I'm using FLightR 0.4.9 to track migration of shorebirds. Tags were deployed in Alaska and recovered at the same site a year later. FLightR gives me nice-looking tracks for the breeding season in Alaska, fall migration to Chile, and the non-breeding season in Chile. But the track for spring migration is consistently problematic -- instead of returning north to Alaska, it heads south toward Antarctica.
Has anyone experienced something similar? Any ideas for what I can do?
Calibration periods are from the study site (lon = -150.725, lat = 61.272): one from the beginning of the study (shortly after tag deployment) and another from the end (shortly before tag recovery). Both verified by plot_slopes_by_location.
> Calibration.periods <- data.frame(calibration.start=as.POSIXct(c("2009-05-17", "2010-05-10")),
calibration.stop=as.POSIXct(c("2009-06-15", NA)),lon=-150.725, lat=61.272)
calibration.start calibration.stop lon lat
1 2009-05-17 2009-06-15 -150.725 61.272
2 2010-05-10 <NA> -150.725 61.272
Calibrating from pre-deployment data instead yields similar results. For the particle filter run I've tried known.last=TRUE and known.last=FALSE. Changing behavioral masks, outlier check, nParticles, etc. also do not seem to help.
> all.in <- make.prerun.object(Proc.data, Grid, start=c(-150.725, 61.272), Calibration=Calibration)
> Result <- run.particle.filter(all.in, threads=-1, nParticles=nParticles, known.last=TRUE, check.outliers=TRUE)
Since I'm using the correct lon/lat at the end of the track to calibrate, why might the output show my end coordinates so far away from there?