Plant-pollinator interactions that have high conservation value (i.e. keystone interactions) within and between land-use types
We assessed differences in interaction richness, uniqueness and strength among land-uses using GLMMs (Brooks et al. 2017). In these models, either interaction richness, uniqueness or strength was the response variable and land-use (categorical) was the fixed effect. We included sampling site identity as a random effect to account for the dependent data structure of multiple sites within land-use categories. We then compared interaction richness, uniqueness and strength among land-uses using pairwise least squared means contrasts in theemmeans package (Lenth 2018) and determined significance with false discovery rate (FDR) corrected P values (at α = 0.05) (Verhoeven et al. 2005). Finally, we tested the significance of each observed PDI value by comparison against a null distribution of 999 PDI values, for each pollen-insect interaction, generated by a null model (for which we give a brief description, see Vázquez et al. 2007 for further details). The null model algorithm we used randomized the total number of pollen-insect interactions occurring at each site, as observed in the original network, by first creating a binary matrix and then filling matrix cells according to the probability of a pollen-insect interaction occurring at a given site. Therefore, each pollen-insect interaction and site occurred at least once in each random network. Following this, the remaining pollen-insect occurrences at each site were distributed to the filled cells, thus maintaining the original network connectance. The combination of complementary network indices (richness, uniqueness and strength) allowed us to identify the importance of different land-uses for maintaining plant-pollinator interactions from both a qualitative and quantitative perspective.
All statistical analyses were conducted in R (v.3.6.0, R Core Team 2019).