Biological Conservation 186 (2015) 134–142

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Biological Conservation
journal homepage: www.elsevier.com/locate/biocon

Age and residency duration of loggerhead turtles at a North Paciﬁcbycatch hotspot using skeletochronology
Calandra N. Turner Tomaszewicz a,b,⇑, Jeffrey A. Seminoff b, Larisa Avens c, Lisa R. Goshe c,S. Hoyt Peckham d, Juan M. Rguez-Baron e, Kalyn Bickerman f, Carolyn M. Kurle aaDivision of Biological Sciences, Ecology, Behavior, and Evolution Section, University of California, San Diego, La Jolla, CA 92093-0116, USA
Southwest Fisheries Science Center, NOAA-National Marine Fisheries Service, La Jolla, CA 92037, USA
Southeast Fisheries Science Center, NOAA, National Marine Fisheries Service, Beaufort, NC 28516, USAdCenter for Ocean Solutions, Stanford University, Paciﬁc Grove, CA 93940, USAeMarine Biology Department, Universidad Autonoma de Baja California Sur., La Paz, Baja California Sur, MexicofSchool of Biology and Ecology, University of Maine, Orono, ME 04469, USAbca r t i c l e

i n f oArticle history:
Received 12 December 2014
Received in revised form 9 March 2015
Accepted 15 March 2015

Keywords:
Endangered species
Demography
Survivorship
Sink habitat
Sea turtle
Age-at-maturationa b s t r a c t
For migratory marine animals, like sea turtles, effective conservation can be challenging because key
demographic information such as duration of life stages and exposure to spatially explicit threats indifferent habitats are often unknown. In the eastern Paciﬁc near the Baja California Peninsula (BCP),
Mexico, tens of thousands of endangered North Paciﬁc loggerhead sea turtles (Caretta caretta)
concentrate at a foraging area known to have high rates of ﬁshery bycatch. Because stage survivorshipof loggerheads in the BCP will vary signiﬁcantly depending on the number of years spent in this region,
we applied skeletochronology to empirically estimate residency duration in this loggerhead hotspot. The
observed age distribution obtained from skeletochronology analysis of 146 dead-stranded loggerheads
ranged from three to 24 years old, suggesting a BCP residency of >20 years. Given the maximum
estimated age and a one-year migration to western Paciﬁc nesting beaches, we infer age-at-maturationfor BCP loggerheads at 25 years old. We also examine survivorship at varying BCP residency durations
by applying our ﬁndings to current annual mortality estimates. Predicted survivorship of loggerheads
spending over 20 years in this BCP foraging habitat is less than 10%, and given that 43,000 loggerhead
turtles forage here, a signiﬁcant number of turtles are at extreme risk in this region. This is the ﬁrst
empirical evidence supporting estimated age-at-maturation for BCP North Paciﬁc loggerheads, and theﬁrst estimates of BCP stage survivorship. Our ﬁndings emphasize the urgent need for continued andeffective international conservation efforts to minimize bycatch of this endangered species.
Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction
Animals with complex life histories, particularly those that are
long-lived and migratory, present unique conservation challenges(Wilson et al., 2006; Martin et al., 2007). For many species,
important life stages are poorly understood and key conservationquestions remain unknown, such as: How long do certain stages
last? Where do animals go during cryptic life stages? Which life
stages should be targeted for conservation to maximize potential
reproductive value and best inﬂuence recovery of a threatened
population? Effective management of migratory species depends
on a solid, foundational understanding of the species’ ecology⇑ Corresponding author at: University of California, San Diego, 9500 Gilman Dr.,La Jolla, CA 92093-0116, USA. Tel.: +1 858 334 2842.
E-mail address: cturnert@ucsd.edu (C.N. Turner Tomaszewicz).
http://dx.doi.org/10.1016/j.biocon.2015.03.015
0006-3207/Ó 2015 Elsevier Ltd. All rights reserved.

