4. Calculating overlaps

4.1. Calculating overlaps for group dBBMM

When utilization distribution areas are calculated for group dBBMM, models are calculated at the track level for each monitored animal. This analysis does not provide standardized tracks, and start and end times vary among tracked individuals depending on when they were present within the study area. Consequently, this option will simply calculate the general overlapping areas among the groups of interest:

overlap.save <- getOverlaps(areas.group)
overlap.save$areas$`0.95`$absolute

overlap.save$areas$`0.95`$percentage

In the example we can notice that R64K-4075 and R64K-4125 used 76.07% of the same areas, whereas R64K-4075 and R64K-4128 only overlapped in 70.91%. Now we can use plotOverlaps() to see exactly where in the study area these overlaps took place:

plotOverlaps(overlaps = over.save, areas = areas.save, base.raster = water.shape, 
    groups = c("R64K-4075", "R64K-4125"), level = 0.95) 
plotOverlaps(overlaps = over.save, areas = areas.save, base.raster = water.shape, 
    groups = c("R64K-4075", "R64K-4128"), level = 0.95)

Warning message:
Raster pixels are placed at uneven horizontal intervals and will be shifted. Consider using geom_tile() instead.

Please note that these plots can return a warning. This is issued by ggplot2 because, when there are multiple tracks/tags in the same group, the empty cells of the raster are cleared out to improve plotting efficiency. Please be aware that this warning is harmless for the map created.

4.2. Calculating overlaps for timeslot dBBMM

The standardized tracks returned from timeslot dBBMM can be used to calculate overlaps between multiple groups both in space and time.

overlap.save <- geOverlaps(areas.group)
overlap.save$areas$`0.95`$absolutes$`128`

overlap.save$areas$`0.95`$percentage$`128`

plotOverlaps(overlaps = overlap.save, areas = areas.group, base.raster = water.shape, 
  groups = c("Bream", "Tarwhine"), timeslot = 127, level = 0.95, title = "timeslot 127") 


plotOverlaps(overlaps = overlap.save, areas = areas.group, base.raster = water.shape, 
  groups = c("Bream", "Tarwhine"), timeslot = 128, level = 0.95, title = "timeslot 128") 

Note that if the two groups don’t overlap, the following message will be issued:

M: No overlap found between 'Bream' and 'Tarwhine'. Plotting only the separate areas.

4.2.1. Obtain overlap data from timeslot dBBMM for applying further statistical analysis

Maybe you are interested in better understanding the potential factors influencing the overlapping areas between different biological groups. If that’s your case, and you have ran a timeslot dBBMM analysis, the function getOverlapData() is what you are looking for. You’ll need to provide the outputs from getOverlaps() (input) and dynBBMM() (dbbmm), and select the two biological groups of interest (groups) together with the desired level of the dBBMM contour to extract the overlaping data for (level). Overlaps for each timeslot will then be returned at both absolute and percentage values.

df.overlap <- getOverlapData(input = overlap.data, dbbmm = dbbmm.data, 
    groups = c("G1", "G2"), level = 0.5) 
df.overlap