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Predicting the fate of biodiversity using species' distribution models: enhancing model comparability and
Genoveva Rodríguez-Castañeda1, Anouschka R Hof, Roland Jansson
1Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America. genoveva@life.bio.sunysb.edu
Plos One
|September 18, 2012
Summary
Species distribution models (SDMs) lack comparability due to inconsistent reporting. Our study reveals how modeling choices significantly alter species distribution predictions, impacting conservation efforts.
Area of Science:
- Ecology
- Conservation Biology
- Biodiversity Informatics
Background:
- Species distribution modeling (SDM) is crucial for predicting species' geographic ranges.
- Existing SDM studies often lack methodological transparency, hindering comparability and reliable conservation planning.
Purpose of the Study:
- To assess the impact of methodological choices on SDM outcomes.
- To highlight the need for standardized reporting in SDM to improve reliability.
Main Methods:
- Reviewed recent publications for SDM reporting standards.
- Modeled six Falco species in Northern Europe using varying spatial data and output transformations.
- Analyzed the influence of spatial bias, geographic extent, and threshold choices on model predictions.
Main Results:
- 79% of reviewed SDM studies failed to report crucial comparability metrics.
- Modeling decisions, including data bias and threshold application, significantly altered distribution forecasts for Falco species.
- Predicted range changes varied drastically, from 80% contraction to no net loss, depending on methodological choices.
Conclusions:
- Inconsistent SDM methodologies compromise the reliability of species distribution predictions.
- Standardized reporting and evaluation of modeling decisions are essential for robust conservation recommendations.
- Improved transparency in SDM is vital for evidence-based policy and effective species management.
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