The Performance of the Endangered Species Act

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Abstract

Arguably the most notable success of the Endangered Species Act (ESA) is that listed species improve in status through time. More species are downlisted than the converse; more species transition from stable to improving status than the converse. Although some listed species have gone extinct, this number is smaller than expected. Given modest recovery funding, the fraction of listed species responding positively is remarkable. Several factors have been linked to improving species status including recovery expenditures, critical habitat listing, and time spent under protection. The inability of government to fully empower the agencies to implement the law has been the most notable failure of the ESA. Listing of species has not matched need, recovery expenditures do not match need or agency-set priorities, and critical habitat determinations have lagged. Alternative protection strategies to listing may be having a positive effect, but are difficult to assess because of sparse data.

Most cited references 66

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What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

Robin S Waples, Oscar E Gaggiotti (2006)

We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered 'populations'. Units for these criteria are migration rate (m) for the ecological paradigm and migrants per generation (Nm) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellite-like) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high ( approximately 100%; P < 0.001) even with high gene flow (Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L. Under the standard parameter set, power to detect restricted gene flow below a certain level X (H(0): Nm < X) can also be high, provided that true Nm < or = 0.5X. Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow (Nm < or = 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.