Hybrid networks reveal contrasting effects of agricultural intensification on antagonistic and mutualistic motifs

Architecture and stability of tripartite ecological networks with two interaction types

Over the past few decades, studies on empirical ecological networks have primarily focused on single antagonistic or mutualistic interactions. However, many species engage in multiple interactions that support distinct ecosystem functions. The architecture of networks integrating these interactions, along with their cascading effects on community dynamics, remains underexplored in ecological research. In this study, we compiled two datasets of empirical plant-herbivore/host-parasitoid (PHP) and pollinator-plant-herbivore (PPH) networks, representing two common types of tripartite networks in terrestrial ecosystems: antagonism-antagonism and mutualism-antagonism. We identified the patterns of subnetwork structures and interconnection properties in these networks and examined their relationships with community stability. Our findings revealed distinct pathway effects of network architecture on persistence and local stability in both PHP and PPH networks, with subnetwork modularity and nestedness showing a few strong direct effects and mediating the indirect effects of subnetwork size and connectance. In PHP networks, subnetwork modularity enhanced persistence and local stability, whereas subnetwork nestedness directly undermined them. However, both subnetwork topologies consistently mediated the destabilizing effects of subnetwork size and connectance on the entire network. In PPH networks, persistence was primarily affected by the plant-herbivore subnetwork, while the size, connectance, and modularity of different subnetworks had opposing effects on local stability. Regarding interconnection properties, the correlation of interaction similarity destabilized PHP networks, whereas the correlation of interaction degree promoted local stability in PPH networks. Further analysis indicated that structure-persistence relationships vary significantly across guilds, and the network-level effects of network architecture can be reversed, negligible, or biased in specific guilds. These findings advance our understanding of how network architecture influences ecosystem stability and underscore the importance of considering multiple interaction types when predicting community dynamics.

Local and landscape factors shape alpha and beta trophic interaction diversity in urban gardens

Promoting urban green spaces is an effective strategy to increase biodiversity in cities. However, our understanding of how local and landscape factors influence trophic interactions in these urban contexts remains limited. Here, we sampled cavity-nesting bees and wasps and their natural enemies within 85 urban gardens in Zurich (Switzerland) to identify factors associated with the diversity and dissimilarity of antagonistic interactions in these communities. The proportions of built-up area and urban green area at small landscape scales (50 m radius), as well as the management intensity, sun exposure, plant richness and proportion of agricultural land at the landscape scale (250 m radius), were key drivers of interaction diversity. This increased interaction diversity resulted not only from the higher richness of host and natural enemy species, but also from species participating in more interactions. Furthermore, dissimilarity in community structure and interactions across gardens (beta-diversity) were primarily influenced by differences in built-up areas and urban green areas at the landscape scale, as well as by management intensity. Our study offers crucial insights for urban planning and conservation strategies, supporting sustainability goals by helping to understand the factors that shape insect communities and their trophic interactions in urban gardens.

A network perspective for sustainable agroecosystems

Nature-based management aims to improve sustainable agroecosystem production, but its efficacy has been variable. We argue that nature-based agroecosystem management could be significantly improved by explicitly considering and manipulating the underlying networks of species interactions. A network perspective can link species interactions to ecosystem functioning and stability, identify influential species and interactions, and suggest optimal management approaches. Recent advances in predicting the network roles of species from their functional traits could allow direct manipulation of network architecture through additions or removals of species with targeted traits. Combined with improved understanding of the structure and dynamics of networks across spatial and temporal scales and interaction types, including social-ecological, applying these tools to nature-based management can contribute to sustainable agroecosystems.