Recommendations for quantitative uncertainty consideration in ecology and evolution

Simmonds, Emily G. and Adjei, Kwaku P. and Cretois, Benjamin and Dickel, Lisa and González-Gil, Ricardo and Laverick, Jack H. and Mandeville, Caitlin P. and Mandeville, Elizabeth G. and Ovaskainen, Otso and Sicacha-Parada, Jorge and Skarstein, Emma S. and O’Hara, Bob (2024) Recommendations for quantitative uncertainty consideration in ecology and evolution. Trends in Ecology and Evolution, 39 (4). pp. 328-337. ISSN 0169-5347 (https://doi.org/10.1016/j.tree.2023.10.012)

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Abstract

Ecological and evolutionary studies are currently failing to achieve complete and consistent reporting of model-related uncertainty. We identify three key barriers: a focus on parameter-related uncertainty, obscure uncertainty metrics, and limited recognition of uncertainty propagation, which have led to gaps in uncertainty consideration. But these gaps can be closed. We propose that uncertainty reporting in ecology and evolution can be improved through wider application of existing statistical solutions and adoption of good practice from other scientific fields. Our recommendations include greater consideration of input data and model structure uncertainties, field-specific uncertainty standards for methods and reporting, and increased uncertainty propagation through use of hierarchical models.

ORCID iDs

Simmonds, Emily G., Adjei, Kwaku P., Cretois, Benjamin, Dickel, Lisa, González-Gil, Ricardo, Laverick, Jack H. ORCID logoORCID: https://orcid.org/0000-0001-8829-2084, Mandeville, Caitlin P., Mandeville, Elizabeth G., Ovaskainen, Otso, Sicacha-Parada, Jorge, Skarstein, Emma S. and O’Hara, Bob;
CORE (COnnecting REpositories)