Using exclusion rate to unify niche and neutral perspectives on coexistence |
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| Authors: | Yohay Carmel Yevhen F. Suprunenko William E. Kunin Rafi Kent Jonathan Belmaker Avi Bar‐Massada Stephen J. Cornell |
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| Affiliation: | 1. Faculty of Civil and Environmental Engineering, The Technion, Haifa, Israel;2. http://orcid.org/0000‐0001‐6026‐5236;3. Inst. of Integrative Biology, Univ. of Liverpool, Liverpool, L69 7ZB, UK;4. School of Biology, Univ. of Leeds, Leeds, UK;5. Dept of Geography and Environment, Bar‐Ilan Univ., Ramat‐Gan, Israel;6. Dept of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv Univ, Tel Aviv, Israel;7. Dept of Biology and Environment, Univ. of Haifa at Oranim, Kiryat Tivon, Israel |
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| Abstract: | The competitive exclusion principle is one of the most influential concepts in ecology. The classical formulation suggests a correlation between competitor species similarity and competition severity, leading to rapid competitive exclusion where species are very similar; yet neutral models show that identical species can persist in competition for long periods. Here, we resolve the conflict by examining two components of similarity – niche overlap and competitive similarity – and modeling the effects of each on exclusion rate (defined as the inverse of time to exclusion). Studying exclusion rate, rather than the traditional focus on binary outcomes (coexistence versus exclusion), allows us to examine classical niche and neutral perspectives using the same currency. High niche overlap speeds exclusion, but high similarity in competitive ability slows it. These predictions are confirmed by a well‐known model of two species competing for two resources. Under ecologically plausible scenarios of correlation between these two factors, the strongest exclusion rates may be among moderately similar species, while very similar and highly dissimilar competitors have very low exclusion rates. Adding even small amounts of demographic stochasticity to the model blurs the line between deterministic and probabilistic coexistence still further. Thus, focusing on exclusion rate, instead of on the binary outcome of coexistence versus exclusion, allows a variety of outcomes to result from competitive interactions. This approach may help explain species coexistence in diverse competitive communities and raises novel issues for future work. |
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