analysis for conservation and ecology
Description
Summary
- Power analysis is an important step in designing effective monitoring programs to detect trends in plant or animal populations. Although project goals often focus on detecting changes in population abundance, logistical constraints may require data collection on population indices, such as detection/non-detection data for occupancy estimation.
- We describe the open-source R package, rSPACE, for implementing a spatially based power analysis for designing monitoring programs. This method incorporates information on species biology and habitat to parameterize a spatially explicit population simulation. A sampling design can then be implemented to create replicate encounter histories which are subsampled and analysed to estimate the power of the monitoring program to detect changes in population abundance over time, using occupancy as a surrogate.
- The proposed method and software are demonstrated with an analysis of wolverine monitoring in a U.S. Northern Rocky Mountain landscape.
- The package will be of use to ecologists interested in evaluating objectives and performance of monitoring programs.
Bibliographic Citation
Ellis, M. M., J. S. Ivan, J. M. Tucker, and M. K. Schwartz. 2015. rSPACE: Spatially based power analysis for conservation and ecology. Methods in Ecology and Evolution 6:621-625. https://doi.org/10.1111/2041-210X.12369
Creator
Ellis, Martha M.
Ivan, Jacob S.
Tucker, Jody M.
Schwartz, Michael K.
Subject
Detection probability
Occupancy estimation
Population monitoring
Population trends
Power analysis
Sampling design
Spatial simulation
Extent
5 pages
Date Created
2015-03-11
Type
Article
Format
application/pdf
Language
English
Is Part Of
Methods in Ecology and Evolution
Collection
Citation
Ellis, Martha M. et al., “rSPACE: spatially based power analysis for conservation and ecology,” CPW Digital Collections, accessed April 24, 2024, https://cpw.cvlcollections.org/items/show/276.