Table 2: Open in new tab Generalized...

Table 2:

Generalized linear mixed-effect models (GLMMs) results for biomass production as a function of elevation, warming and nitrogen addition

Model	k	LL	AIC_c	ΔAIC_c	wAIC_c	$R_{m}^{2}$
E	5	−386.050	783.009	0.000	0.843	13.64%
1	3	−390.654	787.660	4.651	0.082	0.00%
N	4	−390.088	788.773	5.764	0.047	2.02%
W	4	−390.644	789.885	6.876	0.027	0.04%

Model	k	LL	AIC_c	ΔAIC_c	wAIC_c	$R_{m}^{2}$
E	5	−386.050	783.009	0.000	0.843	13.64%
1	3	−390.654	787.660	4.651	0.082	0.00%
N	4	−390.088	788.773	5.764	0.047	2.02%
W	4	−390.644	789.885	6.876	0.027	0.04%

Notes: Fixed effects are elevation (E: 2700, 3200 and 3400 m), experimental warming (W: Control and Warming), nitrogen addition (N: Control and Nitrogen addition) and their interactions. Random effects are experimental blocks. Shown are maximum log-likelihood (LL), the estimated number of model parameters (k), the information-theoretic Akaike’s information criterion corrected for small samples (AIC_c), the change in AIC_c relative to the top-ranked model (ΔAIC_c), AIC_c weighted (wAIC_c = model probability) and the marginal variance explained (⁠ $R_{m}^{2}$ ⁠) as a measure of the model’s goodness-of-fit.

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