- Open Access
The value of using measurements of geomagnetic field in addition to irradiance and sea surface temperature to estimate geolocations of tagged aquatic animals
© The Author(s) 2017
- Received: 8 February 2017
- Accepted: 6 August 2017
- Published: 2 September 2017
In this commentary, we describe how geomagnetic intensity can be used to estimate latitude, discuss its strengths and weaknesses, and argue for its potential use along with irradiance measurements for estimating the latitude of a migratory fish carrying an archival tag. We conclude this commentary by suggesting that researchers and tag manufacturers estimate positions using as many inputs as possible, environmental irradiance, sea surface temperature, and geomagnetic field. Each environmental property will provide a better estimate of position at different times of the year and locations on earth. We contend that one geolocation estimation approach is not better than another, as each functions optimally under different circumstances and thus should be used accordingly.
- Geomagnetic intensity
- Archival tags
As widely used in aquatic biotelemetry studies, the archival tag is a microprocessor-based recorder with sensors to measure behavioral properties of aquatic animals that can include heading, depth, and acceleration as well as environmental properties such as subsurface irradiance, water temperature, and geomagnetic field. These measurements, or a processed subset of them, are stored in electronic memory aboard the tag. A daily geographic position, termed a “geolocation,” can be inferred for a tag holder from measurements of environmental properties, which to date have mainly been submarine illumination and sea surface water temperature (SST). In addition, depth measurements are taken commonly to ensure surface proximity when using maps of SST, to correct light curves, and to compare maximum observed diving depth to the bathymetry at a candidate position. The majority of geolocating archival tags have determined longitude using a method similar to that used by early mariners to navigate in the ocean. They found their longitude based on the difference between the “apparent” time, when they observed the sun was at its highest point in the sky at their current location, and the “true” time of noon, when the sun was at its highest point at a reference location (e.g., Greenwich, England). This time difference was recorded with an accurate clock, a chronometer. The archival tag similarly has a very accurate internal clock, which is initialized to universal time, yet is unable to find noon by the position of the disk of the sun because the fish tag is underwater and unable to distinguish celestial objects. Alternatively, the tag estimates the times of sunrise and sunset from rapid changes in the intensity of “irradiance” (energy in wavelengths near the visible region of the electromagnetic spectrum in contrast to “light” energy in the wavelengths visible to the human’s eye) at dawn and dusk, respectively. Apparent noon, midway between the rapid increase in light at sunrise and the rapid decrease in light at sunset, can be compared to true noon to determine longitude—each hour difference between apparent and true noon equals an offset of ca. 15° from the prime meridian on the circumference of the earth. Latitude can also be estimated from irradiance measurements. Day length, or the time between sunrise and sunset (or conversely night length), varies with distance along a meridian on the earth’s surface and thus is an indicator of latitude. The length of the day (or night) at the established longitude at the known time of the year is then entered into a mathematical algorithm that solves for latitude. The relative accuracy irradiance-based estimates of longitude are greater than similar estimates of latitude. To start with, latitudinal estimates are unreliable during the equinoxes, when the durations of daytime and nighttime area equal over the earth. They are most accurate during the solstices when the difference in the length of day varies greatest with latitude.
Furthermore, there are other sources of error in latitudinal estimates with biological causes. This is because of the necessity to correlate a point on the irradiance curve with a particular elevation of the sun. As an example, consider using 3.5 × 10−2 W/m2 (~4 lx) as a threshold for the determination of latitude. Irradiance of this magnitude exists at the sea surface during civil twilight during sunrise when the sun is 6° below the horizon. The irradiance intensity recorded by the sensor will be lower than that present at the sea surface if it is covered sessile organisms such as algae or barnacles or if the fish is swimming at depths well below the sea surface. Consequently, the sensor will record that intensity later in the morning and an equal amount earlier in the evening. The measured day length is shortened, resulting in a latitude error. On the contrary, the time of apparent noon will not change, as it lies half way between the two points on the curve, and the estimate of longitude estimate will be comparatively unaffected by these conditions. The systematic improvements in light-based geolocation estimates are reviewed in the introduction to a description of the use of light measurements from moored tags to calibrate the curves recorded on the animal . These permit them to be entered into a state-space model to increase the accuracy of geolocations.
