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Third traitstrap imputation trail #21

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Third traitstrap imputation trail #21

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3c0fcb1
Added a third try for trait imputatino with traitstrap. Trait_summari…
RagnhildGya Feb 14, 2022
385d90e
Remove treatment, and add month in the scale
RagnhildGya Feb 21, 2022
2787361
Remove code for old imputation trails
RagnhildGya Feb 23, 2022
2bb9b47
Comment out the install packages code so that this is only done when …
RagnhildGya Feb 23, 2022
1e74514
Adding a second bootstrapping to divide into control and burn treatment
RagnhildGya Feb 23, 2022
a6bedbc
Adding month in the select, and filtering by treatment
RagnhildGya Feb 23, 2022
ff61a3a
Adding the control and burnt to the rest of the functions to get the …
RagnhildGya Feb 23, 2022
63b302b
Summarizing both boostrappings, and merging them back togther.
RagnhildGya Feb 23, 2022
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77 changes: 48 additions & 29 deletions scripts/DA1_traitstrap.R
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Original file line number Diff line number Diff line change
Expand Up @@ -7,8 +7,8 @@ source(here::here(path = "scripts/0_data_import.R"))
### Packages----

# install.packages("remotes")
remotes::install_github("richardjtelford/traitstrap")
# library(traitstrap)
#remotes::install_github("richardjtelford/traitstrap")
library(traitstrap)

species %>%
select(taxon, cover, site, treatment, plot_id) %>%
Expand All @@ -17,15 +17,19 @@ species %>%

### Trait Imputation ----

trait_imputation =
# Bootstrapping of control datasets ----

trait_imputation_control =
trait_impute(
# input data (mandatory)
comm = species %>%
select(taxon, cover, site, treatment, plot_id) %>%
mutate(treatment = as.factor(treatment)),
select(taxon, cover, site, treatment, plot_id, year, season, month) %>%
mutate(treatment = as.factor(treatment)) %>%
filter(treatment == "C"),
traits = traits %>%
select(taxon, trait, value, site, treatment, plot_id) %>%
mutate(treatment = as.factor(treatment)),
select(taxon, trait, value, site, treatment, plot_id, year, season, month) %>%
mutate(treatment = as.factor(treatment)) %>%
filter(treatment == "C"),

# specifies columns in your data (mandatory)
abundance_col = "cover",
Expand All @@ -34,27 +38,26 @@ trait_imputation =
value_col = "value",

# specifies sampling hierarchy
scale_hierarchy = c("site", "plot_id"),

# specifying experimental design
treatment_col = "treatment",
treatment_level = "site",
scale_hierarchy = c("year", "season", "month","site", "plot_id"),


# min number of samples
min_n_in_sample = 3
)

# no experimental design
# Bootstrapping of burnt datasets ----

trait_imputation_2 =
trait_imputation_burnt =
trait_impute(
# input data (mandatory)
comm = species %>%
select(taxon, cover, site, treatment, plot_id) %>%
mutate(treatment = as.factor(treatment)),
select(taxon, cover, site, treatment, plot_id, year, season, month) %>%
mutate(treatment = as.factor(treatment)) %>%
filter(treatment == "NB"),
traits = traits %>%
select(taxon, trait, value, site, treatment, plot_id) %>%
mutate(treatment = as.factor(treatment)),
select(taxon, trait, value, site, treatment, plot_id, year, season, month) %>%
mutate(treatment = as.factor(treatment)) %>%
filter(treatment == "NB"),

# specifies columns in your data (mandatory)
abundance_col = "cover",
Expand All @@ -63,32 +66,48 @@ trait_imputation_2 =
value_col = "value",

# specifies sampling hierarchy
scale_hierarchy = c("site", "treatment", "plot_id"),
scale_hierarchy = c("year", "season", "month","site", "plot_id"),


# min number of samples
min_n_in_sample = 3
)

# Nonparametric Bootstrapping ----

bootstrapped_moments =
bootstrapped_moments_control =
trait_np_bootstrap(
trait_imputation_control,
nrep = 200
)

bootstrapped_moments_burnt =
trait_np_bootstrap(
trait_imputation,
trait_imputation_burnt,
nrep = 200
)


# Summarise Bootstrapping Output ----
# Summarize Bootstrapping Output ----

sum_boot_moment_control <- trait_summarise_boot_moments(bootstrapped_moments_control) %>%
mutate(treatment = "C")

sum_boot_moment_burnt <- trait_summarise_boot_moments(bootstrapped_moments_burnt) %>%
mutate(treatment = "NB")

# Merge bootstrapped data sets ----

sum_boot_moments_full <- sum_boot_moment_control %>%
bind_rows(sum_boot_moment_burnt)

sum_boot_moment <- trait_summarise_boot_moments(
np_bootstrapped_moments
)
sum_boot_moment

# Some 'random' plots ----

autoplot(trait_imputation) +
autoplot(trait_imputation_control) +
theme(axis.text.x = element_text(size = 8, angle = 90, vjust = 0.5))

autoplot(trait_imputation_burnt) +
theme(axis.text.x = element_text(size = 8, angle = 90, vjust = 0.5))

autoplot(trait_imputation_2) +
theme(axis.text.x = element_text(size = 8, angle = 90, vjust = 0.5))
sum_boot_moments_full %>% ggplot(aes(x = treatment, y = mean, fill = treatment)) + geom_boxplot() + facet_grid(trait ~ site, scales = "free")