Evidence for Geomagnetic Imprinting and Magnetic Navigation in the Natal Homing of Sea Turtles

Abstract

Natal homing is a pattern of behavior in which animals migrate away from their geographic area of origin and then return to reproduce in the same location where they began life [1-3]. Although diverse long-distance migrants accomplish natal homing [1-8], little is known about how they do so. The enigma is epitomized by loggerhead sea turtles (Caretta caretta), which leave their home beaches as hatchlings and migrate across entire ocean basins before returning to nest in the same coastal area where they originated [9, 10]. One hypothesis is that turtles imprint on the unique geomagnetic signature of their natal area and use this information to return [1]. Because Earth's field changes over time, geomagnetic imprinting should cause turtles to change their nesting locations as magnetic signatures drift slightly along coastlines. To investigate, we analyzed a 19-year database of loggerhead nesting sites in the largest sea turtle rookery in North America. Here we report a strong association between the spatial distribution of turtle nests and subtle changes in Earth's magnetic field. Nesting density increased significantly in coastal areas where magnetic signatures of adjacent beach locations converged over time, whereas nesting density decreased in places where magnetic signatures diverged. These findings confirm central predictions of the geomagnetic imprinting hypothesis and provide strong evidence that such imprinting plays an important role in natal homing in sea turtles. The results give credence to initial reports of geomagnetic imprinting in salmon [11, 12] and suggest that similar mechanisms might underlie long-distance natal homing in diverse animals.
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Evidence for Geomagnetic Imprinting and Magnetic
Navigation in the Natal Homing of Sea Turtles
Highlights
dSea turtle nesting density varies with slight changes in
Earth’s magnetic field
dResults imply that sea turtles locate nesting beaches using
geomagnetic cues
dTurtles likely imprint on the unique magnetic signature of
their natal beach
dSimilar mechanisms may explain natal homing in diverse
long-distance migrants
Authors
J. Roger Brothers, Kenneth J. Lohmann
Correspondence
brotherj@live.unc.edu
In Brief
How sea turtles return to nest on their
natal beaches after long migrations has
remained enigmatic. Brothers and
Lohmann report a relationship between
sea turtle nesting density and small
changes in Earth’s magnetic field.
Results imply that turtles use
geomagnetic cues to find nesting areas
and may imprint on the magnetic field of
the natal beach.
Brothers & Lohmann, 2015, Current Biology 25, 392–396
February 2, 2015 ª2015 Elsevier Ltd All rights reserved
http://dx.doi.org/10.1016/j.cub.2014.12.035

Current Biology 25, 392–396, February 2, 2015 ª2015 Elsevier Ltd All rights reserved http://dx.doi.org/10.1016/j.cub.2014.12.035
Report
Evidence for Geomagnetic Imprinting
and Magnetic Navigation
in the Natal Homing of Sea Turtles
J. Roger Brothers
1,
*and Kenneth J. Lohmann
1
1
Department of Biology, University of North Carolina, CB 3280,
Chapel Hill, NC 27599, USA
Summary
Natal homing is a pattern of behavior in which animals
migrate away from their geographic area of origin and then
return to reproduce in the same location where they began
life [1–3]. Although diverse long-distance migrants accom-
plish natal homing [1–8], little is known about how they
do so. The enigma is epitomized by loggerhead sea turtles
(Caretta caretta), which leave their home beaches as hatch-
lings and migrate across entire ocean basins before return-
ing to nest in the same coastal area where they originated
[9, 10]. One hypothesis is that turtles imprint on the unique
geomagnetic signature of their natal area and use this
information to return [1]. Because Earth’s field changes
over time, geomagnetic imprinting should cause turtles to
change their nesting locations as magnetic signatures drift
slightly along coastlines. To investigate, we analyzed a
19-year database of loggerhead nesting sites in the largest
sea turtle rookery in North America. Here we report a strong
association between the spatial distribution of turtle nests
and subtle changes in Earth’s magnetic field. Nesting den-
sity increased significantly in coastal areas where magnetic
signatures of adjacent beach locations converged over time,
whereas nesting density decreased in places where mag-
netic signatures diverged. These findings confirm central
predictions of the geomagnetic imprinting hypothesis
and provide strong evidence that such imprinting plays an
important role in natal homing in sea turtles. The results
give credence to initial reports of geomagnetic imprinting
in salmon [11, 12] and suggest that similar mechanisms
might underlie long-distance natal homing in diverse
animals.
