Beyond pairwise mechanisms of species coexistence in complex communities

Journal name:
Nature
Volume:
546,
Pages:
56–64
Date published:
DOI:
doi:10.1038/nature22898
Received
Accepted
Published online

Abstract

The tremendous diversity of species in ecological communities has motivated a century of research into the mechanisms that maintain biodiversity. However, much of this work examines the coexistence of just pairs of competitors. This approach ignores those mechanisms of coexistence that emerge only in diverse competitive networks. Despite the potential for these mechanisms to create conditions under which the loss of one competitor triggers the loss of others, we lack the knowledge needed to judge their importance for coexistence in nature. Progress requires borrowing insight from the study of multitrophic interaction networks, and coupling empirical data to models of competition.

At a glance

Figures

  1. Coexistence mechanisms that emerge only with more than two competitors.
    Figure 1: Coexistence mechanisms that emerge only with more than two competitors.

    a, Strictly pairwise competition between a forb and a grass, showing both interspecific and intraspecific interactions. b, An interaction chain in which a shrub provides indirect benefits (red arrow) to a grass through the suppression of a forb. Grey arrows indicate pairwise interactions that are not directly involved in the interaction chain or higher-order interactions. c, A higher-order interaction in which a shrub alters the per capita effect of a forb on a grass. In this case, the shrub induces a plastic change in the forb that leads it to root at more shallow depths of soil, bringing it into greater competitive contact with the grass. Arrow widths in a–c indicate the strength of the per capita competitive effect.

  2. A competitive network and an extinction cascade.
    Figure 2: A competitive network and an extinction cascade.

    a, An intransitive competitive network or 'tournament', in which arrows point from the winner to the loser in pairwise competition. The system is composed of a number of smaller intransitive loops (for example, between the light blue, the dark blue and the pink species) that are nested in larger loops that include all seven species (see ref. 3 for examples of competitive network structure). b, Simulation of the dynamics of the system following the methods of ref. 6. Owing to intransitive competitive relationships, the seven species shown would coexist indefinitely, cycling around an equilibrium in which the red and dark-green species have a proportional abundance (the proportion of individuals that belong to each species) of 1/3, the light and dark blue species have a proportional abundance of 1/9 and the light green, orange and pink species have a proportional abundance of 1/27. At year 50, the dark blue species is sent to extinction, which causes a further 3 species to become extinct owing to the disruption of the intransitivity that stabilized their dynamics. The remaining three species oscillate in a rock–paper–scissors fashion around a proportional abundance of 1/3. The y-axis is presented on a square-root scale to improve the visibility of species with low abundance.

  3. A data-driven approach to modelling species dynamics.
    Figure 3: A data-driven approach to modelling species dynamics.

    Observational or experimental data can be fitted to models, which are then used to analyse the effects of interaction chains or higher-order interactions on dynamics. Between-year patterns of abundance (top) are converted into demographic transitions as a function of size (middle). For a size-based model, all individuals may be considered as circles of a given area. The change in size of species i (Si) from one year to the next can be modelled as a function of the abundance or collective size of other individuals within a given radius or neighbourhood, assuming pairwise or higher-order interactions. Similar models can be built for survival and reproduction. The fitted functions can then be used to inform individual-based or integral projection models of community dynamics (bottom). These models and their parameters can be manipulated to add or remove particular mechanisms of coexistence, which enables their contribution to diversity maintenance to be evaluated.

