Unfeasible expectations: why simple predictors outperform structural stability measures for understanding community assembly DOI Creative Commons
J. Christopher D. Terry

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Abstract Understanding what determines community assembly and disassembly in a changing environment is core challenge for ecology. Recently family of structural stability approaches that determine the range intrinsic growth rates compatible with system feasibility have been gaining popularity as measure how likely able to persist fluctuating conditions. This offers theoretical basis understanding predicting complex multi-species communities from only interaction network structures. However, here I show high sensitivity calculations domain, coupled empirical uncertainties inherent estimated interactions, are preclude approach’s reliable application settings. Across four reanalyses previous demonstrations approach, more parsimonious explanations based on species connectance provide better patterns or dynamic stability. Calculation metrics therefore appears lose, rather than synthesise, information embedded matrices. success simpler measures good news purposes prediction emphasises value multiple-competing hypotheses validation tests demonstrate value-added associated new approaches.

Language: Английский

Coexistence Theory for Microbial Ecology, and Vice Versa DOI Creative Commons
James Orr, David Armitage, Andrew D. Letten

et al.

Environmental Microbiology, Journal Year: 2025, Volume and Issue: 27(3)

Published: March 1, 2025

ABSTRACT Classical models from theoretical ecology are seeing increasing uptake in microbial ecology, but there remains rich potential for closer cross‐pollination. Here we explore opportunities stronger integration of ecological theory into research (and vice versa) through the lens so‐called “modern” coexistence theory. Coexistence can be used to disentangle contributions different mechanisms (e.g., resource partitioning, environmental variability) make species coexistence. We begin with a short primer on fundamental concepts theory, an emphasis relevance communities. next present systematic review, which highlights paucity empirical applications systems. In light this gap, then identify and discuss ways which: (i) help answer applied questions particularly spatio‐temporally heterogeneous environments, (ii) experimental systems leveraged validate advance Finally, address several unique often surmountable challenges posed by systems, as well some conceptual limitations. Nevertheless, thoughtful presents wealth advancement both ecology.

Language: Английский

Citations

0

Unfeasible expectations: why simple predictors outperform structural stability measures for understanding community assembly DOI Creative Commons
J. Christopher D. Terry

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Abstract Understanding what determines community assembly and disassembly in a changing environment is core challenge for ecology. Recently family of structural stability approaches that determine the range intrinsic growth rates compatible with system feasibility have been gaining popularity as measure how likely able to persist fluctuating conditions. This offers theoretical basis understanding predicting complex multi-species communities from only interaction network structures. However, here I show high sensitivity calculations domain, coupled empirical uncertainties inherent estimated interactions, are preclude approach’s reliable application settings. Across four reanalyses previous demonstrations approach, more parsimonious explanations based on species connectance provide better patterns or dynamic stability. Calculation metrics therefore appears lose, rather than synthesise, information embedded matrices. success simpler measures good news purposes prediction emphasises value multiple-competing hypotheses validation tests demonstrate value-added associated new approaches.

Language: Английский

Citations

0