May, R. M. Will a large complex system be stable? Nature 238, 413–414 (1972).
Google Scholar
May, R. M. & Mac Arthur, R. H. Niche overlap as a function of environmental variability. Proc. Natl Acad. Sci. USA 69, 1109–1113 (1972).
Google Scholar
May, R. M. Stability and Complexity in Model Ecosystems (Princeton Univ. Press, 2019).
Sinha, S. Complexity vs. stability in small-world networks. Phys. A 346, 147–153 (2005).
Google Scholar
Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856 (2010).
Google Scholar
Mougi, A. & Kondoh, M. Diversity of interaction types and ecological community stability. Science 337, 349–351 (2012).
Google Scholar
Allesina, S. & Tang, S. Stability criteria for complex ecosystems. Nature 483, 205–208 (2012).
Google Scholar
Allesina, S. & Tang, S. The stability–complexity relationship at age 40: a random matrix perspective. Popul. Ecol. 57, 63–75 (2015).
Google Scholar
Qian, J. J. & Akçay, E. The balance of interaction types determines the assembly and stability of ecological communities. Nat. Ecol. Evol. 4, 356–365 (2020).
Google Scholar
Landi, P., Minoarivelo, H. O., Brännström, Å., Hui, C. & Dieckmann, U. in Systems Analysis Approach for Complex Global Challenges (eds Mensah, P. et al.) 209–248 (Springer, 2018).
Townsend, S. E., Haydon, D. T. & Matthews, L. On the generality of stability–complexity relationships in Lotka–Volterra ecosystems. J. Theor. Biol. 267, 243–251 (2010).
Google Scholar
Pimm, S. L., Lawton, J. H. & Cohen, J. E. Food web patterns and their consequences. Nature 350, 669–674 (1991).
Google Scholar
Yodzis, P. The stability of real ecosystems. Nature 289, 674–676 (1981).
Google Scholar
Winemiller, K. O. Must connectance decrease with species richness? Am. Naturalist 134, 960–968 (1989).
Google Scholar
Warren, P. H. Variation in food-web structure: the determinants of connectance. Am. Nat. 136, 689–700 (1990).
Google Scholar
de Ruiter, P. C., Neutel, A.-M. & Moore, J. C. Energetics, patterns of interaction strengths, and stability in real ecosystems. Science 269, 1257–1260 (1995).
Google Scholar
Schmid-Araya, J. M. et al. Connectance in stream food webs. J. Anim. Ecol. 71, 1056–1062 (2002).
Google Scholar
Neutel, A.-M. et al. Reconciling complexity with stability in naturally assembling food webs. Nature 449, 599–602 (2007).
Google Scholar
James, A. et al. Constructing random matrices to represent real ecosystems. Am. Nat. 185, 680–692 (2015).
Google Scholar
Jacquet, C. et al. No complexity–stability relationship in empirical ecosystems. Nat. Commun. 7, 12573 (2016).
Google Scholar
Thompson, L. R. et al. A communal catalogue reveals earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).
Google Scholar
Huttenhower, C. et al. Structure, function and diversity of the healthy human microbiome. Nature 486, 207 (2012).
Google Scholar
Fricker, A. M., Podlesny, D. & Fricke, W. F. What is new and relevant for sequencing-based microbiome research? A mini-review. J. Adv. Res. 19, 105–112 (2019).
Google Scholar
Sander, E. L., Wootton, J. T. & Allesina, S. Ecological network inference from long-term presence-absence data. Sci. Rep. 7, 7154 (2017).
Google Scholar
Steinway, S. N., Biggs, M. B., Loughran Jr, T. P., Papin, J. A. & Albert, R. Inference of network dynamics and metabolic interactions in the gut microbiome. PLoS Comput. Biol. 11, e1004338 (2015).
Google Scholar
Bucci, V. et al. Mdsine: microbial dynamical systems inference engine for microbiome time-series analyses. Genome Biol. 17, 121 (2016).
Google Scholar
Stein, R. R. et al. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLoS Comput. Biol. 9, e1003388 (2013).
