Connectivity, conservation and catch: Understanding the effects of dispersal between harvested and protected patches.

IF 1.2 4区 生物学 Q4 ECOLOGY
Femke N Reurik, Juan Segura, Frank M Hilker
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引用次数: 0

Abstract

Overharvesting is a pressing global problem, and spatial management, such as protecting designated areas, is one proposed solution. This study examines how connectivity (in terms of dispersal rate) between protected and harvested areas affects the asymptotic total population size and the asymptotic yield, which are key questions for conservation management and the design of protected areas. We utilize a two-patch model with heterogeneous habitat qualities, symmetric dispersal and density-dependent growth functions in both discrete and continuous time. One patch is subject to proportional harvesting, while the other one is protected. Our results show that increased dispersal does not always increase the asymptotic total population size or the asymptotic yield. Depending on the circumstances, dispersal enables the protected patch to rescue the harvested patch from overexploitation, potentially increasing both total population size and yield. However, high levels of dispersal can also lead to a lower total population size or even cause extinction of both patches if harvesting pressure is strong. The population in the protected patch needs to have high reproductive potential and the protected patch needs to be the effectively larger patch in order to benefit monotonically from increased dispersal. These findings provide a fundamental understanding of how dispersal influences dynamics in fragmented landscapes under harvesting pressure.

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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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