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Goldilocks and the Raster Grid: Selecting Scale when Evaluating Conservation Programs.

Andre Fernandes Tomon Avelino1, Kathy Baylis1, Jordi Honey-Rosés2

  • 1Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, Urbana, Illinois, United States of America.

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Summary
This summary is machine-generated.

The modifiable areal unit problem (MAUP) significantly biases conservation impact evaluations. Choosing the wrong scale or unit can lead to inaccurate results, often underestimating true effects.

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Area of Science:

  • Spatial analysis
  • Conservation science
  • Impact evaluation

Background:

  • Spatial data analysis requires careful selection of scale and unit.
  • Previous conservation studies used diverse scales and units, affecting impact estimates.
  • The modifiable areal unit problem (MAUP) is a known bias in spatial analysis.

Purpose of the Study:

  • Introduce the MAUP to conservation impact evaluation literature.
  • Explore tradeoffs in selecting different areal units for analysis.
  • Illustrate MAUP consequences using a protected area in Mexico and simulations.

Main Methods:

  • Examined scale selection effects on a Mexican protected area's impact evaluation.
  • Developed a Monte Carlo experiment simulating conservation interventions.
  • Analyzed bias from scale choices relative to data generation and decision units.

Main Results:

  • Treatment effect and coefficient estimates are accurate only under specific conditions.
  • Biased estimates arise from scales too large or too small.
  • MAUP may cause errors-in-variables bias, pronounced at smaller scales.

Conclusions:

  • Aggregation can reduce bias for continuous variables but worsen it for discrete treatment measures.
  • Treatment effects are generally underestimated.
  • Researchers need strategies to navigate scale and unit choices in conservation policy evaluation.