https://github.com/tom-n-walker/uphill-plants-soil-carbon
Tip revision: 951e73295060ad88bddf5d48a3aa4b9d90475312 authored by Tom Walker on 07 September 2021, 14:32:36 UTC
Merge branch 'main' of github.com:tom-n-walker/uphill-plants-soil-carbon into main
Merge branch 'main' of github.com:tom-n-walker/uphill-plants-soil-carbon into main
Tip revision: 951e732
summarise_cover.R
################################################################################
#### 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)
}