Local and landscape effects in a host-parasitoid interaction network along a forest-cropland gradient

Power laws in species' biotic interaction networks can be inferred from co-occurrence data

Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species' biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.

Ecological network complexity scales with area

Larger geographical areas contain more species-an observation raised to a law in ecology. Less explored is whether biodiversity changes are accompanied by a modification of interaction networks. We use data from 32 spatial interaction networks from different ecosystems to analyse how network structure changes with area. We find that basic community structure descriptors (number of species, links and links per species) increase with area following a power law. Yet, the distribution of links per species varies little with area, indicating that the fundamental organization of interactions within networks is conserved. Our null model analyses suggest that the spatial scaling of network structure is determined by factors beyond species richness and the number of links. We demonstrate that biodiversity-area relationships can be extended from species counts to higher levels of network complexity. Therefore, the consequences of anthropogenic habitat destruction may extend from species loss to wider simplification of natural communities.

Species diversity and food web structure jointly shape natural biological control in agricultural landscapes

Land-use change and agricultural intensification concurrently impact natural enemy (e.g., parasitoid) communities and their associated ecosystem services (ESs), i.e., biological pest control. However, the extent to which (on-farm) parasitoid diversity and food webs mediate landscape-level influences on biological control remains poorly understood. Here, drawing upon a 3-year study of quantitative parasitoid-hyperparasitoid trophic networks from 25 different agro-landscapes, we assess the cascading effects of landscape composition, species diversity and trophic network structure on ecosystem functionality (i.e., parasitism, hyperparasitism). Path analysis further reveals cascaded effects leading to biological control of a resident crop pest, i.e., Aphis gossypii. Functionality is dictated by (hyper)parasitoid diversity, with its effects modulated by food web generality and vulnerability. Non-crop habitat cover directly benefits biological control, whereas secondary crop cover indirectly lowers hyperparasitism. Our work underscores a need to simultaneously account for on-farm biodiversity and trophic interactions when investigating ESs within dynamic agro-landscapes.

Distinct responses of antagonistic and mutualistic networks to agricultural intensification

Species interaction networks, which govern the maintenance of biodiversity and ecosystem processes within ecological communities, are being rapidly altered by anthropogenic activities worldwide. Studies on the response of species interaction networks to anthropogenic disturbance have almost exclusively focused on one interaction type at a time, such as mutualistic or antagonistic interactions, making it challenging to decipher how networks of different interaction types respond to the same anthropogenic disturbance. Moreover, few studies have simultaneously focused on the two main components of network structure: network topology (i.e., architecture) and network ecology (i.e., species identities and interaction turnover), thereby limiting our understanding of the ecological drivers underlying changes in network topology in response to anthropogenic disturbance. Here, we used 16,400 plant-pollinator and plant-herbivore interaction observations from 16 sites along an agricultural intensification gradient to compare changes in network topology and ecology between mutualistic and antagonistic networks. We measured two aspects of network topology-nestedness and modularity-and found that although the mutualistic networks were consistently more nested than antagonistic networks and antagonistic networks were consistently more modular, the rate of change in nestedness and modularity along the gradient was comparable between the two network types. Change in network ecology, however, was distinct between mutualistic and antagonistic networks, with partner switching making a significantly larger contribution to interaction turnover in the mutualistic networks than in the antagonistic networks, and species turnover being a strong contributor to interaction turnover in the antagonistic networks. The ecological and topological changes we observed in the antagonistic and mutualistic networks have different implications for pollinator and herbivore communities in agricultural landscapes, and support the idea that pollinators are more labile in their interaction partner choice, whereas herbivores form more reciprocally specialized, and therefore more vulnerable, interactions. Our results also demonstrate that studying both topological and ecological network structure can help to elucidate the effects of anthropogenic disturbance on ecological communities, with applications for conservation and restoration of species interactions and the ecosystem processes they maintain.

