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).