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Improving credibility and transparency of conservation impact evaluations through the partial identification approach
Matthew M McConnachie1, Claudia Romero2, Paul J Ferraro3
1Department of Botany & Zoology, Centre for Invasion Biology, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa.
Summary
Evaluating conservation impact is challenging due to the unobservable counterfactual. Partial identification (PI) offers a more transparent method by bounding potential outcomes, improving credibility in conservation science.
Area of Science:
- Conservation Science
- Ecological Impact Assessment
- Environmental Program Evaluation
Background:
- Evaluating conservation interventions requires estimating outcomes versus an unobservable counterfactual.
- Conventional methods use point estimates, relying on untestable assumptions about control groups.
- Non-experimental contexts often suffer from a lack of transparency and credibility in impact assessments.
Purpose of the Study:
- To introduce and apply partial identification (PI) as an alternative to conventional point-estimate approaches for evaluating conservation interventions.
- To compare the PI approach with traditional methods using a case study of invasive tree removal.
- To highlight the benefits of PI in addressing selection bias and improving stakeholder consensus.
Main Methods:
- Partial identification (PI) was used to estimate counterfactual bounds under minimal assumptions.
- Bounds were narrowed using credible assumptions about intervention selection and response.
- The PI approach was applied to a conservation program in the Cape Floristic Region.
Main Results:
- The conservation program's control costs were estimated to be 1.4 times higher using the largest PI impact estimate compared to conventional methods.
- Partial identification provided a bounded estimate, offering a different perspective on the program's cost-effectiveness.
- The study demonstrated the practical application of PI in a real-world conservation scenario.
Conclusions:
- Partial identification (PI) enhances transparency and credibility in conservation impact evaluation.
- PI encourages a deeper understanding of selection biases and can reveal limitations of conventional methods.
- PI may facilitate stakeholder agreement on impact estimates and reduce advocacy bias in conservation science.
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