Table 1.
scale of tree cover measurement (km2) | linear model | GAM | |
---|---|---|---|
tree cover coefficient±s.e. | model R2 | tree cover coefficient±s.e. | |
9 | 0.36±0.063 | 0.64 | 0.19±0.068 |
25 | 0.40±0.069 | 0.64 | 0.22±0.076 |
49 | 0.45±0.073 | 0.65 | 0.26±0.081 |
81 | 0.50±0.076 | 0.66 | 0.30±0.086 |
121 | 0.54+0.078 | 0.66 | 0.34±0.090 |
225 | 0.58±0.081 | 0.67 | 0.37±0.097 |
361 | 0.62±0.083 | 0.67 | 0.41±0.103 |
625 | 0.66±0.087 | 0.67 | 0.46±0.112 |
1369 | 0.70±0.092 | 0.67 | 0.51±0.125a |
2401 | 0.70±0.097 | 0.67 | 0.50±0.136a |
5329 | 0.72±0.103 | 0.66 | 0.54±0.155 |
9409 | 0.77±0.109 | 0.66 | 0.62±0.173 |
At these two scales only, the optimal GAM suggested a nonlinear relationship between tree cover and rainfall (i.e. the estimated degrees of freedom for the tree cover parameter were greater than 1). However, EDFs did not greatly exceed 1, and models in which tree cover was included as a linear predictor did not have a significantly higher residual deviance than models which included the optimal smooth function of tree cover (F-test of deviance, p>0.05 in both cases). The coefficient from GAMs in which tree cover was included as a linear predictor is therefore shown for all scales.