References

  1. Hutchinson, G. E. The paradox of the plankton. Am. Nat. 95, 137145 (1961).
  2. Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343366 (2000).
  3. Barabás, G., Michalska-Smith, M. J. & Allesina, S. The effect of intra- and interspecific competition on coexistence in multispecies communities. Am. Nat. 188, E1E12 (2016).
    This paper investigates how the specific arrangement of competition coefficients in a network structure affects stability.
  4. Hubbell, S. P. Neutral theory in community ecology and the hypothesis of functional equivalence. Funct. Ecol. 19, 166172 (2005).
  5. Kraft, N. J. B., Valencia, R. & Ackerly, D. D. Functional traits and niche-based tree community assembly in an Amazonian forest. Science 322, 580582 (2008).
  6. Allesina, S. & Levine, J. M. A competitive network theory of species diversity. Proc. Natl Acad. Sci. USA 108, 56385642 (2011).
    This paper uses mathematical theory to show how intransitive competitive loops emerge and stabilize coexistence in diverse competitive networks.
  7. Billick, I. & Case, T. J. Higher order interactions in ecological communities: what are they and how can they be detected? Ecology 75, 15291543 (1994).
  8. Friedman, J., Higgins, L. M. & Gore, J. Community structure follows simple assembly rules in microbial microcosms. Nature Ecol. Evol. 0109 (2017).
  9. Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853856 (2010).
  10. Stouffer, D. B. & Bascompte, J. Compartmentalization increases food-web persistence. Proc. Natl Acad. Sci. USA 108, 36483652 (2011).
  11. Montoya, J. M., Woodward, G., Emmerson, M. C. & Solé, R. V. Press perturbations and indirect effects in real food webs. Ecology 90, 24262433 (2009).
  12. Solé, R. V. & Montoya, J. A. Complexity and fragility in ecological networks. Proc. R. Soc. B 268, 20392045 (2001).
  13. Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. B 271, 26052611 (2004).
  14. Rezende, E. L., Lavabre, J. E., Guimarães, P. R., Jr, Jordano, P. & Bascompte, J. Non-random coextinctions in phylogenetically structured mutualistic networks. Nature 448, 925928 (2007).
  15. Case, T. J. Invasion resistance, species build-up and community collapse in metapopulation models with interspecies competition. Biol. J. Linn. Soc. 42, 239266 (1991).
  16. Stone, L. & Roberts, A. Conditions for a species to gain advantage from the presence of competitors. Ecology 72, 19641972 (1991).
  17. Kerr, B., Riley, M. A., Feldman, M. W. & Bohannan, B. J. M. Local dispersal promotes biodiversity in a real-life game of rock–paper–scissors. Nature 418, 171174 (2002).
    This paper shows how a rock–paper–scissors competitive loop can stabilize the dynamics of multiple strains of E. coli in the laboratory.
  18. Wootton, J. T. Indirect effects and habitat use in an intertidal community: interaction chains and interaction modifications. Am. Nat. 141, 7189 (1993).
  19. Padilla, F. M. et. al. Early root overproduction not triggered by nutrients decisive for competitive success belowground. PLoS ONE 8, e55805 (2013).
  20. May, R. M. Will a large complex system be stable? Nature 238, 413414 (1972).
  21. Yodzis, P. The indeterminancy of ecological interactions as perceived through perturbation experiments. Ecology 69, 508515 (1988).
  22. Allesina, S. & Tang, S. Stability criteria for complex ecosystems. Nature 483, 205208 (2012).
  23. May, R. M. & Leonard, W. J. Nonlinear aspects of competition between three species. SIAM J. Appl. Math. 29, 243253 (1975).
  24. Levine, S. H. Competitive interactions in ecosystems. Am. Nat. 110, 903910 (1976).
  25. Vandermeer, J. Indirect and diffuse interactions: complicated cycles in a population embedded in a large community. J. Theor. Biol. 142, 429442 (1990).
