rSPACE: Spatially based power analysis for conservation and ecology

• Published in: Methods in Ecology and Evolution
• Main Authors: Ellis, Martha M., Ivan, Jacob S., Tucker, Jody M., Schwartz, Michael K.
• Other Authors: Poisot, Timothée, USFS, RMRS, PECASE, USFWS Region 6
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2015
• Subjects: wolverine
• Online Access: http://dx.doi.org/10.1111/2041-210x.12369; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2F2041-210X.12369; https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12369; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/2041-210X.12369; https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12369

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.