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Research

Identifying global favourable habitatfor early juvenile loggerhead sea turtles
Cheryl S. Harrison1,2,3, Jessica Y. Luo1,4, Nathan F. Putman5, Qingfeng Li6,
Pooja Sheevam2,7, Kristen Krumhardt1,2, Jessica Stevens3
and Matthew C. Long1
1National Center for Atmospheric Research, Boulder, CO 80305, USA
Institute of Alpine and Arctic Research, University of Colorado, Boulder, CO 80303, USA
3
School of Earth Environmental and Marine Science, University of Texas, Rio Grande Valley, Port Isabel,
TX 78578, USA
4
NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA
5
LGL Ecological Research Associates, Bryan, TX 77802, USA
6
Laramie High School, Laramie, WY 82070, USA
7
Department of Geological Sciences and Engineering, University of Nevada, Reno, NV 89557, USA
2

Cite this article: Harrison CS, Luo JY, Putman
NF, Li Q, Sheevam P, Krumhardt K, Stevens J,
Long MC. 2021 Identifying global favourable
habitat for early juvenile loggerhead sea
turtles. J. R. Soc. Interface 18: 20200799.
https://doi.org/10.1098/rsif.2020.0799

Received: 2 October 2020
Accepted: 29 January 2021

Subject Category:Life Sciences–Physics interface
Subject Areas:
biogeochemistry, biogeography, environmental
science
Keywords:
Caretta caretta, loggerhead, dispersal, pelagic
habitat, ocean current, Earth system modelling

Author for correspondence:
Cheryl S. Harrison
e-mail: cheryl.harrison@utrgv.edu

CSH, 0000-0003-4544-947X; JYL, 0000-0002-0032-9370; NFP, 0000-0001-8485-7455;
KK, 0000-0002-8980-056X; JS, 0000-0002-1132-3070; MCL, 0000-0003-1273-2957
Loggerhead sea turtles (Caretta caretta) nest globally on sandy beaches, withhatchlings dispersing into the open ocean. Where these juveniles go andwhat habitat they rely on remains a critical research question for informing
conservation priorities. Here a high-resolution Earth system model is used todetermine the biophysical geography of favourable ocean habitat for loggerhead sea turtles globally during their first year of life on the basis of ocean
current transport, thermal constraints and food availability (defined here as
the summed lower trophic level carbon biomass). Dispersal is simulated
from eight major nesting sites distributed across the globe in four representative years using particle tracking. Dispersal densities are identified for all
turtles, and for the top 15% ‘best-fed’ turtles that have not encountered metabolically unfavourable temperatures. We find that, globally, rookeries are
positioned to disperse to regions where the lower trophic biomass is greatest
within loggerheads’ thermal range. Six out of the eight nesting sites areassociated with strong coastal boundary currents that rapidly transporthatchlings to subtropical–subpolar gyre boundaries; narrow spatial
migratory corridors exist for ‘best-fed’ turtles associated with these sites.
Two other rookeries are located in exceptionally high-biomass tropicalregions fuelled by natural iron fertilization. ‘Best-fed’ turtles tend to be
associated with lower temperatures, highlighting the inverse relationshipbetween temperature and lower trophic biomass. The annual mean isotherms between 20°C and the thermal tolerance of juvenile loggerheads
are a rough proxy for favourable habitat for loggerheads from rookeries
associated with boundary currents. Our results can be used to constrain
regions for conservation efforts for each subpopulation, and better identify
foraging habitat for this critical early life stage.

1. Introduction

Electronic supplementary material is available
online at https://doi.org/10.6084/m9.figshare.
c.5305517.

Conservation of migratory marine animals presents a number of challenges owing
to their complex life cycles, vast distances travelled and the difficulty of obtaining
information on their spatio-temporal distributions. Sea turtles epitomize this problem; like many migratory marine vertebrates, the majority of sea turtle species are
endangered or threatened (e.g. [1]). Loggerhead sea turtles (Caretta caretta) nest on
sandy beaches from temperate to tropical latitudes; upon hatching they migrate
offshore to escape the heavy predation that occurs in coastal waters (e.g. [2,3]).
Small loggerheads spend five or more years in the open ocean before returning
to coastal habitats; upon reaching maturity one to three decades later, they largely© 2021 The Author(s) Published by the Royal Society. All rights reserved.

