Fig 1.
Dynamic changes in community composition and species traits, as shown by nonmetric multidimensional scaling (NMDS) of plant (a), pollinator (b) community composition, pairwise interactions (c), plant traits (d), and pollinator traits (e) in each month. Different colors indicated the different months. The closer the two points are, the more similar they are. The smaller the points are, the better the goodness of fit are.
Fig 2.
Comparison between observed and predicted structure parameters (estimate ± 95% confidence intervals) for the monthly and yearly networks.
RSA, ST, and RSA & ST indicate the predicted pollination network based on the relative species abundance, species traits, and both, respectively. Nevertheless, the predicted network was based on RSA only in 2016 (a), where the black and red circles indicate the observed and predicted values, respectively, and the circles in the shaded and light areas are for “nestedness” and “weighted NODF”, respectively. For the other panels of 2017, the black and red circles, as well as the black and red lines, indicate the predicted “nestedness” and “weighted NODF”, respectively.
Table 1.
The dynamic pollination network metrics (Nestedness and Weighted NODF) of both observed networks and predicted networks based on relative species abundance in each month and each year of 2016 and 2017.
Table 2.
Results of likelihood analyses showing whether relative species abundance (RSA), species traits, or their combination (Species traits & RSA), is a good indicator for pairwise interaction.
Fig 3.
The linear regression between observed and predicted interaction frequency based on the relative species abundance.
The solid lines show the fit of a quadratic model and the 95% confidence interval.