#' Daubenmire raw data
#'
#' Contains raw daubenmire data. For analysis, you likely do not want this data
#' frame, but instead want one of these three:
#' \code{\link{cover}}, \code{\link{milkweed}}, \code{\link{litter}}.
#'
#' This data.frame exists so that data issues can be checked. If you find an
#' error in one of the three data.frames listed above and the error is also in
#' this data.frame, then the error is in the raw data. If you find an error in
#' one of the three data.frames listed above and the error is not here, then
#' it is caused by the script data-raw/daubenmire.R that constructs those three
#' data.frames.
#'
#' @format A data.frame with the following columns:
#' \itemize{
#' \item filepath: character, the name of the file that these data came from
#' \item date: Date, the date survey was taken
#' \item round: character, round number for the survey: 1, 2, or 3
#' \item observer: character, the individual/group who did the survey
#' \item siteID: character, unique identifier for the site
#' \item transectID: character, unique identified for the transect
#' \item section: character, point along the transect at which data was collected inside a 0.5m square
#' \item remaining columns are cover or counts for various responses
#' }
#' @seealso \code{\link{cover}}, \code{\link{milkweed}}, \code{\link{litter}}, \code{\link{daubenmire_surveys}}
#'
"daubenmire_raw"
#' Daubenmire surveys
#'
#' Dates and observers for Daubenmire surveys
#'
#' This data.frame was used primarily to fill in any missing data in the
#' Daubenmire data sets. As of 2020-05-15, there was no missing data and thus
#' this is just duplicated information for what can be found in the other
#' Daubenmire data.frames:
#' \code{\link{cover}}, \code{\link{milkweed}}, \code{\link{litter}}, \code{\link{daubenmire_raw}}
#'
#' @format A data.frame with the following columns:
#' \itemize{
#' \item date: Date, survey date
#' \item round: character, round number for the survey: 1, 2, or 3
#' \item observer: character, the individual/group who did the survey
#' \item transectID: character, unique identified for the transect
#' }
#'
#' @seealso \code{\link{cover}}, \code{\link{milkweed}}, \code{\link{litter}}
#'
"daubenmire_surveys"
#' Cover - Sourced from Daubenmire
#'
#' This data set contains daubenmire land cover percentages observed at 10m intervals inside a 0.5m square along a transect.
#'
#' @section Data Collection Protocol:
#'
#' **Note** Daubenmire and robel data share the same directory and are both saved with the same file name except that robel data is saved with a '2' after the .csv extension.
#' site_transect_round.csv2
#'
#' Daubenmire survey was done at 10m lengths along a permanent transect line
#'
#' Observer placed a quadrant (1 meter x 0.5m rectangle) on the left side of the transect
#'
#' Quadrant was placed with 1 meter edge perpendicular to the 100m tape and 0.5 meter edge extending from transect point to 0.5 meters along transect length.
#'
#' Observations started at 0 meters on the transect and were taken every 10m of the transect.
#'
#' Observations were at a point on the transect and did not encompass the full length of a section.
#'
#' Data collection began at 0 meter starting point of the transect and stopped before the transect ended.
#'
#' A transect length of 100m will have points recorded for 0 meters through 90 meters; 10 points.
#'
#' Data is not taken at the final point on the transect as this area is outside the transect.
#'
#' @section Variable Notes:
#'
#' **section** --Denotes the point along the transect at which the observation was made.
#'
#' **class** --*csg* *wsg* *forbs* *milkweed* *woody_species* *bare_ground* *leaf_litter*
#'
#' All values are percentages.
#'
#' Data points represent a daubenmire coverage class based off Daubenmire 1959.
#'
#' Observer looks from a top-down/birds eye view and estimates the area of the frame the specific plant material covers.
#'
#' Due to cover existing at different heights with potential for overlap, total percent cover of all cover classes combined can be greater than 100%. Example: quadrant could potentially have 16% WSG, 86% CSG, 38% forbs, 16% milkweed, 3% woody vegetation, 16% bare ground, and 38% leaf litter. When these percentages are added together, they exceed 100%. (A milkweed could be covering 16% of the frame and still have grasses taking up area underneath it.)
#'
#' Daubenmire percentage coverage classes are as follows:
#'
#' 0: None
#'
#' 1: Trace
#'
#' 3: 1-5
#'
#' 16: 5-25
#'
#' 38: 25-50
#'
#' 63: 50-75
#'
#' 86: 75-95
#'
#' 98: 95-100
#'
#' *csg* Cool season grass. Includes sedges and equisetum. Does not differentiate between native and non-native species.
