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It has been suggested that the importance of network architecture to species diversity and stability should be based on preference networks (comprised of niche differentiations), rather than observational networks, because species abundance may significantly affect interaction frequencies. Considering that resource abundance is usually greater for herbivores than parasites, we hypothesize that the abundance effect is stronger for parasitic than herbivory interactions. To test this hypothesis, we collected 80 quantitative observational networks including 34 herbivorous and 46 parasitic networks from the published literature, and derived preference networks by removing the effects of species abundance. We then determined the network nestedness using both weighted NODF and spectral radius. We also determined species degree distribution, interaction evenness, weighted connectance and robustness for both observational and preference networks. The observational networks (including both herbivory and parasitic networks) were more nested judged by weighted NODF than spectral radius. Preference networks were less nested for parasitic than herbivory networks in terms of both weighted NODF and spectral radius, possibly because removing the abundance effect increased interaction evenness. These trends indicate that the abundance effect on network nestedness is stronger for parasitic than herbivory networks. Weighted connectance and robustness were greater in most preference networks than observational networks, indicating that preference networks may have high network stability and community persistence compared with observational ones. The data indicate that future network analyses should not only address the structural difference between mutualistic and antagonistic interactions, but also between herbivory and parasitic interactions. [ABSTRACT FROM AUTHOR]

Unraveling the determinants of herbivorous insect diversity has been a significant challenge in ecology. Despite the strong association between insect and plant species, previous studies conducted in natural systems have shown great variation in the strength of the correlation between their species richness. Such variation could be attributed to the proportion of generalist insect species (generality). However, both higher and lower generality may weaken the correlation because (a) generalist insect species are less dependent on the number of plant species, and (b) specialist insect species utilize only a proportion of the total plant species. To explore these contradictory effects, we studied plant and herbivorous insect communities in seminatural grasslands in Japan. Plant–insect interactions were evaluated in a unique way with a particular focus on the staying and herbivory behaviors of insects, which reflect their habitat use as well as host use. We found that lower generality of insect communities strengthened the correlation between species richness of plants and insects, but this was not the case when plant species that had no interaction with insect species were also considered. This was because lower generality increased the number of plant species that did not interact with insects. The results indicate that insect generality has contradictory effects on the plant–insect diversity relationship, which emphasizes the importance of distinguishing the effects to understand the variation in the relationship between plant and insect diversity in natural systems. [ABSTRACT FROM AUTHOR]

Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical data set, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants' generalism with regard to pollinators is positively correlated to their generalism with regard to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterizing the way different interaction types are combined within ecological networks. [ABSTRACT FROM AUTHOR]

Pollination and herbivory networks have mainly been studied separately, highlighting their distinct structural characteristics and the related processes and dynamics. However, most plants interact with both pollinators and herbivores, and there is evidence that both types of interaction affect each other. Here we investigated the way plants connect these mutualistic and antagonistic networks together, and the consequences for community stability. Using an empirical dataset, we show that the way plants connect pollination and herbivory networks is not random and promotes community stability. Analyses of the structure of binary and quantitative networks show different results: the plants’ generalism with regards to pollinators is positively correlated to their generalism with regards to herbivores when considering binary interactions, but not when considering quantitative interactions. We also show that plants that share the same pollinators do not share the same herbivores. However, the way plants connect pollination and herbivory networks promotes stability for both binary and quantitative networks. Our results highlight the relevance of considering the diversity of interaction types in ecological communities, and stress the need to better quantify the costs and benefits of interactions, as well as to develop new metrics characterising the way different interaction types are combined within ecological networks.This article is protected by copyright. All rights reserved. [ABSTRACT FROM AUTHOR]