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get_data_shortgrass_steppe.R
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get_data_shortgrass_steppe.R
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#' @title get Shortgrass Steppe rodent data
#'
#' @inheritParams get_mtquad_data
#' @return list of abundance, covariates, and metadata
#'
#' @export
get_sgs_data <- function(path = file.path(get_default_data_path(),
"shortgrass-steppe-lter"))
{
data_tables <- import_retriever_data(path = path)
sgs_data <- data_tables$shortgrass_steppe_lter_shortgrass_data
# select key columns
# filter out unknown species and recaptures
sgs_data <- sgs_data %>%
dplyr::select_at(c("session", "year", "veg", "web", "spp")) %>%
dplyr::filter(.data$spp != "NA",
.data$spp != "")
# get data into wide format
# summarize counts for each species in each period
sgs_abundance <- sgs_data %>%
dplyr::count(.data$year, .data$session, .data$spp) %>%
tidyr::spread(key = .data$spp, value = .data$n, fill = 0)
season <- rep(0, nrow(sgs_abundance))
season[grepl("Sep", sgs_abundance$session)] <- 0.5
sgs_abundance$samples <- sgs_abundance$year + season
# split into two dataframes and save
abundance <- dplyr::select_at(sgs_abundance, dplyr::vars(-c("year", "session", "samples")))
covariates <- dplyr::select_at(sgs_abundance, c("year", "session", "samples"))
species_table = tibble::tibble(id = c("CHHI",
"DIOR",
"MIOC",
"MUMU",
"ONLE",
"PEFL",
"PEMA",
"REME",
"REMO",
"SPTR",
"SYAU",
"THTA"),
genus = c("Chaetodipus",
"Dipodomys",
"Microtus",
"Mus",
"Onychomys",
"Perognathus",
"Peromyscus",
"Reithrodontomys",
"Reithrodontomys",
"Spermophilus",
"Sylvilagus",
"Thomomys"),
species = c("hispidus",
"ordii",
"ochrogaster",
"musculus",
"leucogaster",
"flavus",
"maniculatus",
"megalotis",
"montanus",
"tridecemlineatus",
"auduboni",
"talpoides"))
metadata <- list(timename = "samples", effort = NULL, period = 0.5,
species_table = species_table,
is_community = TRUE,
location = c("latitude" = 40 + 49/60,
"longitude" = -(104 + 46/60)))
out <- list("abundance" = abundance,
"covariates" = covariates,
"metadata" = metadata) %>%
append_retriever_citation(path)
attr(out, "class") <- "matssdata"
return(out)
}