Table 1. Simulated loggerhead rookeries, including location and hatching season. Sites are plotted in ﬁgure 1.

2

latitudelongitude

hatching season

1

Japan

30.3

130.5

15 July–15 Oct

2
3

FloridaCape Verde

25.9
16.1

−80.1
−22.9

1 July–30 Sep
1 Sep– 30 Nov

4
5

Oman
west Australia

20.3
−25.8

58.7
113

1 Apr–30 Jun
1 Jan–30 Mar

6
7east Australia
Brazil

−24.7
−12.7

152.4
−37.9

1 Jan–30 Mar
1 Dec–30 Mar

8South Africa

−27.4

32.7

1 Jan–30 Mar

return to the vicinity of their natal site to reproduce (e.g. [4]).
While conservation efforts have led to increases in nesting forseveral populations in recent decades [5], many remain threatened or endangered [6]. Key questions about turtle life
histories needed to inform conservation efforts, and in particular our ability to predict climate change impacts, remainunanswered [1,6–10]. Because sea turtle population abundance
appears to be strongly related to the successful dispersal fromnesting beaches to oceanic habitats [11,12], one of the mostimportant questions is the dispersal fate of hatchlings from
natal beaches in their first year of life [13].
Early juvenile turtle dispersal is termed the ‘lost years’,
owing to the post-hatchling disappearance of juveniles fromcoastal waters where they are easily observed [14,15]. There
are many critical gaps in our understanding of the biogeography of sea turtles in early juvenile stages, including:identifying key pelagic foraging habitats, what parametersdelineate and control spatio-temporal variation in pelagic habitats and how nesting sites connect to these foraging grounds[1,10]. Turtle hatchlings are difficult to observe owing to theirsmall size, rapid growth rates and high mortality; because ofweight constraints, satellite tracking only becomes feasible
when they are many months old [16–19]. While genetic studies
have made great advances in understanding the connection
between rookeries and late-juvenile foraging grounds [20,21],
details of where hatchlings go in the first year and what pelagic
habitat they rely on remain elusive. Understanding the connection between rookeries and favourable pelagic habitat is criticalfor managing this most enigmatic life stage, and it is here that
ocean models have great utility.
Ocean models are increasingly being used to support andinform turtle management and in situ studies. Particle tracking, following simulated water trajectories through time,either as passive transport or with biologically motivatedsimulated swimming, has been used to model the movements of a number of sea turtle species at different life
stages across various ocean basins to answer a variety of
research questions (e.g. [13,22–28]). Modelling particle trajectories requires ocean velocity representation of mesoscale(10–100 km) features such as jets and eddies that are integral
to dispersal [29,30]. However, physics-only ocean models do
not represent the limitations on oceanic habitat due to foodavailability, necessitating models that include ocean ecosystem simulation. Running eddy-resolving simulations at the
global scale with ocean biogeochemistry is computationallyexpensive; such simulations are just beginning to be used
for biogeochemical and ecological research (e.g. [31–34]).

The goal of this study is to examine loggerhead dispersal
from eight major nesting sites across the globe [35,36] and identify key pelagic habitat for juveniles in their first year based on: (i)transport of turtles by ocean currents, (ii) sea surface temperatures (SSTs) within a physiologically acceptable range, and (iii)likely food availability for turtles. For the first time, we use aglobal high-resolution Earth system model with ocean biogeochemistry to simulate global loggerhead juvenile dispersal
and the along-path food availability. We estimate food availability for juvenile loggerheads along their dispersal paths bysumming phytoplankton and zooplankton biomass fields inthe model, termed ‘bioC’ (see Methods). This methodology
allows us to simulate where turtles with the greatest foraging
opportunities within a favourable thermal range are likely to
be concentrated during their first year, and thus what oceanographic conditions should contribute to increased fitness forloggerheads during the ‘lost years’.

