Quantifying invasibility
Abstract
Invasibility, the chance of a population to grow from rarity and to establish a large-abundance colony, plays a fundamental role in population genetics, ecology, and evolution. For many decades, the mean growth rate when rare has been employed as an invasion criterion. Recent analyses have shown that this criterion fails as a quantitative metric for invasibility, with its magnitude sometimes even increasing while the invasibility decreases. Here we employ a new large-deviations (Wentzel-Kramers-Brillouin, WKB) approach and derive a novel and easy-to-use formula for the chance of invasion in terms of the mean growth rate and its variance. We also explain how to extract the required parameters from abundance time series. The efficacy of the formula, including its accompanying data analysis technique, is demonstrated using synthetic and empirically-calibrated time series from a few canonical models.
02 /Specification & Classification
Click any tag to browse matching papers- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Invasion fitness, inclusive fitness, and reproductive numbers in heterogeneous populations
Laurent Lehmann, Charles Mullon, … Jeremy Van Cleve·bioRxiv·Jan 19, 2016
- Mean growth rate when rare is not a reliable metric for persistence of species
- Species invasiveness and community invasibility of US freshwater fish fauna revealed via trait-based analysis
G. Su, A. Mertel, … J. M. Calabrese·bioRxiv·Mar 4, 2022
- Invasion analysis for structured populations: analytical principles and numerical workflows
Joe Wan, Hsiang-Chih Lo, … Po-Ju Ke·bioRxiv·Nov 6, 2026
- Evolutionary processes make invasion speed difficult to predict
Ben Phillips·bioRxiv·Jan 11, 2015
- Predicting species invasiveness with genomic data: is Genomic Offset related to establishment probability?
Louise Camus, Mathieu Gautier, Simon Boitard·Evolutionary ApplicationsPeer-reviewed·Jun 1, 2024