Hierarchical compound topology uncovers complex structure of species interaction networks.

Nestedness and modularity have been found in many species interaction networks. Despite being conceptually distinct, negatively correlated and having different causes, these patterns often co-occur. A realistic but seldom investigated alternative to these simple topologies is hierarchical compound networks, in which the entire network is modular, and modules are internally nested. In compound networks, nestedness is suppressed by modularity at higher network hierarchical levels, but prevails at lower levels, within modules. The aims of this study are (i) to evaluate the prevalence of simple and hierarchical compound topologies in binary and weighted networks describing different kinds of species interactions and (ii) to probe the relationships between modularity and nestedness at different network hierarchical levels. With a procedure that discriminates between simple and compound structures, we re-analysed the topology of 142 well-studied binary networks including seed dispersal, host-parasite, pollination and plant-herbivore interactions; 68 of these also had quantitative information. Additionally, we tested the relationship between robustness and topology of binary networks and compared the robustness of networks with compound topologies to different sequences of species removals. Compound topologies were detected in 34% of binary and 71% of weighted networks of all interaction kinds. These results establish the hierarchical compound topology as a widespread network architecture, often undetected without quantitative data. Furthermore, they disentangle an apparent paradox: despite conflicting with overall nestedness, modularity usually co-occurs with high values of low-level nestedness. Nestedness progressively decreased, while modularity increased, from seed dispersal to host-parasite, pollination and plant-herbivore networks. There were no consistent differences in the robustness of networks with nested and compound topologies. However, compound topologies were especially vulnerable to removal sequences that accelerate the exclusion of entire modules. Compound topologies improve the depiction of ecological networks and differentiate ecological and evolutionary processes that operate at different hierarchical levels, with the potential to advance our understanding of network dynamics, stability and response to species loss or change. Quantitative data often reveal specialization patterns that are indistinguishable in binary networks, strongly improving the detection of modular and compound topologies.

Influences of sampling effort on detected patterns and structuring processes of a Neotropical plant-hummingbird network.

Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 '), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks.

Ectoparasites and endoparasites of fish form networks with different structures.

Hosts and parasites interact with each other in a variety of ways, and this diversity of interactions is reflected in the networks they form. To test for differences in interaction patterns of ecto- and endoparasites we analysed subnetworks formed by each kind of parasites and their host fish species in fish-parasite networks for 22 localities. We assessed the proportion of parasite species per host species, the relationship between parasite fauna composition and host taxonomy, connectance, nestedness and modularity of each subnetwork (n = 44). Furthermore, we evaluated the similarity in host species composition among modules in ecto- and endoparasite subnetworks. We found several differences between subnetworks of fish ecto- and endoparasites. The association with a higher number of host species observed among endoparasites resulted in higher connectance and nestedness, and lower values of modularity in their subnetworks than in those of ectoparasites. Taxonomically related host species tended to share ecto- or endoparasites with the same interaction intensity, but the species composition of hosts tended to differ between modules formed by ecto- and endoparasites. Our results suggest that different evolutionary and ecological processes are responsible for organizing the networks formed by ecto- and endoparasites and fish.

A Comparison of Social Bee-Plant Networks between Two Urban Areas.

In the last decade, several studies demonstrated the effectiveness of ecological network analysis to a better understanding of the structure bee-plant interaction networks; however, such approaches involving urban areas are still scarce. Here, we analyzed two assemblages of corbiculate bees (Apoidea, Apidae) in two geographically distinct urban areas in Brazil. In both study areas, apid bees visiting flowers were captured with an insect net. Surveys were performed biweekly and alternately in each area, over a 1-year period. Both urban areas were very similar for most indices. The two social bee-plant networks were significantly nested, a pattern usually described for bee-plant networks and somehow expected in our study, considering the recognized behavior of social apid bees in exploring a wide range of plant species. The modularity measures were low and very similar for the networks of both urban areas, a finding that could be due at least in part to the low phylogenetic distance between corbiculate bees and the broad dietary habits of the social apid bees. Network-level indices showed that both bee assemblages had a relatively low niche overlap, indicating that the set of social apid species studied exploited differently the arrays of plants available. Species level index (resource range) showed that in both urban areas, Trigona spinipes (Fabr.) and Apis mellifera L. showed the higher number of interactions, a result that demonstrates the importance of these species in social bee-plant interaction networks in urban areas. Similarly to other ecosystems, these two apid species behaved as super-generalists in the two urban areas surveyed herein.

Network Connectance Analysis as a Tool to Understand Homeostasis of Plants under Environmental Changes.

The homeostasis of plants under environmental constraints may be maintained by alterations in the organization of their physiological networks. The ability to control a network depends on the strength of the connections between network elements, which is called network connectance. Herein, we intend to provide more evidence on the existence of a modulation pattern of photosynthetic networks, in response to adverse environmental conditions. Two species (Glycine max-C3 metabolism, and Brachiaria brizantha-C4 metabolism) were submitted to two environmental constraints (water availability, and high and low temperatures), and from the physiological parameters measured, the global connectance (Cgtotal) and the modules connectance (gas exchange-Cgge and photochemical-Cgpho) were analyzed. Both types of environmental constraints impaired the photosynthetic capacity and the growth of the plants, indicating loss of their homeostasis, but in different ways. The results showed that in general the Cgtotal of both species increased with temperature increment and water deficit, indicating a higher modulation of photosynthetic networks. However, the Cg variation in both species did not influence the total dry biomass that was reduced by environmental adversities. This outcome is probably associated with a loss of system homeostasis. The connectance network analyses indicated a possible lack of correspondence between the photosynthetic networks modulation patterns and the homeostasis loss. However, this kind of analysis can be a powerful tool to access the degree of stability of a biological system, as well as to allow greater understanding of the dynamics underlying the photosynthetic processes that maintain the identity of the systems under environmental adversities.