Demographic meta-analysis: synthesizing vital rates for spotted owls

Authors

  • MARK S. BOYCE,

    Corresponding author
      Mark S. Boyce, Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2E9 (fax +780 492 9234; e-mail boyce@ualberta.ca).
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  • LARRY L. IRWIN,

    1. Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2E9; National Council for Air and Stream Improvement, Stevensville, MT 57870, USA; and
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  • RICHARD BARKER

    1. Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand
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Mark S. Boyce, Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2E9 (fax +780 492 9234; e-mail boyce@ualberta.ca).

Summary

  • 1Effective resource management ultimately influences vital rates of fecundity and survival for target species. Meta-analysis can be used to combine results from multiple demographic studies replicated in time and space to obtain estimates of vital rates as well as metrics of population growth.
  • 2Workshop formats were used to conduct meta-analyses of mark–recapture experiments on spotted owls Strix occidentalis in the western USA. The implied motivation for demographic studies of spotted owls has been that changes in vital rates and population growth, λ, reflect the success of conservation strategies, but how to interpret results may not be obvious. Demographic analysis is of little practical utility until vital rates can be linked to management. In the case of spotted owls, future meta-analyses must focus on co-variation between vital rates and habitat variables, and experiments will be necessary.
  • 3Sensitivity of population growth to variation in vital rates is central to demographic analysis, but results must be interpreted cautiously because these sensitivities are not likely to identify the vital rates most responsible for variation in population size, and cannot reveal which vital rates will be most responsive to conservation investments.
  • 4Difficulties in documenting dispersal seriously compromised estimates of juvenile survival and thereby biased estimates of λpm from a projection matrix, a problem that was resolved in later workshops by estimating λRJS directly using a reparameterized Jolly–Seber mark–recapture method.
  • 5Several sources of bias for estimates of vital rates and λ were reviewed. Bias exists in meta-analysis estimates of λ combined over spatial replicates because λ is a non-linear function of vital rates. Bias also exists in estimates of average population growth where λt varies over time. This problem can be reduced by calculating the geometric mean of λ. Research to measure biases associated with the estimation of vital rates and the selection of study areas will be necessary to validate meta-analyses of demography for spotted owls.
  • 6Synthesis and applications. Meta-analysis is ideally suited to studies of the demography of long-lived species because of the large areas involved, high costs for each individual study, and multiple jurisdictions within which the organisms occur. Mixed models selected using information–theoretic approaches provide a powerful way to combine research results from several studies in a meta-analysis.

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