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Ncomms1663.Pdf ARTICLE Received 18 May 2011 | Accepted 3 Jan 2012 | Published 7 Feb 2012 DOI: 10.1038/ncomms1663 Emergent neutrality leads to multimodal species abundance distributions Remi Vergnon1, Egbert H. van Nes1 & Marten Scheffer1 Recent analyses of data sampled in communities ranging from corals and fossil brachiopods to birds and phytoplankton suggest that their species abundance distributions have multiple modes, a pattern predicted by none of the existing theories. Here we show that the multimodal pattern is consistent with predictions from the theory of emergent neutrality. This adds to the observations, suggesting that natural communities may be shaped by the evolutionary emergence of groups of similar species that coexist in niches. Such self-organized similarity unifies niche and neutral theories of biodiversity. 1 Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Lumen (Building 100) Droevendaalsesteeg 3a, PO Box 47, Wageningen 6700 AA, The Netherlands. Correspondence and requests for materials should be addressed to R.V. (email: [email protected]). NatURE COMMUNicatiONS | 3:663 | DOI: 10.1038/ncomms1663 | www.nature.com/naturecommunications © 2012 Macmillan Publishers Limited. All rights reserved. ARTICLE NatURE COMMUNicatiONS | DOI: 10.1038/ncomms1663 pecies abundance distributions (SADs) summarize how abun- So far, empirical support for EN comes from ‘lumpiness’ reported dance varies among species and are amongst the most studied in the size distributions of species ranging from phytoplankton and Sdescriptors of community structure in ecology. One common zooplankton to mammals and birds23–25. As body size is a major approach to plot SADs is to show a histogram of number of spe- aspect in determining the ecological niche of many organisms26,27, cies on the y-axis against log-transformed abundance on the x-axis1. the existence of such groups of species of similar size suggests clus- Over the years, there has been a remarkable proliferation of SAD tering in the niche space, as predicted by the theory. Recently, a novel models2,3 that all, without exception, predict unimodal curves on a empirical test pointed to EN as the only theory consistent with pat- log scale. However, there is evidence that SADs may, in fact, be mul- terns observed within a real marine phytoplankton community28. timodal (for example, Fig. 1). For instance, Dornelas and Connolly4 Further analyses carried out on different communities are now being find a multimodal SAD in coral data collected by extensive sampling published29,30 that will ultimately show how common this result is. around a Pacific island. In this analysis, multimodality is robust to Here we show that, unlike any other competition or evolution sampling noise, strongly suggesting that the underlying distribution theory, EN predicts the multimodal SADs. To do so, we run the EN of species abundances genuinely departs from unimodality. Simi- model under realistic conditions and compute the corresponding larly, McGill et al.3 note that a three-mode distribution best fits the SAD in the Barro Colorado Island tree data set, a survey that has so a b Fossil brachiopods far only been used to compare models producing classic unimodal 25 Corals 35 curves5,6. There are several reasons why multiple modes could be 30 s 20 s regularly ‘missed’ in SADs. First of all, binning methods are prone to 25 3 blur such patterns . Also, the common approach that combines data 15 20 across guilds and/or regions can easily mask multimodality occur- 15 ring at the local scale3,4,7. More fundamentally, the idea that SADs 10 3 10 Number of specie could be multimodal has been largely overlooked . Dornelas and 5 Number of specie Connolly4 recently mentioned possible multimodality in published 5 3,8 9 10 11 SADs of communities of trees , birds , fish , fossil brachiopods , 0 0 1 4 6 1 0 12 13,14 15 15 16 64 10 benthos , phytoplankton , insects and nematodes . We col- 25 100 ,00 1,024 4,096 1,000 10 lected some of those data sets and carried out statistical analyses Species abundance (log classes) 2 Species abundance (log2 classes) that confirmed multimodality Fig.( 1b–d; Supplementary Table S1 c 15 British breeding birds d Phytoplankton for details). Many more data sets remain to be explored, but our 40 overview suggests that multimodal SADs might well be frequent in nature. Obviously, accepting this point of view would mean hav- 30 ing to reject every existing SAD theory that assume some level of 10 3 species symmetry including the classical resource-partitioning 20 16,17 18 models , models based on stochastic population dynamics and 5 19,20 10 neutral models , which all yield unimodal curves. As we will Number of species demonstrate, emergent neutrality (EN)21 may be a notable excep- Number of species tion, as it predicts multimodal SADs under virtually all conditions. 