and life history (Webster et al., 2002; Marra et al., 2010). This
includes identifying key habitats and resources, and elucidating
the timing and frequency of migrations and ontogenetic shifts(Sutherland, 1998; Fahrig, 2001; Gerber et al., 2005). Given thatdifferent spatially explicit threats exist among locations, species
survival rates may vary drastically as they migrate among distinct
habitats. By determining where animals live during each life stage,and how long they inhabit each location, managers can better
assess threats and prioritize management efforts.
One approach to conservation prioritization is to identify distinct habitats used during various life stages that have signiﬁcantly
different survival rates (Brooks et al., 2006; Wallace et al., 2011).
Two contrasting categories for habitats are ‘‘source’’ or ‘‘sink’’(Pulliam, 1988). A source habitat, characterized by high survival
rates and typically inhabited by individuals of high reproductive
value, contributes to positive population growth (Pulliam, 1988).

C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142

Conversely, a sink habitat, characterized by individuals of highreproductive value facing low survival rates, contributes to population decline (Pulliam, 1988; Dias, 1996). Habitats identiﬁed as
population sinks, including those habitats considered ecologicaltraps, are a primary focus for managing species of conservation
concern (Battin, 2004; Kappel, 2005). This includes habitats withhigh resource quality but where the presence of anthropogenic
impacts degrades overall habitat quality and species’ health andsurvival. Since Pulliam (1988), many examples of population sinks,
and the potential consequences on protected species, illustrate theconservation impacts and management challenges sink habitats
present for a wide range of taxa, including marine species (anadromous ﬁsh, Hickford and Schiel, 2011; marine ﬁsh, Dayton et al.,
1995; and marine megafauna (marine mammals, seabirds, andsea turtles), Lewison et al., 2004, 2014).
Sea turtles are an example of megafauna that exhibit complex
life histories, undergo ontogenetic shifts in habitat use, and occupy
a wide variety of habitats and ocean regions throughout their life

135

cycle (Wyneken et al., 2013). As a result, many sea turtle populations will reside in a sink habitat during at least one of their life
stages, increasing their conservation risks. Determining theduration of time and the speciﬁc life stage spent in such habitats
for threatened or endangered sea turtles is a top priority for
managers of these species (Hamann et al., 2010; NRC, 2010).
The North Paciﬁc loggerhead (Caretta caretta), declared aDistinct Population Segment in 2011 by the USFWS and NMFS
(NMFS and USFWS, 2011), is an endangered population known tosuffer high juvenile mortality at a developmental foraging hotspot
in the eastern Paciﬁc off the western coast of Mexico’s Baja
California Peninsula (BCP; Peckham et al., 2008; Koch et al.,2013; Fig. 1). All nesting for North Paciﬁc loggerheads occurs in
the western Paciﬁc – largely, if not exclusively, in Japan – andhatchlings undergo lengthy developmental migrations to foraging
areas in the central North Paciﬁc (CNP) and eastern Paciﬁc, including in the BCP (Bowen et al., 1995; Kobayashi et al., 2008;
Abecassis et al., 2013). Upon reaching maturity, turtles migrate

Fig. 1. Study site off the Paciﬁc coast of the Baja California Peninsula (BCP), Mexico. Samples were collected at Playa San Lázaro. Shaded area shows 95% kernel density
estimator utilization distribution (UD), core area of distribution, of loggerhead sea turtles for 2005–2007 during aerial surveys (Seminoff et al., 2014). Dashed lines show 95%
UD contours of 30 satellite tracked loggerhead turtles (Peckham et al., 2007).

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C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142

