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    Power to detect trends in abundance within a distance sampling framework

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    Andersen_and_Steidl_2019_J_App ...
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    Author
    Andersen, Erik M.
    Steidl, Robert J.
    Affiliation
    Univ Arizona, Sch Nat Resources & Environm
    Issue Date
    2019-11-18
    Keywords
    distance sampling
    monitoring
    occupancy
    power analysis
    sample size
    sampling design
    statistical power
    trend detection
    
    Metadata
    Show full item record
    Publisher
    WILEY
    Citation
    Andersen, EM, Steidl, RJ. Power to detect trends in abundance within a distance sampling framework. J Appl Ecol. 2019; 00: 1– 10. https://doi.org/10.1111/1365-2664.13529
    Journal
    JOURNAL OF APPLIED ECOLOGY
    Rights
    © 2019 The Authors. Journal of Applied Ecology © 2019 British Ecological Society.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Ensuring that inferences from biological monitoring are reliable requires a level of sampling effort that is commensurate with programmatic objectives and reflects attributes of target populations. Consensus guidelines have emerged to guide allocation of sampling effort for programmes designed to detect trends in occupancy but not for abundance, despite its prevalence as a target parameter. We evaluated the influence of population attributes (density, availability, detection probability and magnitude of trend) and sampling design features (number of sites, number of repeat surveys, and survey-year interval) on a Bayesian analogue of statistical power to detect declines in abundance estimated using distance sampling methods. For a range of values common to terrestrial vertebrates, we simulated spatially and temporally replicated populations from which we generated survey data. We then analysed each dataset with a hierarchical open-population model that allowed for temporary emigration to estimate power for periods of 5-20 years. For a given amount of sampling effort, power to detect trends was highest when effort was allocated to maximizing the number of sites by decreasing the number of repeat surveys within a year and increasing the interval between survey years. For example, to have an 80% chance of detecting a 3% annual decline required 40% longer when 67 sites were surveyed three times per year compared to 600 sites surveyed once every three years despite both allocations requiring 4,000 surveys over 20 years. Notably, these patterns were independent of density or detectability of the target species, which contrasts with occupancy studies where optimal allocation shifts from surveying more sites to more repeat surveys when detectability is low or occupancy is high. Synthesis and applications. Our findings provide guidance for allocating resources efficiently for distance sampling studies focused on terrestrial vertebrates. By comparing the approximate density and detectability of target populations to those we considered, monitoring programmes can balance the amount of survey effort allocated to sites, surveys per site, and annual revisits to help ensure sufficient power to meet objectives effectively and efficiently. These decisions are increasingly important as budgets for conservation decrease and consequences of inaction continue to increase.
    Note
    12 month embargo; published online: 30 October 2019
    ISSN
    0021-8901
    DOI
    10.1111/1365-2664.13529
    Version
    Final accepted manuscript
    Sponsors
    Arizona Game and Fish Department [I14008]; U.S. Bureau of Land Management [3007730]
    ae974a485f413a2113503eed53cd6c53
    10.1111/1365-2664.13529
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