Generic assembly patterns in complex ecological communities

Abstract

Ecological communities have mainly been investigated theoretically in two ways: piecewise, a few species at a time; or as complex networks, simulated in exhaustive detail. But our empirical knowledge of networks is limited, and the space of simulation models and parameters is mindbogglingly vast. We show that a large fraction of that space of possibilities exhibits generic dynamics, which can be predicted from a single minimal model. To demonstrate this, we consider a wide array of ecological models, from resource competition to predation and mutualism, known to display very different behaviors for a few species. We simulate large communities, and show that equilibrium diversity, functioning and stability can often be predicted analytically from only four broad statistical properties of the community. Our approach provides a convenient framework for exploring generic patterns in ecosystem assembly and quantifying the added value of detailed models and measurements.

Tractable models of ecological assembly

“…Inspired by recent experiments in microbial ecology (Bittleston et al, 2019;Goldford et al, 2018), as well as theoretical developments (Barbier et al, 2018;Biroli et al, 2018;Bunin, 2017;Serván et al, 2018), we have attempted connecting the "top-down assembly" process, in which all species from a pool are introduced in an environment at the same time, with the "bottom-up assembly" process, in which species invade the system one at a time. To draw this connection, we sidestepped some of the main obstacles to the development of a theory of ecological assembly, by assuming that invasions are rare, invaders enter the system at low abundance, and that each community settles into a stable equilibrium.…”

“…The last proposition then implies that we do not need global acyclicity for G to be accessible, we simply need the graph restricted to feasible sets to be acyclic which is a more local condition, especially if the typical behavior of the community is that a considerable fraction of the species cannot coexist (Barbier et al, 2018;Biroli et al, 2018;Bunin, 2017;Serván et al, 2018). It remains to show the last statement of theorem 1.…”

“…In this area, a popular experiment is to take the microbial community from an environmental sample and challenge it with a novel, synthetic environment (e.g., grow the community in batch laboratory culture with serial dilution), following the dynamics by which the original community loses members, eventually settling into a sub-community of coexisting species (Bittleston et al, 2019;Goldford et al, 2018). Interestingly, recent theoretical advances considered the same exact scenario (Barbier et al, 2018;Biroli et al, 2018;Bunin, 2017;Serván et al, 2018) because of its analytical tractability. In abstract, a set of n species is introduced (at the same time) in the new environment, and assembly consists of the dynamical pruning of the community down to a set of coexisting species-we therefore term this process "top-down" assembly.…”

Effects of phylogeny on coexistence in model communities

“…When the number of traits is comparable to the number of species, our model is an instance of a Lotka-Volterra model with random interactions. The analysis of models considering random interactions between species has a long tradition in ecology [1,17,27], and in recent years the field has moved beyond questions concerning the stability and feasibility of the whole system, focusing more closely on the properties of sub-communities that coexist through the dynamics [3,6,10,33]. In these models, one must usually assume that species interactions are independent of species identity (but see [2,16]).…”

“…The explicit incorporation of community dynamics allows us to move from pairwise comparisons to global aspects of community structure. Furthermore, we advance the growing body of literature on random interaction models [3,6,10,33] by analyzing a case in which the correlations between interaction strengths are controlled by phylogenetic relatedness.…”