back to their natal beaches in the western Paciﬁc for reproduction
and foraging around the Japanese Archipelago (Nichols et al., 2000;
Hatase et al., 2002; Kamezaki et al., 2003).
The BCP is the largest known foraging hotspot in the eastern
Paciﬁc for this endangered loggerhead population and exhibitshigh mortality of loggerheads (Peckham et al., 2007; INAPESCA,
2012). For example, in the summer of 2012 alone, over 500
loggerheads stranded along a 44.3-km beach near the foraging area
(PROFEPA, 2012; Peckham et al., 2013). The loggerhead mortality
in this region resulted in Mexico being identiﬁed under the High
Seas Driftnet Moratorium Protection Act for not adopting a regulatory program that is comparable to the United States to end
or reduce bycatch, taking into account differing conditions(NOAA-Fisheries, 2013). To fully understand the biological andmanagement implications of this ﬁshery interaction, a thoroughunderstanding of the age of turtles affected by this mortality, andthe length of time turtles spend in this high-mortality area, isnecessary.
Skeletochronology, the study of regular growth increments inbones, has proven useful for studying age and growth rates ofmany species, including sea turtles. Multiple studies have validated the annual formation of growth layers in sea turtle bones,
especially for populations that inhabit ocean regions thatexperience seasonal variability in water temperature, food source,and overall productivity (e.g. Snover and Hohn, 2004; Goshe et al.,2010; Snover et al., 2011). Skeletochronology has been applied toestimate age, regional demographics, and growth patterns for
multiple sea turtle species in a variety of regions (e.g. Zug andGlor, 1998; Bjorndal et al., 2003; Avens et al., 2012; Petitet et al.,2012).
Here we apply skeletochronology to sea turtle humerus bones
to generate age estimates for 146 dead-stranded loggerhead turtles
collected in the BCP. We used the estimated age ranges ofthese turtles to determine residency duration and calculate ageat-maturation, thereby facilitating estimates of survivorship forloggerheads in the BCP. In applying estimated stage duration toexisting annual survivorship rates, we predict the likelihood ofjuvenile turtles inhabiting this foraging area surviving to maturity.
Our study provides greater context for previous estimates of stage
duration and age-at-maturation for this population (Van Houtan
and Halley, 2011; Seminoff et al., 2014), and further underscores
the demographic and conservation implications of the BCP as asink habitat.
2. Methods
2.1. Study site
Tens of thousands of juvenile loggerheads congregate in the
BCP (Fig. 1), an eastern Paciﬁc hotspot known for high productivity and abundant food resources for sea turtles and other marinevertebrates (Etnoyer et al., 2006; Wingﬁeld et al., 2011). In the
BCP, which is located within the California Current Large
Marine Ecosystem, loggerheads forage upon swarms of pelagic
red crab (Pleuroncodes planipes), pelagic and benthic invertebrates, and ﬁsh species discarded by ﬁsheries (Aurioles-Gamboa,
1992; Peckham et al., 2011, S.H. Peckham, pers. comm.).
Seasonal upwelling supports industrial, and especially artisanal,ﬁshing efforts that target a variety of species and use multiple
gear types that impact turtles including bottom-set gillnets andlonglines (Peckham et al., 2007, 2008; Ramírez-Rodríguez andOjeda-Ruíz, 2012; Wallace et al., 2013). The overlap of high turtle
numbers and intense ﬁshing effort in the BCP results insigniﬁcant sea turtle mortality rates and makes this foraging areaa sink habitat (Peckham et al., 2007; Koch et al., 2013; Lewison
et al., 2014).

2.2. Sample collection and preparation
We collected humerus bones from 146 dead-stranded
loggerhead turtles from 2003 to 2011 in the BCP. All samples werecollected along a 44.3-km stretch of beach, Playa San Lázaro, inBaja California Sur, Mexico, just north of Bahía Magdalena andimmediately adjacent to the Gulf of Ulloa (Fig. 1). Humeri were collected as part of the long term index shoreline stranding surveythat Grupo Tortuguero de las Californias and Proyecto Caguama haveconducted on Playa San Lázaro since 2003 (Peckham et al., 2008).
We extracted humerus bones from the front ﬂippers ofdead-stranded turtles, removed the ﬂesh, air dried the bones, thenstored them at room temperature prior to processing forskeletochronology. We also reprocessed and analyzed an additional 11 bones from small juvenile North Paciﬁc loggerhead turtles captured in the CNP between 1991 and 1992 and previously
analyzed in Zug et al. (1995) (see Zug et al., 1995 and Wetherall
et al., 1993 for additional details on these samples). These archived,
dried, and unprocessed bones from the 11 juvenile CNP turtles
underwent the same skeletochronology processing, at the sametime, as the more recently collected bones from Mexico.
We recorded curved carapace length (CCL) from the nuchal
notch to the posterior marginal tip for most of the turtles(n = 107); however, CCL was not recorded at the time of bonecollection for 50 turtles. For these animals, we estimated the CCL
at stranding based on the humerus diameter (HD, mm), a measurement made distal to the insertion scar, according to the equation

