Literature DB >> 10746724

Predictive accuracy of population viability analysis in conservation biology.

B W Brook1, J J O'Grady, A P Chapman, M A Burgman, H R Akçakaya, R Frankham.   

Abstract

Population viability analysis (PVA) is widely applied in conservation biology to predict extinction risks for threatened species and to compare alternative options for their management. It can also be used as a basis for listing species as endangered under World Conservation Union criteria. However, there is considerable scepticism regarding the predictive accuracy of PVA, mainly because of a lack of validation in real systems. Here we conducted a retrospective test of PVA based on 21 long-term ecological studies--the first comprehensive and replicated evaluation of the predictive powers of PVA. Parameters were estimated from the first half of each data set and the second half was used to evaluate the performance of the model. Contrary to recent criticisms, we found that PVA predictions were surprisingly accurate. The risk of population decline closely matched observed outcomes, there was no significant bias, and population size projections did not differ significantly from reality. Furthermore, the predictions of the five PVA software packages were highly concordant. We conclude that PVA is a valid and sufficiently accurate tool for categorizing and managing endangered species.

Mesh:

Year:  2000        PMID: 10746724     DOI: 10.1038/35006050

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  40 in total

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4.  Effects of weather and climate on the dynamics of animal population time series.

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5.  Population-level assessment of risks of pesticides to birds and mammals in the UK.

Authors:  R M Sibly; H R Akçakaya; C J Topping; R J O'Connor
Journal:  Ecotoxicology       Date:  2005-11-22       Impact factor: 2.823

6.  Environmental stochasticity in dispersal areas can explain the "mysterious" disappearance of breeding populations.

Authors:  Vincenzo Penteriani; Fermín Otalora; Fabrizio Sergio; Miguel Ferrer
Journal:  Proc Biol Sci       Date:  2005-06-22       Impact factor: 5.349

7.  Metapopulation extinction risk is increased by environmental stochasticity and assemblage complexity.

Authors:  James C Bull; Nicola J Pickup; Brian Pickett; Michael P Hassell; Michael B Bonsall
Journal:  Proc Biol Sci       Date:  2007-01-07       Impact factor: 5.349

8.  Modeling effects of disturbance across life history strategies of stream fishes.

Authors:  Robert J Fournier; Nick R Bond; Daniel D Magoulick
Journal:  Oecologia       Date:  2021-05-20       Impact factor: 3.225

9.  Long-term differences in extinction risk among the seven forms of rarity.

Authors:  Paul G Harnik; Carl Simpson; Jonathan L Payne
Journal:  Proc Biol Sci       Date:  2012-10-24       Impact factor: 5.349

10.  How important is individual foraging specialisation in invasive predators for native-prey population viability?

Authors:  Pablo García-Díaz; Rachelle N Binny; Dean P Anderson
Journal:  Oecologia       Date:  2021-01-08       Impact factor: 3.225

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