Drivers of endophyte richness
To test the effects of host identity (i.e. host species), abiotic
variables (maximum and minimum temperatures, temperature standard
deviation, light intensity, relative humidity and soil moisture) and
biotic variables (tree basal area per BC, tree height and distance to
the forest edge) on ASV richness, GLMMs, with a Poisson distribution and
a log-link function were used (Zuur et al. , 2009). Interaction
terms between host identity and all abiotic and biotic variables were
fit within the model and BC identity was included in the model as a
random variable (McCulloch, 1997). Best subset modelling, based on the
lowest AIC-value, was used to assess which predictor variables from the
global model should be retained (Burnham and Anderson, 2002). The model
was overdispersed, therefore overdispersion was corrected by employing
the observation-level random effects approach (Lawson et al. ,
1999; Elston et al. , 2001). Marginal and conditional
R2-values were calculated (Nakagawa et al. ,
2017).