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Tytuł:
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Evaluating Impact Using Time-Series Data.
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Autorzy:
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Wauchope HS; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK; Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, TR10 9FE, UK. Electronic address: .
Amano T; School of Biological Sciences, University of Queensland, Brisbane, Australia; Centre for Biodiversity and Conservation Science, University of Queensland, Brisbane, Australia.
Geldmann J; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK; Center for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Johnston A; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK; Lab of Ornithology, Cornell University, Ithaca, New York, USA.
Simmons BI; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK; Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, TR10 9FE, UK; Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S10 2TN, UK.
Sutherland WJ; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK.
Jones JPG; School of Natural Sciences, Bangor University, Bangor, LL57 2UW, UK.
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Źródło:
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Trends in ecology & evolution [Trends Ecol Evol] 2021 Mar; Vol. 36 (3), pp. 196-205. Date of Electronic Publication: 2020 Dec 10.
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Typ publikacji:
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Journal Article; Research Support, Non-U.S. Gov't; Review
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Język:
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English
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Imprint Name(s):
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Publication: Barking : Elsevier Science Publishers
Original Publication: Amsterdam [Netherlands] : Elsevier Science Publishers B.V. [(Biomedical Division)], c1986-
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MeSH Terms:
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Biodiversity*
Conservation of Natural Resources*
Ecology
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Contributed Indexing:
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Keywords: before-after-control-intervention; causal inference; counterfactual; difference in differences; interrupted time series; longitudinal data
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Entry Date(s):
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Date Created: 20201214 Date Completed: 20210222 Latest Revision: 20210222
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Update Code:
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20240104
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DOI:
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10.1016/j.tree.2020.11.001
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PMID:
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33309331
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Humanity's impact on the environment is increasing, as are strategies to conserve biodiversity, but a lack of understanding about how interventions affect ecological and conservation outcomes hampers decision-making. Time series are often used to assess impacts, but ecologists tend to compare average values from before to after an impact; overlooking the potential for the intervention to elicit a change in trend. Without methods that allow for a range of responses, erroneous conclusions can be drawn, especially for large, multi-time-series datasets, which are increasingly available. Drawing on literature in other disciplines and pioneering work in ecology, we present a standardised framework to robustly assesses how interventions, like natural disasters or conservation policies, affect ecological time series.
(Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)
