Biological traits predict species’ time-varying responses to multiple global change drivers

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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Publication Details

Journal
Nature Communications
Published
2026-03-14
DOI
https://doi.org/10.1038/s41467-026-70606-w
Primary Topic
Physiological and biochemical adaptations
Type
article
Field-Weighted Citation Impact
0.00

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article

Biological traits predict species’ time-varying responses to multiple global change drivers

Judi E. Hewitt, Kamryn Carter, Simon F. Thrush, Shinji Shimode et al.
Nature Communications
Physiological and biochemical adaptations
article

Biological traits predict species’ time-varying responses to multiple global change drivers

Judi E. Hewitt, Kamryn Carter, Simon F. Thrush, Shinji Shimode, Naohiro I. Ishii, Sarah F. Hailes, Emily J. Douglas, Barry L. Greenfield, Andrew Martin Lohrer, Maiko Kagami, Orlando Lam-Gordillo, Rebecca V. Gladstone-Gallagher, Katie M. Cook, Takehiro Sasaki, Yoshiki Takayama, Yuki Iwachido
article en

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.

Nature Communications
University of Auckland (NZ), Flinders University (AU), Yokohama National University (JP), Clinical Trials New Zealand (NZ), Gifu University (JP), Tottori University (JP)
Waikato Regional Council, Royal Society Te Apārangi, Ministry of Education, Culture, Sports, Science and Technology, Core Research for Evolutional Science and Technology
Life below water
Openalex Percentile: Top 27%
Physiological and biochemical adaptations
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