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Factors influencing the detectability of early warning signals of population collapse


Clements, Christopher F; Drake, John M; Griffiths, Jason I; Ozgul, Arpat (2015). Factors influencing the detectability of early warning signals of population collapse. The American Naturalist, 186(1):50-58.

Abstract

The recent description of potentially generic early warning signals is a promising development that may help conservationists to anticipate a population's collapse prior to its occurrence. So far, the majority of such warning signals documented have been in highly controlled laboratory systems or theoretical models.
Data from wild populations, however, are typically restricted both temporally and spatially due to limited monitoring resources and intrinsic ecological heterogeneity – limitations that may affect the detectability of generic early warning signals, as they add additional stochasticity to population abundance estimates. Consequently, spatial and temporal subsampling may serve either to muffle or magnify early warning signals.
Using a combination of theoretical models and analysis of experimental data, we evaluate the extent to which statistical warning signs are robust to data corruption.

Abstract

The recent description of potentially generic early warning signals is a promising development that may help conservationists to anticipate a population's collapse prior to its occurrence. So far, the majority of such warning signals documented have been in highly controlled laboratory systems or theoretical models.
Data from wild populations, however, are typically restricted both temporally and spatially due to limited monitoring resources and intrinsic ecological heterogeneity – limitations that may affect the detectability of generic early warning signals, as they add additional stochasticity to population abundance estimates. Consequently, spatial and temporal subsampling may serve either to muffle or magnify early warning signals.
Using a combination of theoretical models and analysis of experimental data, we evaluate the extent to which statistical warning signs are robust to data corruption.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:2015
Deposited On:18 Jan 2016 16:58
Last Modified:08 May 2016 00:00
Publisher:University of Chicago Press
ISSN:0003-0147
Additional Information:© 2015 by The University of Chicago Press
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1086/681573

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