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Evaluating impact using time-series data

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Wauchope_2021_TEE_Evaluating_impact_time_series_data_CC.pdf (1.637Mb)
Date
03/2021
Author
Wauchope, Hannah S.
Amano, Tatsuya
Geldmann, Jonas
Johnston, Alison
Simmons, Benno
Sutherland, William J.
Jones, Julia P. G.
Keywords
Before-after-control-intervention
Longitudinal data
Counterfactual
Interrupted time series
Causal inference
Difference in differences
GE Environmental Sciences
QA Mathematics
QH301 Biology
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Abstract
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.
Citation
Wauchope , H S , Amano , T , Geldmann , J , Johnston , A , Simmons , B , Sutherland , W J & Jones , J P G 2021 , ' Evaluating impact using time-series data ' , Trends in Ecology & Evolution , vol. 36 , no. 3 , pp. 196-205 . https://doi.org/10.1016/j.tree.2020.11.001
Publication
Trends in Ecology & Evolution
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.tree.2020.11.001
ISSN
0169-5347
Type
Journal item
Rights
Copyright © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.
Description
H.S.W. was supported by the Cambridge Trust Poynton Scholarship, Cambridge Department of Zoology J.S. Gardiner Studentship, and Cambridge Philosophical Society; T.A. was supported by the Australian Research Council Future Fellowship (FT180100354), and the University of Queensland strategic funding; J.G. was supported by European Union’s Horizon 2020 Marie Skłodowska-Curie program (No. 706784), and VILLUM FONDEN (VKR023371); B.I.S. was supported by a Royal Commission for the Exhibition of 1851 Research Fellowship; W.J.S. is funded by Arcadia and J.P.G.J. was supported by the Leverhulme Trust: RPG-2014-056.
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/24397

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