Google Scholar
Fisher, C. K. & Mehta, P. Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression. PloS ONE 9, e102451 (2014).
Google Scholar
Gerber, G. K., Onderdonk, A. B. & Bry, L. Inferring dynamic signatures of microbes in complex host ecosystems. PLoS Comput. Biol. 8, e1002624 (2012).
Google Scholar
Cao, H.-T., Gibson, T. E., Bashan, A. & Liu, Y.-Y. Inferring human microbial dynamics from temporal metagenomics data: pitfalls and lessons. BioEssays 39, 1600188 (2017).
Google Scholar
David, L. A. et al. Host lifestyle affects human microbiota on daily timescales. Genome Biol. 15, R89 (2014).
Google Scholar
Caporaso, J. G. et al. Moving pictures of the human microbiome. Genome Biol. 12, R50 (2011).
Google Scholar
Buffie, C. G. et al. Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to clostridium difficile-induced colitis. Infect. Immun. 80, 62–73 (2012).
Google Scholar
Dohlman, A. B. & Shen, X. Mapping the microbial interactome: statistical and experimental approaches for microbiome network inference. Exp. Biol. Med. 244, 445–458 (2019).
Google Scholar
Faust, K. & Raes, J. Microbial interactions: from networks to models. Nat. Rev. Microbiol. 10, 538–550 (2012).
Google Scholar
Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012).
Google Scholar
Jiang, D. et al. Microbiome multi-omics network analysis: statistical considerations, limitations, and opportunities. Front. Genet. 10, 995 (2019).
Google Scholar
Faust, K. Open challenges for microbial network construction and analysis. ISME J. 15, 3111–3118 (2021).
Google Scholar
Bashan, A. et al. Universality of human microbial dynamics. Nature 534, 259–262 (2016).
Google Scholar
Vila, J. C., Liu, Y.-Y. & Sanchez, A. Dissimilarity–overlap analysis of replicate enrichment communities. ISME J. 14, 2505–2513 (2020).
Google Scholar
Moitinho-Silva, L. et al. The sponge microbiome project. Gigascience 6, gix077 (2017).
Google Scholar
Swierts, T., Cleary, D. & de Voogd, N. Prokaryotic communities of Indo-Pacific giant barrel sponges are more strongly influenced by geography than host phylogeny. FEMS Microbiol. Ecol. 94, fiy194 (2018).
Google Scholar
Jost, L. Entropy and diversity. Oikos 113, 363–375 (2006).
Google Scholar
Suweis, S., Grilli, J., Banavar, J. R., Allesina, S. & Maritan, A. Effect of localization on the stability of mutualistic ecological networks. Nat. Commun. 6, 10179 (2015).
Google Scholar
Grilli, J., Barabás, G., Michalska-Smith, M. J. & Allesina, S. Higher-order interactions stabilize dynamics in competitive network models. Nature 548, 210–213 (2017).
Google Scholar
Butler, S. & O’Dwyer, J. P. Stability criteria for complex microbial communities. Nat. Commun. 9, 2970 (2018).
Google Scholar
Allesina, S. & Grilli, J. in Theoretical Ecology: Concepts and Applications (eds McCann, K. & Gellner, G.) Ch. 6 (Oxford Univ. Press, 2020).
Jayant, P. & Shnerb, N. M. How temporal environmental stochasticity affects species richness: destabilization neutralization and the storage effect. J. Theor. Biol. 539, 111053 (2022).
Google Scholar
Faith, J. J. et al. The long-term stability of the human gut microbiota. Science 341, 1237439 (2013).
Google Scholar
Gajer, P. et al. Temporal dynamics of the human vaginal microbiota. Sci. Transl. Med. 4, 132ra52–132ra52 (2012).
Google Scholar
Van der Maaten, L. & Hinton, G. Visualizing data using t-sne. J. Mach. Learn. Res. 9, 2579–2605 (2008).
Bunin, G. Ecological communities with Lotka-Volterra dynamics. Phys. Rev. E 95, 042414 (2017).
Google Scholar
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