Given the difficulty in estimating latitude from irradiance levels, researchers have estimated latitude by matching the temperature recorded by archival tags when the bearer swam near the surface to the sea surface temperature (SST) present at the longitude estimated based on irradiance. For example, the ARGOS-based positions of the endpoints of pop-up satellite archival tags and recapture locations of archival tags of salmon (Lamna ditropis) and blue sharks (Prionace glauca) in the North Pacific Ocean from 40 to 60°N were compared to the last geolocations of longitude based on irradiance and latitude based on sea surface temperature . The root-mean-square errors of the irradiance-based longitude estimates were 0.89 and 0.55°, while for SST latitude estimates, the root-mean-square errors were 1.47 and 1.16° for salmon sharks and blue sharks, respectively. Simulations were carried out that indicated that difference between the SST measured by the electronic tag and the remotely sensed SST at a given location was the predominant influence on the accuracy of SST latitude estimates. Positional accuracy can be improved further by using a motion filter (e.g., Kalman, particle, and grid) within a state-space model to process longitude and latitude estimates based on measurements of both irradiance and SST . This technique has been evaluated by comparing geolocations estimated by archival tags attached to thermistor-equipped drifting buoys located using the global positioning system (GPS). Hence, SST has been used in conjunction with irradiance and improved using state-space models, to increase the reliability of geolocation estimates of archival tags.
However, the earth’s magnetic field intensity is another environmental property that can be used to estimate latitude, which for the most part has been largely overlooked in aquatic biotelemetry. Klimley and Mangan  first proposed that an electronic tag could infer the latitude at which a fish was swimming based upon the measurement of the intensity of the earth’s magnetic field. They argued these estimates could be more accurate at certain times of the years (i.e., the equinoxes) and areas on the earth (i.e., near the equator). Furthermore, even during the solstices and in temperate and polar latitudes when and where day length changes along a north south gradient, there are both environmental and biological factors that can reduce the accuracy of latitude estimates based on irradiance.
The earth’s total field intensity is the sum of three orthogonal vectors, often described with a vertical, north–south, and east–west component. The intensity of the total field is measured throughout the year at magnetic observatories located over the entire surface of the earth. A series of spherical harmonics are used to determine Gauss coefficients to fit the thousands of magnetic measurements by the worldwide magnetic survey to a spherical dipole. The best fit is an inclined dipole with its axis passing through the center of the earth between north and south geomagnetic poles. This technique has been used to produce the International Geographical Reference Field (IGRF)  and the World Magnetic Model (WMM)  that map the earth’s total field intensity in three dimensions. While IGRF and WMM model the main field only, the Enhanced Magnetic Model (EMM) [7, 8] also incorporates crustal magnetic anomalies with a minimal geographical extent of 56 km . The modeled magnetic field can be visualized as a globe covered by isoclines, lines indicating similar magnetic strengths, looping around the earth. This feature, whose intensity varies largely along a north–south axis, is a prime candidate for estimating latitude. In this commentary, we describe how geomagnetic intensity can be used to estimate latitude, discuss its strengths and weaknesses for use in aquatic biotelemetry, and argue for its use along with irradiance measurements, sea surface temperature (SST) and other available gradients such as magnetic field inclination for estimating the latitude of a fish carrying an archival tag.
In order to estimate latitude based on magnetic field intensity, it is necessary to first estimate the longitude of the tag. This is determined using irradiance measurements. This technique has already been described in detail within the scientific literature . However, latitude can now also be determined based on the measurement of the average magnetic field intensity. Magnetic field intensity can be measured using a 3-axis magnetometer aboard an archival tag. The intensities recorded on the three axes must be summed to provide an overall measurement of total field intensity. The component measurements can be made when the tag holder is at any depth because the strength of the main magnetic field varies only slightly as a function of depth. The difference in the intensity of field between that present at surface and at a depth of 2000 m, the typical maximum operating depth of most tags, is only roughly 0.1% of the magnitude of the earth’s main field at the surface. This discrepancy is dwarfed by other sources of error such as the uncertainty of WMM measurements, which is roughly 0.3% of the strength of main field . The measurement of the intensity of the earth’s main field must then be paired with an estimate of longitude, derived from the daily series of irradiance measurements. These values are stored in memory aboard the tag and are available for removal upon recovery of the tag. If a fish carrying the tag swims at the surface, and the tag’s antenna is out of water, the measurements can be transmitted via a radio frequency from a platform transmitting terminal (PTT) to the ARGOS satellite, given that it passes overhead when the fish (and tag) is at the sea surface. Archival tags that release from the fish and float to the surface can also transmit their stored information to the satellite. Given the longitude of the tagged animal, the latitude can be determined based upon the measurement of total field intensity. Software is available from the United State Geological Survey that will provide a user with total field intensity, given a longitude and latitude of any point on earth. An algorithm can be used to find the estimated latitude through an iterative examination, searching for the matching intensity along a series of modeled intensities along the estimated line of longitude until a match is found between measured and the modeled field intensity. The process is illustrated on a map of the earth’s main field (Fig. 3). A meridian is drawn on the WMM map at the estimated longitude to isoclines with the measured geomagnetic intensity.