Spatial variability of hosts, parasitoids and their interactions across a homogeneous landscape

Species assemblages and their interactions vary through space, generating diversity patterns at different spatial scales. Here, we study the local-scale spatial variation of a cavity-nesting bee and wasp community (hosts), their nest associates (parasitoids), and the resulting antagonistic network over a continuous and homogeneous habitat. To obtain bee/wasp nests, we placed trap-nests at 25 sites over a 32 km2 area. We obtained 1,541 nests (4,954 cells) belonging to 40 host species and containing 27 parasitoid species. The most abundant host species tended to have higher parasitism rate. Community composition dissimilarity was relatively high for both hosts and parasitoids, and the main component of this variability was species turnover, with a very minor contribution of ordered species loss (nestedness). That is, local species richness tended to be similar across the study area and community composition tended to differ between sites. Interestingly, the spatial matching between host and parasitoid composition was low. Host β-diversity was weakly (positively) but significantly related to geographic distance. On the other hand, parasitoid and host-parasitoid interaction β-diversities were not significantly related to geographic distance. Interaction β-diversity was even higher than host and parasitoid β-diversity, and mostly due to species turnover. Interaction rewiring between plots and between local webs and the regional metaweb was very low. In sum, species composition was rather idiosyncratic to each site causing a relevant mismatch between hosts and parasitoid composition. However, pairs of host and parasitoid species tended to interact similarly wherever they co-occurred. Our results additionally show that interaction β-diversity is better explained by parasitoid than by host β-diversity. We discuss the importance of identifying the sources of variation to understand the drivers of the observed heterogeneity.

Interaction strength in plant-pollinator networks: Are we using the right measure?

Understanding how ecological networks are assembled is important because network structure reflects ecosystem functioning and stability. Quantitative network analysis incorporates measures of interaction strength as an estimate of the magnitude of the effect of interaction partners on one another. Most plant-pollinator network studies use frequency of interaction between individual pollinators and individual plants (encounter) as a surrogate of interaction strength. However, the number of flowers visited per encounter may strongly vary among pollinator and plant species, and therefore not all encounters are quantitatively equivalent. We sampled plant-pollinator interactions in a Mediterranean scrubland and tested whether using a measure of interaction strength based on the number of flowers visited resulted in changes in species (species strength, interaction species asymmetry, specialization) and network descriptors (nestedness, H2', interaction evenness, plant generality, pollinator generality) compared to the encounter-based measure. Several species (including some of the most abundant ones) showed important changes in species descriptors, notably in specialization. These changes were especially important in plant species with large floral displays, which became less specialized with the visit-based measure of interaction strength. At the network level we found significant changes in all properties analysed. With the encounter-based approach plant generality was much higher than pollinator generality (high specialization asymmetry between trophic levels). However, with the visit-based approach plant generality was greatly reduced so that plants and pollinators had similar levels of generalization. Interaction evenness also decreased strongly with the visit-based approach. We conclude that accounting for the number of flowers visited per encounter provides a more ecologically relevant measure of interaction strength. Our results have important implications for the stability of pollination networks and the evolution of plant-pollinator interactions. The use of a visit-based approach is especially important in studies relating interaction network structure and ecosystem function (pollination and/or exploitation of floral resources).

Seasonal dynamics in a cavity-nesting bee-wasp community: Shifts in composition, functional diversity and host-parasitoid network structure

Ecological communities are composed of species that interact with each other forming complex interaction networks. Although interaction networks have been usually treated as static entities, interactions show high levels of temporal variation, mainly due to temporal species turnover. Changes in taxonomic composition are likely to bring about changes in functional trait composition. Because functional traits influence the likelihood that two species interact, temporal changes in functional composition and structure may ultimately affect interaction network structure. Here, we study the seasonality (spring vs. summer) in a community of cavity-nesting solitary bees and wasps (‘hosts’) and their nest associates (‘parasitoids’). We analyze seasonal changes in taxonomic compostion and structure, as well as in functional traits, of the host and parasitoid communities. We also analyze whether these changes result in changes in percent parasitism and interaction network structure. Our host and parasitoid communities are strongly seasonal. Host species richness increases from spring to summer. This results in important seasonal changes in functional composition of the host community. The spring community (almost exclusively composed of bees) is characterized by large, univoltine, adult-wintering host species. The summer community (composed of both bees and wasps) is dominated by smaller, bivoltine, prepupa-wintering species. Host functional diversity is higher in summer than in spring. Importantly, these functional changes are not only explained by the addition of wasp species in summer. Functional changes in the parasitoid community are much less pronounced, probably due to the lower parasitoid species turnover. Despite these important taxonomic and functional changes, levels of parasitism did not change across seasons. Two network metrics (generality and interaction evenness) increased from spring to summer. These changes can be explained by the seasonal increase in species richness (and therefore network size). The seasonal shift from a bee-dominated community in spring to a wasp-dominated community in summer suggests a change in ecosystem function, with emphasis on pollination in spring to emphasis on predation in summer.

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.