Results and Discussion
Ever since John James Audubon tied silver threads to the legs
of young songbirds and observed their return the following
year [13], evidence has accumulated that many animals return
to their natal areas after migrating to distant locations [1–8]. An
extreme example exists in loggerhead sea turtles, which leave
their natal beaches as hatchlings and traverse entire ocean
basins before returning to nest, at regular intervals, on the
same stretch of coastline where they hatched [9, 10, 14].
How sea turtles accomplish natal homing has remained an
enduring mystery of animal behavior [1, 14–16].
Turtles derive long-distance navigational information from
the Earth’s magnetic field by detecting the intensity and
inclination angle (the angle at which field lines intersect Earth’s
surface) [17–20]. These parameters vary predictably across
the globe [21, 22]. As a result, each area of coastline is typically
marked by a different isoline of inclination and a different
isoline of intensity (Figure 1A) and thus has a unique magnetic
signature [1]. In principle, if turtles were to imprint on the incli-
nation angle and/or intensity of their natal beach, then return-
ing might be relatively simple: a turtle might need only to locate
the coast and then swim north or south until it encounters the
correct magnetic signature (Figure 1A). No evidence presently
exists, however, to support or refute this hypothesis.
An important consideration for the geomagnetic imprinting
hypothesis is that Earth’s magnetic field changes slowly over
time. Because of this field change, known as secular variation
[24], the magnetic signatures that mark natal sites often drift
slightly along the coast while turtles are gone [1, 25]. Thus, if
an adult female selects her nesting sites by seeking out the
magnetic signature on which she imprinted as a hatchling,
she will inevitably change her nesting location in accordance
with secular variation [26, 27]. Such individual changes might
result in detectable population-level shifts in nesting distribu-
tions, providing a unique opportunity to test the geomagnetic
imprinting hypothesis.
Specifically, the hypothesis predicts that when isolines of
inclination or isolines of intensity converge along the coast,
the magnetic signatures marking natal locations between
those isolines will also converge (Figure 1). Thus, returning
turtles will nest on a shorter length of coastline, and the num-
ber of nests per kilometer should increase (Figures 1B and 1C).
By contrast, when isolines diverge, magnetic signatures also
diverge, so returning turtles will nest over a longer length
of coastline and the concentration of nests should decrease
(Figures 1B and 1C). Until now, this possibility has not been
investigated.
We analyzed a 19-year (1993–2011) database of loggerhead
nesting sites for each of the 12 counties on the east (Atlantic)
coast of Florida [28], an area encompassing the largest sea tur-
tle rookery in North America. To evaluate secular variation, we
developed an objective metric (convergence index) that quan-
tifies the degree of isoline movement along the coast within
each county during 17 two-year time steps (see Experimental
Procedures). A positive convergence index indicates that iso-
lines within a particular coastal area moved closer together,
with higher values indicating greater convergence. A negative
convergence index indicates that isolines moved apart, with
more negative values indicating greater divergence. For each
county and time-step combination, we calculated two different
convergence indices, one based on the movement of inclina-
tion isolines and the other based on the movement of intensity
isolines. We then analyzed the relationship between each
convergence index and changes in nesting density.
Analyses confirmed the predictions of the geomagnetic
imprinting hypothesis. For inclination, regardless of year or
location, isoline convergence was associated with increased
nesting density, whereas isoline divergence was associated
with decreased nesting density (p = 5.34 310
24
)(Figure 2).
Moreover, a linear mixed-effects model revealed a highly sig-
nificant relationship between the magnitude of isoline move-
ments and the magnitude of changes in nesting density (p =
3.67 310
24
)(Figure 3;Table S1): the highest convergence
indices were associated with the greatest increases in nesting
*Correspondence: brotherj@live.unc.edu

density, and the lowest convergence indices were associated
with the greatest decreases in nesting density. This trend per-
sisted within each of the 12 counties on Florida’s east coast
(Figure 4;Table S2).
For intensity, there were no areas along the coast where iso-
lines converged; thus, all convergence indices were negative.
In all other regards, however, the results of the analysis were
qualitatively identical to those of the inclination analysis. A
linear mixed-effects model revealed a strong positive relation-
ship between convergence index and changes in nesting den-
sity (p = 8.2 310
24
)(Figure 3;Table S1): as convergence index
increased, so did the percent change in nesting density. This
trend persisted within all 12 counties on Florida’s east coast
(Figure 4;Table S2).
