Evaluating Impact Using Time-Series Data

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Evaluating Impact Using Time-Series Data. / Wauchope, Hannah S.; Amano, Tatsuya; Geldmann, Jonas; Johnston, Alison; Simmons, Benno I.; Sutherland, William J.; Jones, Julia P.G.

In: Trends in Ecology and Evolution, Vol. 36, No. 3, 2021, p. 196-205.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Wauchope, HS, Amano, T, Geldmann, J, Johnston, A, Simmons, BI, Sutherland, WJ & Jones, JPG 2021, 'Evaluating Impact Using Time-Series Data', Trends in Ecology and Evolution, vol. 36, no. 3, pp. 196-205. https://doi.org/10.1016/j.tree.2020.11.001

APA

Wauchope, H. S., Amano, T., Geldmann, J., Johnston, A., Simmons, B. I., Sutherland, W. J., & Jones, J. P. G. (2021). Evaluating Impact Using Time-Series Data. Trends in Ecology and Evolution, 36(3), 196-205. https://doi.org/10.1016/j.tree.2020.11.001

Vancouver

Wauchope HS, Amano T, Geldmann J, Johnston A, Simmons BI, Sutherland WJ et al. Evaluating Impact Using Time-Series Data. Trends in Ecology and Evolution. 2021;36(3):196-205. https://doi.org/10.1016/j.tree.2020.11.001

Author

Wauchope, Hannah S. ; Amano, Tatsuya ; Geldmann, Jonas ; Johnston, Alison ; Simmons, Benno I. ; Sutherland, William J. ; Jones, Julia P.G. / Evaluating Impact Using Time-Series Data. In: Trends in Ecology and Evolution. 2021 ; Vol. 36, No. 3. pp. 196-205.

Bibtex

@article{7527b8a70c894e7ebcd76a8835e9de5a,
title = "Evaluating Impact Using Time-Series Data",
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.",
keywords = "before-after-control-intervention, causal inference, counterfactual, difference in differences, interrupted time series, longitudinal data",
author = "Wauchope, {Hannah S.} and Tatsuya Amano and Jonas Geldmann and Alison Johnston and Simmons, {Benno I.} and Sutherland, {William J.} and Jones, {Julia P.G.}",
year = "2021",
doi = "10.1016/j.tree.2020.11.001",
language = "English",
volume = "36",
pages = "196--205",
journal = "Trends in Ecology & Evolution",
issn = "0169-5347",
publisher = "Elsevier Ltd. * Trends Journals",
number = "3",

}

RIS

TY - JOUR

T1 - Evaluating Impact Using Time-Series Data

AU - Wauchope, Hannah S.

AU - Amano, Tatsuya

AU - Geldmann, Jonas

AU - Johnston, Alison

AU - Simmons, Benno I.

AU - Sutherland, William J.

AU - Jones, Julia P.G.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - before-after-control-intervention

KW - causal inference

KW - counterfactual

KW - difference in differences

KW - interrupted time series

KW - longitudinal data

U2 - 10.1016/j.tree.2020.11.001

DO - 10.1016/j.tree.2020.11.001

M3 - Journal article

C2 - 33309331

VL - 36

SP - 196

EP - 205

JO - Trends in Ecology & Evolution

JF - Trends in Ecology & Evolution

SN - 0169-5347

IS - 3

ER -

ID: 256077581