21 Viable Populations in Dynamic Forests

I have heard some foresters and biologists say, “We manage habitat, not populations.” The Field of Dreams approach to wildlife management: Build it and they will come. But will they? Can they, given the limited mobility of some species and intervening forest conditions now and 50 years from now? If they do come to the new habitat, how long will they last there? How does their presence contribute to ensuring that the greater population is not going extinct? All of these questions relate to understanding population viability.

Population viability analysis (PVA) is a structured approach to examining population performance—to link population performance with the quantity, quality, and distribution patterns of habitat and to predict the probability of population extinction or persistence. The approach is based on a marriage among the concepts of demography, population dynamics, habitat selection, and landscape dynamics. Many of the concepts covered in this book to this point provide the foundation for an assessment of population viability in forested landscapes. PVA models and analyses originally were developed in response to the concern for the persistence of small or isolated populations, a response to law (e.g., the Endangered Species Act and the National Forest Management Act), and to large-scale regional assessments. More recent applications include predicting the potential success of reintroductions of plants and animals and assessing strategic development of habitat improvement projects (Knight 2012, Bonnot et al. 2013). PVA techniques are both elegant and uncertain. PVA is a modeling exercise and, as Box and Draper (1987) have said, “All models are wrong, but some are useful.” The results from a PVA can be useful in guiding management alternatives if uncertainty is understood and included in the decision-making process.

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Viable Populations in Dynamic Forests from Wildlife Habitat Management

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Wildlife Habitat Management Copyright © 2022 by Brenda C. McComb is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.