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Coexistence holes characterize the assembly and disassembly of multispecies systems

  • 1.

    Fukami, T. Historical contingency in community assembly: integrating niches, species pools, and priority effects. Annu. Rev. Ecol. Evol. Syst. 46, 1–23 (2015).

    Google Scholar 

  • 2.

    Tylianakis, J. M., Martínez-García, L. B., Richardson, S. J., Peltzer, D. A. & Dickie, I. A. Symmetric assembly and disassembly processes in an ecological network. Ecol. Lett. 21, 896–904 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 3.

    Chase, J. M., Blowes, S. A., Knight, T. M., Gerstner, K. & May, F. Ecosystem decay exacerbates biodiversity loss with habitat loss. Nature 584, 238–243 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 4.

    Vellend, M. The Theory of Ecological Communities (MPB-57) (Princeton Univ. Press, 2016).

  • 5.

    Hutchinson, G. E. Homage to Santa Rosalia or why are there so many kinds of animals? Am. Nat. 93, 145–159 (1959).

    Google Scholar 

  • 6.

    Tilman, D. Resource Competition and Community Structure (Princeton Univ. Press, 1982).

  • 7.

    Barbier, M., Arnoldi, J.-F., Bunin, G. & Loreau, M. Generic assembly patterns in complex ecological communities. Proc. Natl Acad. Sci. USA 115, 2156–2161 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 8.

    Serván, C. A., Capitán, J. A., Grilli, J., Morrison, K. E. & Allesina, S. Coexistence of many species in random ecosystems. Nat. Ecol. Evol. 2, 1237–1242 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 9.

    MacArthur, R. Species packing and competitive equilibrium for many species. Theor. Popul. Biol. 1, 1–11 (1970).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 10.

    Medeiros, L. P., Boege, K., del Val, E., Zaldivar-Riverón, A. & Saavedra, S. Observed ecological communities are formed by species combinations that are among the most likely to persist under changing environments. Am. Nat. https://doi.org/10.1086/711663 (2020).

  • 11.

    Barabás, G., D’Andrea, R. & Stump, S. M. Chesson’s coexistence theory. Ecol. Monogr. 88, 277–303 (2018).

    Google Scholar 

  • 12.

    Grainger, T. N. & Gilbert, J. M. L. B. The invasion criterion: a common currency for ecological research. Trends Ecol. Evol. 34, 925–935 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 13.

    Alberch, P. The logic of monsters: evidence for internal constraint in development and evolution. Geobios 22, 21–57 (1989).

    Google Scholar 

  • 14.

    Clements, F. E. Nature and structure of the climax. J. Ecol. 24, 252–284 (1936).

    Google Scholar 

  • 15.

    Odum, E. P. & Barrett, G. W. Fundamentals of Ecology 5th edn (Thomson Brooks/Cole, 2005).

  • 16.

    Friedman, J., Higgins, L. M. & Gore, J. Community structure follows simple assembly rules in microbial microcosms. Nat. Ecol. Evol. 1, 0109 (2017).

    Google Scholar 

  • 17.

    Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).

    Google Scholar 

  • 18.

    Drake, J. A. Community-assembly mechanics and the structure of an experimental species ensemble. Am. Nat. 137, 1–26 (1991).

    Google Scholar 

  • 19.

    Warren, P. H., Law, R. & Weatherby, A. J. Mapping the assembly of protist communities in microcosms. Ecology 84, 1001–1011 (2003).

    Google Scholar 

  • 20.

    Schreiber, S. J. & Rittenhouse, S. From simple rules to cycling in community assembly. Oikos 105, 349–358 (2004).

    Google Scholar 

  • 21.

    Chase, J. M. & Leibold, M. A. Ecological Niches: Linking Classical and Contemporary Approaches (Univ. Chicago Press, 2003).

  • 22.

    Kraft, N. J. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015).

    Google Scholar 

  • 23.

    Moore, R., Robinson, W., Lovette, I. & Robinson, T. Experimental evidence for extreme dispersal limitation in tropical forest birds. Ecol. Lett. 11, 960–968 (2008).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 24.

    Maherali, H. & Klironomos, J. N. Influence of phylogeny on fungal community assembly and ecosystem functioning. Science 316, 1746–1748 (2007).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 25.

