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Density dependence buffers natural populations against multiple stressors

Density dependence buffers natural populations against multiple stressors

This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.

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Authors

Man Qi , Rob Salguero-Gomez, Àlex Giménez Romero, Jiamiao Chen, Qianzhao Sun, Tao Sun

Abstract

Predicting population persistence under global change requires understanding how populations buffer against interacting stresses. Gradual stresses, such as droughts, suppress individual performance, whereas abrupt stresses, such as harvesting, remove individuals from populations. Because these stresses interact through density-dependent responses of growth, reproduction and survival, predicting their combined effects requires understanding density dependence processes. Here, we introduce a mechanistic framework linking individual-level density dependence to population buffering by integrating the constant final yield rule, self-thinning, and the hydra effect. Using field experiments and individual-based modelling of the annual marsh plant Suaeda salsa, we show that gradual stress suppresses individual growth, weakens competition and reduces population buffering against abrupt disturbances. Consequently, synergistic interactions between gradual and abrupt stresses become increasingly likely as population density declines or gradual stress intensifies. We further show that the slope of the relationship between body mass and population density provides a robust indicator for population buffering. Our framework offers a powerful tool to understand and predict population persistence under multiple interacting stresses.

DOI

https://doi.org/10.32942/X2738V

Subjects

Ecology and Evolutionary Biology, Life Sciences

Keywords

Dates

Published: 2026-08-14 10:25

Last Updated: 2026-08-14 10:25

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data and Code Availability Statement:
Data and code for the Suaeda salsa experiment can be found at https://github.com/ManQiEcology/Dataset-and-code-for-Density-dependence-buffers-natural-populations-against-multiple-stressors. The code of the IBM model can be found at https://github.com/agimenezromero/plant-growth-model/.

Language:
English

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