Ability of Archival Tags to Provide Estimates of Geographical Position Based on Light Intensity

Abstract

Abstract:We tested the ability of archival tags and their associated algorithms to estimate geographical position based on ambient light intensity by attaching six tags (three tags each from Northwest Marine Technologies [NMT] and Wildlife Computers [WC]) at different depths to a stationary mooring line in the Pacific Ocean (approx. 166º42'W, 24º00'N), for approximately one year (29-Aug-98 to 16-Aug-99). Upon retrieval, one tag each from the two vendors had malfunctioned: from these no data (NMT) or only partial data (WC) could be downloaded. An algorithm onboard the NMT tag automatically calculated geographical positions. For the WC tags, three different algorithms were used to estimate geographical positions from the recorded light intensity data. Estimates of longitude from all tags were significantly less variable than those for latitude. The mean absolute error for longitude estimates from the NMT tags ranged from 0.29 to 0.35º, and for the WC tags from 0.13 to 0.25º. The mean absolute error in latitude estimates from the NMT tags ranged from 1.5 to 5.5º, and for the WC tags from 0.78 to 3.50º. Ambient weather conditions and water clarity will obviously introduce errors into any geoposition algo-

Migratory behaviour of Atlantic cod Gadus morhua: natal homing is the prime stock-separating mechanism

“…The Greenwich hour angle (GHA) between local noon and UCT gives longitude. Although celestial methods are highly accurate in principle, the precision is impaired due to measurement errors caused, for instance, by variation in cloud cover and seawater transparency, and obtained raw geolocations often deviate with hundreds of kilometres from their true positions (Musyl et al 2001).…”

“…By analysing records on various physical factorsalone or in combination -such as light (Musyl et al 2001 and references therein), depth (i.e. pressure), tidal signals and temperature (e.g.…”

Performance of pop-up satellite archival tags

“…Descriptive plots suggested that (1) more geolocation data were returned by PSATs in later production years because of improved reporting rates, (2) deployments on deeper-diving species returned fewer geolocation data due to lower reporting rates and/or possible problems recording surface light (Musyl et al 2001, Dewar et al 2011, and (3) MT PSATs returned more geolocation data than WC PSATs, perhaps because of more efficient data transmission schedules (MT PSATs broadcast data only when they are assumed to be in the footprint of Argos satellites instead of continuously). In addition, since the majority of tags were shed before their scheduled pop-up date, data priority schemes in WC PSATs may have favored broadcast of depth and temperature data over geolocation data (see 'Materials and methods -rationale for variable selection' [Variable 4]).…”

“…Chaprales et al (1998), Lutcavage et al (2001), Swimmer et al (2002), Prince et al (2002), Thorsteinsson (2002), Domeier et al (2003), Gilly et al (2006) and Epperly et al (2007). Current-generation PSATs record data on ambient light-level irradiance from which geolocations can be calculated (Musyl et al 2001), along with depth (pressure) and temperature. PSATs are increasingly used in marine fisheries research (Arnold & Dewar 2001, Brill & Lutcavage 2001, Gunn & Block 2001, Thorsteinsson 2002, Bolle et al 2005 to chronicle horizontal and vertical movements (e.g.…”

Strongly directional and differential swimming behavior of an adult female white shark, Carcharodon carcharias (Chondrichthyes: Lamnidae) from Guadalupe Island, Mexico

“…Notably, most of the existing information on oceanic migrations of white sharks comes from pop-up archival transmitting (PAT) tags, whose estimated tracks are prone to large position uncertainties especially in latitude (Musyl et al, 2001;Itoh et al, 2003). Even when Kalman filter models integrating SST satellite data are used to improve position estimates (Sibert et al, 2003;Nielsen et al, 2006), they typically have root mean square errors of 1.84° in latitude and 0.78° in longitude and mean great-circle errors of 213 ± 54 km between locations (Wilson et al, 2007).…”