CCL ¼ ð2:582  HDÞ þ 2:704
derived from turtles measured at Playa San Lázaro, as well as the
CNP, and used in this study (n = 107, r2 = 0.84, p < 0.001). Any carapace lengths recorded as straight carapace length (SCL) instead of
CCL were converted using equation

CCL ¼ ðSCL  0:369Þ=0:932
from Peckham et al. (2008). All CCL data were rounded to the nearest cm.
2.3. Skeletochronology
Bones were measured, cross-sectioned, decalciﬁed, stained, andimaged according to Goshe et al. (2009) and Avens et al. (2012).
Most of the humeri from the BCP (n = 100), and all CNP humeri,were decalciﬁed using Cal-Ex II (Fisher Chemical), a decalcifying
agent commonly used for sea turtle skeletochronology processing
due to its multifunction as both a ﬁxative and decalciﬁer. The
remaining 46 bones were processed using a different decalciﬁer,
RDO (Apex Engineering), as we found that RDO yielded higher
quality sectioning and images for the remaining sea turtle bones
from the BCP. These bones were separately ﬁxed in 10% formalinprior to decalciﬁcation. Upon ﬁnal processing, humerus sections
were photographed and then digitized into high-resolution images
for aging analysis (Goshe et al., 2010).
2.4. Age estimation
Images of all humerus cross sections were independently
assessed by at least two of the authors (CTT, LG, LA, KB), and thelocation and number of observed lines of arrested growth (LAGs)
were determined as described in Goshe et al. (2009, 2010). For eachbone, the total number of LAGs was counted and each LAG diameter was measured (e.g. Snover and Hohn, 2004; Goshe et al., 2010;
Piovano et al., 2011). We assumed annual LAG deposition based on
the results of validation studies of loggerheads in the Atlantic(Klinger and Musick, 1992; Coles et al., 2001; Snover and Hohn,
2004; Snover et al., 2007; Avens et al., 2013), and green turtles

C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142(Chelonia mydas) in the Paciﬁc (Snover et al., 2011). Any bones
containing a distinctive diffuse mark that is characteristic of theﬁrst-year annulus, marking the ﬁrst year of a turtle’s life (Snoverand Hohn, 2004), we interpreted similarly and categorized as ‘‘directly aged’’ samples (n = 14) (e.g. Avens et al., 2013; Fig. 2). Anybones without the ﬁrst-year annulus mark (n = 143) were assumed
to have resorbed some LAGs during bone growth, requiring application of a correction factor to estimate the number of LAGs lost as
described in Goshe et al. (2010) and Avens et al. (2012). Two correction factors were used for these bones, depending on whether
the diameter of the innermost LAG was larger or smaller thanthe largest LAG from the directly aged bones (18.5 mm). First, forbones without a ﬁrst-year annulus but with an innermost LAG
diameter less than or equal to 18.5 mm, we used one correction
factor, termed the ‘‘ﬁrst order correction factor.’’ For larger bones
without a ﬁrst-year annulus but with the smallest retained LAGlarger than 18.5 mm, we used a different correction factor, termedthe ‘‘second order correction factor.’’ The estimated age-at-stranding of each turtle was then calculated by summing together the
total number of observed LAGs with the calculated number of
LAGs lost.
Similar to the process described in Avens et al. (2012, 2013), age
was adjusted to account for partial-year age and growth. This isrequired, for example, when a turtle hatched during a summer
month dies during a different time of the year. LAGs form during
periods of slower growth, and for ectothermic reptiles in the northern hemisphere, we assume this would typically occur during thewinter and spring as was concluded by Snover et al. (2011) for
green turtles in the North Paciﬁc, and was observed by Snoverand Hohn (2004) for Kemp’s ridley (Lepidochelys kempii).
Following LAG deposition, a period of more rapid growth occurs
during the warmer, more productive summer and fall months
and is observed as the diffuse space in bones that exists between
LAGs (Zug et al., 1986; Castanet et al., 1993; Snover et al., 2011).
Mean hatching period for loggerheads in Japan is during thesummer months (June, July, August), therefore, loggerhead turtles
stranded in the BCP during these same summer months received
no age adjustment. However, for BCP strandings that occurred
during the fall (September, October, November), age was adjusted
by +0.25 year. For winter and spring strandings, those that
occurred during the presumed formation of LAGs, age was adjusted
depending on whether growth was observed beyond the outermost LAG or not. If growth was observed beyond the outermost
LAG, age was adjusted by +0.5 year for winter strandings(December, January, February), and by +0.75 year for spring
strandings (March, April, May). If no growth was observed beyond
the outermost LAG, it was assumed that the LAG was newly137

