Rare but Resilient: Dispersal diversity buffers species vulnerability
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866917447194378240 |
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| author | Bernardi, Davide Nicoletti, Giorgio Padmanabha, Prajwal Suweis, Samir Azaele, Sandro Levin, Simon A. Rinaldo, Andrea Maritan, Amos |
| author_facet | Bernardi, Davide Nicoletti, Giorgio Padmanabha, Prajwal Suweis, Samir Azaele, Sandro Levin, Simon A. Rinaldo, Andrea Maritan, Amos |
| contents | Predicting species persistence within ecological communities is a fundamental challenge for both empirical and theoretical ecology. Existing methods span from mechanistic models, whose parameters are difficult to estimate from data, to statistical tools whose context-specific parameters are less interpretable. Here, we present a general framework, grounded in the statistical physics of complex systems, that integrates the key processes governing species survival into a single measurable quantity: the competitive balance. This metric quantifies a focal species' vulnerability beyond its abundance by incorporating the diversity of dispersal strategies and the structure of interspecific interactions within the community. Crucially, it can be inferred from spatial abundance data, thus circumventing the need to estimate species traits or dispersal parameters. Our results reveal that greater heterogeneity in dispersal strategies reduces vulnerability for a given abundance. Although we validate the framework using tropical and temperate forest data, it can be applied to a range of different ecosystems, providing a systemic and interpretable tool for assessing a context-dependent species vulnerability that accounts for its interactions with the entire community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_26589 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Rare but Resilient: Dispersal diversity buffers species vulnerability Bernardi, Davide Nicoletti, Giorgio Padmanabha, Prajwal Suweis, Samir Azaele, Sandro Levin, Simon A. Rinaldo, Andrea Maritan, Amos Populations and Evolution Statistical Mechanics Predicting species persistence within ecological communities is a fundamental challenge for both empirical and theoretical ecology. Existing methods span from mechanistic models, whose parameters are difficult to estimate from data, to statistical tools whose context-specific parameters are less interpretable. Here, we present a general framework, grounded in the statistical physics of complex systems, that integrates the key processes governing species survival into a single measurable quantity: the competitive balance. This metric quantifies a focal species' vulnerability beyond its abundance by incorporating the diversity of dispersal strategies and the structure of interspecific interactions within the community. Crucially, it can be inferred from spatial abundance data, thus circumventing the need to estimate species traits or dispersal parameters. Our results reveal that greater heterogeneity in dispersal strategies reduces vulnerability for a given abundance. Although we validate the framework using tropical and temperate forest data, it can be applied to a range of different ecosystems, providing a systemic and interpretable tool for assessing a context-dependent species vulnerability that accounts for its interactions with the entire community. |
| title | Rare but Resilient: Dispersal diversity buffers species vulnerability |
| topic | Populations and Evolution Statistical Mechanics |
| url | https://arxiv.org/abs/2604.26589 |