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. Author manuscript; available in PMC: 2018 Sep 13.
Published in final edited form as: Folia Geobot. 2017 Mar;52(1):83–99. doi: 10.1007/s12224-016-9281-9

Table 1.

Results of likelihood-ratio test generalized linear mixed models (GLMM) which compared the full models to the reduced ones by the particular factors. Sampling plots nested within compartment were used as random variable. Response variable of: GLMM1 was herb cover, GLMM2 total species richness, GLMM3 species richness of short-lived species and GLMM4 species richness of long-lived species.

model combination Df AIC LRT Pr(Chi)
GLMM 1 full model 121.8
year 3 152.4 36.6 <0.001
treatment 2 130.8 12.9 0.002
tree species 1 157.9 38.0 <0.001
full model 18.6
year : treatment : tree species 6 23.7 17.1 0.009

GLMM 2 full model 832.8
year 3 835.4 8.6 0.035
treatment 2 837.5 8.6 0.013
tree 1 835.7 4.9 0.028
full model 810.2
year 3 812.7 8.6 0.035
treatment : tree species 2 832.8 26.7 <0.001

GLMM 3 full model 718.6
year 3 726.6 14.0 0.003
treatment 2 722.0 7.4 0.025
tree species 1 725.2 8.5 0.003
full model 573.7
year 3 568.1 0.4 0.939
treatment : tree species 2 582.8 13.0 0.001

GLMM 4 full model 743.9
year 3 751.9 14.0 0.003
treatment 2 749.4 9.4 0.009
tree species 1 770.6 28.6 <0.001
full model 692.3
year 3 700.22 14.0 0.003
treatment : tree species 2 718.63 30.4 <0.001