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Improving quantitative synthesis to achieve generality in ecology

Spake, R. ORCID:, O'Dea, R. E., Nakagawa, S., Doncaster, C. P., Ryo, M., Callaghan, C. T. and Bullock, J. M. (2022) Improving quantitative synthesis to achieve generality in ecology. Nature Ecology & Evolution, 6 (12). pp. 1818-1828. ISSN 2397-334X

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To link to this item DOI: 10.1038/s41559-022-01891-z


Synthesis of primary ecological data is often assumed to achieve a notion of ‘generality’, through the quantification of overall effect sizes and consistency among studies, and has become a dominant research approach in ecology. Unfortunately, ecologists rarely define either the generality of their findings, their estimand (the target of estimation) or population of interest. Given that generality is fundamental to science, and the urgent need for scientific understanding to curb global-scale ecological breakdown, loose usage of the term ‘generality’ is problematic. In other disciplines, generality is defined as comprising both generalisability: extending an inference about an estimand from the sample to the population, and transferability: the validity of estimand predictions in a different sampling unit or population. We review current practice in ecological synthesis, and demonstrate that by failing to define the assumptions underpinning generalisations and transfers of effect sizes, generality often misses its target. We provide guidance for communicating nuanced inferences, and maximising the impact of syntheses both within and beyond academia. We propose pathways to generality applicable to ecological syntheses, including the development of quantitative and qualitative criteria with which to license the transfer of estimands from both primary and synthetic studies.

Item Type:Article
Divisions:Life Sciences > School of Biological Sciences > Ecology and Evolutionary Biology
ID Code:107031


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