Table 1. Soil effects on OTU richness and Shannon diversity.

The importance of soil properties differed between taxon, substrate and diversity metrics. Carbon content and pH were important in most of the cases. The table shows the coefficients of each predictor in four Bayesian general multivariate regression model using Stochastic Partial Differential Equations (SPDE) that explicitly consider spatial correlation, modelling OTU richness and effective number of OTUs dependent on soil properties for eukaryotes and prokaryotes in litter and soil, respectively. As the organic carbon content and pH are important variables for soil biota, we use them as independent variables. Bold indicates important predictor variables (credible intervals not crossing zero).

			OTU richness			Effective number of OTUs
Taxon	Substrate	Predictor	Mean	0.025 quantile	0.975 quantile	Mean	0.025 quantile	0.975 quantile
Prokaryotes	Soil	Intercept	6.14	2.31	9.95	6.07	2.03	10.43
		pH	0.22	0.16	0.27	0.22	0.17	0.27
		Carbon	−0.13	−0.19	−0.08	−0.15	−0.20	−0.10
		Chemical	−0.08	−0.14	−0.02	−0.08	−0.14	−0.02
		Physical	0.02	0.00	0.04	0.02	−0.01	0.04
	Litter	Intercept	4.14	−4.78	12.65	5.04	−3.97	13.71
		pH	0.03	−0.03	0.08	0.05	0.00	0.10
		Carbon	−0.23	−0.28	−0.17	−0.21	−0.26	−0.16
		Chemical	−0.07	−0.12	−0.01	−0.05	−0.11	0.01
		Physical	0.13	0.10	0.15	0.12	0.10	0.15
Eukaryotes	Soil	Intercept	3.28	−7.36	13.39	3.22	−6.49	13.22
		pH	0.30	0.22	0.38	0.33	0.25	0.41
		Carbon	−0.36	−0.46	−0.26	−0.36	−0.46	−0.27
		Chemical	−0.08	−0.20	0.04	−0.05	−0.17	0.06
		Physical	0.11	0.07	0.15	0.10	0.07	0.14
	Litter	Intercept	4.93	−10.81	19.82	6.07	−10.14	21.34
		pH	0.24	0.15	0.34	0.26	0.16	0.35
		Carbon	−0.22	−0.32	−0.13	−0.23	−0.32	−0.14
		Chemical	−0.01	−0.12	0.10	0.00	−0.10	0.11
		Physical	−0.14	−0.19	−0.09	−0.15	−0.20	−0.10