A different combination of five weather variables gave a highly significant of 

 0.74 when correlated with total production of forbs. The five independent variables in 

 this case were: X3, May precipitation; X5, solar radiation in June; Xg, maximum air 

 temperature (°F.) in June; X^Qj minimum air temperature (°F.) in June; and Xi2j maximum 

 temperature (°F.) of shaded soil surface in June. Total forb production (Y2) can be 

 estimated with a standard error of estimate of 93 lb. /acre (mean production = 590 

 lb. /acre) using the following equation: 



Y2 = 1,039 + 95.2X3 + 2.29X5 - 55.6X5 + 70.6X10 - 18.2X12- " 



Equations developed for predicting total production of graminoids were considerably 

 less precise than those used to predict production of either total vegetation or total 

 forbs. To predict total graminoid production, a combination of four weather measure- 

 ments was superior to any combination of five tested. The following four independent 

 variables gave a significant value of 0.52: X3, May precipitation; X7, maximum air 

 temperature (°F.) in July; X15, wind velocity in June; and X15, in July. The equation 

 derived for predicting total graminoid production (Y3) from these four variables has a 

 standard error of estimate of 60 lb. /acre (mean production = 439 lb. /acre): 



Y3 = -415 + 103X3 + 6.91X7 + 64.7Xi5 - 4I.OX16. 



The correlation coefficients and regression equations examined in this paper are 

 based upon rather tenuous data for meaningful regression analyses. However, they do 

 give some indication of which weather variables may be influential in determining the 

 large yearly variations in herbage production on these mountain grassland ranges. 



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