How biased is our perception of plant-pollinator networks? A comparison of visit- and pollen-based representations of the same networks

Abstract

Most plant-pollinator networks are based on observations of contact between an insect and a flower in the field. Despite significant sampling efforts, some links are easier to report, while others remain unobserved. Therefore, visit-based networks represent a subsample of possible interactions in which the ignored part is variable. Pollen is a natural marker of insect visits to flowers. The identification of pollen found on insect bodies can be used as an alternative method to study plant-pollinator interactions, with a potentially lower risk of bias than the observation of visits, since it increases the number of interactions in the network. Here we compare plant-pollinator networks constructed (i) from direct observation of pollinator visits and (ii) from identification of pollen found on the same insects. We focused on three calcareous grasslands in France, with different plant and pollinator species diversities. Since pollen identification always yields richer, more connected networks, we focused our comparisons on sampling bias at equal network connectance. To do so, we first compared network structures with an analysis of latent blocks and motifs. We then compared species roles between both types of networks with an analysis of specialization and species positions within motifs. Our results suggest that the sampling from observations of insect visits does not lead to the construction of a network intrinsically different from the one obtained using pollen found on insect bodies, at least when field sampling strives to be exhaustive. Most of the significant differences are found at the species level, not at the network structure level, with singleton species accounting for a respectable fraction of these differences. Overall, this suggests that recording plant-pollinator interactions from pollinator visit observation does not provide a biased picture of the network structure, regardless of species richness; however, it provided less information on species roles than the pollen-based network.

Plant‐centred sampling estimates higher beta diversity of interactions than pollinator‐based sampling across habitats

“…This was performed instead of counting the number of pollen grains on the pollinator’s body, as different plant species vary greatly in the amount of pollen produced and on how the pollen grains stick to the body of the flower visitor (e.g. presence of pollenkitt), rendering such counts less informative (Maglianesi et al ., 2015; Sazatornil et al ., 2016; Ramírez‐Burbano et al ., 2017; de Manincor et al ., 2020).…”

Plant-centred sampling estimates higher dissimilarity of interactions than pollinator-based sampling across habitats

“…This was done instead of counting the number of pollen grains on pollinators body as different plant species vary greatly in the amount of pollen produced and on how the pollen grains stick to the body of the flower visitor (e.g. presence of pollenkitt), rendering such counts less informative (Maglianesi et al 2015;Sazatornil et al 2016;Ramírez-Burbano et al 2017;Manincor et al 2020).…”

“…Although pollen data do not always lead to higher estimates of interaction partitioning in pollination networks (Ramirez-Burbano et al 2017;Manincor et al 2020), there is a trend that subsequently calibrating interaction data with "better" estimates of potential pollination, i.e. pollen loads, pollen deposition on stigma and fruit set, will increasingly render only the subsets of interactions constrained by specific coadaptations and higher estimates of interaction specialization (Bosch et al 2009;Santiago-Hernandez et al 2019;Zhao et al 2019).…”

Molecular Assays of Pollen Use Consistently Reflect Pollinator Visitation Patterns in a System of Flowering Plants

“…This is because understanding resource use among mutualists is fundamental to determining the extent to which they rely on each other for population persistence (Roulston and Goodell 2011), support ecosystem functioning (Lucas et al 2018), and mediate interspecific competition and coexistence (Johnson 2019). Two standard approaches for understanding pollination ecology in natural systems are building networks of species interactions using observations of contact between plants and pollinators, and making inferences about plant-pollinator interactions using observations of pollinator foraging behavior (Godoy et al 2018, Manincor et al 2020). Building networks and analyzing their topologies has been a reliable toolkit for illuminating how the community assembly of mutualistic actors operates across space and time (e.g.…”