You can create decadal groups using the %/% (integer division) operator:
library(tidyverse)
# Fake data
set.seed(3)
d = tibble(year= 1931:2020,
SA = cumsum(rnorm(length(1931:2020), 0, 5)) + 50)
d
#> # A tibble: 90 x 2
#> year SA
#> <int> <dbl>
#> 1 1931 45.2
#> 2 1932 43.7
#> 3 1933 45.0
#> 4 1934 39.3
#> 5 1935 40.2
#> 6 1936 40.4
#> 7 1937 40.8
#> 8 1938 46.4
#> 9 1939 40.3
#> 10 1940 46.6
#> # … with 80 more rows
# Create decade groups
d = d %>%
mutate(decade = (year - 1) %/% 10) %>%
group_by(decade) %>%
mutate(decade = paste(range(year), collapse="-"))
d %>% print(n=15)
#> # A tibble: 90 x 3
#> # Groups: decade [9]
#> year SA decade
#> <int> <dbl> <chr>
#> 1 1931 45.2 1931-1940
#> 2 1932 43.7 1931-1940
#> 3 1933 45.0 1931-1940
#> 4 1934 39.3 1931-1940
#> 5 1935 40.2 1931-1940
#> 6 1936 40.4 1931-1940
#> 7 1937 40.8 1931-1940
#> 8 1938 46.4 1931-1940
#> 9 1939 40.3 1931-1940
#> 10 1940 46.6 1931-1940
#> 11 1941 42.9 1941-1950
#> 12 1942 37.3 1941-1950
#> 13 1943 33.7 1941-1950
#> 14 1944 34.9 1941-1950
#> 15 1945 35.7 1941-1950
#> # … with 75 more rows
# Summarise by decade
d %>% group_by(decade) %>% summarise(meanSA=mean(SA))
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 9 x 2
#> decade meanSA
#> <chr> <dbl>
#> 1 1931-1940 42.8
#> 2 1941-1950 34.0
#> 3 1951-1960 19.4
#> 4 1961-1970 31.6
#> 5 1971-1980 41.0
#> 6 1981-1990 24.1
#> 7 1991-2000 30.2
#> 8 2001-2010 41.8
#> 9 2011-2020 61.8
Created on 2020-10-27 by the reprex package (v0.3.0)