These results provide strong evidence that nesting sea tur-
tles use Earth’s magnetic field to locate their natal beaches.
Although the exact geomagnetic component (or components)
exploited by turtles cannot be determined from the analyses,
the findings are consistent with the hypothesis that nest site
selection depends at least partly on magnetic signatures con-
sisting of inclination angle, field intensity, or a combination of
the two.
In a previous study, the migratory route of salmon approach-
ing their natal river was shown to vary with subtle changes in
the Earth’s field [11]. Whereas the endpoint of the salmon
spawning migration was presumably the same regardless of
route, our findings demonstrate for the first time a relationship
between changes in Earth’s magnetic field and the locations
where long-distance migrants return to reproduce.
Sea turtles are long lived, and females undertake reproduc-
tive migrations periodically throughout their adult lives [29].
Thus, the population of turtles that migrate to a given beach
to nest each year consists of two subsets: a group of first-
time nesters, and another, typically larger group of older ‘‘re-
migrants’’ that have nested in the area during previous years.
Genetic analyses indicate that both groups display natal hom-
ing [3, 5, 9, 14]. An unresolved question, however, is whether
both reach the natal region by using the same navigational
strategy and sensory cues [26].
At least two possibilities are compatible with the data. One
is that hatchling turtles imprint on the magnetic signature of
the natal beach and retain this information into adulthood [1].
Alternatively, nesting females might somehow reach the natal
beach the first time without relying on magnetic information
(e.g., by following an experienced nester or by using nonmag-
netic cues) and then learn the magnetic signature of the beach
and use it to return during subsequent nesting migrations.
Although neither possibility can be excluded, we presently
favor the first because ‘‘socially facilitated’’ migration has
never been observed in sea turtles [3, 30], and because no
nonmagnetic cue has been identified that can provide the
necessary positional information for long-distance navigation
[16]. Regardless of how the first return to the natal region is
accomplished, turtles might periodically update their knowl-
edge of the magnetic field at the nesting area each time they
visit so as to minimize navigational errors that might otherwise
accrue due to secular variation [25, 26].
Given the strong relationship between subtle changes in
Earth’s magnetic field and sea turtle nesting density, one pos-
sibility is that turtles are highly sensitive to small differences in
magnetic fields. Alternatively, however, the same relationship
can be explained if, in a typical nesting area, numerous
error-prone individuals seek out a magnetic signature but
miss the target by varying distances. Such imperfect naviga-
tion might, through a process resembling a ‘‘wisdom of the
crowd’’ phenomenon [31, 32], give rise to a nesting distribution
centered on the magnetic signature and, in effect, coupled to
it. Thus, when Earth’s field changes slightly and magnetic sig-
natures move, the population-level nesting distribution might
change even if individual turtles have relatively low magnetic
sensitivity and make considerable navigational errors.
Our findings do not imply that turtles reflexively nest at a
particular magneticsignature regardless of other environmental
ABC
Figure 1. Map Showing Inclination Isolines near Florida and Diagrams
Showing Predicted Effects of Isoline Movement on Nesting Density
(A) Because these isolines trend east/west whereas the coastline trends
north/south, a unique inclination angle marks each area along Florida’s
east coast. Thus, turtles might locate natal beaches by returning to the
appropriate isolines; locations to the north of the target area have steeper
inclination angles, whereas locations to the south have shallower inclination
angles. Black isolines bordering each color indicate increments of 0.5!and
were derived from the IGRF model 11 [23] for the year 2012. The map for in-
tensity isolines is not shown but is qualitatively similar, with different isolines
of intensity existing at each area along Florida’s east coast [16].
(B and C) Horizontal lines indicate three hypothetical isolines, and green
dots represent nesting turtles, each of which has imprinted on the magnetic
signature that marked her natal site as a hatchling. Over the past two de-
cades, isolines near Florida have moved northward, but at variable rates.
Sometimes, isolines to the south moved less than those to the north, result-
ing in divergence (C; upper two isolines). In these situations, the geomag-
netic imprinting hypothesis predicts a decrease in nesting density, because
turtles that imprinted on the fields between the isolines should return to nest
over a larger area. In places where isolines converged (because those to the
south moved more than those to the north), the hypothesis predicts that
nesting density should increase (C; lower two isolines). Tan represents
land; blue represents sea.