2. Methods
Hatchling dispersal was simulated from eight loggerhead nestingsites distributed globally (table 1 and figure 1), by selecting thesite with the largest nesting abundance within each region[5,36]. The Mediterranean Sea was excluded owing to poor representation in the global ocean model. Particles representing
hatchling turtles were released over the hatching season (lasting
3–4 months) from each nesting location (table 1) on a regular 0.1°
grid, extending in a 1° box centred on the nesting beach. Thisinitial wide horizontal spread is intended to account for offshore
directed swimming during the initial post-hatching ‘frenzy’
period [24,37]. Particles were released throughout the hatchingseason for each site (table 1), resulting in approximately 2500 particles released each year from each site, with variation due to thedifferent hatching season durations and coastline orientations.
Hatchlings were simulated over the first year as passive particles,
assuming that after an initial post-hatching frenzy period they are
passively carried by ocean surface currents. Although models indicate that swimming behaviour can substantially contribute to net
movement and the processes influenced by it (e.g. mortality,
growth rates, distribution, etc. [22–24,28,38–40]), our aim in thisstudy was to identify ‘optimal habitat’; that is, locations that arehighly productive and require no (or very little) energetic cost toreach. Such an approach is useful for producing a ‘null hypothesis’for the distribution of marine organisms and shows how ocean current transport contributes to observed spatio-temporal variation in
the distribution and abundance of sea turtles [41–43].
Ecological dispersal simulations use ocean velocity field datafrom an ocean model or remote sensing product, combined with

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60° W

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50° N
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a particle integration model that tracks where the organism inquestion is transported by these velocities. Here velocities weretaken from a high-resolution (0.1°, nominally 10 km) global
ocean simulation with biogeochemistry, the Community Earth
System Model with Biogeochemical Elemental Cycling (CESMBEC). This ocean model simulation was forced by the CoordinatedOcean-Ice Reference Experiments (CORE-I) ‘normal year’ dataset[44], such that the atmospheric forcing fields repeated each year
and variability is entirely internal to the ocean (eddy variability).
The BEC ecosystem model includes three phytoplankton functional types (small phytoplankton, diatoms and diazotrophs)
and one zooplankton functional type, as is common for Earthsystem models (e.g. [33,45]). The horizontal model resolution iseddy resolving globally, the state of the art for computationallyexpensive global biogeochemically enabled models (e.g. [31,33]).
The ocean model simulation was run for 5 years, with average history files written every 5 days. The CESM-BEC model has been
extensively validated with global productivity, export and biogeochemical patterns (e.g. [46]). The high-resolution CESM ocean
simulation used here compares well with observations of physicalparameters such as temperature (electronic supplementarymaterial, figure S1), observed eddy tracks [47] and biological parameters such as chlorophyll [32,33], and net primary productivity(NPP; model compared with satellite-derived NPP in electronic
supplementary material, figure S2).
Virtual loggerhead hatchlings (particles) were released at thesame frequency as the ocean model velocity output, every 5 days,
during each hatching season over the ocean model run, resulting
in four 1-year hatchling simulations for each nesting site. The
Connectivity Modelling System (CMS; [48]) was used to integrate
particle trajectories using the simulated ocean surface velocities
and modified to save food proxies from CESM-BEC, interpolated
daily along the trajectory paths, along with ocean SST. CMS
interpolates the ocean velocity, temperature and food proxies inspace and time and integrates particle trajectories using standard
methods, bilinear for interpolation and fourth-order Runge–
Kutta for integration [48], and has been used extensively in awide range of dispersal studies (e.g. [49–51]).
Loggerhead turtles are poikilothermic, with only a small ability to regulate their internal body temperature, such that watertemperatures below around 10–15°C are metabolically unfavourable; older juveniles and adults are largely observed in much