  26. Hofbauer, J. & Sigmund, K. Evolutionary game dynamics. Bull. Am. Math. Soc. 40, 479519 (2003).
  27. Laird, R. A. & Schamp, B. S. Competitive intransitivity promotes species coexistence. Am. Nat. 168, 182193 (2006).
  28. Huisman, J. & Weissing, F. J. Biodiversity of plankton by species oscillations and chaos. Nature 402, 407410 (1999).
  29. Benincà, E., Ballantine, B., Ellner, S. P. & Huisman, J. Species fluctuations sustained by a cyclic succession at the edge of chaos. Proc. Natl Acad. Sci. USA 112, 63896394 (2015).
  30. Edwards, K. & Schreiber, S. Preemption of space can lead to intransitive coexistence of competitors. Oikos 119, 12011209 (2010).
  31. MacArthur, R. & Levins, R. The limiting similarity, convergence, and divergence of coexisting species. Am. Nat. 101, 377385 (1967).
  32. Pimm, S. L. The structure of food webs. Theor. Popul. Biol. 16, 144158 (1979).
  33. Krause, A. E., Frank, K. A., Mason, D. M., Ulanowicz, R. E. & Taylor, W. W. Compartments revealed in food-web structure. Nature 426, 282285 (2003).
  34. Olesen, J. M., Bascompte, J., Dupont, Y. L. & Jordano, P. The modularity of pollination networks. Proc. Natl Acad. Sci. USA 104, 1989119896 (2007).
  35. Allesina, S. & Pascual, M. Food web models: a plea for groups. Ecol. Lett. 12, 652662 (2009).
  36. Guimerà, R. et. al. Origin of compartmentalization in food webs. Ecology 91, 29412951 (2010).
  37. Grilli, J., Rogers, T. & Allesina, S. Modularity and stability in ecological communities. Nature Commun. 7, 12031 (2016).
  38. Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant–animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 93839387 (2003).
  39. Bastolla, U. et. al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 10181020 (2009).
  40. Sinervo, B. & Lively, C. M. The rock–paper–scissors game and the evolution of alternative male strategies. Nature 380, 240243 (1996).
  41. Lankau, R. A. & Strauss, S. Y. Mutual feedbacks maintain both genetic and species diversity in a plant community. Science 317, 15611563 (2007).
    This paper shows how genetic diversity in a species of mustard helps to stabilize between-species coexistence through an intransitive competitive relationship.
  42. Lankau, R. A. Genetic variation promotes long-term coexistence of Brassica nigra and its competitors. Am. Nat. 174, E40E53 (2009).
  43. Buss, L. W. & Jackson, J. B. C. Competitive networks: nontransitive competitive relationships in cryptic coral reef environments. Am. Nat. 113, 223234 (1979).
  44. Buss, L. W. Competitive intransitivity and size-frequency distributions of interaction populations. Proc. Natl Acad. Sci. USA 77, 53555359 (1980).
  45. Paine, R. T. Ecological determinism in the competition for space: the Robert H. MacArthur Award lecture. Ecology 65, 13391348 (1984).
  46. Keddy, P. A. & Shipley, B. Competitive hierarchies in herbaceous plant communities. Oikos 54, 234241 (1989).
  47. Grace, J. B., Guntenspergen, G. R. & Keough, J. The examination of a competition matrix for transitivity and intransitive loops. Oikos 68, 9198 (1993).
  48. Shipley, B. A null model for competitive hierarchies in competition matrices. Ecology 74, 16931699 (1993).
  49. Diez, H., Steinlein, T. & Ullmann, I. The role of growth form and correlated traits in competitive ranking of six perennial ruderal plant species grown in unbalanced mixtures. Acta Oecol. 19, 2536 (1998).
  50. Cameron, D. D., White, A. & Antonovics, J. Parasite–grass–forb interactions and rock–paper scissor dynamics: predicting the effects of the parasitic plant Rhinanthus minor on host plant communities. J. Ecol. 97, 13111319 (2009).
  51. Zhang, S. & Lamb, E. G. Plant competitive ability and the transitivity of competitive hierarchies change with plant age. Plant Ecol. 231, 1523 (2012).
