Abstract
Multiple drivers of global change are causing rapid biodiversity loss worldwide. However, predicting species’ trajectories remains challenging due to the dynamic and state-dependent nature of ecological responses in real-world ecosystems. Here, we leverage nonlinear time series analysis of a multi-decadal, high-resolution dataset encompassing climate, freshwater, and sediment variables, alongside estuarine macroinvertebrate abundance. Our analysis shows that key biological traits, including body size, mobility, and lifespan predict the mean and variability of the time-varying sensitivity of species to specific environmental drivers. Species with smaller body sizes or lower mobility exhibit consistently negative responses to warming. The temporal variability of species sensitivity, an aspect often overlooked in previous studies of species’ environmental responses, is strongly associated with lifespan, with shorter-lived species showing greater fluctuations over time. These findings did not always align with results from controlled laboratory or short-term field experiments, highlighting the complex, state-dependent responses of species shaped by multiple drivers of global change. We introduce a framework that links biological traits to long-term environmental responses, providing a predictive basis for trait–sensitivity relationships.
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Data availability
The full-time series raw data analyzed in this study were provided with permission from Auckland Council, Waikato Regional Council, and Earth Sciences New Zealand and are subject to data use agreements; therefore, they are not publicly available. The supplementary data required for the essential steps in the analyses and for reproducing the results have been deposited in figshare106. Requests for access to the original data should be directed to the corresponding authors, who will coordinate with the data providers in accordance with the data use agreements.
Code availability
The code required to reproduce the results of this study, together with the supplementary dataset, has been deposited in figshare106.
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Acknowledgements
We thank the Auckland Council and the Waikato Regional Council for funding and their commitment to long-term macroinvertebrate monitoring in New Zealand estuaries. We gratefully acknowledge the field teams and Earth Sciences New Zealand parataxonomists for generating consistently robust time series datasets. This work was financially supported by bilateral collaboration project between New Zealand and Japan grant JPJSBP120241001 (T.S. and A.M.L.) from the Royal Society of New Zealand and the Ministry of Education, Culture, Sports, Science and Technology of Japan, Joint Research Program of Arid Land Research Center, Tottori University grant 06B2005 (T.S.), Asahi Glass Foundation (T.S.), New Zealand’s Strategic Science Investment Funding grant C01X0703 (A.M.L., O.L.G., and E.J.D.), and JST, CREST, Japan grant JPMJCR24J2 (M.K., S.S., and Y.T.).
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T.S., Y.I., O.L.G., K.M.C., E.J.D., R.V.G.G., B.G., S.H., K.C., N.I.I., Y.T., S.S., M.K., J.E.H., S.F.T., and A.M.L. contributed to the conceptualization of the study. Data curation was performed by O.L.G., Y.I., and T.S. Formal analyses were conducted by T.S. and Y.I. The original draft of the paper was written by T.S., Y.I., O.L.G., and A.M.L. T.S., Y.I., O.L.G., K.M.C., E.J.D., R.V.G.G., B.G., S.H., K.C., N.I.I., Y.T., S.S., M.K., J.E.H., S.F.T., and A.M.L. contributed to reviewing and editing the paper.
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Sasaki, T., Iwachido, Y., Lam-Gordillo, O. et al. Biological traits predict species’ time-varying responses to multiple global change drivers. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70606-w
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DOI: https://doi.org/10.1038/s41467-026-70606-w
