make_checklists: Create spreadsheets of eBird species abundance and occurrence...
In adamdsmith/geobird: Query an eBird database by geography (e.g., shapefiles)

Description Usage Arguments Details Value Examples

This function generates, for each queried polygon, a spreadsheet of all species detected on at least one checklist. For each season (see Details), an estimated abundance classification is provided (see Details) if a minimum number of complete checklists min_lists is available. Regardless, the total number of checklists (complete or not) on which each species was observed in each season is reported. Likewise, the amount of effort (# of complete and total checklists) is reported by season.

1 2	make_checklists(geo_ebird_df, min_lists = 10L, exclude_form = TRUE, xls = TRUE, nwrspp = FALSE, out_dir = "../Output/")

`geo_ebird_df`	a `data.frame` created by `geo_ebird`
`min_lists`	integer or numeric vector of length = 1 indicating the minimum number of complete eBird checklists to require in a given season before assigning a seasonal abundance classification
`exclude_form`	logical indicating whether observations from the slightly nebulous "form" category should be excluded (default = TRUE). Setting to FALSE may add certain species (e.g., Red Crossbill) but also more controversial entries (e.g., Northern Red-tailed Hawk)
`xls`	logical indicating whether to output nicely formatted *.xls file (TRUE; default) or to create a `list` of relevant information without any formatting (FALSE; i.e., for further manipulation in R)
`nwrspp`	logical indicating whether a sheet formatted for easy importing into the NWRSpecies database is requested (default = FALSE); only applies if 'xls = TRUE'.
`out_dir`	character string of the file path to the directory in which to save output spreadsheets

Seasons are classified as follows: spring (Mar - May), summer (Jun - Aug), fall (Sep - Nov), and winter (Dec - Feb). Note, this corresponds roughly to the seasonal bird checklists present in many National Wildlife Refuge brochures (which may have had a small part in the decision to use this classification). For monthly patterns of eBird detections by species, relative to eBird effort (i.e., # checklists), see plot_ebird_phen.

Abundance designations are classified based on the proportion of complete checklists on which a given species occurs. The min_lists argument allows the user to determine the number of checklists necessary to even attempt such a designation. The default is 10 complete checklists, although a larger minimum (e.g., 50 or 100) is probably a more reasonable choice for generating an estimate of species relative abundance. Abundance classifications (proportion of complete checklists) are: Abundant (A; > 0.50), Common (C; (0.3 - 0.5]), Uncommon (U; (0.2 - 0.3]), Occasional (O; (0.1 - 0.2]), Rare (R; (0.01 - 0.1]), and Vagrant (V; <= 0.01). Notice that the cutoff for a "Vagrant" designation requires at least 100 checklists; with fewer checklists this designation is lumped with "Rare".

a Microsoft Excel spreadsheet for each distinct polygon (i.e., each (name) in geo_ebird_df) when xls = TRUE or a list of lists

## Not run: 
# Get shapefile
SErefuges <- rgdal::readOGR("../GIS", "refuges", verbose = FALSE, stringsAsFactors = FALSE)

# Query eBird records within Piedmont NWR and 10 km buffer
piedmont <- geo_ebird(SErefuges, which_polys = "Piedmont", buffers = c(0, 10))

# Generate .xls spreadsheet contain abundance, occurrence, and effort information
# Require 100 complete checklists to generate abundance classification
make_checklists(piedmont, min_lists = 100)

## End(Not run)