Table 6 Summary of the model selection procedure for functional diversity index of mammals
From: Diversity of plants and mammals as indicators of the effects of land management types in woodlands
int | x1 | x2 | x3 | x4 | k | log( | AIC | Δi | wi | R2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
−0.66 | 0.05 | − 0.04 | −0.11 | 5 | 107.05 | −202.90 | 0.00 | 0.19 | 0.14 | ||
−0.67 | 0.04 | −0.10 | 4 | 105.46 | −202.13 | 0.76 | 0.13 | 0.09 | |||
−0.67 | − 0.08 | 3 | 103.99 | −201.51 | 1.39 | 0.09 | 0.04 | ||||
−0.69 | 0.03 | 3 | 103.80 | −201.13 | 1.77 | 0.08 | 0.03 | ||||
−0.67 | − 0.03 | −0.08 | 4 | 104.89 | −200.99 | 1.91 | 0.07 | 0.07 | |||
−0.69 | 0.04 | −0.03 | 4 | 104.85 | −200.91 | 1.99 | 0.07 | 0.07 | |||
−0.69 | − 0.03 | 3 | 103.52 | −200.57 | 2.33 | 0.06 | 0.03 | ||||
−0.66 | 0.05 | −0.04 | 0.01 | −0.10 | 6 | 107.09 | −200.46 | 2.44 | 0.06 | 0.14 | |
−0.69 | 0.04 | −0.04 | 0.03 | 5 | 105.71 | −200.22 | 2.68 | 0.05 | 0.10 | ||
−0.69 | 0.02 | 3 | 103.26 | −200.06 | 2.84 | 0.05 | 0.01 | ||||
−0.69 | − 0.03 | 0.03 | 4 | 104.30 | −199.83 | 3.07 | 0.04 | 0.05 | |||
−0.66 | 0.04 | 0.00 | −0.10 | 5 | 105.46 | −199.73 | 3.17 | 0.04 | 0.09 | ||
−0.69 | 0.03 | 0.02 | 4 | 104.19 | −199.59 | 3.31 | 0.04 | 0.05 | |||
SW | 1.00 | 0.67 | 0.56 | 0.28 | 0.60 | ||||||
β | −0.67 | 0.04 | −0.04 | 0.02 | −0.10 | ||||||
SE | 0.03 | 0.02 | 0.02 | 0.03 | 0.05 | ||||||
)- Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log(
), AIC criterion, Δi = AICi– minAIC, Akaike weight (wi), and adjusted R2. Models are ordered in terms of Δi for AIC. At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x1 - DW in tree, x2 - DW on ground, x3 - DW Removed; categorical variable: x4 - land management type (protected area/grazed woodlands-intercept-))
), AIC criterion, Δi = AICi– minAIC, Akaike weight (wi), and adjusted R2. Models are ordered in terms of Δi for AIC. At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x1 - DW in tree, x2 - DW on ground, x3 - DW Removed; categorical variable: x4 - land management type (protected area/grazed woodlands-intercept-))