Conservation Biology and Real-World Conservation

Abstract:  In the 20 years since Conservation Biology was launched with the aim of disseminating scientific knowledge to help conserve biodiversity and the natural world, our discipline has hugely influenced the practice of conservation. But we have had less impact outside the profession itself, and we have not transformed that practice into an enterprise large enough to achieve our conservation goals. As we look to the next 20 years, we need to become more relevant and important to the societies in which we live. To do so, the discipline of conservation biology must generate answers even when full scientific knowledge is lacking, structure scientific research around polices and debates that influence what we value as conservationists, go beyond the certitude of the biological sciences into the more contextual debates of the social sciences, engage scientifically with human-dominated landscapes, and address the question of how conservation can contribute to the improvement of human livelihoods and the quality of human life.     

Bayesian Methods in Conservation Biology

Abstract: Bayesian statistical inference provides an alternate way to analyze data that is likely to be more appropriate to conservation biology problems than traditional statistical methods. I contrast Bayesian techniques with traditional hypothesis-testing techniques using examples applicable to conservation. I use a trend analysis of two hypothetical populations to illustrate how easy it is to understand Bayesian results, which are given in terms of probability. Bayesian trend analysis indicated that the two populations had very different chances of declining at biologically important rates. For example, the probability that the first population was declining faster than 5% per year was 0.00, compared to a probability of 0.86 for the second population. The Bayesian results appropriately identified which population was of greater conservation concern. The Bayesian results contrast with those obtained with traditional hypothesis testing. Hypothesis testing indicated that the first population, which the Bayesian analysis indicated had no chance of declining at > 5% per year, was declining significantly because it was declining at a slow rate and the abundance estimates were precise. Despite the high probability that the second population was experiencing a serious decline, hypothesis testing failed to reject the null hypothesis of no decline because the abundance estimates were imprecise. Finally, I extended the trend analysis to illustrate Bayesian decision theory, which allows for choice between more than two decisions and allows explicit specification of the consequences of various errors. The Bayesian results again differed from the traditional results: the decision analysis led to the conclusion that the first population was declining slowly and the second population was declining rapidly.     

Conservation Biology in Historical Perspective

Book reviewed in this article:
The American Conservation Movement: John Muir and His Legacy . Fox, S.
Aldo Leopold: His Life and Work. Meine, C.
An Overview of Biodiversity
Biodiversity. Wilson, E. O., editor.
Value of Biodiversity
Why Preserve Natural Variety? Norton, B.G.
Management of Common Property Resources
Proceedings of the Conference on Common Property Resource Management. Panel on Common Property Resource Management (Bromley, D. W., chair).
Conservation and Management of Bird Populations
The Pheasant: Ecology, Management and Conservation. Hill, D., and Robertson, P.
Ecology and Conservation of Grassland Birds. Goriup, P. D., editor.
Mammal Populations
Mammal Populations Mammal Population Studies. Harris, S., editor.
Taking a Stand for Forests
Last Stand of the Red Spruce . Mello, R. A.