Abstract
Abstract Predicting plant–pollinator interaction networks over space and time will improve our understanding of how environmental change is likely to impact the functioning of ecosystems. Here we propose a framework for producing spatially explicit predictions of the occurrence and number of pairwise plant–pollinator interactions and of the species richness, diversity and abundance of pollinators visiting flowers. We call the framework ‘MetaComNet’ because it aims to link metacommunity dynamics to the assembly of ecological networks. To illustrate the MetaComNet functionality, we used a dataset on bee–flower networks sampled at 16 sites in southeast Norway along with random forest models to predict bee–flower interactions. We included variables associated with climatic conditions (elevation) and habitat availability within a 250 m radius of each site. Regional commonness, site‐specific distance to conspecifics, social guild and floral preference were included as bee traits. Each plant species was assigned a score reflecting its site‐specific abundance, and four scores reflecting the bee species that the plant family is known to attract. We used leave‐one‐out cross‐validations to assess the models' ability to predict pairwise plant–bee interactions across the landscape. The relationship between observed occurrence or absence of interactions and the predicted probability of interactions was nearly proportional (GLMlogistic regression slope = 1.09), matching the data well (AUC = 0.88), and explained 30% of the variation. Predicted probability of interactions was also correlated with the number of observed pairwise interactions (r = 0.32). The sum of predicted probabilities of bee–flower interactions were positively correlated with observed species richness (r = 0.50), diversity (r = 0.48) and abundance (r = 0.42) of wild bees interacting with plant species within sites. Our findings show that the MetaComNet framework can be a useful approach for making spatially explicit predictions and mapping plant–pollinator interactions. Such predictions have the potential to identify areas where the pollination potential for wild plants is particularly high, and where conservation action should be directed to preserve this ecosystem function.
Highlights
Nine of every 10 species of flowering plants rely on interactions, mainly with insects, for cross-pollination (Ollerton et al, 2011)
|2 M ethods in Ecology and Evoluঞon of predicted probabilities of bee–flower interactions were positively correlated with observed species richness (r = 0.50), diversity (r = 0.48) and abundance (r = 0.42) of wild bees interacting with plant species within sites
Our findings show that the MetaComNet framework can be a useful approach for making spatially explicit predictions and mapping plant–pollinator interactions
Summary
Nine of every 10 species of flowering plants rely on interactions, mainly with insects, for cross-pollination (Ollerton et al, 2011). Most approaches to modelling plant–pollinator interactions in heterogeneous landscapes have focused on network properties, such as modularity (reviewed in Pellissier et al, 2018), but these properties may not fully encapsulate the underlying community assembly processes (Olito & Fox, 2015). An alternative approach is to model pairwise plant–pollinator interactions directly, and to derive network properties by aggregating model predictions (Graham & Weinstein, 2018), for instance by including plant and pollinator abundances, traits and phylogenies (e.g. Benadi et al, in press; Pichler et al, 2020; Stock et al, 2021). We therfore hypothesise that the number of pairwise interactions between plants and pollinators can be effectively modelled as a function of plant and pollinator affiliations and of variables underlying pollinator community assembly at different spatial scales. We propose a conceptual framework to make spatial predictions of pairwise interactions between plants and pollinators, which we refer to as ‘MetaComNet’ because it aims at linking meta-community structuring factors to the structure of ecological networks
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
