JennyL Posted May 23, 2019 Share Posted May 23, 2019 Hi, all 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) > print(Calibration.periods) 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) > nParticles=1e6 > 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? Jenny Link to comment Share on other sites More sharing options...
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