Generalized Lotka-Volterra Systems with Time Correlated Stochastic Interactions

In this Letter, we explore the dynamics of species abundances within ecological communities using the generalized Lotka-Volterra (GLV) model. At variance with previous approaches, we present an analysis of GLV dynamics with temporal stochastic fluctuations in interaction strengths between species. We develop a dynamical mean field theory (DMFT) tailored for scenarios with colored noise interactions, which we term annealed disorder, and simple functional responses. Our DMFT framework enables us to show that annealed disorder acts as an effective environmental noise; i.e., every species experiences a time-dependent environment shaped by the collective presence of all other species. We then derive analytical predictions for the species abundance distribution that well match empirical observations. Our results suggest that annealed disorder in interaction strengths favors species coexistence and leads to a large pool of very rare species in the systems, supporting the insurance theory of biodiversity. This Letter offers new insights not only into the modeling of large ecosystem dynamics but also proposes novel methodologies for examining ecological systems.

Authors

Institutions

Publication Details

Journal
Physical Review Letters
Published
2024-10-16
DOI
https://doi.org/10.1103/physrevlett.133.167101
Citations
24
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
11.94
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generalized Lotka-Volterra Systems with Time Correlated Stochastic Interactions

Francesco Ferraro, Samir Suweis, Sandro Azaele, Amos Maritan et al.
24 citations
Physical Review Letters
Mathematical and Theoretical Epidemiology and Ecology Models
11.94
article

Generalized Lotka-Volterra Systems with Time Correlated Stochastic Interactions

Francesco Ferraro, Samir Suweis, Sandro Azaele, Amos Maritan, Christian Grilletta
article en
24 citations

Abstract

In this Letter, we explore the dynamics of species abundances within ecological communities using the generalized Lotka-Volterra (GLV) model. At variance with previous approaches, we present an analysis of GLV dynamics with temporal stochastic fluctuations in interaction strengths between species. We develop a dynamical mean field theory (DMFT) tailored for scenarios with colored noise interactions, which we term annealed disorder, and simple functional responses. Our DMFT framework enables us to show that annealed disorder acts as an effective environmental noise; i.e., every species experiences a time-dependent environment shaped by the collective presence of all other species. We then derive analytical predictions for the species abundance distribution that well match empirical observations. Our results suggest that annealed disorder in interaction strengths favors species coexistence and leads to a large pool of very rare species in the systems, supporting the insurance theory of biodiversity. This Letter offers new insights not only into the modeling of large ecosystem dynamics but also proposes novel methodologies for examining ecological systems.

Physical Review LettersVol. 133(16)
University of Padua (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Padova (IT), National Biodiversity Institute (CR)
Openalex Percentile: Top 1%
Mathematical and Theoretical Epidemiology and Ecology Models
11.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Generalized Lotka-Volterra Systems with Time Correlated Stochastic Interactions — Francesco Ferraro, Samir Suweis, et al. · Physical Review Letters (2024) | TGRS Research Map | TGRS