ArticleConservation biology : the journal of the Society for Conservation Biology2020
Statistical matching for conservation science.
Article in Conservation biology : the journal of the Society for Conservation Biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed, 204 citations in OpenAlex.
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- Article
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- The contribution of other effective area-based conservation measures (OECMs) to protecting global biodiversity.Nature communications · 2025Article
- Effect of reserve protection level and governance on tree cover loss and gain.Conservation biology : the journal of the Society for Conservation Biology · 2025Article
- Evidence on scaling forest restoration from the Atlantic Forest Restoration Pact in Brazil.Nature communications · 2025Article
- Global risk of wildfire across timber production systems.Nature communications · 2025Article
- Navigating data challenges in socioeconomic impact assessments of conservation regimes.Conservation biology : the journal of the Society for Conservation Biology · 2025Review
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Authors and funding
6 authors at 5 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The awareness of the need for robust impact evaluations in conservation is growing and statistical matching techniques are increasingly being used to assess the impacts of conservation interventions. Used appropriately matching approaches are powerful tools, but they also pose potential pitfalls. We outlined important considerations and best practice when using matching in conservation science. We identified 3 steps in a matching analysis. First, develop a clear theory of change to inform selection of treatment and controls and that accounts for real-world complexities and potential spillover effects. Second, select the appropriate covariates and matching approach. Third, assess the quality of the matching by carrying out a series of checks. The second and third steps can be repeated and should be finalized before outcomes are explored. Future conservation impact evaluations could be improved by increased planning of evaluations alongside the intervention, better integration of qualitative methods, considering spillover effects at larger spatial scales, and more publication of preanalysis plans. Implementing these improvements will require more serious engagement of conservation scientists, practitioners, and funders to mainstream robust impact evaluations into conservation. We hope this article will improve the quality of evaluations and help direct future research to continue to improve the approaches on offer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.