    Serván, C. & Allesina, S. Tractable models of ecological assembly. Ecol. Lett. 24, 1029–1037 (2021).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 26.

    Rosindell, J., Hubbell, S. P. & Etienne, R. S. The unified neutral theory of biodiversity and biogeography at age ten. Trends Ecol. Evol. 26, 340–348 (2011).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 27.

    Case, T. J. Surprising behavior from a familiar model and implications for competition theory. Am. Nat. 146, 961–966 (1995).

    Google Scholar 

  • 28.

    Saavedra, S. et al. A structural approach for understanding multispecies coexistence. Ecol. Monogr. 87, 470–486 (2017).

    Google Scholar 

  • 29.

    Tilman, D. Resources: a graphical-mechanistic approach to competition and predation. Am. Nat. 116, 362–393 (1980).

    Google Scholar 

  • 30.

    May, R. M. & Leonard, W. J. Nonlinear aspects of competition between three species. SIAM J. Appl. Math. 29, 243–253 (1975).

    Google Scholar 

  • 31.

    Dean, A. M. A simple model of mutualism. Am. Nat. 121, 409–417 (1983).

    Google Scholar 

  • 32.

    Song, C., Ahn, S. V., Rohr, R. P. & Saavedra, S. Towards a probabilistic understanding about the context-dependency of species interactions. Trends Ecol. Evol. 35, 384–396 (2020).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 33.

    Saavedra, S., Medeiros, L. P. & AlAdwani, M. Structural forecasting of species persistence under changing environments. Ecol. Lett. https://doi.org/10.1111/ele.13582 (2020).

  • 34.

    Law, R. & Blackford, J. C. Self-assembling food webs: a global viewpoint of coexistence of species in Lotka–Volterra communities. Ecology 73, 567–578 (1992).

    Google Scholar 

  • 35.

    Sigmuiud, K. Darwin’s ‘circles of complexity’: assembling ecological communities. Complexity 1, 40–44 (1995).

    Google Scholar 

  • 36.

    Law, R. & Morton, R. D. Permanence and the assembly of ecological communities. Ecology 77, 762–775 (1996).

    Google Scholar 

  • 37.

    Wilson, J. B., Spijkerman, E. & Huisman, J. Is there really insufficient support for Tilman’s R* concept? A comment on Miller et al. Am. Nat. 169, 700–706 (2007).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 38.

    May, R. M. Simple mathematical models with very complicated dynamics. Nature 261, 459–467 (1976).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 39.

    Cenci, S., Song, C. & Saavedra, S. Rethinking the importance of the structure of ecological networks under an environment-dependent framework. Ecol. Evol. 8, 6852–6859 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 40.

    O’Dwyer, J. P. Whence Lotka-Volterra? Theor. Ecol. 11, 441–452 (2018).

    Google Scholar 

  • 41.

    Levine, J. M., Bascompte, J., Adler, P. B. & Allesina, S.Beyond pairwise mechanisms of species coexistence in complex communities. Nature 546, 56–64 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 42.

    Vandermeer, J. H. The competitive structure of communities: an experimental approach with protozoa. Ecology 50, 362–371 (1969).

    Google Scholar 

  • 43.

    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).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 44.

    Venturelli, O. S. et al. Deciphering microbial interactions in synthetic human gut microbiome communities. Mol. Syst. Biol. 14, e8157 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 45.

    Bucci, V. et al. MDSINE: Microbial Dynamical Systems Inference Engine for microbiome time-series analyses. Genome Biol. 17, 121 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 46.

    Turelli, M. A reexamination of stability in randomly varying versus deterministic environments with comments on the stochastic theory of limiting similarity. Theor. Popul. Biol. 13, 244–267 (1978).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 47.

    May, R. M. Stability and Complexity in Model Ecosystems (Princeton Univ. Press, 2019).

  • 48.

    Allesina, S. & Tang, S. The stability–complexity relationship at age 40: a random matrix perspective. Popul. Ecol. 57, 63–75 (2015).

    Google Scholar 

  • 49.

    Allesina, S. & Tang, S. Stability criteria for complex ecosystems. Nature 483, 205–208 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 50.