We demonstrate how the method works with an archival tag equipped with a magnetometer, irradiance, and temperature sensors on a tag drifting at the surface. It is our intention to provide error estimates independent of behavior, which varies with species, and thus our estimates would be of greater general value to the general tagging community working on a diversity of aquatic species. The drifting tag can be used to compare the positioning methods under a boundary condition of maximum accuracy. A tag on an animal would experience constantly changing depths and variable water conditions, and this would result in error estimates for the different methods unique to a particular species. An animal swimming at depth would experience greater magnetic anomalies in certain regions such as the Galapagos Islands or the Gulf of California, and this would add to (positive anomaly) or subtract from (negative anomaly) the total field, shifting the geoposition estimate to either a higher or lower latitude. The accuracy of the irradiance-based estimates of apparent noon or day length will be reduced due to an animal’s behavior such as diving and the changing environmental conditions encountered that do not affect a drifter. For example, the deeper an animal goes and the greater the attenuation of irradiance, the later the threshold defining dawn will occur in the morning, and the earlier threshold defining dusk will happen in the evening.
The method by which geolocation is determined may vary between manufacturers. Hence, the method by which this Desert Star’s SeaTag estimates longitude and latitude will be explained below. The explanation is general without some details because the information is proprietary. The tag’s wrap-around solar power panel serves as the irradiance sensor. This 360° design provides near-equal response to illumination independent of tag orientation on the fish, thus improving the reliability of local apparent noon and apparent day length measurements. The magnetometer undergoes extensive factory calibrations to maximize the accuracy and reliability of magnetic field intensity measurements in order to accurately compare these measurements to values predicted by geomagnetic models. The irradiance measurements are based on timing the dawn and dusk illumination threshold crossing of an intensity of 1.4 Lux; a value above maximum expected surface moonlight but well below the nominal sunrise and sunset illumination of 400 Lux at the surface. This assures that for an animal located anywhere in the euphotic zone (light absorption ≤99%), dawn timing occurs before sunrise and dusk timing after sunset. Twilight is the period of the steepest irradiance gradient where measurements are least affected by disturbances such as varying turbidity, weather or animal diving behavior. The tag archives the determined local apparent noon, apparent day length, and a 24-h average magnetic field intensity that are used to estimate geolocation in a single daily observation summary packet. This is transmitted in a single ARGOS packet which maximizes the number of daily positions that will be available even if post pop-up transmissions should be interrupted.
Current measurements transmitted after pop-up by the tag in periodically transmitted engineering packets are compared to model predictions for the ARGSO-identified tag location and used to establish sensor biases for compensation. Sensor stability is verified by comparing sensor bias for the start and end of positions of the track. Conversion to geographical coordinates is accomplished by matching tag measurements to geomagnetic models and astronomical equations. If processed through CLS Track&Loc, these are improved based on information from sea surface temperature, bathymetry and coastal maps. The irradiance-based local apparent noon is converted to longitude, while latitude is identified by matching the observed and bias-compensated magnetic field intensity to the intensity at a point on the established line of longitude using the WMM geomagnetic model. The accuracy of the irradiance measurements for a given day, and thus the longitude component, is evaluated by comparing the apparent length of day, after bias compensation, to the length of day predicted for the magnetometer-identified latitude. If the observed day is much shorter than the predicted day, then the measurement of apparent noon may be unreliable due to turbidity, diving behavior, weather, or shading. Conversely, a matching or somewhat long apparent day indicates reliable longitude because the steep light gradient at dawn and dusk provides an upper bound to the observable day length and will only be observed if shading events have not unduly influenced the dawn or dusk irradiance measurements .