  52. Tilman, D. Resource Competition and Community Structure (Princeton Univ. Press, 1982).
  53. Ulrich, W., Soliveres, S., Kryszewski, W., Maestre, F. T. & Gotelli, N. J. Matrix models for quantifying competitive intransitivity from species abundance data. Oikos 123, 10571070 (2014).
  54. Soliveres, S. et. al. Intransitive competition is widespread in plant communities and maintains their species richness. Ecol. Lett. 18, 790798 (2015).
  55. Abrams, P. A. Arguments in favor of higher-order interactions. Am. Nat. 121, 889891 (1983).
  56. Golubski, A. J., Westlund, E. E., Vandermeer, J. & Pascual, M. Ecological networks over the edge: hypergraph trait-mediated indirect interaction (TMII) structure. Trends Ecol. Evol. 31, 344354 (2016).
  57. Bairey, E., Kelsic, E. D. & Kishony, R. Higher-order species interactions shape ecosystem diversity. Nature Commun. 7, 12285 (2016).
    This paper uses mathematical models to show that higher-order interactions can cause communities with greater diversity to be more stable than their species-poor counterparts, contrary to classic theory that is based on pairwise interactions.
  58. Vandermeer, J. H. A further note on community models. Am. Nat. 117, 379380 (1981).
  59. Mayfield, M. M. & Stouffer, D. B. Higher-order interactions capture unexplained complexity in diverse communities. Nature Ecol. Evol. 1, 0062 (2017).
  60. Vandermeer, J. H. The competitive structure of communities: an experimental approach with protozoa. Ecology 50, 362371 (1969).
  61. Neill, W. E. The community matrix and interdependence of the competition coefficients. Am. Nat. 108, 399408 (1974).
  62. Worthen, W. B. & Moore, J. L. Higher-order interactions and indirect effects: a resolution using laboratory Drosophila communities. Am. Nat. 138, 10921104 (1991).
  63. Morin, P. J., Lawler, S. P. & Johnson, E. A. Competition between aquatic insects and vertebrates: interaction strength and higher order interactions. Ecology 69, 14011409 (1988).
  64. Pomerantz, M. J. Do 'higher order interactions' in competition systems really exist? Am. Nat. 117, 583591 (1981).
  65. Adler, F. R. & Morris, W. F. A general test for interaction modification. Ecology 75, 15521559 (1994).
  66. Dormann, C. F. & Roxburgh, S. H. Experimental evidence rejects pairwise modelling approach to coexistence in plant communities. Proc. R. Soc. B 272, 12791285 (2005).
  67. Weigelt, A. et. al. Identifying mechanisms of competition in multi-species communities. J. Ecol. 95, 5364 (2007).
  68. Vandermeer, J. H. A further note on community models. Am. Nat. 117, 379380 (1981).
  69. Huisman, J. & Weissing, F. J. Biological conditions for oscillations and chaos generated by multispecies competition. Ecology 82, 26822695 (2001).
  70. Vasseur, D. A., Amarasekare, P., Rudolf, V. H. W. & Levine, J. M. Eco-evolutionary dynamics enable coexistence via neighbor-dependent selection. Am. Nat. 178, E96E109 (2011).
  71. Bastolla, U., Lässig, M., Manrubia, S. C. & Valleriani, A. Biodiversity in model ecosystems, I: coexistence conditions for competing species. J. Theor. Biol. 235, 521530 (2005).
  72. Jabot, F. & Bascompte, J. Bitrophic interactions shape biodiversity in space. Proc. Natl Acad. Sci. USA 109, 45214526 (2012).
  73. Lasky, J. R., Uriarte, M., Boukili, V. K. & Chazdon, R. L. Trait-mediated assembly processes predict successional changes in community diversity of tropical forests. Proc. Natl Acad. Sci. USA 111, 56165621 (2014).
  74. Kraft, N. J. B., Godoy, O. & Levine, J. M. Plant functional traits and the multidimensional nature of species coexistence. Proc. Natl Acad. Sci. USA 112, 797802 (2015).
  75. Chu, C. & Adler, P. B. Large niche differences emerge at the recruitment stage to stabilize grassland coexistence. Ecol. Monogr. 85, 373392 (2015).