warmer waters [25,52–54], while hatchlings behave normally inwaters as cold as 9°C [55,56]. Trajectories that passed into regions
where the SST was less than 10°C were retained in the main
sample, to provide an indication of where hatchlings may be carried, but were considered ‘frozen’, i.e. outside of their thermal
tolerance limit, and excluded from the subsample of ‘best-fed’
trajectories (see below). Sensitivity analyses were conducted inwhich this thermal threshold was also considered at 12°C and
15°C. Particles that beached (i.e. stranded) at any time during
the first year were considered unsuccessful and not analysed.
This treatment of beached particles accounts for the limited
potential for small turtles to survive in near-shore waters. The
number of particles excluded owing to temperature exposureand stranding varied from site to site, and was often significant,such that the total number of trajectories analysed from each site
for the 10°C threshold was reduced to between 1000 and 6000
total over the 4 years. Sensitivity tests releasing more particles
did not significantly change our results.
Representing global prey distributions for sea turtles is challenging. Loggerhead juveniles are observed to have a diverse
diet heavy on gelatinous zooplankton (e.g. [57]), feeding at
trophic levels not well observed or currently represented inmost Earth system models [58]. Models of NPP based on satellite observations of ocean colour represent the rate of carbon
fixation by phytoplankton per unit area, i.e. phytoplankton production (see electronic supplementary material, figure S2; e.g.
[59,60]). These NPP estimates have often been used as a foodproxy in turtle studies; in terms of observation-based estimates,
NPP is arguably the best available for sea turtle food abundance, as meso-zooplankton and gelatinous zooplankton
observations are fairly sparse [61,62]. However, turtles eat biomass and not the phytoplankton production represented by
NPP, production which is often quickly recycled and not translated into increased biomass. Using the Earth system model
biogeochemical output, we are not limited to observational
measures such as NPP as a food proxy source, and so we constructed a metric that better captures the ability of regional
ocean ecosystems to generate and retain biomass, bioC, thetotal carbon biomass of all simulated phytoplankton and zooplankton (units of gCm−2). For the sake of completeness, wehave also included some evaluation of the model skill in
reproducing observed NPP patterns.

J. R. Soc. Interface 18: 20200799

Figure 1. Loggerhead rookeries, simulated mean ocean conditions and favourable pelagic habitat. Simulated rookeries (black squares; table 1); annual mean totalplanktonic biological carbon biomass (bioC; colourmap) within loggerhead thermal limits; annual mean SST isotherms (black lines), with the 10°C isotherm highlighted (solid black line), representing the lowest thermal tolerance assumed for loggerhead hatchlings. Overlaid are ‘best-fed’ dispersal envelopes for the 10°C
(orange), 12°C (red) and 15°C (purple) thermal thresholds. For some sites, there is no or little change in dispersal with the changing thermal threshold (table 2).
Note that turtle dispersal is simulated in the time-varying ocean, so that dispersal envelopes may exceed the annual mean isotherms.

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0.2

1.00

1.25

0.3

0.4

(b)

1.50

1.75

0.5
0.6
NPP (gCm–2 d–1)

0.7

2.00
2.25
bioC (gCm–2)

0.8

2.50

0.9

1.0

2.75

3.00

Figure 2. (a) Simulated annual mean net primary productivity (NPP), and (b) total depth-integrated planktonic carbon biomass (bioC), shown at model resolution(approx. 0.1°). NPP is higher in tropical biomes, while bioC is greatest at high latitudes.
Total plankton carbon biomass (bioC) and NPP have distinct
spatio-temporal structures (figure 2; electronic supplementarymaterial, movie). Globally, annual mean NPP is highest insmall phytoplankton-dominated tropical regions that havelower zooplankton biomass and bioC than higher latitude systems. These highly recycling biomes have low trophic
efficiency, leading to low biomass and low abundance at midtrophic levels, and thus low forage for higher trophic levels,
making NPP a poor proxy for loggerhead food availability. By
contrast, mean NPP is relatively low in subpolar regions ( poleward of approximately 40°), while biomass is high, resulting
from increased phyto- to zooplankton trophic efficiency in thecolder, more nutrient-rich waters and large standing stocks ofzooplankton throughout the year [60,63]. Here again NPP is
not a good indication of potential food biomass. Validation
data for biomass are limited, but we note that zooplankton biomass, as represented in the COPEPOD database (https://www.
st.nmfs.noaa.gov/copepod/), has similarly high values to bioCin subpolar biomes [61,63].
To visualize the dispersal of those loggerheads that have thehighest probability of survival after the first year, we constructed
dispersal distributions for ‘best-fed’ juveniles. For this, we
assumed that fitness is cumulative, determined by the sum offood availability (bioC) along the turtles’ trajectory for the firstyear. From these distributions, we designated the top 15% fromthe cumulative food availability as ‘best-fed’. The impact ofthermal threshold on ‘best-fed’ dispersal distribution medianvalues was tested using an ANOVA over the 4 years for each site.