For each method, the average expected error is a function of the following: (1) the steepness of the relevant field gradient over space, (2) the error inherent in the model of that field, and (3) the expected measurement error of the sensor aboard the electronic tag. For each approach estimating latitude, a small error can be expected when the gradient is steep as well as when the measurement and model errors are small. The expected error will be larger if the gradient is shallow and the model and measurement errors are large.
The geomagnetic method works best in regions where the magnetic field intensity gradient is steep and runs north–south and thus where the lines of equal magnetic field intensity are dense and run approximately east–west. To understand where geomagnetic geolocations are best used, it is necessary to point out the irregular nature of the inclined dipole fitted to the earth’s field. Strong north–south geomagnetic intensity gradients exist in a latitudinal band over the northern Pacific Ocean, Central America to Canada, northern Atlantic Ocean, northern Africa, and southern Asia (see Fig. 3). Similarly, steep gradients exist in the southern Pacific Ocean, the southern Atlantic Ocean, the extreme northern Indian Ocean, northeast Asia and across Australia. It is in these regions, where steep geomagnetic gradients exist, that geomagnetic latitudinal estimates will be most accurate. Hence, one would expect the accuracy of the positions of the drifter in the northern Atlantic, where magnetic field intensity gradient is steep to be high. This is where the accuracy of geomagnetic geolocations may be greater than those based on irradiance and sea surface temperature.
Comparison of geolocations based on irradiance, magnetic intensity, and sea surface temperature
Irradiance (day length)
Magnetic field intensity
Sea surface temperature
Available from the factory
Requires special equipment and magnetically undisturbed site or facility
Available from the factory
Naturally smooth, varies with time of year, less of gradient with latitude at equinox than solstice
Smooth main field changes slowly over years (intensity, inclination, and declination) with overlaid crustal and man-made anomalies
Highly dynamic over time. High gradients in mid-latitudes, low gradients near equator and high latitudes.
Tag fouling, water clarity, diving depth, sea state, tag orientation if directional; cosine correction or wrap-around collector avoids directionality
Crustal anomalies associated with magnetic lineations and volcanic seamounts and islands, man-made anomalies of wrecks, rare solar storms
Diurnal variations and vertical stratification. Errors arising from small, hot or cold regions or uncertain depth profiles not captured by the model but influencing the tag measurement
Availability at depth
Within the euphotic zone, <200 of meters depending on water clarity
Present at all depths. Main field uniform at surface, anomalies increase with depth or in proximity to magnetized bodies
Mixed layer to a depth captured by model
Typical model error
Civil day length computed using astronomical equations. Negligible modeling error
Mean error of 152 nT for WMM model. This paper uses site-specific maximum anomaly in 0.25° × 0.25° cells per WDMAM
Error of 0.6 °C mean for OSTIA foundation Sea surface (temperature at the indeterminate depth free of diurnal variations)
Typical measurement error
±4 min typical error for measuring equivalent points on the sunrise and sunset irradiance curve. This corresponds to approx. +100/−50% irradiance disturbance due to factors such as weather changes, turbidity changes, animal depth changes and in situ bias compensation
A 300-nT residual error after in situ bias compensation
0.1 °C after in situ bias compensation
It is noticeable that the line indicating magnetic field latitude uncertainty remains at a typical value of roughly a half of a degree of latitude from 34°N to 39°N in the northwestern Atlantic Ocean. The line denoting irradiance geolocation uncertainty indicates roughly 2.0° of latitudinal uncertainty. Note that it decreases slightly with increasing latitude, as the difference in day length with latitude increases toward the poles. Finally, the sea surface temperature curve has two peaks, corresponding with high uncertainty at latitudes where there was little spatial gradient in temperature. However, the curve slopes downward at higher latitudes, where a greater temperature gradient manifests. The steep slopes in the 3-D plot of sea surface temperature exist at these highest latitudes between 38.3° and 39.0°N (see Fig. 6). Figure 7 does not imply that the stated typical or root-mean-square (RMS) latitude uncertainty necessarily produces a latitude error of that amount, but rather indicates the error potential or north–south extent of the 50% confidence interval resulting from the combination of the local field gradient, the measurement uncertainty and the model uncertainty.
