2019/04/01 by Wenping Cui, Robert Marsland, Robert Marsland III +1 · 1 voice · 51 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #Artificial intelligence #Biology #Complex Network Analysis Techniques #Computer science #Ecological systems theory #Ecology #Ecosystem #Eigenvalues and eigenvectors #Environmental resource management #Environmental science #Geography #Mathematics #Physics #Plant and animal studies #Random Matrices and Applications #Random matrix #Resource (disambiguation) #Scaling #Statistical physics #Variety (cybernetics) #cond-mat.stat-mech #physics.bio-ph #q-bio.PE
paper · pdf · doi:10.1103/physreve.104.034416
published in Physical review. E 104(3), 034416 (American Physical Society) · 24 pages
arxiv published 2019/04/01 · arxiv created 2021/09/27 · openalex publication_date 2021/09/27 · arxiv updated 2021/09/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In 1972, Robert May triggered a worldwide research program studying ecological communities using random matrix theory. Yet, it remains unclear if and when we can treat real communities as random ecosystems. Here, we draw on recent progress in random matrix theory and statistical physics to extend May's approach to generalized consumer-resource models. We show that in diverse ecosystems adding even modest amounts of noise to consumer preferences results in a transition to "typicality," where macroscopic ecological properties of communities are indistinguishable from those of random ecosystems, even when resource preferences have prominent designed structures. We test these ideas using numerical simulations on a wide variety of ecological models. Our work offers an explanation for the success of random consumer resource models in reproducing experimentally observed ecological patterns in microbial communities and highlights the difficulty of scaling up bottom-up approaches in synthetic ecology to diverse communities.