%0 Journal Article %1 Polasky20001 %A Polasky, Stephen %A Camm, Jeffrey D. %A Solow, Andrew R. %A Csuti, Blair %A White, Denis %A Ding, Rugang %D 2000 %J Biological Conservation %K conservation reserve-network stochastic-optimization wildlife-corridor %N 1 %P 1 - 10 %R DOI: 10.1016/S0006-3207(99)00171-8 %T Choosing reserve networks with incomplete species information %U http://www.sciencedirect.com/science/article/B6V5X-3YWX3BR-1/2/c396a357355a98ba4c5c5f3466273159 %V 94 %X 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.

@article{Polasky20001, 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.}, added-at = {2010-02-27T09:40:49.000+0100}, author = {Polasky, Stephen and Camm, Jeffrey D. and Solow, Andrew R. and Csuti, Blair and White, Denis and Ding, Rugang}, biburl = {https://www.bibsonomy.org/bibtex/2156ceca31b0447c309be9aa45597827a/kiyan}, description = {Using species distribution data from Oregon as a case study (data produced as part of state funded effort), studies a reserve network construction optimization problem, where the objective is to maximize the expected number of species represented in the network. They compare this with using explicit species distribution information to make decisions (which is probably incomplete and dynamic).}, doi = {DOI: 10.1016/S0006-3207(99)00171-8}, interhash = {0329c9d6c713b421f8604b7b7c26037d}, intrahash = {156ceca31b0447c309be9aa45597827a}, issn = {0006-3207}, journal = {Biological Conservation}, keywords = {conservation reserve-network stochastic-optimization wildlife-corridor}, number = 1, pages = {1 - 10}, timestamp = {2010-02-27T09:40:49.000+0100}, title = {Choosing reserve networks with incomplete species information}, url = {http://www.sciencedirect.com/science/article/B6V5X-3YWX3BR-1/2/c396a357355a98ba4c5c5f3466273159}, volume = 94, year = 2000 }