Thanks for including some code. Next time it would help to have some data and the code in the form of FAQ: What's a reproducible example (`reprex`) and how do I do one?
Here's a solution, assuming your data set is in the form of norw015
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
> library(tibble)
> library(treeclim)
Loading required package: Rcpp
> data(norw015)
> head(norw015)
xxxstd samp.depth
1600 0.6317956 1
1601 0.3966429 1
1602 0.3718675 1
1603 0.4002325 1
1604 0.3752488 1
1605 0.5385194 1
> norw <- rownames_to_column(norw015, var = "year")
> head(norw)
year xxxstd samp.depth
1 1600 0.6317956 1
2 1601 0.3966429 1
3 1602 0.3718675 1
4 1603 0.4002325 1
5 1604 0.3752488 1
6 1605 0.5385194 1
> norw_years <- norw %>% filter(year > 1935)
> head(norw_years)
year xxxstd samp.depth
1 1936 0.9608494 34
2 1937 1.0050585 34
3 1938 0.9518574 34
4 1939 0.9265154 34
5 1940 0.8521800 34
6 1941 1.2747496 34
> norw_36 <- column_to_rownames(norw_years, var = 'year')
> head(norw_36)
xxxstd samp.depth
1936 0.9608494 34
1937 1.0050585 34
1938 0.9518574 34
1939 0.9265154 34
1940 0.8521800 34
1941 1.2747496 34