Join estimated ABMI single-deployment density values

ace_join_dens(x, species, samp_per, nest = FALSE)

Arguments

x	a dataframe of deployments of interest, including at minimum the deployment id and year
species	character; vector of species of interest (common name). If left blank, all species available will be returned.
samp_per	character; vector of sampling period of interest. Available periods include the years 2013-2019, inclusive. If left blank, estimates from all available sampling periods will be returned.
nest	logical; if TRUE, a dataframe nested by species (common name) is returned.

Value

Tidy dataframe of deployments in sampling period(s) specified with two appended columns: species and estimated density.

Details

valid values for argument species currently are:

White-tailed Deer
Mule deer
Moose
Elk (wapiti)
Black Bear
Coyote
Pronghorn
Snowshoe Hare
Woodland Caribou
Canada Lynx
Gray Wolf

valid values for argument samp_per currently are:

2013
2014
2015
2016
2017
2018
2019

Examples

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
# Dataframe of deployment names and year
df <- data.frame(name = c("ABMI-633-NE",
                          "ABMI-633-NW",
                          "ABMI-633-SE",
                          "ABMI-633-SW"),
                 samp_per = c(2015, 2015, 2015, 2015)) %>%
                 mutate_if(is.factor, as.numeric)
# Join density estimates (e.g. Moose in 2015)
df_densities <- ace_join_dens(df, species = "Moose", samp_per = "2015", nest = FALSE)