Background/Question/Methods

Hubbell’s neutral theory, assuming that all species in a community are equivalent in their per capita fitness, have now attracted enormous attention among ecologists and have grandly contributed to our understanding of communities’ ecology. Surprisingly, this theory has never been investigated for other interaction than competition within the same trophic level, most likely because interactions like predation or parasitism are obviously not neutral, i.e. not established independently from species identity. Nevertheless a neutral model of multitrophic community dynamics can be very helpful to discriminate between the effects of the niche’s constrains and of stochastic events on communities structure and stability. Here we present a dynamic model of neutral predator-prey interactions. Our individual-based model has three important features: (1) dynamics within a trophic level follow Hubbell’s zero-sum dynamics, (2) individuals between trophic levels interact as they encounter each other, without any distinction between species, and (3) parameters between trophic levels could differ. We described assembled networks using classic structural indices in bipartite networks studies (diversity, connectance, links density) and explored the diversity-complexity relationship.

Results/Conclusions
We obtained a range of connectance values that is consistent with values of connectance reported for real bipartite networks. Moreover, the complexity-diversity relationship observed in our simulated neutral networks follow a power law with an intermediate slope between the link scaling law (1, Cohen) and the constant connectance hypothesis (2, Martinez 2000), which is also consistent with empirical result (around 1.1, Briand 1983, Dunne 2006). We show that ultimately the network’s complexity is constrained by the caring capacity of communities and by abundance distribution at each trophic level. Hence we conclude that descriptive statistics such as connectance are not good indicators of niche differentiation and that species abundance distributions must be considered in networks studies.