## knops_2018b
library(data.table)
dataset_id <- 'knops_2018b'
load(file = 'data/raw data/knops_2018b/ddata')
setDT(ddata)
setnames(ddata, c('Year','Plot'), c('year','site'))
ddata <- melt(ddata, id.vars = 1:6, variable.name = 'species', value.name = 'value')
ddata <- ddata[value > 0][order(year, site, species)]
ddata[, ':='(treatment = paste0(
fifelse(Fencing == 1, 'Ex', ''),
fifelse(Fertilization > 0, paste0('Fe', Fertilization), ''),
fifelse(Burning == 1, 'Bu', '')
)
)][,
treatment := fifelse(treatment == '', 'control', treatment)
]
# community
ddata[, effort := Trapnights / min(Trapnights)]
ddata[,
':='(N = sum(value) / effort,
ENSPIE = vegan::diversity(x = value, index = 'invsimpson')
),
by = .(year, site)
]
ddata[, S := vegan::rarefy(value, sample = round(sum(value) / effort), 0), by = .(year, site)]
# Sn
ddata[, minN := round(min(N), 0), by = .(site, treatment)] # 0% minN < 6
ddata[, Sn := vegan::rarefy(value, sample = minN), by = .(site, treatment, year)]
ddata[, ':='(
singletons = sum(value == 1),
doubletons = sum(value == 2)
), by = .(site, treatment, year)
][,
coverage := fifelse(
doubletons > 0,
1 - (singletons/N) * (((N - 1)*singletons)/((N - 1)*singletons + 2*doubletons)),
1 - (singletons/N) * (((N - 1)*singletons)/((N - 1)*singletons + 2))
)][, ':='(singletons = NULL, doubletons = NULL)]
ddata[,
':='( dataset_id = dataset_id,
treatment_type = 'prairie management',
grain_m2 = NA,
grain_comment = "'4 traps were set in each plot, one per side of the inner 10 x 10 m sampling area.'",
design = paste0('A', fifelse(treatment == 'control', 'C', "I")),
timepoints = paste0('T', seq_along(unique(year))[match(year, sort(unique(year)))]),
time_since_disturbance = fifelse(treatment == 'control', NA_integer_,
as.integer(year) - 2000),
realm = 'terrestrial',
taxon = 'mammals',
comment = 'Block design with treatments being Ex (Exclosure meaning no grazing), Fe (fertilization (0 + 2 dosages)) and Bu (burning every other year). Effort is standardised by the smallest effort. N is standardised by the relative effort. S is the exected richness for N while Sn is the expected richness for minN.',
species = NULL,
value = NULL,
Fencing = NULL,
Fertilization = NULL,
Burning = NULL,
Trapnights = NULL
)]
ddata <- unique(ddata)
dir.create(paste0('data/wrangled data/', dataset_id), showWarnings = FALSE)
fwrite(ddata, paste0('data/wrangled data/', dataset_id, "/", dataset_id, '.csv'), row.names = FALSE)
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