| Confronting two-sex demographic models with data. | |
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MedLine Citation:
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PMID: 22164838 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Most population dynamics models explicitly track the density of a single sex. When the operational sex ratio can vary, two-sex models may be needed to understand and predict population trajectories. Various functions have been proposed to describe the relative contributions of females and males to recruitment, and these functions can differ qualitatively in the patterns that they generate. Which mating function best describes the dynamics of real populations is not known, since alternative two-sex models have not been confronted with experimental data. We conducted the first such comparison, using laboratory populations of the bean beetle Callosobruchus maculatus. Manipulations of the operational sex ratio and total density provided strong support for a demographic model in which the birth rate was proportional to the harmonic mean of female and male densities, and females, males, and their offspring made unique contributions to density dependence. We offer guidelines for transferring this approach to other, less tractable systems in which possibilities for sex ratio manipulations are more limited. We show that informative experimental designs require strong perturbations of the operational sex ratio. The functional form of density dependence (saturating vs. over-compensatory) and the relative contributions of each sex to density dependence can both determine in which direction and at which population densities such perturbations would be most informative. Our experimental results and guidelines for design strategies promote synthesis of two-sex population dynamics theory with empirical data. |
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Authors:
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Tom E X Miller; Brian D Inouye |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S. |
Journal Detail:
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Title: Ecology Volume: 92 ISSN: 0012-9658 ISO Abbreviation: Ecology Publication Date: 2011 Nov |
Date Detail:
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Created Date: 2011-12-09 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0043541 Medline TA: Ecology Country: United States |
Other Details:
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Languages: eng Pagination: 2141-51 Citation Subset: IM |
Affiliation:
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Department of Ecology and Evolutionary Biology, Rice University, MS-170, Houston, Texas 77005, USA. Tom.Miller@rice.edu |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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