deposited that winter/spring and age was adjusted by 0.5 year
for winter strandings and 0.25 for spring strandings.
3. Results
3.1. Size distribution
The CCL of the 146 BCP turtle humerus bone samples collected
between 2003 and 2011 ranged from 29 to 90 cm. Of these, themean (±SD) CCL was 69 ± 11 cm. All bone samples used in thisstudy were from juvenile turtles with CCL smaller than the mean
nesting size of adult loggerheads in Japan, < 91 cm (Hatase et al.,
2004; Fig. 3a). Of the 14 directly aged turtles, the body sizes forthe 11 bones from the CNP ranged from 15 to 47 cm CCL with anaverage of 29 ± 12 cm and the three from the BCP were 29, 50
and 58 cm CCL.
3.2. Age estimation
The age of the 14 directly aged turtles, based on direct LAG
count, ranged from zero to six years old. These humeri retained atotal of 37 LAGs, and the LAG number and LAG diameter measurements were positively correlated (p < 0.001, adj. r2 = 0.89) anddescribed by the following regression equation (Fig. 4a):LAG diameter ðmmÞ ¼ 1:628  LAG number þ 5:625
We used this equation as the ﬁrst order correction factor toestimate the number of LAGs lost (3 to 8) within the 72 larger
bones that did not retain an annulus or an innermost LAG exceeding 18.5 mm (Fig. 4a). The LAG numbers and LAG diameters fromthe directly aged group (n = 37 LAGs), and from the bones uponwhich the ﬁrst order regression equation was applied (n = 427
LAGs) were combined (total: 86 bones, n = 464 LAGs) in order togenerate the linear regression equation (p = 0.001, adj. r2 = 0.86)
used for the second order correction factor (Fig. 4b):

LAG diameter ðmmÞ ¼ 1:271  LAG number þ 6:652
This second order correction factor was used to estimate theLAGs lost (9 to 18) for the remaining 71 bones. Ages were estimated by adding the number of observed LAGs to the calculated
number of LAGs lost.
Age estimates were rounded to the nearest whole number, andwere adjusted for stranding date. The majority of BCP samples(81.5%) were collected during the summer months and required
no adjustment, whereas 29 bones (18.5%) required age adjustment.
The ﬁnal age estimates of the 146 juvenile turtles from the BCP

Fig. 2. Image of a humerus cross section from a loggerhead stranded in BCP that retained the annulus and for which age was determined to be three years.

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C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142

Fig. 3. Sample size distribution for stranded loggerhead turtles collected at Playa San Lázaro (a) used in the current study and (b) from Peckham et al., 2008.

ranged from three to 24 years (mean ± SD: 15 ± 4.2 years;
Fig. 5). There was no difference between average age ± SD when
the age adjustment was applied, compared to unadjusted ages
(15 ± 4.2 years). Of the 146 turtles, 50% were between the ages of
12 and 19 years old, and between 62 and 76 cm CCL in size.
While the oldest turtles aged in this study (age 24, n = 4) were
not necessarily the largest turtles, there was an overall trend ofincreasing age with increasing body size (n = 157, adj. r2 = 0.69,
p < 0.001, F1,155: 353.1) (Fig. 6).
4. Discussion
Here we present the ﬁrst empirical evidence for residency
duration and age distribution for endangered North Paciﬁcloggerheads foraging in the BCP. Skeletochronology allowed us toestimate the age range of turtles that lived and then dead-strandedin the BCP loggerhead hotspot. These ages provide an estimate of
the length of time turtles spend in this important foraging area,
critical information for conservation managers. Our results
demonstrate the value of analyzing anatomical aspects of deceased
animals to better address questions regarding conservation
ecology, life history, and the variable impact of threats experienced
throughout the lifetime of a species. In addition, it would not be
possible to obtain the results presented here from the study ofliving specimens alone.

