R/joinMicroShrubData.R

In KateMMiller/forestMIDNarch: Package for importing, joining and querying MS Access based MIDN forest database tables.

#' @include joinLocEvent.R
#' @title joinMicroShrubData: compiles shrub data collected in microplots
#'
#' @importFrom dplyr select filter arrange mutate summarise group_by
#' @importFrom magrittr %>%
#'
#' @description This function combines shrub stem (cycle 1) and percent cover (cycle 2+) data from microplots. Must run importData first.
#'
#' @param speciesType Allows you to filter on native, exotic or include all species.
#' \describe{
#' \item{"all"}{Default. Returns all species.}
#' \item{"native"}{Returns native species only}
#' \item{"exotic"}{Returns exotic species only}
#' }
#'
#' @param numMicros Allows you to select 1, 2, or 3 microplots of data to summarize
#'
#' @return returns a dataframe with shrub data collected in microplots
#'
#' @examples
#' importData()
#' # native shrubs in RICH all years
#' native_shrubs <- joinMicroShrubData(park ='RICH', speciesType = 'native')
#'
#' # all parks with exotic shrubs in most recent survey
#' exotic_shrubs <- joinMicroShrubData(from = 2015, to = 2018, speciesType = 'exotic')
#'
#' @export
#'
#------------------------
# Joins microplot tables and filters by park, year, and plot/visit type
#------------------------
joinMicroShrubData <- function(speciesType = c('all', 'native','exotic'), numMicros = 3, park='all',
                             from = 2007, to = 2019, QAQC = FALSE, locType = 'VS', panels = 1:4, output, ...){

  speciesType <- match.arg(speciesType)

  park.plots <- force(joinLocEvent(park = park, from = from,to = to, QAQC = QAQC,locType = locType,
                                 rejected = F, panels = panels, output = 'verbose'))

  park.plots <- park.plots %>% select(Location_ID, Event_ID, Unit_Code, Plot_Name, Plot_Number, X_Coord, Y_Coord,
                                      Panel, Year, Event_QAQC, cycle, Loc_Type)

  # Prepare the sapling data
  shrub1 <- merge(micro, shrub[,c("Microplot_Characterization_Data_ID", "TSN", "Num_Stems",
                                "DBH_DRC", "Cover_Class_ID")], by = "Microplot_Characterization_Data_ID",
                all.x=T, all.y=T)

  shrub2 <- merge(park.plots, shrub1, by = 'Event_ID', all.x = T)

  shrub3 <- merge(shrub2, plants[,c("TSN", "Latin_Name", "Common", 'Exotic')], by = "TSN", all.x = T)

  # For data with # stems or DRC change anything >0 to 1 for Present.old. For % Cover, change cover classes to midpoint
  shrub3 <- shrub3 %>% mutate(present.old =
                                ifelse(Year <= 2010 & (Cover_Class_ID > 0 | Num_Stems > 0 | DBH_DRC > 0), 1, NA))
  # Cycle 1 changed from stem counts and DRC to a combination of % cover and stems in 2009 & 2010 to all cover in 2011.
  # Due to these changes, we're only going to use cover data for cycle 2 (2011) and after, but will record species as
  # present.old if they were recorded from 2007 to 2010.
  shrub3 <- shrub3 %>% mutate(cover =
      case_when(Cover_Class_ID == 1 ~ 0.1,
                Cover_Class_ID == 2 ~ 3,
                Cover_Class_ID == 3 ~ 7.5,
                Cover_Class_ID == 4 ~ 17.5,
                Cover_Class_ID == 5 ~ 37.5,
                Cover_Class_ID == 6 ~ 62.5,
                Cover_Class_ID == 7 ~ 85,
                Cover_Class_ID == 8 ~ 97.5,
                Cover_Class_ID == 0 ~ 0))

  shrub3 <- shrub3 %>% mutate(cover = ifelse(TSN == -9999999951 & Year > 2010, 0, cover)) # Where 'no species recorded' was entered
  # and after % cover being used, record 0.

  shrub4<- if (numMicros==1) {filter(shrub3, Microplot_Name=='UR') %>% droplevels()
  } else if (numMicros==2) {filter(shrub3, Microplot_Name %in% c("UR","B")) %>% droplevels()
  } else if (numMicros==3) {shrub3}

  shrub5<-shrub4 %>% group_by(Event_ID, TSN, Latin_Name, Common, Exotic, Loc_Type) %>%
    summarise(present.old = ifelse(sum(present.old) > 0, 1, NA),
    cover = sum(cover))

    shrub6 <- shrub5 %>% group_by(Event_ID, TSN, Latin_Name, Common, Exotic) %>%
    summarise(present.old = present.old, cover = cover/ ifelse(Loc_Type=='Deer', 1, numMicros))

  shrub7<- if (speciesType=='native'){filter(shrub6,Exotic==FALSE)
  } else if (speciesType=='exotic'){filter(shrub6,Exotic==TRUE)
  } else if (speciesType=='all'){(shrub6)
  }

  shrub8 <- shrub7 %>% filter(TSN != -9999999951) %>% droplevels()

  shrub9<-merge(park.plots,
                shrub8[,c("Event_ID","TSN","Latin_Name","Common","Exotic","present.old","cover")],by="Event_ID",all.x=T)

  shrub9[,'cover'][is.na(shrub9$cover)]<-0
  shrub9[,c('Latin_Name','Common')][is.na(shrub9[,c('Latin_Name','Common')])]<-"No shrub species"
  return(data.frame(shrub9))
} # end of function