According to the competitive exclusion principle, species with low competitive abilities should be excluded by more efficient competitors; yet, they generally remain as rare species. Here, we describe the positive and negative spatial association networks of 326 disparate assemblages, showing a general organization pattern that simultaneously supports the primacy of competition and the persistence of rare species. Abundant species monopolize negative associations in about 90% of the assemblages. On the other hand, rare species are mostly involved in positive associations, forming small network modules. Simulations suggest that positive interactions among rare species and microhabitat preferences are the most probable mechanisms underpinning this pattern and rare species persistence. The consistent results across taxa and geography suggest a general explanation for the maintenance of biodiversity in competitive environments.
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The dataset used in this study is freely available at https://doi.org/10.6084/m9.figshare.9906092.
The R scripts used in this study are freely available at https://doi.org/10.6084/m9.figshare.9906092.
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We thank J. Hortal and S. Allesina for their critical comments on an early version of the manuscript. The simulations were performed on resources provided by the Swedish National Infrastructure for Computing at HPC2N. J.C. is supported by the Carl Tryggers Foundation for Scientific Research (no. CTS 16:384). E.A. is supported by a postdoctoral grant (no. CT39/17) funded by the Universidad Complutense de Madrid. C.J.M. is supported by the Swiss National Science Foundation (grant no. SNSF-31003A-144162). R.B.-M. is supported by the Spanish Ministry of Science and Innovation predoctoral fellowship no. BES-2013-065753. M.S., J.A.B.-C. and J.M.-G. acknowledge support from the University of Geneva (project: C-CIA; no. 309354). X.A. is supported by a Ramón y Cajal research contract by the Spanish Ministry of Economy and Competitiveness (MINECO, no. RYC-2015-18448). M.R. is supported by the Swedish Research Council grant no. 2016-00796. J.A.N. was supported by a Colombian COLCIENCIAS doctoral scholarship (no. 617-2013). F.A.-M. is grateful to CAPES for a doctoral scholarship (no. 120147/2016-01). A.L., P.F. and J.M.-G. were funded by the AGORA Project (MINECO, no. CGL2016-77417-P). C.M.-M. was supported by an IdEx Bordeaux Postdoctoral Fellowship (VECLIMED project). A.H. was supported by the University of Alcalá own research programme 2018 postdoctoral grant and Basque Country Government funding support to FisioClimaCO2 (IT1022-16) research group. L.J. received productivity grants from of CNPq (process no. 307597/2016-4).
The authors declare no competing interests.
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Extended Data Fig. 1 The differences between positive and negative network properties were in general unaffected by sampling effort, null model degrees of freedom, species richness, latitude, longitude or taxa.
Generalized linear model summary statistics including explained deviance (Dev. expl.) for each model. Connectivity (P < N): Probability of negative networks to be more densely connected than their positive pairs. Abundance-degree (P < N): Probability of dominant species to monopolizing negative links but not positive ones (that is, a stronger positive abundance-degree relationship in negative networks). Abundance (P < N): probability of positive networks tending to be composed of less abundant species. Modularity (P > N): probability of positive networks being more modular than their negative pairs.
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Calatayud, J., Andivia, E., Escudero, A. et al. Positive associations among rare species and their persistence in ecological assemblages. Nat Ecol Evol 4, 40–45 (2020). https://doi.org/10.1038/s41559-019-1053-5
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