2.1. Model limitations
The global model used here, while state of the art, has biases pertinent to our findings. The Gulf Stream, Kuroshio and Agulhas
retroflection currents are too far poleward, seen as a warm
winter SST bias in electronic supplementary material, figure S1,
a common bias for western boundary currents (WBCs) [64,65],
and are associated in this simulation with an approximately 2°
C cold bias on their poleward side (electronic supplementarymaterial, figure S1). This likely affects our estimates of juveniles
encountering cold temperatures and suggests our simulated
cold thermal threshold of 10°C could be closer to 12°C for thein situ temperatures of the poleward flank of these boundary currents. Further observational and better validated regionalmodelling studies are needed for accurate assessment of thesegyre boundaries in relation to turtle habitat suitability.
Even at 10 km resolution, coastal physical processes controlling
dispersal and nutrient delivery are poorly represented, as they are
mediated by very near-shore circulation and wind structure notresolved here [58,66,67], thus we have restricted our analysis tonon-beached hatchlings and parameterized the frenzy swimming
period instead of simulating it directly. Additionally, river nutrient
fluxes, similar to other Intergovernmental Panel on Climate Change

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3.1. Oceanographic geography of loggerhead nestingsites
A priori, simulated rookery locations do not appear favourable with respect to food availability for oceanic-stage
hatchlings (figure 1). The majority are positioned near oligotrophic gyres where plankton biomass is globally lowest(figure 2b), and hatchlings are observed to quickly leave productive coastal waters, where predation is thought to behighest (e.g. [14]). Instead of relying on local food availability,
we find that the location of many loggerhead nesting sites
facilitates the dispersal of hatchlings towards high-biomass
regions (figures 1 and 3). While it has long been noted thatmajor loggerhead nesting sites are associated with boundary
currents [11,70], here we can provide a mechanistic context
combining transport and food availability to explain thisassociation.
Five of the eight loggerhead nesting sites simulated areassociated with major WBCs: the Kuroshio (site 1), Gulf
Stream (site 2), East Australian (site 6), Brazil (site 7) andAgulhas Currents (site 8). These nesting sites are locatedinshore of low-production subtropical gyres; WBCs movehatchlings rapidly poleward and into the productive subtropical–subpolar gyre boundaries, where biomass is thehighest within loggerheads’ thermal range (figure 1). Every
major WBC has a loggerhead nesting beach in a similar
oceanographic setting: on the western flank of the poleward-flowing current where it is closest to shore, optimallyplaced for rapid advection to these gyre boundaries, andthese nesting sites represent the most successful in each
WBC region. A sixth nesting site is associated with the Leeuwin Current off west Australia (site 5), a singular easternboundary current in that it is poleward flowing instead ofequatorward, owing to strong onshore flow, which limits
upwelling (e.g. [26,71]). Thus, the Leeuwin functions much
like a WBC, moving hatchlings poleward into more productive, high-biomass subantarctic waters (figure 1; [26]).
Additionally, the Oman site (site 4) is associated with the Arabian Current, a relatively weak boundary current thattransports hatchlings out of the near-shore and into the
Arabian Sea during their first few weeks (figures 1 and 2b).
While the WBC nesting sites disperse to regions of highfood abundance, risk of exposure to cold, metabolicallyunfavourable temperatures can be high (table 2 and figure 1).
In this simulation, Japan and Florida have the highest rate of
exposure to temperatures below 10°C, ranging between
40–58% and 36–59%, respectively, with interannual differences

3.2. Ocean biophysical constraints on hatchling foraging
success
Dispersal distributions of simulated turtles in the top 15% ofalong-track integrated biomass, labelled here as ‘best-fed’,
depict where pelagic habitat is most favourable for the juveniles (figures 1 and 3b). The difference between ‘best-fed’ andtotal dispersal distributions varies by nesting site (figure 3).
From low-dispersal tropical sites (sites 3 and 4), the ‘bestfed’ distributions are more similar to the total dispersal distributions (figure 3a), following the spatially and temporally
consistent high food abundance near these rookeries. For
nesting sites associated with boundary currents, ‘best-fed’
distributions are predominantly skewed poleward, towards
higher food biomass at the subtropical–subpolar gyre boundaries and away from the centres of oligotrophic subtropicalgyres.
‘Best-fed’ distributions have significantly different temperatures relative to total dispersal distributions ( p < 0.05 in
all sites using a Kolmogorov–Smirnov test with 100 bootstrapped samples from the ‘best-fed’ trajectories and fromall trajectories; figure 4). For the 10°C thermal threshold, sixsites have significantly cooler ‘best-fed’ distributions, highlighting the correlation of cool waters, upwelling-driven
nutrient availability and food abundance. For example,
despite the large overlap in total and ‘best-fed’ distributions,the ‘best-fed’ turtles from Oman (site 4) spend more time in
the western and central Arabian Sea (figure 3), where upwelling and monsoon-driven vertical mixing provide higher
productivity, along with cooler temperatures [74,75]. Florida
and Japan have significantly warmer distributions for ‘bestfed’ turtles than all releases (figure 4b). Both of these nestingsites are subject to high rates of encountering temperatures
below 10°C (table 2), constraining the ‘best-fed’ distributions
to warmer waters.
The impact of changing the thermal tolerance on the ‘bestfed’ distributions depends on the nesting site and the5

