Recommendations for quantitative uncertainty consideration in ecology and evolution

Emily G. Simmonds; Kwaku P. Adjei; Benjamin Cretois; Lisa Dickel; Ricardo González-Gil; Jack H. Laverick; Caitlin P. Mandeville; Elizabeth G. Mandeville; Otso Ovaskainen; Jorge Sicacha-Parada; Emma S. Skarstein; Bob O’Hara

doi:10.1016/j.tree.2023.10.012

Recommendations for quantitative uncertainty consideration in ecology and evolution

Emily G. Simmonds, Kwaku P. Adjei, Benjamin Cretois, Lisa Dickel, Ricardo González-Gil, Jack H. Laverick, Caitlin P. Mandeville, Elizabeth G. Mandeville, Otso Ovaskainen, Jorge Sicacha-Parada, Emma S. Skarstein, Bob O’Hara

Mathematics And Statistics

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4 Citations (Scopus)

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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.

Original language	English
Pages (from-to)	328-337
Number of pages	10
Journal	Trends in Ecology and Evolution
Volume	39
Issue number	4
Early online date	28 Nov 2023
DOIs	https://doi.org/10.1016/j.tree.2023.10.012
Publication status	Published - 1 Apr 2024

Funding

We would like to give special thanks to Sigurd Einum and Janne Cathrin Hetle Aspheim for being part of the evolutionary biology team for the interdisciplinary review that inspired this opinion article. We would also like to thank the rest of that interdisciplinary collaboration for providing us with their field-specific best practices for uncertainty consideration. E.G.S. would like to acknowledge funding for the PREDICT project from the Research Council of Norway (project 314952 ). L.D. would like to acknowledge the Research Council of Norway (SFF-III, project 223257 ) (Centre for Biodiversity Dynamics). O.O. was funded by the Academy of Finland (grants 336212 and 345110 ), Jane and Aatos Erkko Foundation, Research Council of Norway through its Centres of Excellence Funding Scheme ( 223257 ), and the European Research Council (ERC) under the EU Horizon 2020 Research and Innovation Programme ( 856506 ; ERC-synergy project LIFEPLAN), the HORIZON-CL6-2021-BIODIV-01 project 101059492 (Biodiversity Genomics Europe), and the HORIZON-INFRA-2021-TECH-01 project 101057437 (Biodiversity Digital Twin for Advanced Modelling, Simulation, and Prediction Capabilities).

Keywords

uncertainty
modelling
parameter
propagation

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10.1016/j.tree.2023.10.012Licence: CC BY 4.0

Simmonds-etal-TEE-2023-Recommendations-for-quantitative-uncertainty-consideration-in-ecology-and-evolutionFinal published version, 1.15 MBLicence: CC BY 4.0

4 Citations
1 Article

Insights into the quantification and reporting of model-related uncertainty across different disciplines
Simmonds, E. G., Adjei, K. P., Andersen, C. W., Aspheim, J. C. H., Battistin, C., Bulso, N., Christensen, H., Cretois, B., Cubero, R., Davidovich, I. A., Dickel, L., Dunn, B., Dunn-Sigouin, E., Dyrstad, K., Einum, S., Giglio, D., Gjerløw, H., Godefroidt, A., González-Gil, R. & Cogno, S. G. & 23 others, Große, F., Halloran, P., Jensen, M. F., Kennedy, J. J., Langsæther, P. E., Laverick, J., Lederberger, D., Li, C., Mandeville, C., Mandeville, E., Moe, E., Schröder, T. N., Nunan, D., Parada, J. S., Simpson, M. R., Skarstein, E. S., Spensberger, C., Stevens, R., Subramanian, A., Svendsen, L., Theisen, O. M., Watret, C. & O’Hara, R. B., 31 Dec 2022, In: iScience. 25, 12, 16 p., 105512.
Research output: Contribution to journal › Article › peer-review

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10 Citations (Scopus)

21 Downloads (Pure)

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Simmonds, E. G., Adjei, K. P., Cretois, B., Dickel, L., González-Gil, R., Laverick, J. H., Mandeville, C. P., Mandeville, E. G., Ovaskainen, O., Sicacha-Parada, J., Skarstein, E. S., & O’Hara, B. (2024). Recommendations for quantitative uncertainty consideration in ecology and evolution. Trends in Ecology and Evolution, 39(4), 328-337. https://doi.org/10.1016/j.tree.2023.10.012

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Simmonds, EG, Adjei, KP, Cretois, B, Dickel, L, González-Gil, R, Laverick, JH, Mandeville, CP, Mandeville, EG, Ovaskainen, O, Sicacha-Parada, J, Skarstein, ES & O’Hara, B 2024, 'Recommendations for quantitative uncertainty consideration in ecology and evolution', Trends in Ecology and Evolution, vol. 39, no. 4, pp. 328-337. https://doi.org/10.1016/j.tree.2023.10.012

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AU - Adjei, Kwaku P.

AU - Cretois, Benjamin

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AU - González-Gil, Ricardo

AU - Laverick, Jack H.

AU - Mandeville, Caitlin P.

AU - Mandeville, Elizabeth G.

AU - Ovaskainen, Otso

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KW - parameter

KW - propagation

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JO - Trends in Ecology and Evolution

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IS - 4

ER -

Recommendations for quantitative uncertainty consideration in ecology and evolution

Abstract

Funding

Keywords

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Research output

Insights into the quantification and reporting of model-related uncertainty across different disciplines

Cite this