#'
#' *wsg* Warm season grass. Does not differentiate between native and non-native species.
#'
#' *forbs* All non-grass herbaceous plants. Does not include milkweed. Does not differentiate between native and non-native species.
#'
#' *milkweed* Milkweed of any species
#'
#' *woody species* Trees or shrubs
#'
#' *bare ground* Soil surface which is not covered with leaf litter, residue, or stems. Includes tree roots, stumps, animal manure, and mushrooms.
#'
#' *leaf litter* All horizontal dead plant material that is no longer rooted: twigs, leaves, grass.
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item date: Date, survey date
#' \item round: character, the round number: 1, 2, or 3
#' \item transectID: character, id of the transect
#' \item section: character, point along the transect at which data was collected inside a 0.5m square
#' \item class: character, daubenmire specific ground cover categories
#' \item percentage: numeric, daubenmire specific cover classes in percentages. Numbers indicatenam birds eye coverage of specific cover category within 0.5m frame
#' }
#' @format A data frame with the variables above.
"cover"
#' Litter - Sourced from Daubenmire
#'
#' This data set contains litter depth in cm sourced from daubenmire survey observed at 10m intervals inside a 0.5m square along a transect.
#'
#' @section Data Collection Protocol:
#'
#' **Note** Daubenmire and robel data share the same directory and are both saved with the same file name except that robel data is saved with a '2' after the .csv extension.
#' site_transect_round.csv2
#'
#' Daubenmire survey was done at 10m lengths along a permanent transect line
#'
#' Observer placed a quadrant (1 meter x 0.5m rectangle) on the left side of the transect
#'
#' Quadrant was placed with 1 meter edge perpendicular to the 100m tape and 0.5 meter edge extending from transect point to 0.5 meters along transect length.
#'
#' Observations started at 0 meters on the transect and were taken every 10m of the transect.
#'
#' Observations were at a point on the transect and did not encompass the full length of a section.
#'
#' Data collection began at 0 meter starting point of the transect and stopped before the transect ended.
#'
#' A transect length of 100m will have points recorded for 0 meters through 90 meters; 10 points.
#'
#' Data is not taken at the final point on the transect as this area is outside the transect.
#'
#' Some litter values were only given as <.25, <.5, or >.5.
#' The inequalities have been removed, but are available in \code{\link{daubenmire_raw}}.
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item date: Date, the date survey was taken
#' \item round: character, the round number: 1, 2, or 3
#' \item transectID: character, id of the transect
#' \item section: character, point along the transect at which data was collected inside a 0.5m square
#' \item depth: numeric, depth of horizontal dead plant material on the soil surface in cm. cm values limited to measurement by 0.25cm increments.
#' }
#' @format A data frame with the variables above.
"litter"
#' Milkweed Ramets - within Daubenmire Frames
#'
#' This data set contains ramet count data for 3 milkweed species observed at 10m intervals inside a 0.5m rectangle along a transect.
#'
#' @section Data Collection Protocol:
#'
#' **Note** Daubenmire and robel data share the same directory and are both saved with the same file name except that robel data is saved with a '2' after the .csv extension.
#' site_transect_round.csv2
#'
#' **Note** This data (milkweed ramet counts within daubenmire frames) was not collected in 2016. Data exists for years 2017-2019
#'
#' Data was collected at same time and in same 0.5m square as daubenmire cover class data.
#'
#' Daubenmire survey was done at 10m lengths along a permanent transect line
#'
#' Observer placed a quadrant (1 meter x 0.5m rectangle) on the left side of the transect
#'
#' Quadrant was placed with 1 meter edge perpendicular to the 100m tape and 0.5 meter edge extending from transect point to 0.5 meters along transect length.
#'
#' Observations started at 0 meters on the transect and were taken every 10m of the transect.
#'
#' Observations were at a point on the transect and did not encompass the full length of a section.
#'
#' Data collection began at 0 meter starting point of the transect and stopped before the transect ended.
#'
#' A transect length of 100m will have points recorded for 0 meters through 90 meters; 10 points.
#'
#' Data is not taken at the final point on the transect as this area is outside the transect.
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item date: Date, the date survey was taken
#' \item round: character, the round number: 1, 2, or 3
#' \item transectID: character, id of the transect
#' \item section: character, point along the transect at which data was collected inside a 0.5m rectangle
#' \item milkweed_species: character, *common_ramet* *swamp_ramet* or *butterfly_ramet*
#' \item ramets: integer, count data of milkweed ramets observed for each of the three species within the 0.5 rectangle
#' }
#'
#'
"milkweed"
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