Choosing reserve networks with incomplete species information

Stephen Polasky; Jeffrey D. Camm; Andrew R. Solow; Blair Csuti; Denis White; Rugang Ding

doi:10.1016/S0006-3207(99)00171-8

Choosing reserve networks with incomplete species information

Stephen Polasky, Jeffrey D. Camm, Andrew R. Solow, Blair Csuti, Denis White, Rugang Ding

Applied Economics

Research output: Contribution to journal › Article › peer-review

150 Scopus citations

Abstract

Existing methods for selecting reserve networks require data on the presence or absence of species at various sites. This information, however, is virtually always incomplete. In this paper, we analyze methods for choosing priority conservation areas when there is incomplete information about species distributions. We formulate a probabilistic model and find the reserve network that represents the greatest expected number of species. We compare the reserve network chosen using this approach with reserve networks chosen when the data is treated as if presence/absence information is known and traditional approaches are used. We find that the selection of sites differs when using probabilistic data to maximize the expected number of species represented versus using the traditional approaches. The broad geographic pattern of which sites are chosen remains similar across these different methods but some significant differences in site selection emerge when probabilities of species occurrences are not near 0 or 1. (C) 2000 Elsevier Science Ltd.

Original language	English (US)
Pages (from-to)	1-10
Number of pages	10
Journal	Biological Conservation
Volume	94
Issue number	1
DOIs	https://doi.org/10.1016/S0006-3207(99)00171-8
State	Published - Jun 2000

Bibliographical note

Funding Information:
Data on Oregon terrestrial vertebrates are a part of the Oregon Gap Analysis Program, US National Biological Service. Part of this work was supported by the Biodiversity Research Consortium (BRC), a group of US government agencies, academic, and non-governmental institutions performing coordinated research on biodiversity assessment and management methods. The BRC acknowledges the support of Cooperative Research Agreement PNW 92-0283 between the USDA Forest Service and Oregon State University, Interagency Agreement DW12935631 between the US EPA and the USDA Forest Service, and the USDA Forest Service, Pacific Northwest Research Station. We thank Eleanor Gaines for directing development of the species distribution data base. We thank Brian Davis, Bob Pressey, Paul Williams for helpful comments.

Keywords

Incomplete information
Reserve selection
Species distributions

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title = "Choosing reserve networks with incomplete species information",

abstract = "Existing methods for selecting reserve networks require data on the presence or absence of species at various sites. This information, however, is virtually always incomplete. In this paper, we analyze methods for choosing priority conservation areas when there is incomplete information about species distributions. We formulate a probabilistic model and find the reserve network that represents the greatest expected number of species. We compare the reserve network chosen using this approach with reserve networks chosen when the data is treated as if presence/absence information is known and traditional approaches are used. We find that the selection of sites differs when using probabilistic data to maximize the expected number of species represented versus using the traditional approaches. The broad geographic pattern of which sites are chosen remains similar across these different methods but some significant differences in site selection emerge when probabilities of species occurrences are not near 0 or 1. (C) 2000 Elsevier Science Ltd.",

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note = "Funding Information: Data on Oregon terrestrial vertebrates are a part of the Oregon Gap Analysis Program, US National Biological Service. Part of this work was supported by the Biodiversity Research Consortium (BRC), a group of US government agencies, academic, and non-governmental institutions performing coordinated research on biodiversity assessment and management methods. The BRC acknowledges the support of Cooperative Research Agreement PNW 92-0283 between the USDA Forest Service and Oregon State University, Interagency Agreement DW12935631 between the US EPA and the USDA Forest Service, and the USDA Forest Service, Pacific Northwest Research Station. We thank Eleanor Gaines for directing development of the species distribution data base. We thank Brian Davis, Bob Pressey, Paul Williams for helpful comments.",

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AU - White, Denis

AU - Ding, Rugang

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N2 - Existing methods for selecting reserve networks require data on the presence or absence of species at various sites. This information, however, is virtually always incomplete. In this paper, we analyze methods for choosing priority conservation areas when there is incomplete information about species distributions. We formulate a probabilistic model and find the reserve network that represents the greatest expected number of species. We compare the reserve network chosen using this approach with reserve networks chosen when the data is treated as if presence/absence information is known and traditional approaches are used. We find that the selection of sites differs when using probabilistic data to maximize the expected number of species represented versus using the traditional approaches. The broad geographic pattern of which sites are chosen remains similar across these different methods but some significant differences in site selection emerge when probabilities of species occurrences are not near 0 or 1. (C) 2000 Elsevier Science Ltd.

AB - Existing methods for selecting reserve networks require data on the presence or absence of species at various sites. This information, however, is virtually always incomplete. In this paper, we analyze methods for choosing priority conservation areas when there is incomplete information about species distributions. We formulate a probabilistic model and find the reserve network that represents the greatest expected number of species. We compare the reserve network chosen using this approach with reserve networks chosen when the data is treated as if presence/absence information is known and traditional approaches are used. We find that the selection of sites differs when using probabilistic data to maximize the expected number of species represented versus using the traditional approaches. The broad geographic pattern of which sites are chosen remains similar across these different methods but some significant differences in site selection emerge when probabilities of species occurrences are not near 0 or 1. (C) 2000 Elsevier Science Ltd.

KW - Incomplete information

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KW - Species distributions

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Choosing reserve networks with incomplete species information

Abstract

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