Although magnetic geolocations are relatively more accurate in certain areas on the earth’s surface, they are less so in other regions. Weak meridian gradients are present from Canada northward in northern America, over the equatorial Pacific Ocean, much of Brazil and the equatorial Atlantic Ocean, and south of Australia (see Fig. 3). In these regions of the globe, the geomagnetic intensity gradient is minimal and thus geomagnetic geolocations will not be accurate. Furthermore, in the southern Indian Ocean geomagnetic field intensity-based latitude estimation will be inaccurate because the lines of equal magnetic field intensity run approximately north–south, thus producing an east–west gradient rather than the desired north–south gradient. However, here measurements of the inclination of the earth’s magnetic field could be used, rather than its intensity, as the proxy for latitude, as the inclination gradient is steep and runs north–south .
There are disturbances in the earth’s main field both in time and in space, and these can affect the accuracy of geomagnetic geolocations. WMM models the long-wave or smooth components of the earth’s magnetic field, which originates within the earth’s fluid outer core . While the field is disturbed by external fields such as from solar storms, these are too infrequent to be of much consequence for position estimation. For example, from 2010 to 2015, the United States Geological Survey lists ten significant magnetic disturbance events with total observed field disturbances up to around 500 nT with durations of from 1 to 6 days. With regard to space, man-made anomalies can be very strong, and we have observed disturbances up to 2500 nT during a boat-based magnetometer survey along the length of the lower Niagara River (Marco Flagg, pers. commun.). However, they are small in size and their association with human activities provides a basis to consider or ignore their impact based on the likelihood of sustained animal presence around such structures. Crustal magnetic anomalies are produced by basalt extruded from the earth’s mantle that contains tiny particles of magnetite. The seafloor is composed of bands of crust with alternating strong and weak magnetization, created by the periodic reversal of the earth’s dipole field. These disturbances are evident as sharp peaks and troughs oriented usually in a north–south direction. Islands and seamounts, which are produced by volcanic activity, have a dipole field associated with the crater and peaks and troughs leading away from them produced by the lava flows. The crustal anomalies create a total error of the WMM of 152 nT typical, which is <1% of the main field .
One must therefore be careful of estimating geolocations using latitude estimates from magnetic field intensity in areas characterized by unusually large crustal anomalies. The WDMAM  identifies the area around the Galapagos Islands as a region of major crustal magnetic anomalies, produced by the Galapagos spreading center. The anomalies captured in the WDMAM data set in this area, range from −1163 to +1060 nT. These anomalies caused a prominent north–south displacement of the geomagnetic track of a whale shark carrying a SeaTag (Desert Star Systems), with intensities up to 1200 nT per day producing a displacement of 250 n.m. along the north–south gradient of the WMM. This produced large latitudinal departures from the track of a whale shark tracked off the Galapagos Islands (Alex Hearn, pers. commun.). These errors diminished as the shark approached the coast of Colombia where large anomalies were not present.
We would like to conclude this commentary by suggesting researchers and tag manufacturers to consider estimating positions from archival tags using as many inputs as possible, environmental irradiance, sea surface temperature, and geomagnetic field. We are not advocating using one sensor over another, as each functions better than the other under different circumstances. These should be considered when estimating latitude using either irradiance, SST, or geomagnetic approaches. Using measurements from all sensors in tandem will likely produce the most accurate and robust tracks. Ideally, in the future more experiments will be carried out, in which drifters are deployed at different times and locations with ARGOS transmitters that provide a reference to compare the three methods. Similarly, insights will be gained from aquatic animals dual tagged with multi-sensor archival tags and ARGOS satellite tags serving as a reference for comparison of geoposition estimates. In the case of tags with a sufficiently long post pop-up reporting period for drift observations, such experiments might be incidental to animal tagging while providing a baseline estimate for the track accuracy available with a given complement of inputs in a given area and season. Using this approach, archival tags will likely to provide more accurate and more reliable position determinations in the future. It is ironic that with regard to the orientation of animals, magnetic cues were first shown to perceive latitude based upon the obvious north–south gradients and only later to be used to estimate longitude based on properties of the earth’s magnetic field .
