
Below you'll find results and code associated with the following article (*): Bozzuto, C, Ives, AR (2024): Predictability of ecological and evolutionary dynamics in a changing world. Proceedings of the Royal Society B, 291: 20240980. https://doi.org/10.1098/rspb.2024.0980 ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship. (*) previously a preprint on bioRxiv: https://doi.org/10.1101/2023.11.01.565089
Ecology, Conservation biology, Time series analysis, Evolutionary biology, ARIMA, Predictability, Phenotypic dynamics, Predictions, FOS: Biological sciences, Biodiversity loss, Ecological dynamics, Forecasting
Ecology, Conservation biology, Time series analysis, Evolutionary biology, ARIMA, Predictability, Phenotypic dynamics, Predictions, FOS: Biological sciences, Biodiversity loss, Ecological dynamics, Forecasting
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