Specific results from mixed models fit with lme

I feel like this is a simple and stupid question but I cannot seem to find an answer that works.

How do I calculate specific statistical results in a mixed model analysis with 'lme()'?

Data:

year Plot SeedingDate Rep Treat CalDays
2017 11 Sep 1 Controlled 161
2017 12 Sep 1 Deep Fraze 35
2017 13 Sep 1 Verticut 161
2017 14 Sep 1 Less Fraze 84
2017 15 Sep 1 Scalped 63
2017 21 Sep 2 Less Fraze 63
2017 22 Sep 2 Deep Fraze 49
2017 23 Sep 2 Verticut 84
2017 24 Sep 2 Scalped 84
2017 25 Sep 2 Controlled 84
2017 31 Sep 3 Scalped 35

Code:
library(nlme)
setwd("/Users/mc1499/Documents/Thesis Measurements/2017 & 2018 Fall/GDD Rye")
dat<-read.csv("GDD Rye CSV.csv")
block<-as.factor(dat$Rep)
trt<-as.factor(dat$Treat)
seeddate<-as.factor(dat$SeedingDate)
yr<-as.factor(dat$year)

DIA0WAS<-lme(CalDays ~ Treat*SeedingDate,random = ~1|year/Rep,data=dat)
anova(DIA0WAS)

I am trying to graph my data and the program needs either % critical value or standard deviation, but anova does not give me those.
What code can I use to get that from my data?