4.7 Article

Linking management changes to population dynamic responses: the transfer function of a projection matrix perturbation

期刊

JOURNAL OF APPLIED ECOLOGY
卷 41, 期 6, 页码 1155-1161

出版社

WILEY
DOI: 10.1111/j.0021-8901.2004.00959.x

关键词

Eigenvalue; population management; robust control; sensitivity; trade-off; transition rate

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1. An important task in applied population ecology is to understand how changes to individual life-history parameters, such as survival, growth and fecundity, affect population dynamics. Parameter changes, or perturbations, may be caused by deliberate attempts to manage populations (e.g. in pest control, harvesting or conservation) or they may be side-effects of pollution, genetic modification and climate change. 2. For organisms with complicated life cycles, links between individual life histories and population dynamics are made using population projection matrix (PPM) modelling. 3. Changes to individual, or groups of, life-history transition rates within a PPM have a nonlinear impact on the resulting eigenvalues. Conventional sensitivity analysis calculates the derivative of the perturbation-eigenvalue curve to provide tangential linear extrapolation. Until now, only the simulation of perturbed PPMs has captured nonlinear perturbation effects. 4. Here we describe the transfer function of a matrix perturbation. The transfer function captures analytically the true relationship between perturbation magnitude and PPM eigenvalues. This analytical link extends easily to multi-transition and multiple perturbations, promotes an understanding of matrix properties, and provides a simple method to predict the perturbation required to achieve a desired population rate of increase. 5. We use the transfer function approach to analyse a PPM for the desert tortoise Gopherus agasizzii Cooper, in the context of conservation management decisions. 6. Synthesis and applications. The transfer function offers a novel and powerful framework for the analysis of population projection matrices (PPMs), giving precise predictive power and analytical understanding of population-level responses to life-history perturbations, for example in the design of conservation, pest control and population harvesting strategies, prediction of population effects of pollution in ecotoxicology, and in ecological risk assessment. A useful focus is to set a target for the desired rate of increase (or decline) of a population, and use the transfer function to determine how best to achieve this rate.

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