[R-meta] standard error in predictive nonlinear meta-regression

Dear all,

Yesterday I could solve my question re SE in a nonlinear model following Phillip and Wolfgang?s great suggestions using the delta method. 

Now I need to compute SE for a linear meta-regression:

summary(ECMmeta <- rma(es, var, data=ecm ,control=list(stepadj=.5), mods= ~ 1 + MAP + MAT*CO2dif, knha=TRUE))

Model Results:

            estimate      se     tval    pval    ci.lb    ci.ub     
intrcpt       0.5754  0.1828   3.1481  0.0031   0.2057   0.9451   **
MAP           0.0002  0.0001   2.6648  0.0111   0.0000   0.0003    *
MAT          -0.0589  0.0179  -3.2842  0.0022  -0.0952  -0.0226   **
CO2dif       -0.0019  0.0007  -2.7384  0.0093  -0.0032  -0.0005   **
MAT:CO2dif    0.0002  0.0001   3.6366  0.0008   0.0001   0.0003  ***


How can I compute SE for a particular pixel with known MAP, MAT and CO2dif?
Thanks