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, 103 (16), 6230-5

Self-organized Similarity, the Evolutionary Emergence of Groups of Similar Species

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Self-organized Similarity, the Evolutionary Emergence of Groups of Similar Species

Marten Scheffer et al. Proc Natl Acad Sci U S A.

Abstract

Ecologists have long been puzzled by the fact that there are so many similar species in nature. Here we show that self-organized clusters of look-a-likes may emerge spontaneously from coevolution of competitors. The explanation is that there are two alternative ways to survive together: being sufficiently different or being sufficiently similar. Using a model based on classical competition theory, we demonstrate a tendency for evolutionary emergence of regularly spaced lumps of similar species along a niche axis. Indeed, such lumpy patterns are commonly observed in size distributions of organisms ranging from algae, zooplankton, and beetles to birds and mammals, and could not be well explained by earlier theory. Our results suggest that these patterns may represent self-constructed niches emerging from competitive interactions. A corollary of our findings is that, whereas in species-poor communities sympatric speciation and invasion of open niches is possible, species-saturated communities may be characterized by convergent evolution and invasion by look-a-likes.

Conflict of interest statement

Conflict of interest statement: No conflicts declared.

Figures

Fig. 1.
Fig. 1.
To study competition, we place species randomly along a hypothetical niche axis. To facilitate an intuitive interpretation, one may think of the niche axis as a gradient that is related to the size of organisms. If we assume that individuals of the same size compete strongest, niche overlap and resulting competition coefficients can be computed (45) for sets of species of given size distributions (see Methods).
Fig. 2.
Fig. 2.
Self-organized lumpy patterns in the abundance of competing species along a niche axis. (a) A transient state after a simulation run of 1,000 generation times. (b) A stable pattern of species abundance reached after 5,000 generation times in the presence of mild density-dependent losses (g = 0.02, H = 0.1, Eq. 2). (c) The competitive threshold for invasion of a new species expressed as percentage deviation of its carrying capacity (K) relative to that of the resident species is lowest in the species lumps, showing that these represent relative windows of opportunity for invasion, and attractors in the fitness landscape. Note that the relatively low predation loss at low densities allows starting invaders to enter with a competitive power (K) slightly below that of residents.
Fig. 3.
Fig. 3.
Simulated evolution of 100 species (dots in a) that are initially randomly distributed over the niche axis results in convergence toward self-organized lumps of similar species in the presence of density-dependent losses. The carrying capacity of the species is randomly drawn between 9 and 10. (bd) Resulting frequency distributions of species sizes for increasing values of the parameter representing random variation in other factors that affect evolutionary pressure (w = 0.025, 0.04, and 0.05, respectively). g = 0.5, H = 5, Eq. 2.
Fig. 4.
Fig. 4.
A slight preexisting niche, simulated by a tiny dip in the background mortality rate around the value 0.5 on the niche axis [Top; the function used to generate this particular example is f(L) = mAa(1/2 + 1/2cos((L + 0.5)2π))20, mA = 0.005 d−1; a = 0.005 d−1], is enough to function as a “condensation point” that anchors the self-organized pattern of species lumps to a fixed position (Middle, after 5,000 time steps; Bottom, after 20,000 time steps).
Fig. 5.
Fig. 5.
Size distributions of species in nature often show a lumpy pattern, illustrated here for European aquatic beetles (a, data compiled by Drost et al.; ref. 46), phytoplankton species of the Dutch Border Lakes (b, unpublished data from the RIZA Institute), and American prairie birds (c, data compiled by Holling; ref. 38).

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