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3. Results and discussion

driven by eddy variability. When hatchlings are restricted towarmer thermal thresholds, the proportion of cold-stressed
hatchlings increases to 67–77% and 44–67% for 12°C and to
87–94% and 73–84% for 15°C, respectively. Similarly, while
simulated cold exposure is low for the South African rookery
at 10°C (3–9%), it more than triples for 12°C (22–33%), anddoubles again for 15°C (50–62%). Other boundary current
associated nesting sites, such as Brazil and east Australia,
have no exposure to temperatures below 10°C, and very
little danger of thermal stress at warmer thresholds (0–5% at15°C). The two tropical sites in Oman and Cape Verde Islands,
along with the western Australian rookery, have no thermal
limitation at any threshold.
The two tropical sites not associated with major boundary
currents, Cape Verde Islands (site 3) and Oman (site 4), aresimilar in that they feature high food abundance, warm temperatures over the first year and low or moderate dispersal
distances over the first year (table 2 and figure 4). These nesting sites are located in regions with exceptionally highbiomass for tropical waters (figure 1), such that integrated
biomass is as high as or higher than that for many of theboundary current associated sites over the first year (table 2
and figure 4). Exceptional productivity in these two regions
is driven by a combination of Aeolian iron fertilization andcoastal upwelling [72,73].

royalsocietypublishing.org/journal/rsifclass Coupled Model Intercomparison Project Phase 5 (CMIP5)
models [68], are not simulated. The result of these missing nutrient
sources is a low-productivity model bias in coastal regions whereriver nutrients (e.g. Amazon, Mississippi) and upwelling (e.g. eastern South Atlantic) sources are important (electronic
supplementary material, figure S2). We note that the model agrees
well with observation-based productivity estimates off-shelf (electronic supplementary material, figure S2), so that the pelagic
favourable turtle habitat found here should be quite robust. Since
loggerhead hatchlings are observed to rapidly swim offshore toleave coastal waters, a behaviour that is likely to reduce predation
risk [69], on-shelf productivity is arguably not the most importantfactor controlling their survival in the first year.

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PDF

Figure 3. Simulated loggerhead dispersal. (a) Two-dimensional probability distribution functions (PDF) of dispersal (colourmaps) from each rookery (orange squares)
for all non-stranded particles. (b) ‘Best-fed’ (top 15%) dispersal distributions, which exclude simulated hatchlings that have encountered temperatures less than 10°C;
extent of total dispersal (black contours) is shown for comparison. Annual mean isotherms (grey) as in figure 1. ‘Best-fed’ dispersal envelopes for the 12°C and 15°C
thermal thresholds are shown in figure 1 and the probability distributions in electronic supplementary material, figure S3.

