Correction to: Local drivers of the structure of a tropical bird­seed dispersal network.

Unfortunately, the detailed description of the ESM material went wrong in the published version of the dataset.

Local drivers of the structure of a tropical bird-seed dispersal network.

One of the major challenges in ecology is to understand the relative importance of neutral- and niche-based processes structuring species interactions within communities. The concept of neutral-based processes posits that network structure is a result of interactions between species based on their abundance. On the other hand, niche-based processes presume that network structure is shaped by constraints to interactions. Here, we evaluated the relative importance of neutral-based process, represented by species' abundance (A) and fruit production (F) models, and niche-based process, represented by spatial overlap (S), temporal overlap (T) and morphological barrier (M) models, in shaping the structure of a bird-seed dispersal network from the Brazilian Atlantic Forest. We evaluated the ability of each model, singly or in combination, to predict the general structure [represented by connectance, nestedness (NODF), weight nestedness (WNODF), interaction evenness and complementary specialization] and microstructure of the network (i.e., the frequency of pairwise interactions). Only nestedness (both NODF and WNODF) was predicted by at least one model. NODF and WNODF were predicted by a neutral-based process (A), by a combination of niche-based processes (ST and STM) and by both neutral- and niche-based processes (AM). NODF was also predicted by F and FM model. Regarding microstructure, temporal overlap (T) was the most parsimonious model able to predict it. Our findings reveal that a combination of neutral- and niche-based processes is a good predictor of the general structure (NODF and WNODF) of the bird-seed dispersal network and a niche-based process is the best predictor of the network's microstructure.

Understanding and planning ecological restoration of plant-pollinator networks.

Theory developed from studying changes in the structure and function of communities during natural or managed succession can guide the restoration of particular communities. We constructed 30 quantitative plant-flower visitor networks along a managed successional gradient to identify the main drivers of change in network structure. We then applied two alternative restoration strategies in silico (restoring for functional complementarity or redundancy) to data from our early successional plots to examine whether different strategies affected the restoration trajectories. Changes in network structure were explained by a combination of age, tree density and variation in tree diameter, even when variance explained by undergrowth structure was accounted for first. A combination of field data, a network approach and numerical simulations helped to identify which species should be given restoration priority in the context of different restoration targets. This combined approach provides a powerful tool for directing management decisions, particularly when management seeks to restore or conserve ecosystem function.

Two classes of bipartite networks: nested biological and social systems.

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

Why nestedness in mutualistic networks?

We investigate the relationship between the nested organization of mutualistic systems and their robustness against the extinction of species. We establish that a nested pattern of contacts is the best possible one as far as robustness is concerned, but only when the least linked species have the greater probability of becoming extinct. We introduce a coefficient that provides a quantitative measure of the robustness of a mutualistic system.

Analysis and assembling of network structure in mutualistic systems.

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g., plants and pollinators or plants and seed dispersers) approximately follow a truncated power law (TPL). We show that nestedness and TPL distributions are intimately linked, and that any biological reasons for such truncation are superimposed to finite size effects. We further explore the internal organization of bipartite networks by developing a self-organizing network model (SNM) that reproduces empirical observations of pollination systems of widely different sizes. Since the only inputs to the SNM are numbers of plant and animal species, and their interactions (i.e., no data on local abundance of the interacting species are needed), we suggest that the well-known association between species frequency of interaction and species degree is a consequence rather than a cause, of the observed network structure.