    Grilli, J., Rogers, T. & Allesina, S. Modularity and stability in ecological communities. Nat. Commun. 7, 12031 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 51.

    Hoek, T. A. et al. Resource availability modulates the cooperative and competitive nature of a microbial cross-feeding mutualism. PLoS Biol. 14, e1002540 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 52.

    Case, T. J. An Illustrated Guide to Theoretical Ecology (Oxford Univ. Press, 2000).

  • 53.

    Freedman, H. & So, J.-H. Global stability and persistence of simple food chains. Math. Biosci. 76, 69–86 (1985).

    Google Scholar 

  • 54.

    Posfai, A., Taillefumier, T. & Wingreen, N. S. Metabolic trade-offs promote diversity in a model ecosystem. Phys. Rev. Lett. 118, 028103 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 55.

    Gould, A. L. et al. Microbiome interactions shape host fitness. Proc. Natl Acad. Sci. USA 115, E11951–E11960 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 56.

    Kehe, J. et al. Massively parallel screening of synthetic microbial communities. Proc. Natl Acad. Sci. USA 116, 12804–12809 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 57.

    Xiao, Y. et al. Mapping the ecological networks of microbial communities. Nat. Commun. 8, 2042 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 58.

    AlAdwani, M. & Saavedra, S. Is the addition of higher-order interactions in ecological models increasing the understanding of ecological dynamics? Math. Biosci. 315, 108222 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 59.

    Weibel, C. A. in History of Topology (ed. James, I.) 797–836 (North-Holland, 1999).

  • 60.

    Carlsson, G. Topology and data. Bull. Am. Math. Soc. 46, 255–308 (2009).

    Google Scholar 

  • 61.

    Rabadán, R. & Blumberg, A. J. Topological Data Analysis for Genomics and Evolution: Topology in Biology (Cambridge Univ. Press, 2019).

  • 62.

    Sizemore, A. E., Phillips-Cremins, J. E., Ghrist, R. & Bassett, D. S. The importance of the whole: topological data analysis for the network neuroscientist. Netw. Neurosci. 3, 656–673 (2019).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 63.

    Sugihara, G. Graph theory, homology and food webs. In Proc. Symposia in Applied Mathematics 30, 83–101 (American Mathematical Society, 1984).

  • 64.

    Singh, G., Mémoli, F. & Carlsson, G. E. Topological methods for the analysis of high dimensional data sets and 3D object recognition. In Symposium on Point Based Graphics 91–100 (The Eurographics Association, 2007).

  • 65.

    Giusti, C., Ghrist, R. & Bassett, D. S. Two’s company, three (or more) is a simplex. J. Comput. Neurosci. 41, 1–14 (2016).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 66.

    Bauer, U. Ripser: efficient computation of Vietoris–Rips persistence barcodes. Preprint at https://arxiv.org/abs/1908.02518 (2019).

  • 67.

    Fort, H. On predicting species yields in multispecies communities: quantifying the accuracy of the linear Lotka–Volterra generalized model. Ecol. Model. 387, 154–162 (2018).

    Google Scholar 

  • 68.

    Halty, V., Valdés, M., Tejera, M., Picasso, V. & Fort, H. Modeling plant interspecific interactions from experiments with perennial crop mixtures to predict optimal combinations. Ecol. Appl. 27, 2277–2289 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 69.

    Tabi, A. et al. Species multidimensional effects explain idiosyncratic responses of communities to environmental change. Nat. Ecol. Evol. 4, 1036–1043 (2020).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 70.

    Jansen, W. A permanence theorem for replicator and Lotka–Volterra systems. J. Math. Biol. 25, 411–422 (1987).

    Google Scholar 

  • 71.

    Schreiber, S. J. Criteria for Cr robust permanence. J. Differ. Equ. 162, 400–426 (2000).

    Google Scholar 

  • 72.

    Angulo, M. T., Moreno, J. A., Lippner, G., Barabási, A.-L. & Liu, Y.-Y. Fundamental limitations of network reconstruction from temporal data. J. R. Soc. Interface 14, 20160966 (2017).

    PubMed 
    PubMed Central 

    Google Scholar 


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