vignettes/BIRDS.R

In Greensway/BIRDS: Biodiversity Information Review and Decision Support

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----install package, eval = F------------------------------------------------
#  remotes::install_github('GreenswayAB/BIRDS')

## ----checkPROJ, echo=FALSE----------------------------------------------------
projVer <- sf::sf_extSoftVersion()["PROJ"]
doNextChunk <- as.logical(compareVersion("5.1.0", projVer) == -1)

## ----basic example, eval = doNextChunk----------------------------------------
#  library(BIRDS)
#  library(sf)
#    # Create a grid for your sample area that will be used to summarise the data:
#    grid <- makeGrid(gotaland, gridSize = 10)
#    # The grid can be easily created in different ways.
#
#    # Import the species observation data:
#    PBD <- bombusObs
#    # alternatively, you could load a previously downloaded .CSV file
#
#    # Convert the data from an observation-based to a visit-based format, adding a
#    # unique identifier for each visit:
#    OB <- organizeBirds(PBD, sppCol = "scientificName", simplifySppName = FALSE)
#
#    # Summarise the data:
#    SB <- summariseBirds(OB, grid=grid)
#
#  # Look at some summarised variables:
#  # Number of observations
#  EBnObs <- exportBirds(SB, dimension = "temporal", timeRes = "yearly",
#                        variable = "nObs", method = "sum")
#  # Number of visits
#  EBnVis <- exportBirds(SB, dimension = "temporal", timeRes = "yearly",
#                        variable = "nVis", method = "sum")
#  # The ratio of number of observations over number of visits
#  relObs <- EBnObs/EBnVis
#
#  # Average species list length (SLL) per year (a double-average, i.e. the mean
#  # over cell values for the median SLL from all visits per year and cell)
#  EBavgSll <- colMeans(SB$spatioTemporal[,,"Yearly","avgSll"], na.rm = TRUE)

## ----figure 1, eval = doNextChunk, fig.show='hold', fig.width= 7, fig.height= 5, fig.cap = "Time series for *Bombus* spp. dataset."----
#  oldpar <- par(no.readonly =TRUE)
#  par(mar=c(4,4,1,6), las=1)
#  plot(time(EBnObs), EBnObs, type = "l", lwd = 3, xlab = "Year", ylab = "Number",
#       ylim=c(0, max(EBnObs)), xaxp=c(2000, 2018, 18))
#  lines(time(EBnObs), EBnVis, lwd=3, lty=2)
#  lines(time(EBnObs), relObs * max(EBnObs) / max(relObs), lwd=3, lty=1, col="#78D2EB")
#  lines(time(EBnObs), EBavgSll * max(EBnObs) / max(EBavgSll), lwd=3, lty=1, col="#FFB3B5")
#  axis(4, at = seq(0, max(EBnObs), length.out = 5),
#       labels = round(seq(0,max(relObs), length.out = 5), 1),
#       lwd = 2, col = "#78D2EB", col.ticks = "#78D2EB")
#  axis(4, at = seq(0, max(EBnObs), length.out = 5) ,
#       labels = round(seq(0,max(EBavgSll), length.out = 5), 1),
#       lwd = 2, col = "#FFB3B5", col.ticks = "#FFB3B5", line = 3)
#  legend("topleft", legend=c("n.observations","n.visits"),
#         lty = c(1,2), lwd = 3, bty = "n")
#  legend("bottomright", legend=c("n.observations / n.visits", "avg. SLL per cell"),
#         lty = 1, lwd = 3, col = c("#78D2EB", "#FFB3B5"), bty = "n")
#  par(oldpar)

## ----figure 2, eval = doNextChunk, fig.show='hold', fig.width= 7, fig.height= 3----
#  wNonEmpty <- whichNonEmpty( SB$overlaid )
#  EB <- exportBirds(SB, "Spatial", "Month", "nYears", "sum")
#  # because the dimension is "spatial", the result is a 'SpatialPolygonDataFrame'
#
#  palBW <- leaflet::colorNumeric(c("white", "navyblue"),
#                                 c(0, max(st_drop_geometry(EB), na.rm = TRUE)),
#                                 na.color = "transparent")
#  oldpar <- par(no.readonly =TRUE)
#  par(mfrow=c(1,3), mar=c(1,1,1,1))
#  plot(SB$spatial$geometry[wNonEmpty], col="grey", border = NA)
#  plot(gotaland$geometry, col=NA, border = "grey", lwd=1, add=TRUE)
#  mtext("Visited cells", 3, line=-1)
#
#  plot(EB$geometry, col=palBW(EB$Jul), border = NA)
#  plot(gotaland$geometry, col=NA, border = "grey", lwd=1, add=TRUE)
#  mtext("Number of years for which \nJuly was sampled", 3, line=-2)
#
#  plot(EB$geometry, col=palBW(EB$Dec), border = NA)
#  plot(gotaland$geometry, col=NA, border = "grey", lwd=1, add=TRUE)
#  mtext("Number of years for which \nDecember was sampled", 3, line=-2)
#  legend("bottomleft",
#         legend=seq(0, max(st_drop_geometry(EB), na.rm = TRUE), length.out = 5),
#         col = palBW(seq(0, max(st_drop_geometry(EB), na.rm = TRUE), length.out = 5)),
#         title = "Number of years", pch = 15, bty="n")
#  par(oldpar)

## ----figure 3, eval = doNextChunk, fig.show='hold', fig.width= 7, fig.height= 4----
#  oldpar <- par(no.readonly =TRUE)
#  par(mfrow=c(1,2), mar=c(1,1,1,1))
#  palBW <- leaflet::colorNumeric(c("white", "navyblue"),
#                                 c(0, max(SB$spatial$nVis, na.rm = TRUE)),
#                                 na.color = "transparent")
#  seqNVis <- round(seq(0, max(SB$spatial$nVis, na.rm = TRUE), length.out = 5))
#  plot(SB$spatial$geometry, col=palBW(SB$spatial$nVis), border = NA)
#  plot(gotaland$geometry, col=NA, border = "grey", lwd=1, add=TRUE)
#  legend("bottomleft", legend=seqNVis, col = palBW(seqNVis),
#        title = "Number of \nobservations", pch = 15, bty="n")
#
#  ign <- exposeIgnorance(SB$spatial$nVis, h = 5)
#  palBWR <- leaflet::colorNumeric(c("navyblue", "white","red"), c(0, 1),
#                                  na.color = "transparent")
#  plot(gotaland$geometry, col="grey90", border = "grey90", lwd=1)
#  plot(SB$spatial$geometry, col=palBWR(ign), border = NA, add=TRUE)
#  plot(gotaland$geometry, col=NA, border = "grey", lwd=1, add=TRUE)
#  legend("bottomleft", legend=c(seq(0, 1, length.out = 5), "NA"),
#        col = c(palBWR(seq(0, 1, length.out = 5)), "grey90"),
#        title = "Ignorance \nnVis, \nO0.5=5", pch = 15, bty="n")
#  par(oldpar)