abstract: Despite years of effort, the field of conservation biology still struggles to incorporate theories of animal behavior. I introduce in Chapter I the issues surrounding the disconnect between behavioral ecology and conservation biology, and propose the use of behavioral knowledge in population viability analysis. In Chapter II, I develop a framework that uses three strategies for incorporating behavior into demographic models, outline the costs of each strategy through decision analysis, and build on previous work in behavioral ecology and demography. First, relevant behavioral mechanisms should be included in demographic models used for conservation decision-making. Second, I propose rapid behavioral assessment as a useful tool to approximate demographic rates through regression of demographic phenomena on observations of related behaviors. This technique provides behaviorally estimated parameters that may be applied to population viability analysis for use in management. Finally, behavioral indices can be used as warning signs of population decline. The proposed framework combines each strategy through decision analysis to provide quantitative rules that determine when incorporating aspects of conservation behavior may be beneficial to management. Chapter III applies this technique to estimate birthrate in a colony of California sea lions in the Gulf of California, Mexico. This study includes a cost analysis of the behavioral and traditional parameter estimation techniques. I then provide in Chapter IV practical recommendations for applying this framework to management programs along with general guidelines for the development of rapid behavioral assessment. / Dissertation/Thesis / M.S. Biology 2012
| Identifer | oai:union.ndltd.org:asu.edu/item:15085 |
| Date | January 2012 |
| Contributors | Wildermuth, Robert Paul (Author), Gerber, Leah R (Advisor), Collins, James (Committee member), Smith, Andrew (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 85 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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