If you redefine your NAs as below to be detected as some arbitrary large
number, then the code should work through. Any 5's left in your dataset can
be replaced just as easily by NAs again. Not elegant, but effective.
site <- c("s1", "s1", "s1", "s2","s2", "s2")
pref <- c(1, 2, 3, 1, 2, 3)
R1 <- c(NA, NA, 1, NA,NA,NA)
R2 <- c(NA, 0, 1, 1, NA, 1)
R3 <- c(NA, 1, 1, NA, 1, 1)
R4 <- c(0, NA, 0, 1, NA, 0)
R5 <- c(NA, 0, 1, NA, 1, 1)
datum <- data.frame(site, pref, R1, R2, R3, R4, R5)
## For 1 column;
datum$R1[is.na(datum$R1)==T]<-5
tapply(datum$R1, datum$site, min, na.rm=T)
## Can loop this over all columns;
new<-matrix(0,5,2)
for (i in 3:7)
{datum[,i][is.na(datum[,i])==T]<-5
new[i-2,]<-tapply(datum[,i], datum$site, min, na.rm=T)}
--
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