Fig 1.
Predicted vs. observed network architecture.
For each network, simulations were run to equilibrium and its architecture (modularity, nestedness, and connectance) recorded. Predictions are the averages of the last 200 time units after the dynamics stabilize.
Fig 2.
Robustness vs. network structure.
For each simulation, the model was ran up t = 150, after which its structure was recorded. The generalist species were sequentially removed and the level of robustness recorded. Panels show the relationship between robustness and connectance, link density, nestedness, resource-consumer ratio, skewness of the degree distribution and modularity in both adaptive and rigid networks. R50 was used as the measure of robustness. Cyan lines indicate regressions for adaptive networks (cyan dots) while red lines for rigid networks (red dots). Spearman’s rank correlation coefficients are summarised in Table 1.
Table 1.
Spearman’s rank correlations between network structure and robustness (R50, is the percentage of generalist resources that need to be removed before at least 50% of consumer species go extinct).
Fig 3.
Robustness to the removal of species in adaptive and rigid networks.
Panels (a) and (c) correspond to the real network, N41 while (b) and (d) correspond to N43 in S1 Table in the supporting information. For panels (a) and (b), generalist species were sequentially removed while for (c) and (d), specialists were sequentially removed. Points show the percentage of consumer extinctions that resulted from the removal of a certain percentage of generalist (a and b) or specialist (c and d) resource species from an adaptive or rigid network.
Fig 4.
Robustness to the removal of generalists and specialists in two networks (N41 and N43 in S1 Table).
Points show the percentage of consumer extinctions that result from the removal of a certain percentage of resource generalists and specialists. Panels (a) and (b) correspond to adaptive networks while (c) and (d) correspond to rigid networks.
Fig 5.
Genaralised additive model lines of fit of robustness with different threshold percentages on modularity and nestedness.
R10—R70 correspond to the percentage of resources that need to be removed before at least 10–70% of consumer species go extinct in an adaptive network while R50ns corresponds to the percentage of resources that need to be removed before at least 50% of consumer species go extinct in a rigid network. Panels (a) and (b) indicate the removal of generalists while (c) and (d) indicate the removal of specialists.
Table 2.
Variance explained measured by adjusted R2 from the generalised additive model fitting of robustness on specific models.