4.1. Age distribution and population representation
Age estimates for turtles in this study were normally distributed, with no evidence of bimodal age distribution (Fig. 5), suggesting that the likelihood of experiencing ﬁshery interaction is not
age-dependent. The observed variation in turtle body size at agiven age (Fig. 6) reﬂects individual differences which could bebased on a number of factors, such as variable foraging patterns
or habitats, genetic plasticity, compensatory growth, and or
environmental stochasticity. Additionally, the number of LAGs inindividual humeri and the variation in size-at-age observed in thisstudy are comparable to ﬁndings from other skeletochronology
studies (see review in Avens and Snover, 2013).
To ensure that the length frequency of turtles used in this study
is representative of turtles found in the BCP, we compared the
distribution of turtle sizes used in this study to the size distributionof previous studies with larger sample sizes. The distribution ofbody sizes (CCL) for the BCP turtles used in this study is similar
to the normal size distribution presented in Peckham et al.
(2008), which assessed length frequency of nearly 2,000 loggerheads stranded in Baja California from 2003 to 2007 (Peckham
et al., 2008 mean 78 ± 9 cm CCL vs. this study mean 69 ± 11 cm
CCL; Fig. 3). As expected for turtles nearing reproductive maturity
in the BCP, the CCL of the largest turtles aged in this study(maximum 90 cm) approach the average size of nesting females

C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142

139

Fig. 4. The linear relationships between line of arrested growth (LAG) diameter and LAG number. The linear regression equations from these relationships were used for (a)the ﬁrst order correction applied to 72 bones, (humerus diameter (HD) range 17.3–27.5 mm, and CCL range 45–81 cm); and (b) second order correction applied to 71 bones(HD range 20.3–33.6 mm, and CCL range 51–90 cm).

Fig. 5. Estimated age distribution using skeletochronology analysis of 146 loggerhead turtles stranded on Playa San Lázaro. Estimated age is equal to the sum of the numberof retained LAGs and the number of resorbed LAGs calculated by applying correction factor equations described in the text.

observed in Japan (91 cm; Hatase et al., 2004), and Peckham et al.
(2008) found only 9 (of 2000) turtles in the BCP larger than
91 cm.
Further, the turtles aged in the present study were largely, if not
exclusively, composed of loggerheads that had interacted with thelocal artisanal ﬁshery, a primary conservation concern for thispopulation (Peckham et al., 2008). Fishery interaction is likely as
there were no obvious signs of other injuries, illness, or impact
from pollution on carcasses. There was no indication of asize-based bias in turtles dead-stranding at this site that would
be related to body size (net escape ability, ﬁshing gear size, etc.)
or behavior (foraging location, depth, prey preference, net

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C.N. Turner Tomaszewicz et al. / Biological Conservation 186 (2015) 134–142

Fig. 6. Range of curved carapace length (CCL, cm) for estimated age of stranded loggerhead turtles from the central North Paciﬁc (CNP) (n = 11) and the Baja California
Peninsula (BCP) (n = 146).

