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  1. rSPACE: Spatially based power analysis for conservation and ecology

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    Author(s): Martha M. Ellis; Jacob S. Ivan; Jody M. Tucker; Michael K. Schwartz
    Date: 2015
    Source: Methods in Ecology and Evolution. doi: 10.1111/2041-210X.12369.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    DOI: https://doi.org/10.1111/2041-210X.12369
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    Description

    1.) 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. 2.) 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. 3.) The proposed method and software are demonstrated with an analysis of wolverine monitoring in a U.S. Northern Rocky Mountain landscape. 4.) The package will be of use to ecologists interested in evaluating objectives and performance of monitoring programs.

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    Citation

    Ellis, Martha M.; Ivan, Jacob S.; Tucker, Jody M.; Schwartz, Michael K. 2015. rSPACE: Spatially based power analysis for conservation and ecology. Methods in Ecology and Evolution. doi: 10.1111/2041-210X.12369.

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    Keywords

    detection probability, occupancy estimation, population monitoring, population trends, power analysis, sampling design, spatial simulation

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