Table 4. Multiple regression spatial mixed models of the slopes of SARs (a) with, and (b) without species richness as a predictor. All predictor variables, except the rate of increase in habitat heterogeneity, are measured at the 10km scale. Model fit is measured by Akaike Information Criteria (AIC), and here we report ΔAIC values, i.e. the difference between the focal modelís AIC and that of the best fitting model (that with the smallest AIC). Model weights are provided in brackets and represent the probability that the model provides the best fit to the data out of those created. We provide each best fitting model until a cumulative model weight of 0.9 is achieved and this set of models represents the best candidate set of models (Johnson and Omland 2004). Parameter estimates for the intercept and predictor variables are provided. Note that r2 values cannot be calculated from these spatial models, but are reported for non-spatial equivalents solely to give an indication of explanatory power. We provide both the model r2 value and partial r2 values for each predictor, the latter being in square brackets.

  


(a)
response intercept species
richness
summer temp annual NDVI rate of increase in habitat diversity Δ AIC
(model weight)
model
r2
z - from power SAR 0.299 -0.002 [0.62] -0.002 [0.01] -0.032 [0.03] 0.0 (0.89) 0.893
" 0.306 -0.002 [0.62] -0.003 [0.02] -0.007 [0.03] -0.003 [0.010] 5.0 (0.08) 0.899
m - from semi-log SAR 25.402 -0.111 [0.58] -0.076 [0.03] -0.891 [0.002] 0.0 (0.70) 0.889
" 25.273 -0.111 [0.57] -0.068 [0.03] -0.878 [0.004] +0.057 [0.002] 2.5 (0.20) 0.891

  
(b)
response intercept summer temp annual NDVI rate of increase in habitat diversity log10 human density Δ AIC
(model weight)
model
r2
z - from power SAR 0.308 -0.012 [0.152] -0.054 [0.025] +0.032 [0.011] 0.0 (0.91) 0.284
m - from semi-log SAR 26.347 -0.832 [0.183] -2.118 [0.013] +2.413 [0.018] 0.0 (0.76) 0.325
" 26.541 -0.856 [0.048] -2.051 [0.014] +2.465 [0.010] -0.057 [0.007] 2.8 (0.19) 0.332