Multiple peaks of species abundance distributions induced by sparse interactions

We investigate the replicator dynamics with “sparse” symmetric interactions which represent specialist-specialist interactions in ecological communities. By considering a large self-interaction $u$, we conduct a perturbative expansion which manifests that the nature of the interactions has a direct impact on the species abundance distribution. The central results are all species coexistence in a realistic range of the model parameters and that a certain discrete nature of the interactions induces multiple peaks in the species abundance distribution, providing the possibility of theoretically explaining multiple peaks observed in various field studies. To get more quantitative information, we also construct a non-perturbative theory which becomes exact on tree-like networks if all the species coexist, providing exact critical values of $u$ below which extinct species emerge. Numerical simulations in various different situations are conducted and they clarify the robustness of the presented mechanism of all species coexistence and multiple peaks in the species abundance distributions.

Figure 1

Critical values of productivity $u_c$ plotted against $\mathrm{\Delta }$ for $c=3$. The points are the non-perturbative results, and the dashed line corresponds to the second-order perturbation. Both of the values locate well below the general upper bound $u_c^{\left(\mathrm{UB}\right)}=2c=6$.

Figure 2

The SADs for $\mathrm{\Delta }=-0.8$ (a), 0 (b), and $0.8$ (c) at $c=3$.

Figure 3

The diversity $\alpha \left(0\right)$ and $\alpha \left(1\right)$ are plotted against $\mathrm{\Delta }$ for $u=6$ (a) and 3 (b) at $c=3$. The dependence on $\mathrm{\Delta }$ is not monotonic.

Figure 4

The SAD with the interactions generated from Eq. (18), the network structure of which is a random graph of single degree $c=3$. The parameters are $u=6.03, N=16000$.

Figure 5

The SADs for the square lattice with unbiased binary interactions (a), a heterogeneous random network with degrees $c=3,4,5,6$ and unbiased binary interactions (b), and random self interactions on a single degree network $c=3$ with unbiased binary interactions (c).