Figure 2. Changes in Nesting Density for Coastal Areas with Converging
and Diverging Inclination Isolines
At times and places in which isolines converged (n = 29), nesting density
increased by an average of 35%. At times and places in which isolines
diverged (n = 172), nesting density decreased by an average of 6%. The
mean changes of the two groups were significantly different (p = 5.34 3
10
24
). Error bars represent standard error of the mean.
393

conditions, or that nesting distributions will track the steady
movement of isolines along a coast no matter what. Successful
nesting requires deposition of eggs in a location suitable for in-
cubation. Factors such as beach erosion, sand quality, visual
cues, and predation are known to influence where turtles nest
on a local scale [1, 26]. Because these and other environmental
conditions also affect the likelihood that a nest will yield viable
hatchlings [26, 33], natural selection is likely to act against
turtles that choose nesting locations by relying on magnetic
cues to the exclusion of all else. Moreover, sensory cues other
than geomagnetism are likely to help guide natal homing, espe-
cially once turtles have arrived in the vicinity of the nesting area
[25, 26].
Given that geomagnetic cues appear to play an important
role in natal homing, an intriguing speculation is that, over
evolutionary time, turtles might have had difficulty locating
their natal beaches during brief periods of rapid field change,
as are thought to have occurred during some magnetic polarity
reversals [34]. During these intervals, turtles might have had a
tendency to stray into new nesting areas, which subsequent
generations could then locate reliably as the field stabilized
and geomagnetic imprinting once more became an effective
strategy for natal homing [1].
Because sea turtles nest in different environmental settings
worldwide, it is possible that different nesting populations
exploit geomagnetic cues in different ways during natal
homing [1, 16, 35]. Our analysis suggests that turtles use
geomagnetic cues to locate natal areas along continental
coastlines, the most common setting for large sea turtle
rookeries worldwide [16]. In other settings, such as on small
islands, turtles must nest in specific, restricted areas
because no alternative exists. In such situations, a clear rela-
tionship between field changes and nesting sites is unlikely
because, over time, magnetic signatures that once marked
the natal site drift offshore where nesting is impossible
[1, 26]. In these cases, turtles might use magnetic cues to
navigate to the vicinity of the island and then use odorants
or other supplemental local cues to locate the nesting beach
[16, 35, 36].
Regardless of these considerations, our results provide
the strongest evidence to date that sea turtles find their nest-
ing areas at least in part by navigating to unique magnetic
signatures along the coast. In addition, our results are
consistent with the hypothesis that turtles accomplish natal
homing largely on the basis of magnetic navigation and
geomagnetic imprinting. These findings, in combination
with recent studies on Pacific salmon [11, 12], suggest that
similar mechanisms might underlie natal homing in diverse
long-distance migrants such as fishes [2, 4], birds [37, 38],
and mammals [6].
AB
-50
0
50
100
150
-0.004 -0.002 0.000 0.002
Inclination Convergence Index
Percent change in nesting density
-50
0
50
100
150
-0.006 -0.004 -0.002 0.000
Intensity Convergence Index
Percent change in nesting density
Figure 3. Relationship between Isoline Move-
ment and Change in Nesting Density
Each data point represents values for one county
in one time step.
(A) For inclination, a significant, positive relation-
ship exists between convergence index and
change in nesting density (p = 3.67 310
24
;
n = 204) (Table S1). As the degree of isoline
convergence increased, so did the change in
nesting density; the greatest increases in nesting
were associated with the highest rates of
convergence, and the greatest decreases in
nesting were associated with the highest rates
of divergence.
(B) For intensity, a significant positive relation-
ship also exists between convergence index
and change in nesting density (p = 8.2 310
24
;
n = 204) (Table S1). The slope and intercept for
each red line were estimated with mixed-effects
models that included convergence index as a
fixed effect and a random slope and intercept
for time step.
AB
-50
0
50
100
150
-0.004 -0.002 0.000 0.002
Inclination Convergence Index
Percent change in nesting density
County
Nassau
Duval
St Johns
Flagler
Volusia
Brevard
Indian River
St Lucie
Martin
Palm Beach
Broward
Miami-Dade
-50
0
50
100
150
-0.006 -0.004 -0.002 0.000
Intensity Convergence Index
Percent change in nesting density
Figure 4. Relationship between Isoline Move-
ment and Change in Nesting Density for Individ-
ual Counties
Each data point represents values for one county
in one time step; each county is represented by
a different color. In the color key, counties are
arranged from north (top) to south (bottom). For
both the inclination analysis (A) and the intensity
analysis (B), all counties show a positive relation-
ship between convergence index and change in
nesting density (n = 17 for each county) (Table
S2). The greatest increases in nesting were asso-
ciated with the highest rates of convergence,
and the greatest decreases in nesting were asso-
ciated with the highest rates of divergence. For
inclination, this relationship was significant in
eight individual counties (p < 0.05), and the trend
was present in all. For intensity, the relation-
ship was significant in seven individual counties
(p < 0.05), and the trend was present in all.
