Observation Index

This function extracts the proportion of visits (or observations) detecting a focal species to all visits (or observations) over time or space.

obsIndex(
  x,
  dimension,
  timeRes = NULL,
  focalSp = NULL,
  visits = TRUE,
  fs.rm = TRUE,
  norm = TRUE
)

Arguments

x	an object of class ‘SummarizeBirds’.
dimension	a character string indicating if the export should be "spatial" or "temporal"
timeRes	the time resolution as a character string if dimension = "temporal": "Yearly", "Monthly" or "Daily"
focalSp	the focal species to look for
visits	if TRUE (default) the observation index is calculated over number of visits, else uses the number of observations
fs.rm	if TRUE, assumes that the observations for the focal species are included in 'group' and will remove them
norm	if TRUE, the result is nomalized to a 0-1 range

Value

If dimension = "spatial" a ‘SpatialPolygonsDataFrame’ or a ‘xts’ timeseries if dimension = "temporal".

Note

It implements the following algorithm to calculate the observation index: OI = log ( (At / (At + Rt) ) / ( A / (A + R) ) ) where At is the sum of observations of a focal species during time t (or gridcell), Rt is sum of observations of all species in reference group during t (or gridcell), A and R are the total sums for observations. If the ratio to log = 0 it adds 0.1 to avoid -Inf results.

References

Telfer, Preston 6 Rothery (2002) <doi:10.1016/S0006-3207(02)00050-2>

Examples

# \donttest{
grid <- makeGrid(gotaland, gridSize = 10)
PBD <- bombusObsShort
OB <- organizeBirds(PBD, sppCol = "scientificName", simplifySppName = TRUE)
SB <- summariseBirds(OB, grid=grid)
#> 149 observations did not overlap with the grid and will be discarded.
spp <- listSpecies(SB)
tempOI <- obsIndex(SB, "temporal", "yearly", focalSp=spp[3], fs.rm = FALSE)
plot(tempOI$relObs, main=spp[3])
spatOI <- obsIndex(SB, "spatial", focalSp=spp[3])
minOI <- min(spatOI$relObs, na.rm=TRUE)
maxOI <- max(spatOI$relObs, na.rm=TRUE)
palRW <- leaflet::colorNumeric(c("white", "red"), c(minOI, maxOI), na.color = "transparent")
plot(spatOI, col=palRW(spatOI$relObs), border="grey", main=spp[3])
legend("bottomleft", legend=seq(minOI, maxOI, length.out = 5),
       col = palRW(seq(minOI, maxOI, length.out = 5)), pch = 15, bty="n")
# }