- Department Fish Ecology and Evolution, EAWAG-ETH, Zurich and Lucerne, Switzerland
- Biodiversity, Biogeography, Food webs, Interaction networks, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecology
Why scaling up uncertain predictions to higher levels of organisation will underestimate change
Uncertain predictions of species responses to perturbations lead to underestimate changes at ecosystem level in diverse systems
Different sources of uncertainty are known to affect our ability to predict ecological dynamics (Petchey et al. 2015). However, the consequences of uncertainty on prediction biases have been less investigated, especially when predictions are scaled up to higher levels of organisation as is commonly done in ecology for instance. The study of Orr et al. (2020) addresses this issue. It shows that, in complex systems, the uncertainty of unbiased predictions at a lower level of organisation (e.g. species level) leads to a bias towards underestimation of change at higher level of organisation (e.g. ecosystem level). This bias is strengthened by larger uncertainty and by higher dimensionality of the system.
This general result has large implications for many fields of science, from economics to energy supply or demography. In ecology, as discussed in this study, these results imply that the uncertainty of predictions of species’ change increases the probability of underestimation of changes of diversity and stability at community and ecosystem levels, especially when species richness is high. The uncertainty of predictions of species’ change also increases the probability of underestimation of change when multiple ecosystem functions are considered at once, or when the combined effect of multiple stressors is considered.
The consequences of species diversity on ecosystem functions and stability have received considerable attention during the last decades (e.g. Cardinale et al. 2012, Kéfi et al. 2019). However, since the bias towards underestimation of change increases with species diversity, future studies will need to investigate how the general statistical effect outlined by Orr et al. might affect our understanding of the well-known relationships between species diversity and ecosystem functioning and stability in response to perturbations.
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Kéfi S, Domínguez‐García V, Donohue I, Fontaine C, Thébault E, Dakos V (2019) Advancing our understanding of ecological stability. Ecology Letters, 22, 1349–1356. https://doi.org/10.1111/ele.13340
Orr JA, Piggott JJ, Jackson A, Arnoldi J-F (2020) Why scaling up uncertain predictions to higher levels of organisation will underestimate change. bioRxiv, 2020.05.26.117200. https://doi.org/10.1101/2020.05.26.117200
Petchey OL, Pontarp M, Massie TM, Kéfi S, Ozgul A, Weilenmann M, Palamara GM, Altermatt F, Matthews B, Levine JM, Childs DZ, McGill BJ, Schaepman ME, Schmid B, Spaak P, Beckerman AP, Pennekamp F, Pearse IS (2015) The ecological forecast horizon, and examples of its uses and determinants. Ecology Letters, 18, 597–611. https://doi.org/10.1111/ele.12443