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Population stabilityControl methodsExtinctionEffective population sizeRicker model

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dc.contributor.author TUNG, SUDIPTA en_US
dc.contributor.author Mishra, Abhishek en_US
dc.contributor.author DEY, SUTIRTH en_US
dc.date.accessioned 2019-02-25T09:04:14Z
dc.date.available 2019-02-25T09:04:14Z
dc.date.issued 2014-09 en_US
dc.identifier.citation Journal of Theoretical Biology, 356, 163-173. en_US
dc.identifier.issn 0022-5193 en_US
dc.identifier.issn 1095-8541 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2057
dc.identifier.uri https://doi.org/10.1016/j.jtbi.2014.04.036 en_US
dc.description.abstract Over the last two decades, several methods have been proposed for stabilizing the dynamics of biological populations. However, these methods have typically been evaluated using different population dynamics models and in the context of very different concepts of stability, which makes it difficult to compare their relative efficiencies. Moreover, since the dynamics of populations are dependent on the life-history of the species and its environment, it is conceivable that the stabilizing effects of control methods would also be affected by such factors, a complication that has typically not been investigated. In this study, we compare six different control methods with respect to their efficiency at inducing a common level of enhancement (defined as 50% increase) for two kinds of stability (constancy and persistence) under four different life-history/environment combinations. Since these methods have been analytically studied elsewhere, we concentrate on an intuitive understanding of realistic simulations incorporating noise, extinction probability and lattice effect. We show that for these six methods, even when the magnitude of stabilization attained is the same, other aspects of the dynamics like population size distribution can be very different. Consequently, correlated aspects of stability, like the amount of persistence for a given degree of constancy stability (and vice versa) or the corresponding effective population size (a measure of resistance to genetic drift) vary widely among the methods. Moreover, the number of organisms needed to be added or removed to attain similar levels of stabilization also varies for these methods, a fact that has economic implications. Finally, we compare the relative efficiencies of these methods through a composite index of various stability related measures. Our results suggest that Lower Limiter Control (LLC) seems to be the optimal method under most conditions, with the recently proposed Adaptive Limiter Control (ALC) being a close second. en_US
dc.language.iso en en_US
dc.publisher Elsevier B.V. en_US
dc.subject Population stability en_US
dc.subject Control methods en_US
dc.subject Extinction en_US
dc.subject Effective population en_US
dc.subject size Ricker model en_US
dc.subject 2014 en_US
dc.title Population stabilityControl methodsExtinctionEffective population sizeRicker model en_US
dc.type Article en_US
dc.contributor.department Dept. of Biology en_US
dc.identifier.sourcetitle Journal of Theoretical Biology en_US
dc.publication.originofpublisher Foreign en_US


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