394

Experimental Procedures
Using data from Florida’s Statewide Nesting Beach Survey [28], which re-
ports the number of kilometers surveyed within each county and the corre-
sponding number of sea turtle nests counted, we calculated the loggerhead
turtle nesting density in Florida’s 12 east coast counties for each of 19 years
(1993–2011). We then calculated each county’s percent change in nesting
density for 17 two-year time steps (e.g., from 1993 to 1995, 1994 to 1996,
and so on). Because the total number of loggerhead nests on Florida’s
east coast varied from year to year [39], we estimated the change in nesting
density attributable to population fluctuations by calculating the average
change in nesting for all counties and time steps. We then calculated the dif-
ference between this average and each data point and used the resulting
value in our analyses.
Two-year time steps were used because adult female loggerheads typi-
cally return to nest on their natal beach every two to three years [29]; thus,
this time step reflects isoline movement that turtles realistically encounter
during successive reproductive migrations. Ideally, an analysis of nesting
data designed to test geomagnetic imprinting would be limited to first-
time migrants and would also use a longer time step that coincides with
the interval between hatching and first migration, but this was impractical
because no existing dataset spans a sufficient time period or distinguishes
between first-time and experienced migrants.
To assign coastal position, we used Google Earth to calculate distance
along a line parallel to the east coast of Florida (Figure S1). We then used
data from the International Geomagnetic Reference Field model 11 (IGRF-
11) [23] to calculate the distance isolines traveled along the coast over the
same two-year time steps for which we evaluated changes in nesting den-
sity. We described isoline movement as a function of coastal position (Fig-
ure S2A). The derivative of this function, with respect to position, quantifies
isoline convergence or divergence (Figure S2B). This metric, referred to as
the convergence index, was calculated at the midpoint of each county for
each time step. A convergence index was calculated for both inclination
and intensity isolines.
Over the past two decades, isolines near Florida have moved northward,
but at variable rates. At some times and places, isolines to the south moved
less than those to the north, resulting in the divergence of isolines. In such
cases, the derivative (convergence index) is negative (Figure S2). At other
times and places, isolines to the south traveled farther than those to the
north, resulting in the convergence of isolines. In these places, the derivative
(convergence index) is positive (Figure S2). In addition, the degree of isoline
convergence or divergence is proportional to the magnitude of the deriva-
tive; a more positive derivative indicates high rates of convergence, while
a more negative derivative indicates high rates of divergence.
To characterize the relationship between convergence index and change
in nesting density, we evaluated several linear models, including ordinary
least-squares regression, mixed-effects regressions with random effects
for time step, and mixed-effects regressions with random effects for county.
The random effects included in the models take into account the year-to-
year variations in nesting density along the Florida coast, as well as the
county-to-county variations. While all models revealed equivalent results,
the best-fit models for both the inclination analysis and the intensity analysis
include convergence index as a fixed effect and a random intercept and
slope for time step (Table S1). We evaluated the difference between nesting
changes for areas with converging or diverging inclination isolines using a
mixed-effects model with convergence or divergence as a fixed effect and
time step as a random effect. This last analysis was not performed for inten-
sity isolines because there were no coastal areas with converging intensity
isolines.
Supplemental Information
Supplemental Information includes two figures and two tables and can be
found with this article online at http://dx.doi.org/10.1016/j.cub.2014.12.035.
Author Contributions
The study was conceived by J.R.B. and K.J.L. The data were analyzed by
J.R.B. The manuscript was written by J.R.B. and K.J.L.
Acknowledgments
The authors thank Professor Michael Lavine for statistical assistance and
Dr. Catherine Lohmann, David Ernst, and Vanessa Be
´zy for comments on
manuscript drafts. This work was supported by National Science Founda-
tion grant IOS-1022005 and Air Force Office of Scientific Research grant
FA9550-14-1-0208.
Received: November 11, 2014
Revised: December 10, 2014
Accepted: December 11, 2014
Published: January 15, 2015
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