    This paper describes state-of-the-art approaches for combining observational data with mathematical models to project the importance of particular coexistence mechanisms in nature.
  76. Godoy, O., Stouffer, D. B., Kraft, N. J. & Levine, J. M. Intransitivity is infrequent and fails to promote annual plant coexistence without pairwise niche differences. Ecology http://dx.doi.org/10.1002/ecy.1782 (2017).
  77. Ellner, S. P., Snyder, R. E. & Adler, P. B. How to quantify the temporal storage effect using simulations instead of math. Ecol. Lett. 19, 13331342 (2016).
  78. Antonopoulos, D. A. et. al. Reproducible community dynamics of the gastrointestinal microbiota following antibiotic perturbation. Infect. Immun. 77, 23672375 (2009).
  79. Costello, C. et. al. Status and solutions for the world's unassessed fisheries. Science 338, 517520 (2012).
  80. Eklof, A. & Ebenman, B. Species loss and secondary extinctions in simple and complex model communities. J. Anim. Ecol. 75, 239246 (2006).
  81. Levine, J. M., Adler, P. B. & Yelenik, S. G. A meta-analysis of biotic resistance to exotic plant invasions. Ecol. Lett. 7, 975989 (2004).
  82. Silvertown, J., Dodd, M. E., Gowing, D. J. G. & Mountford, J. O. Hydrologically defined niches reveal a basis for species richness in plant communities. Nature 400, 6163 (1999).
  83. Adler, P. B., HilleRisLambers, J. & Levine, J. M. A niche for neutrality. Ecol. Lett. 10, 95104 (2007).
  84. Goh, B. S. Global stability in many-species systems. Am. Nat. 111, 135143 (1977).
  85. Roberts, A. The stability of a feasible random ecosystem. Nature 251, 608609 (1974).
  86. Vandermeer, J. H. Interspecific competition: a new approach to the classical theory. Science 188, 253255 (1975).
  87. Stone, L. Some Problems of Community Ecology: Processes, Patterns and Species Persistence in Ecosystems. PhD thesis, Monash Univ. (1988).
  88. Logofet, D. O. Matrices and Graphs: Stability Problems in Mathematical Ecology (CRC, 1992).
  89. Case, T. J. An Illustrated Guide to Theoretical Ecology (Oxford Univ. Press, 2000).
  90. Rohr, R. P., Saavedra, S. & Bascompte, J. On the structural stability of mutualistic systems. Science 345, 1253497 (2014).
  91. Justus, J. Ecological and Lyapunov stability. Philos. Sci. 75, 421436 (2008).
  92. Thom, R. Structural Stability and Morphogenesis (Addison-Wesley, 1994).
  93. Solé, R. V. & Valls, J. On structural stability and chaos in biological systems. J. Theor. Biol. 155, 87102 (1992).
  94. Saavedra, S. et. al. A structural approach for understanding multispecies coexistence. Ecol. Monogr. http://dx.doi.org/10.1002/ecm.1263 (2017).

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Affiliations

  1. Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zürich, 8092 Zürich, Switzerland.

    • Jonathan M. Levine
  2. Department of Evolutionary Biology and Environmental Studies, University of Zurich, 8057 Zurich, Switzerland.

    • Jordi Bascompte
  3. Department of Wildland Resources and the Ecology Center, Utah State University, Logan, Utah 84322, USA.

    • Peter B. Adler
  4. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA.

    • Stefano Allesina

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The authors declare no competing financial interests.

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Author Contributions All authors researched the literature to assemble the review. J.M.L. assembled the first draft of the paper, with all authors contributing individual sections and revisions.

Reviewer Information Nature thanks A. Golubski, E. Thebault and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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