Table 4.

Regression tree spatial model results.

Variables Tested and Model Type	Year	R2	Most important variables in model
All variables Regression Tree	All		Precip W17, W19
		48.24	Temp W35
	2004		Precip W29, W28
		70.95	Temp W28
	2005		Temp W33
		55.57	Precip W24, W26
	2006	67.22	Temp W35, W27
			Precip W19
	2007		Temp W17, W22
		61.63	Mean elevation
Weather variables only Regression Tree	All		Precip W17, W19
		48.24	Temp W35
	2004		Precip W28, W29
		68.67	Temp W28
	2005		Temp W33
		56.27	Precip W24, W26
	2006		Temp W35, W27
		67.99	Precip W19
	2007		Temp W17, W22
		61.16	Precip W15
Non-weather variables only Regression Tree	All	8.28	Impervious surface, % pre-40's housing, % 50's housing
	2004	47.41	Minimum elevation, Mean elevation, impervious surface
	2005	32.23	Maximum elevation, impervious surface, Human population
	2006	48.83	Maximum elevation, impervious surface, Human population
	2007	42.03	Maximum elevation, impervious surface, Human population

The R² value indicates the ability of random forests to predict mosquito infection in weeks 32 to 34. Also included are the most important variables from the models listed in order of importance. Results are divided according to which variables were included in the models.