gpkg <- unique(rslt$gpkg)
print(gpkg)
## [1] "MV_Hartola" "MV_Kitee" "MV_Korsnas" "MV_Parikkala"
## [5] "MV_Pori" "MV_Pyhtaa" "MV_Raasepori" "MV_Simo"
## [9] "MV_Vaala" "MV_Voyri"
All simulated branching_groups must be listed in the file /params/regimes.csv !! Based on this the regime names are merged to the results.
## [1] NA
## [2] "Selection cut_1"
## [3] "Selection cut_2"
## [4] "Selection cut_3"
## [5] "Selection cut_4"
## [6] "Tapio thinning"
## [7] "Tapio thinning nature"
## [8] "Short rotation thinning 5"
## [9] "Long rotation thinning 5"
## [10] "Long rotation thinning 10"
## [11] "Long rotation thinning 15"
## [12] "Long rotation thinning 30"
## [13] "Tapio harvest without thinnings -20"
## [14] "Short rotation harvest 5"
## [15] "Tapio harvest"
## [16] "Tapio harvest nature scene"
## [17] "Tapio harvest without thinnings"
## [18] "Long rotation harvest 5"
## [19] "Long rotation harvest 10"
## [20] "Tapio harvest without thinnings 10"
## [21] "Long rotation harvest 15"
## [22] "Long rotation harvest 30"
stands <- rslt %>%
group_by(gpkg) %>%
summarise(simulated_stands = n_distinct(id),
min_stand_size = min(AREA),
max_stand_size = max(AREA),
mean_size = mean(AREA))
kable(stands) %>% kable_styling()
gpkg | simulated_stands | min_stand_size | max_stand_size | mean_size |
---|---|---|---|---|
MV_Hartola | 5 | 0.771 | 2.467 | 1.5679802 |
MV_Kitee | 5 | 0.496 | 2.404 | 1.1994000 |
MV_Korsnas | 5 | 0.289 | 4.861 | 2.0297640 |
MV_Parikkala | 5 | 0.152 | 1.200 | 0.8710000 |
MV_Pori | 5 | 0.112 | 0.637 | 0.3596000 |
MV_Pyhtaa | 5 | 0.498 | 2.448 | 1.2284896 |
MV_Raasepori | 5 | 0.068 | 1.784 | 0.2184878 |
MV_Simo | 5 | 0.141 | 4.792 | 2.6578507 |
MV_Vaala | 5 | 0.454 | 4.682 | 3.0449601 |
MV_Voyri | 5 | 0.355 | 1.238 | 0.6504268 |
meanV <- rslt[rslt$regime %in% c("BAU", "SA", "CCF_1") , ] %>%
group_by(year, regime, gpkg) %>%
summarise(meanV = mean(V)) %>%
ggplot(aes(year, meanV)) +
geom_line( aes(color = regime)) +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks=c(2016, 2026, 2036, 2046, 2056, 2066, 2076, 2086, 2096, 2106)) +
facet_wrap(. ~gpkg)
plot(meanV)
Cash flow = The sum of all revenues and costs for a specific forest stand
meanCash <- rslt[rslt$regime %in% c("BAU", "SA", "CCF_1") , ] %>%
group_by(year, regime, gpkg) %>%
mutate(cash_flow = ifelse(is.na(cash_flow), 0, cash_flow)) %>%
summarise(meanCash = mean(cash_flow), na.rm = TRUE) %>%
ggplot(aes(year, meanCash)) +
geom_line( aes(color = regime)) +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks=c(2016, 2026, 2036, 2046, 2056, 2066, 2076, 2086, 2096, 2106)) +
facet_wrap(. ~gpkg)
plot(meanCash)