Energy landscape analysis elucidates the multistability of ecological communities across environmental gradients. Issue 3 (20th June 2021)

• Record Type: Journal Article
• Authors: Suzuki, Kenta; Nakaoka, Shinji; Fukuda, Shinji; Masuya, Hiroshi
• Is Part Of: Ecological monographs. Volume 91:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-20
• Subjects: alternative stable states -- community assembly -- compositional stability -- energy landscape -- historical contingency -- Markov network -- multistability -- pairwise maximum entropy model -- presence/absence data -- principle of maximum entropy -- regime shift -- stability landscape; Ecology -- Periodicals; Ecology; Écologie; Electronic journals; Periodicals; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 577
• DOI: 10.1002/ecm.1469
• Languages: English
• ISSNs: 0012-9615

Abstract

Abstract: Compositional multistability is widely observed in multispecies ecological communities. Since differences in community composition often lead to differences in community function, understanding compositional multistability is essential to comprehend the role of biodiversity in maintaining ecosystems. In community assembly studies, it has long been recognized that the order and timing of species migration and extinction influence structure and function of communities. The study of multistability in ecology has focused on the change in dynamical stability across environmental gradients, and was developed mainly for low‐dimensional systems. As a result, methodologies for studying the compositional stability of empirical multispecies communities are not well developed. Here, we show that models previously used in ecology can be analyzed from a new perspective, the energy landscape, to unveil compositional stability in observational data. To show that our method can be applicable to real‐world ecological communities, we simulated assembly dynamics driven by population‐level processes, and show that results were mostly robust to different simulation assumptions. Our method reliably captured the change in the overall compositional stability of multispecies communities over environmental change, and indicated a small fraction of community compositions that may be channels for transitions between stable states. When applied to murine gut microbiota, our method showed the presence of two alternative states whose relationship changes with age, and suggested mechanisms by which aging affects the compositional stability of the murine gut microbiota. Our method provides a practical tool to study the compositional stability of communities in a changing world, and will facilitate empirical studies that integrate the concept of multistability from different fields.