0 0 0 1 0 10 The theory of EN predicts a competition-driven, self-organ- 10 1,000 21 100,00 10,000 ized evolutionary emergence of groups of similar species . EN 1,000,000 10,000,000 implies that species in nature should be organized in clusters where Species abundance (log classes) Species abundance (log classes) they coexist in essentially the same niche, thereby bridging a gap between niche22 and neutral theory20. A core idea is that there are Figure 1 | Examples of multimodal species-abundance distributions on two different ways for species to coexist, being sufficiently differ- log scales. (a) Corals around Lizard Island, Great Barrier Reef (modified ent or being sufficiently similar. The EN model simulates a com- from Dornelas and Connolly4); (b) Fossil Permian Brachiopods from the munity of competing species, each characterized by their position Lower Word Formation, Texas (modified from Olszewski and Erwin11); on a ‘niche axis’21. Species that are closer on the niche axis compete (c) British breeding birds (data compiled by Baker et al.41); and (d) more strongly. Species are created randomly along the niche axis Carribean phytoplankton (data taken from Margalef42). Abundance is and compete with their neighbors, depending on how similar and recorded as (a) colonies counted in 275 transects, (b) abundance of abundant these are. Each species slowly evolves its position on the species in geological sequence, (c) population size estimates as given niche axis in the direction where it experiences less competition. by the British Trust for Ornithology (mean values were taken when only Although one would expect that the survivors of this evolutionary size ranges were available), (d) abundance of species estimated from game would be species that are equally spread out over the niche 1,144 of 150 ml-samples taken in the South-East Caribbean Sea. Following axis, the surprising result is a pattern of self-organized modes that the method described extensively by Dornelas and Connolly4, we fitted contain multiple coexisting species21 (Supplementary Fig. S1). mixtures of one, two and three Poisson lognormal distributions to the data Coexistence of different modes is a straightforward effect of com- and compared goodness-of-fit, using Akaike information criterion (AIC), petition avoidance. However, species that are similar enough escape Bayesian information criterion (BIC) and the likelihood ratio tests (LRT). this rule of limiting similarity and may coexist within the modes. In The black dots correspond to the best fit. All goodness-of-fit measures each of the modes, species are almost equivalent—almost neutral— suggest the presence of two modes in SAD (b) and two or three modes in and as no species is clearly superior to another, the process of dis- the data set (c). AIC and LRT indicate two modes in SAD (d), but the much placement is very slow. As a consequence, competitive exclusion can more conservative BIC did not pick up multimodality in that case. Dornelas easily be prevented by common density-dependent mechanisms and Connolly4 analyzed the data set (a) and found three modes in the that promote stable coexistence. The evolutionary convergence of abundance distribution. Data set (a) is binned in log2 abundance classes species towards a same niche seems counter-intuitive. However, it (1, 2–3, 4–7, 8–15 and so on). SAD (b) is binned in log2 abundance classes has long been known that as species niches become more closely of width 2, whereas SADs (c) and (d) are binned in log abundance packed, positions between species can turn into the worst places to classes of width 1. Note that these different representations are used to be in the ‘fitness landscape’ and evolutionary convergence between show as clearly as possible the underlying modes and have no influence close species may occur22. on the result of the statistical analysis itself. NatURE COMMUNicatiONS | 3:663 | DOI: 10.1038/ncomms1663 | www.nature.com/naturecommunications © 2012 Macmillan Publishers Limited. All rights reserved. NatURE COMMUNicatiONS | DOI: 10.1038/ncomms1663 ARTICLE SADs, looking specifically at the presence or absence of multiple a modes. In a first simulation, we run the original model without evo- 0.30 lution21 and examine how the abundance of the randomly gener- 0.25 ated competing species becomes distributed. Although evolution is 0.20 central in explaining the robustness of EN predictions, this simpler 0.15 model is sufficient to illustrate how competition affects differently undance 0.10 the species’ abundances along the niche axis. In natural communi- Ab ties, it is unlikely that the entire niche space is equally suitable25,31, 0.05 and resource availability or the intensity of physiological or ener- 0.00 getic constraints may vary among externally imposed pre-existing 0.0 0.2 0.4 0.6 0.8 1.0 niches. To integrate such heterogeneity, we relax in a second simula- Niche axis tion the assumption that all niches are self-organized by organisms, b 40 and allow parts of the niche space to be inherently better than oth- ers.
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