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• W2097520543 abstract "Abstract: Conservation biology must be able to provide guidelines even when available data are incomplete, because data on rare and endangered species are usually limited. For instance, data on the effect of additional—human‐induced—sources of mortality on vertebrate populations, such as bycatch of seabirds by longline fisheries, are typically incomplete. The importance of an additional source of mortality can be evaluated by comparing it with the maximum annual growth rate of the species of concern, and various authors have attempted to determine the maximum growth rate from incomplete data. We developed a procedure we call the “demographic invariant method” (DIM). First we determined that the maximum growth rate per generation does not vary, by recalling that it is a dimensionless number primarily independent of body weight and also by empirically establishing its near constancy over a restricted set of bird species for which reliable demographic information was available. This first step provided an implicit function linking generation time and maximum annual growth rate, from which we obtained the maximum annual growth rate as a simple function of generation time. From several different ways of obtaining estimates of generation time, we derived in turn several ways to estimate the maximum annual growth rate of a bird species from incomplete demographic data set. We applied our approach to the Black‐footed Albatross (Phoebastria nigripes) and determined from incomplete data that longline fishery bycatch has a biologically significant impact on the growth potential of Black‐footed Albatross populations. Our method can be applied broadly to the conservation and management of harvested bird populations." @default.
• W2097520543 created "2016-06-24" @default.
• W2097520543 creator A5001604829 @default.
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• W2097520543 date "2005-06-01" @default.
• W2097520543 modified "2023-10-13" @default.
• W2097520543 title "Using Demographic Invariants to Detect Overharvested Bird Populations from Incomplete Data" @default.
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• W2097520543 doi "https://doi.org/10.1111/j.1523-1739.2005.00310.x" @default.
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