Table 1 PSR richness GLM results for oomycetes (a), fungal pathogens (b), and fungal saprotrophs (c).

Subset of samples	Predictor variables	Estimate	p value
(a) Oomycetes
All samples	Disturbance	−0.022	0.389
	Disturbance × Mean annual precipitation	0.004	0.863
	Disturbance × Mean annual temperature	−0.036	0.183
Remnant samples only	Mean annual precipitation	0.033	0.046
	Mean annual temperature	−0.012	0.494
	Precipitation × Temperature	−0.03	0.233
Disturbed samples only	Mean annual precipitation	0.029	0.123
	Mean annual temperature	0.024	0.257
	Precipitation × Temperature	−0.002	0.951
(b) Fungal pathogens
All samples	Disturbance	−0.005	0.990
	Disturbance × Mean annual precipitation	0.645	0.080
	Disturbance × Mean annual temperature	−0.369	0.326
Remnant samples only	Mean annual precipitation	0.559	0.059
	Mean annual temperature	−0.386	0.199
	Precipitation × Temperature	0.990	0.017
Disturbed samples only	Mean annual precipitation	−0.094	0.620
	Mean annual temperature	−0.018	0.921
	Precipitation × Temperature	−0.282	0.412
(c) Fungal saprotrophs
All samples	Disturbance	−0.353	0.314
	Disturbance × Mean annual precipitation	0.366	0.291
	Disturbance × Mean annual temperature	−0.090	0.748
Remnant samples only	Mean annual precipitation	0.415	0.126
	Mean annual temperature	−0.524	0.035
	Precipitation × Temperature	1.033	0.001
Disturbed samples only	Mean annual precipitation	0.050	0.817
	Mean annual temperature	−0.444	0.001
	Precipitation × Temperature	−0.041	0.840

These tests are univariate tests including either the interaction of the predictor variable and disturbance (if across all sites), or only the predictor variable in determining PSR richness. Tests of all samples include a random effect of disturbance nested within site; tests of remnant or disturbed samples include a random effect of plot. The model distribution is poisson. All significant predictors are in bold.

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