Rare but Resilient: Dispersal diversity buffers species vulnerability
Davide Bernardi, Giorgio Nicoletti, Prajwal Padmanabha, Samir Suweis, Sandro Azaele + 3 more
TLDR
A new framework quantifies species vulnerability using 'competitive balance,' revealing dispersal diversity enhances resilience.
Key contributions
- Presents "competitive balance" to quantify species vulnerability beyond abundance.
- Integrates dispersal diversity and interspecific interaction structure within communities.
- Inferred from spatial abundance data, bypassing the need for species trait estimation.
- Demonstrates that greater heterogeneity in dispersal strategies reduces species vulnerability.
Why it matters
This framework provides a systemic, interpretable tool for assessing species vulnerability, crucial for conservation efforts. It simplifies prediction by using readily available spatial abundance data, making it widely applicable across various ecosystems.
Original Abstract
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.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.