detection or avoidance, etc.). We acknowledge that if behavioral
differences that affect bycatch rates exist among turtle size classes(e.g. shallower dive depths of smaller turtles) there could be anunderrepresentation of certain size classes. However, to date, nopublished data exists supporting such size-based differences, butwarrants further study. Therefore, we believe the approach appliedin this study is appropriate to investigate the demography ofloggerheads in this BCP sink habitat.
4.2. Loggerhead residency duration
Our skeletochronology results indicate that North Paciﬁc loggerheads may remain in the bycatch hotspot of the BCP for at least
20 years. The youngest and smallest BCP turtles included in thisstudy (three to six years old and 29–45 cm CCL, respectively)
represent the earliest age and smallest size at which loggerheads
are likely to recruit to nearshore foraging habitats in the eastern
Paciﬁc. Likewise, the oldest and the largest turtles (24 years old
and 90 cm CCL, respectively) encountered in this study represent
the oldest age and largest size at which loggerheads are likely toremain in the east Paciﬁc. Thus, if we subtract the minimum age
at recruitment to the BCP from the maximum age observed in
the BCP, we can estimate the maximum residency duration.
Duration estimates may differ according to variations inindividual behavior, climatic conditions, and ﬁshing effort. For
example, actual BCP duration may be longer than 20 years giventhat all turtles in this study were stranded, and therefore had diedprior to having the opportunity to emigrate back to the western
Paciﬁc. In addition, the largest turtles included in this study were
not the largest North Paciﬁc loggerheads ever found in this region(90 cm CCL this study vs. 98 cm CCL; Peckham et al., 2007).
Similarly, immigration and emigration may vary amongindividuals, with some arriving in the eastern Paciﬁc at an older
age or larger size, and some leaving the eastern Paciﬁc at a younger
age or smaller size, thereby potentially reducing the estimatedresidency duration.
4.3. Age-at-maturation
The oldest BCP turtle aged in this study was 24 years old.
Based on data from satellite and ﬂipper-tagged large turtles fromthe BCP (Resendiz et al., 1998; Nichols et al., 2000; Peckham
et al., 2007), the migration duration from the eastern Paciﬁc backto nesting beaches in the western Paciﬁc is approximately one
year. Therefore, we estimate that reproductive maturity and initial

nesting in the western Paciﬁc begins at >25 years of age. Previous
age-at-maturation studies have yielded similar ﬁndings and werebased on body size at ﬁrst nesting, remigration intervals, andclimate forcing models (Kamezaki et al., 1995; Hatase et al., 2004;
Van Houtan and Halley, 2011).
Our results support current knowledge on general sea turtle life
history patterns and age-at-maturity estimates. For Atlantic
loggerheads, age-at-maturity has been approximated at 10–
40 years by a variety of methods including mark recapture, length
frequency, and skeletochronology studies (see reviews: Heppell
et al., 2003; Avens and Snover, 2013). Estimates for age-at-maturity
for Paciﬁc loggerheads include 36 years for the South Paciﬁc
population using mark-recapture techniques (Frazer et al., 1994),
and 25 years for the North Paciﬁc population using climate
forcing models that incorporated observed Japan nesting numbers
and trends (Van Houtan and Halley, 2011).

4.4. Implications for demographic impacts and conservation
management
The application of loggerhead turtle BCP residency duration to
key sea turtle demographic parameters indicate that the
population-level impact of this loggerhead mortality is extreme.
Current estimates for annual mortality rate in this region are11% (Seminoff et al., 2014). Using this value, we can estimate
survivorship for juveniles foraging in the BCP at varying residency
durations (Table 1). North Paciﬁc loggerheads spending 20 years inthis area have a predicted survivorship rate of 10%. Survivorshipincreases to 30% if turtles spend half as many years (10 years) inthe BCP. However, if turtles remain in this region for 25–30 years,
predicted survivorship drops below 5%.
These are bleak odds for the tens of thousands of juvenile
loggerheads known to inhabit this eastern Paciﬁc developmental

Table 1
Survivorship of loggerhead sea turtles at varying residency duration times off the
Paciﬁc coast of the Baja California Peninsula (BCP) based on 11% annual mortality rate
(Seminoff et al., 2014). Stage survivorship = annual survivorship^residency duration.
Residency duration (years)

