https://github.com/tom-n-walker/uphill-plants-soil-carbon
Tip revision: 05e1672664e587a3808d326d6f78d29ca5e44c01 authored by Tom Walker on 07 September 2021, 14:31:53 UTC
Added all analyses, streamlined pipelines and improved statistical models. Removed data export (all done via drake cache).
Added all analyses, streamlined pipelines and improved statistical models. Removed data export (all done via drake cache).
Tip revision: 05e1672
summarise_cover.R
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#### Project: Lowland plant migrations alpine soil C loss
#### Title: Function | Summarise cover at plot level
#### Author: Tom Walker (thomas.walker@usys.ethz.ch)
#### Date: 26 May 2021
#### ---------------------------------------------------------------------------
summarise_cover <- function(raw_relevees, named){
# summarise cover by site, grid_id, species
sum_cover <- named %>%
group_by(site, grid_id, accepted_name) %>%
summarize(total_cover = sum(total_cover)) %>%
mutate(accepted_name = make.names(accepted_name)) %>%
ungroup
# group by site, nest, map for cover, treatments
allCover <- sum_cover %>%
group_by(site) %>%
nest %>%
# pivot data wider and replace missing with zeros
mutate(all_cover = map(data, pivot_wider, "grid_id", "accepted_name", values_from = "total_cover")) %>%
mutate(all_cover = map(all_cover, function(x) replace(x, is.na(x), 0))) %>%
mutate(treatments = map(all_cover, ~join_treats(., raw_relevees$collars))) %>%
mutate(all_cover = map(all_cover, ~select(., -grid_id)))
# map for focal ID
allCover$focals <- list(
select_focals(raw_relevees$focals, "calanda"),
select_focals(raw_relevees$focals, "lavey")
)
# map for focal/bkgnd cover, rel_abund all covers, biomass
allCover <- allCover %>%
# get focal cover and summarise at group level
mutate(focal_cover = map2(all_cover, focals, subset_focals)) %>%
mutate(group_cover = map2(all_cover, focal_cover, biomass)) %>%
# remove unknown, bare ground and moss from background community
mutate(all_cover = map(all_cover, function(x) select(x, -bare.ground, -mosses, -unknown))) %>%
# subset for background cover
mutate(bkgnd_cover = map2(all_cover, focals, subset_bckgnd)) %>%
# recalculate as relative abundances
mutate(focal_ra = map(focal_cover, ra_t_df)) %>%
mutate(bkgnd_ra = map(bkgnd_cover, ra_t_df)) %>%
mutate(all_ra = map(all_cover, ra_t_df))
# subset for columns of interest
out <- allCover %>%
select(site, treatments,
all_cover, focal_cover, bkgnd_cover, group_cover,
all_ra, focal_ra, bkgnd_ra)
# return
return(out)
}