Evaluating Impact Using Time-Series Data. (March 2021)

• Record Type: Journal Article
• Authors: Wauchope, Hannah S.; Amano, Tatsuya; Geldmann, Jonas; Johnston, Alison; Simmons, Benno I.; Sutherland, William J.; Jones, Julia P.G.
• Is Part Of: Trends in ecology & evolution. Volume 36:Number 3(2021)
• Page Start: 196
• Page End: 205
• Publication Date: 2021-03
• Subjects: before-after-control-intervention -- longitudinal data -- counterfactual -- interrupted time series -- causal inference -- difference in differences; Ecology -- Periodicals; Evolution (Biology) -- Periodicals; 576.8
• DOI: 10.1016/j.tree.2020.11.001
• Languages: English
• ISSNs: 0169-5347

Abstract

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. Highlights: Ecologists have called for more robust studies on the impact of conservation interventions, or environmental shocks, on outcomes of interest, such as populations, habitat loss, or pressures. Time-series data are increasingly available and can, if appropriately analysed, allow such causal inferences. However, there are important pitfalls that make large-scale analyses involving multiple time series problematic. There has been progress in a range of fields, but the literature is fragmented and not all is easily accessible to ecologists. A framework is presented, with clear and consistent terminology, to support ecologists to conduct effective impact evaluation with time-series data. This will allow them to contribute to better-informed environmental management decisions.