Annual survivorshipStage survivorship

5
10
20
25
30

0.89
0.89
0.89
0.89
0.89

0.56
0.31
0.10
0.05
0.03

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foraging area. Future research that quantiﬁes the proportion ofloggerheads from the entire North Paciﬁc population utilizing the
BCP foraging grounds will better elucidate the full impact that thisregional bycatch-related mortality has on the recovery ability ofthe population. Yet even without the quantiﬁcation of this value,
a long, multi-decadal residency in this region of low survivorshipwill signiﬁcantly impact the recovery ability of North Paciﬁcloggerheads.
The most recent abundance estimate of ca. 43,000 BCP foragers,
compared with population estimates based on annual nesting
abundance in Japan, suggests that a signiﬁcant proportion ofjuvenile North Paciﬁc loggerheads spend time foraging in the BCP
region (Seminoff et al., 2014). Furthermore, evidence from thepresent study shows these turtles could spend >20 year in the
BCP, a substantial amount of time to be exposed to high rates of
bycatch. Further, the majority of turtles in this region are large
juveniles, a life stage known to have high reproductive value aswell as high sensitivity and therefore impact on the overall
population growth rate (Crouse et al., 1987; Crowder et al., 1994).
High mortality rates experienced by juvenile turtles are known
to contribute to declining population levels (Crowder et al.,1994), as have been observed for this loggerhead population overthe past several decades (Kamezaki et al., 2003; Peckham et al.,2007; NMFS and USFWS, 2011).
Compounding the already difﬁcult situation for loggerheads inthis region, an unprecedented 841 turtles were observed deadstranded during 2012 (PROFEPA, 2012), a stark contrast with theannual average of 477 strandings (January through December;
2003–2007) (Peckham et al., 2008). The January 2013 identiﬁcationof Mexico by the US Government under the High Seas Driftnet
Moratorium Protection Act for a failure to adopt a regulatory
program that is comparable to the United States to end or reduce
bycatch taking into account differing conditions emphasizes theinternational urgency to address this conservation issue (NMFS,
2013). Wildlife conservation efforts are often most effective when
focused on habitats where there is a large impact on the
population’s survival rate and reproductive value, and these areasof high conservation priority are frequently identiﬁed sinkhabitats. The BCP foraging ground in the eastern Paciﬁc represents
a sink habitat for the endangered North Paciﬁc population ofloggerhead sea turtles and continued international management
is necessary to ensure its recovery.
Acknowledgements
We acknowledge the many partners in Mexico for multiple
years worth of sample collection and permitting by members of
Grupo Tortuguero de las Californias and Proyecto Caguama,
especially Victor and Vladimir de la Toba and Jesus Lucero. We also
thank Erin LaCasella, Robin LeRoux, Joel Schumacher, Camryn Allen,
and Matt Leslie for assistance with sample permitting, processing
and publication prep, as well as Kerri Danil, Nicky Beaulieu,
Michelle McCartha, Anji Shakya, Emily Chou, and Rosario
Marroquin Flores for assistance in the lab. This work was supported
by NOAA Fisheries, and C.T.T. was supported by the University ofCalifornia San Diego (UCSD), NIH T32 GM007240 Cell andMolecular Genetics Training Program, Jeanne Messier Memorial
Fellowship, ARCS Foundation Scholarship, and a Hearts de Vite
Research Grant. The shoreline stranding survey at Playa San
Lázaro was funded from 2003 to 2011 with support from the US
Fish & Wildlife Service, NMFS-SWFSC, Western Paciﬁc Fisheries
Management Council (NOAA Grant FNA05NMF4411092), theDavid and Lucile Packard Foundation. Fieldwork and sample processing by Grupo Tortuguero de las Californias was also supported
by C. & H. Shea, B. & S. Turner, D. & C. Yohn, T. & N. Tomaszewicz, M.
Tomaszewicz, T. Dunbar, J. & E. Paisley, K. & E. Roeland, S. Baird, F. &141

D. O’Cathain, S. Bakeman, H. & M. Diller, and C. Kopp. All research
activities and permits were authorized by the Mexican government
through SEMARNAP and SEMARNAT permits 150496-213-03,
280597-213-03, 190698-213-03, 280499-213-03, 280700-213-03,
SGPA/DGVS/002 4661, SGPA/DGVS/10358, SGPA/ DGVS/03501/06,
SGPA/DGVS/03406/07, SGPA/DGVS/03481/09, SGPA/DGVS/04990/10,
and SGPA/DGVS/04568/11. All exported and imported CITES regulated samples were authorized by the Mexican government
through export permit numbers MX-58124 and MX-64301, andthe United States government through import permit numbers
11US844694/9 and 12US844694/9.

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