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Table 3 Algorithm parameters used to compute locations for both assessment data sets

From: A probabilistic algorithm to process geolocation data

Model parameter Description Value used
particle.number number of particles computed for each point cloud 10 000
iteration.number number of track iterations 200
sunrise.sd & sunset.sd shape, scale and delay values describing the assumed uncertainty structure for each twilight event following a log normal distribution 2.49/ 0.94/ 0a
range.solar range of solar angles used -7° to -1°
boundary.box the range of longitudes and latitudes likely to be used by tracked individuals 120 W to 40 E
90 S to 0
day.around.spring.equinox & days.around.fall.equinox number of days before and after an equinox event in which a random latitude will be assigned includes the entire wandering albatross tracking period
speed.dry fastest most likely speed, speed standard deviation (sd) and maximum speed allowed when the logger is not submerged in sea water 12/ 6/ 45 m/s
for black-browed albatrossb & 12/ 7/ 70 m/s
for wandering albatrossb
speed.wet fastest most likely speed, speed sd and maximum speed allowed when the logger is submerged in sea water 1/ 1.3/ 5 m/sc
sst.sd logger-derived sea surface temperature (SST) sd 0.5 °Cd
max.sst.diff maximum tolerance in SST variation 3 °C
east.west.comp compute longitudinal movement compensation for each set of twilight event [37] used
  1. a The resulting uncertainty structure for both twilight events is illustrated in Additional file 1. These parameters are chosen as they resemble the twilight error structure of open habitat species in [20]
  2. inferred from GPS tracks (see Additional file 3 for details)
  3. c Antarctic circumpolar current speed up to fast current speeds (i.e. Malvinas current) [38] as the tagged animal is assumed to not actively move when the logger is immerged in seawater
  4. d logger temperature accuracy