APK conceived of the idea for the commentary, provided guidance in the plotting and presentation of data, and wrote the article. MF estimated the positions of the drifting transmitter based on geomagnetic, irradiance, and SST measurements and edited the manuscript. NH provided the files of sensor measurements and ARGOS-determined positions from the drifter in the North Pacific and edited the manuscript. AH provided the file of measurements of geomagnetic field intensity measured by a transmitter tracked at the Galapagos Islands in the Tropical Eastern Pacific and edited the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
The dataset used during thing the current study are available from the corresponding author, APK. The position determinations of the drifting electronic tag are present in an archive maintained by NH and AH; the analyses and data, with which the graphs were plotted, are in archive maintained by MF. The contributing author will obtain the data, with which the plots were made, from these two sources, given that there is interest in re-analyzing them.
Consent for publication
Ethics approval and consent to participate
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Basson M, Bravington MV, Hartog JR, Patterson TA. Experimentally derived likelihoods for light-based geolocation. Methods Ecol Evol. 2016;7:980–9.View ArticleGoogle Scholar
- Teo SLH, Boustany A, Blackwell S, Walli A, Weng KC, Block BA. Validation of geolocation estimates based on light level and sea surface temperature from electronic tags. Mar Ecol Prog Ser. 2004;283:81–98.View ArticleGoogle Scholar
- Nielsen A, Bigelow KA, Musyl MK, Sibert JR. Improving light-based geolocation by including sea surface temperature. Fish Oceanogr. 2006;15:154–325.View ArticleGoogle Scholar
- Klimley AP, Mangan WJ. Optimizing positional accuracy of archival tags with irradiance and magnetic sensors. In: Klimley, AP, Prince ED, Brill RW, Holland K, editors. Archival tags 1994: present and future. NOAA Technical Memorandum NMFS-SEFSC-357. 1994. p. 3.Google Scholar
- Skiles DD. The geomagnetic fields: its nature, history, and biological relevance. In: Kirschvink JL, Jones DS, MacFadden BL, editors. Magnetite biomineralization and magnetoreception in organisms. Berlin: Plenum Press; 1985. p. 43–100.View ArticleGoogle Scholar
- Chulliat A, Macmillan S, Alken P, Beggan C, Nair M, Hamilton B, Woods A, Ridley V, Maus S, Thomson A. Accuracy of the world magnetic model (WMM) and international geomagnetic reference field (IGRF): the US/UK world magnetic model for 2015–2020: Technical Report, Section 3.4 ‘Error Model’. National Geophysical Data Center. NOAA. 2015. doi:10.7289/V5TB14V7.
- Dyment, J, Lesur V, Hamoudi M, Choi Y, Thebault E, Catalan M. The WDMAM task force, the WDMAM evaluators, and the WDMAM data providers, world digital magnetic anomaly map version 2.0. 2015. http://www.wdmam.org.
- National Geophysical Data Center. Enhanced Magnetic Model 2010. National Geophysical Data Center, NOAA, 2009. doi:10.7289/V5HH6H0D.
- Flagg, M, Klimley AP. Opportunities and limitations for the use of geomagnetic field intensity measurements as a tool to enhance the confidence and accuracy of position estimated tracks for migratory species. In: 68th Tuna Conference, Lake Arrowhead, California, 2017.Google Scholar
- Hammerschlag N, Broderick AC, Coker JW, Coyne MS, Dodd M, Frick MG, Godfrey MH, Godley BJ, Griffin DB, Hartog K, Murphy SR, Murphy TM, Nelson ER, Williams KL, Witt MJ, Hawkes LA. Evaluating the landscape of fear between apex predatory sharks and mobile sea turtles across a large dynamic seascape. Ecology. 2015;96:2117–26.View ArticlePubMedGoogle Scholar
- Unites States Patent 7,411,512. Tracking the geographic location of an animal. Michael L. Domeier, 12 Aug 2008.Google Scholar
- Qayum HA, Klimley AP, Newton R, Richert JE. Broad-band versus narrow-band irradiance for estimating latitude by archival tags. Mar Biol. 2006;151(2);467-481.View ArticleGoogle Scholar
- Putman NF, Endres CS, Lohmann CMF, Lohmann KJ. Longitude perception and bicoordinate magnetic maps in sea turtles. Curr Biol. 2011;21:463–6.View ArticlePubMedGoogle Scholar