Suppose you estimate a model of the price of corn as a function of precipitation. The model has an AR(1) serial autocorrelation error structure, which you account for by estimating feasible generalized least squares. You estimate the coefficient associated with the precipitation variable to be $-0.78$, which is statistically significant at a $95\%$ confidence level.

How would you interpret this marginal effect?