From species-area relationships to biodiversity risk assessment

Summary

This paper develops a mechanistic approach to translate commonly-measured species-area relationships into quantitative biodiversity risk metrics—specifically collapse probabilities and lower-tail probability distributions—without requiring direct estimation of full richness distributions. The authors demonstrate that when regional species abundances follow Fisher's log-series, an immigration-extinction model yields a closed-form stationary distribution coupling mean SAR to richness variability and tail risk measures. Empirical validation using ForestGEO tree census data across tropical, subtropical, and temperate forests supports these theoretical predictions, positioning the framework as a practical tool for conservation planning and risk-based biodiversity assessment.

Regional applicability

The study is global in scope with empirical validation across multiple forest biomes. Findings are potentially applicable to United Kingdom woodland and forest management and conservation planning, though applicability would depend on whether temperate forest data within the ForestGEO network includes UK sites and whether local species abundance distributions conform to the Fisher's log-series assumption.

Key measures

Species-area relationships (SAR), local species richness distributions, collapse probability, lower-tail quantiles, Fisher's log-series parameter estimation, fluctuation-response identities

Outcomes reported

The study demonstrates a mechanistic framework linking species-area relationships to biodiversity risk metrics including collapse probability and lower-tail quantiles. Empirical validation was conducted using high-resolution tree census data from tropical, subtropical, and temperate forests across multiple spatial scales.

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