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The inherent complexity and multi-causality of nature makes attempts to gain understanding and guidance about critical issues including rates of biodiversity loss, or the effectiveness of actions such as tree planting, wickedly difficult and often subject to poorly-substantiated assertions about their generality. 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. Assertions about generality should raise the question: what exactly is generality? Ecologists rarely define either the generality of their findings, their estimand (what is estimated, based on the question of interest) or population of interest. Given that generality is fundamental to the philosophy of science, and the urgent need for scientific understanding and applied conservation actions to curb ecological breakdown, the loose use 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 that underpin generalisations and transfers of effect sizes, generality often misses its target. We then provide guidance for communicating nuanced inferences, and maximising the impact of syntheses both within and beyond academia. We finally propose pathways to generality applicable to ecological syntheses, which includes development of quantitative and qualitative criteria with which to license the transfer of estimands from both primary and synthetic studies. |
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