The influence of functional traits on CS
We obtained data on primate (body size; degree of frugivory and dietary
guild) and plant (fruit length and seed diameter) (Table S2) to test
whether they affect the magnitude of the CS, by characterizing each
interaction by its Procrustean residual. We accounted for the possible
influence of the sample size to control for sampling bias (Supplementary
Material S3).
Fruit length and seed diameter are traits that tend to be conserved
along the phylogenetic tree (Jordano 1995, Moles et al. 2005), thus we
used average values obtained for each plant genera as measures. We
tested the model for multicollinearity of the variables by using the
variance inflation factor (VIF). Multicollinearity occurs when two or
more predictors are correlated and provide redundant information about
the response. VIF values for body size was found to be high (VIF=8.39,
tolerance = 0.08), which were also correlated with model intercept
(0.9). Facing the likely confounding property of body size added to the
collinearity produced, we decided to suppress it from our model (see
explanation in Supplementary Material S3).
We
fitted
our final model with variables describing primate biology in terms of
the amount of fruit intake and functional role played according to
dietary category, such as the frugivory degree (percentage of the diet
that corresponds to fruit pulp, excluding seed predatory interactions)
and dietary guild (percentage of each food item in the diet). The former
adds information on the real amount of fruit pulp in diet, whereas the
latter informs about the effects of morphological variation resulting
from adaptations of the digestive tract (Hawes and Peres 2014), with
relevant consequences for the ability of seeds to germinate after being
defecated (Fuzessy et al. 2016). Our GLMM included then Procrustean
residuals as a response variable, primate species and plant genera as
random effects, and functional traits (frugivory degree and dietary
guilds for primates; fruit length and seed diameter for plants) as fixed
effects, using the
‘lmerTest’
package (Kuznetsova et al. 2017).