1. Evaluating Impact Using Time-Series Data
- Author
-
Jonas Geldmann, Tatsuya Amano, Julia P. G. Jones, William J. Sutherland, Benno I. Simmons, Hannah S. Wauchope, Alison Johnston, Wauchope, Hannah [0000-0001-5370-4616], Sutherland, William [0000-0002-6498-0437], and Apollo - University of Cambridge Repository
- Subjects
before-after-control-intervention ,0106 biological sciences ,Counterfactual thinking ,longitudinal data ,Conservation of Natural Resources ,Ecology (disciplines) ,Psychological intervention ,Affect (psychology) ,010603 evolutionary biology ,01 natural sciences ,counterfactual ,interrupted time series ,causal inference ,Natural disaster ,Environmental planning ,Ecology, Evolution, Behavior and Systematics ,difference in differences ,Ecology ,010604 marine biology & hydrobiology ,Biodiversity ,Difference in differences ,Intervention (law) ,Geography ,FOS: Biological sciences ,Causal inference - 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.
- Published
- 2021
- Full Text
- View/download PDF