COS 33-10 - Assessing predictions of population viability analysis:  Peregrine falcon populations in California

Tuesday, August 9, 2011: 11:10 AM
19B, Austin Convention Center
J. Timothy Wootton, Ecology and Evolution, University of Chicago, Chicago, IL and Douglas A. Bell, East Bay Regional Park District, Oakland, CA
Background/Question/Methods

Population viability models (PVM) have become a tool that is regularly used to guide management of species of conservation interest.   Frequently these methods are employed prior to implementing management change, but follow-up analyses after implementing  new management plans to assess the predictive ability of PFMs is rare.  We tested predictions from our previously published (Ecol. Appl. 1992) PVM that probed the outcome of terminating supplemental releases of captive-bred peregrine falcons (Falco peregrinus) in California using a spatially structured two-stage matrix model.  Our model predicted that the population would grow (ln(λ) = 0.032) in the absence of population supplementation, when parameters were estimated from a combination of well-documented independent data on fecundity and numbers of released birds and estimated parameters (stage-specific survivorship) from fits of the model to contemporary data on population size. To test this prediction we first needed to identify an appropriate proxy for population size because intensive annual population monitoring was terminated when population supplements ceased in 1993.  We then used this proxy to generate annual estimates of population growth from 1993 onward.

Results/Conclusions

Breeding Bird Survey data and average counts per unit effort from Christmas Bird Counts corresponded relatively poorly to intensive population censuses, but the proportion of Christmas Birds Counts with observations of peregrine falcons fit the data well  (r2 = 0.989).  Using these data for 1993 onward, we found that population growth following termination of management was 0.033 + .119 (sd), in good agreement with our prior model predictions.  Our results suggest that population viability models can effectively predict outcomes following changes in management of populations of conservation concern over moderate time scales.

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