## bateman_2018
library(data.table)
dataset_id <- 'bateman_2018'
load(file = 'data/raw data/bateman_2018/ddata')
setDT(ddata)
setnames(ddata, old = c('reach', 'site_code','common_name','bird_count','survey_date'),
new = c('site', 'block', 'species','value','date'))
ddata[, ':='(year = as.integer(format(date, '%Y')),
month = as.integer(format(date, '%m')))]
# Selecting surveys between January and May, excluding 2018 which has only January
ddata <- ddata[ year != 2018 & month <= 5]
ddata[is.na(value), value := 1]
# Community
ddata[, ':='(N = sum(value),
S = length(unique(species)),
ENSPIE = vegan::diversity(x = value, index = 'invsimpson')
),
by = .(site, block, year, date)
]
ddata[, minN := min(N), by = .(site, block)] # 0% minN < 6
ddata[, Sn := vegan::rarefy(value, sample = minN), by = .(site, block, year, date)]
ddata[, ':='(
singletons = sum(value == 1),
doubletons = sum(value == 2)
), by = .(site, block, year, date)
][,
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 <- ddata[,
lapply(.SD, mean),
by = .(site, block, year),
.SDcols = c('N','minN','S','Sn','ENSPIE','coverage')
]
ddata[, ':='(
dataset_id = dataset_id,
treatment = fifelse(site %in% c('Ave35','Ave67','Price','Priest'), 'urban_notRestored',
fifelse(site %in% c('BM','Rio'), 'urban_restored',
'notUrban_notRestored')
),
treatment_type = 'riverbank vegetation restoration',
grain_m2 = pi*30^2,
grain_comment = "listening point of 30m radius - estimated",
timepoints = paste0('T', seq_along(unique(year))[match(year, sort(unique(year)))]),
time_since_disturbance = fifelse(site == 'BM', year - 2012,
fifelse(site == 'Rio', year - 2005, NA_integer_)
),
realm = 'terrestrial',
taxon = 'birds',
comment = 'Some restored and some unrestored sites along the Salt river. Each station was surveyed several times a year (2 to 9). Abundances are summed per year and divided by the number of sampling events. One listening point (30m radius circle) per site per survey.'
)
][, design := paste0('A', fifelse(treatment == "urban_restored", 'I', 'C'))]
dir.create(paste0('data/wrangled data/', dataset_id), showWarnings = FALSE)
fwrite(ddata, paste0('data/wrangled data/', dataset_id, '/', dataset_id, '.csv'), row.names=FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.