{"title":"How Combined Pairwise and Higher-Order Interactions Shape Transient Dynamics","authors":"Sourin Chatterjee, Sayantan Nag Chowdhury","doi":"arxiv-2409.09521","DOIUrl":null,"url":null,"abstract":"Understanding how species interactions shape biodiversity is a core challenge\nin ecology. While much focus has been on long-term stability, there is rising\ninterest in transient dynamics-the short-lived periods when ecosystems respond\nto disturbances and adjust toward stability. These transitions are crucial for\npredicting ecosystem reactions and guiding effective conservation. Our study\nintroduces a model that blends pairwise and higher-order interactions, offering\na more realistic view of natural ecosystems. We find pairwise interactions slow\nthe journey to stability, while higher-order interactions speed it up. This\nmodel provides fresh insights into ecosystem resilience and recovery, helping\nimprove strategies for managing species and ecological disruptions.","PeriodicalId":501044,"journal":{"name":"arXiv - QuanBio - Populations and Evolution","volume":"64 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Populations and Evolution","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.09521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding how species interactions shape biodiversity is a core challenge
in ecology. While much focus has been on long-term stability, there is rising
interest in transient dynamics-the short-lived periods when ecosystems respond
to disturbances and adjust toward stability. These transitions are crucial for
predicting ecosystem reactions and guiding effective conservation. Our study
introduces a model that blends pairwise and higher-order interactions, offering
a more realistic view of natural ecosystems. We find pairwise interactions slow
the journey to stability, while higher-order interactions speed it up. This
model provides fresh insights into ecosystem resilience and recovery, helping
improve strategies for managing species and ecological disruptions.