magnitude of the thermal threshold (table 3, figures 1, 4 and 5
and electronic supplementary material, figure S3). With all
thermal thresholds, there is no impact on ‘best-fed’ distributions for the two tropical nesting sites (table 3, figures 1,
4 and 5), as simulated encounter temperatures for Oman
and the Cape Verde Islands are always well above 20°C
(figure 4b). Additionally, the ‘best-fed’ dispersal distributions
for the two Australian and the Brazil sites do not significantly
depend on temperature (ANOVA, F2,3 < 17, p > 0.05 for all
three sites). Using a 15°C thermal threshold significantly
affects the ‘best-fed’ dispersal distributions, in both latitude
and longitude, for the Japan, Florida and South Africa nesting sites (ANOVA, F2,3 > 17, p < 0.05 for all sites; table 3 andfigure 5). For the Japan release site and a 15°C thermal
threshold, a large proportion of ‘best-fed’ hatchlings are
retained in a persistent Kuroshio meander off the Japanese
coast (electronic supplementary material, figure S3b), resulting in the dispersal envelope median shifting over 20°
westward (table 3 and figure 5) and reducing the median dispersal distance by over 1000 km (figure 4c). The Florida ‘bestfed’ dispersal distribution for 15°C is also shifted west andsouth (figure 5; electronic supplementary material, figure S3),
resulting in reduced dispersal distance (figure 4c). For theSouth African site, the 15°C ‘best-fed’ dispersal medianmoves over 20° west (table 3) and from the Indian to the
Atlantic Ocean (figure 5). For all of these last three sites,

the restriction to warmer waters leads to a decrease in food
exposure for ‘best-fed’ hatchlings over the first year (figure 4).
Changing the thermal threshold from 10°C to 12°C has less
impact for these sites, with a large overlap in the ‘best-fed’envelopes (figure 2) and less change in food exposure,mean temperature and distance travelled (figure 4) andmedian dispersal (table 3 and figure 5).

3.3. Defining global favourable pelagic juvenile
loggerhead habitat
A posteriori, favourable pelagic juvenile loggerhead habitat in
the first year can be defined by comparing average ocean conditions with ‘best-fed’ turtle dispersal envelopes (figure 1).
Here, we find that rookeries are positioned globally to disperse to the highest biomass regions within loggerheads’
thermal range. This is accomplished either by the nestingsites being located in high-biomass regions (sites 3 and 4)
or by rapidly dispersing to such regions via boundary currents (all other sites). In the latter case, pelagic favourable
habitat can be characterized by isotherms associated withsubtropical–subpolar gyre boundaries. The annual mean isotherm range from the loggerhead cold threshold (e.g. 10°C) to
20°C is a good thermal proxy for favourable loggerhead
hatchling habitat for all boundary current associated nestingsites, as indicated by the ‘best-fed’ dispersal envelopes after

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Brazil S Africa

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0
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Figure 4. Intersite statistics for (a) bioC integrated over the first year, (b) average SST over the first year and (c) distance from nesting site at the end of the firstyear. Combined distributions for the four simulation years are shown for all releases (grey), and ‘best-fed’ distributions at the 10°C (gold), 12°C (red) and 15°C
(purple) thermal tolerance thresholds.
Table 2. Summary model results for each nesting site, taken along trajectories for the ﬁrst year, combining four dispersal years. SST is the median SST acrossall releases and all times, bioC is the median of the summed along-track lower trophic carbon biomass and distance is the median of the great circle distancefrom the nesting site at the end of 1 year. Proportion ‘frozen’ is the per cent of releases that encounter temperatures below the given thermal threshold (10°C,
12°C and 15°C) at any time in the ﬁrst year, with ranges for interannual variability.
proportion

proportion

proportion

SST

bioC

‘frozen’ (%)‘frozen’ (%)‘frozen’site no.

location(°C)(gCm−2)

distance (km)for 10°C

for 12°C(%) for 15°C

1

Japan

16

640

4310

40–58

67–77

87–94

2

Florida

19

560

3740

36–59

44–67

73–84

3

Cape Verde

24

620

2420

0

0

0

4

Oman

26

720

810

0

0

0

5

west Australia

22

680

1060

0

0

0

6

east Australia

22

750

1660

0

0–1

0–5

7

Brazil

26

540

2410

0

0

0–3

8

South Africa

20

910

2650

3–9

22–33

50–62

the initial narrow corridor stage (figure 1). Indeed, themajority of the ocean area with high biomass is associatedwith waters colder than 20°C.
For any thermal threshold used, the ‘best-fed’ distributions from boundary current sites are always skewed
towards the thermal threshold, where ocean bioC is highest(figures 2 and 5; electronic supplementary material,
figure S3). Thus, using a warmer thermal threshold does

not modify the main results that favourable pelagic habitatis largely at the subpolar–subtropical gyre boundaries, but
simply shifts the favourable habitat equatorward.
Adult loggerheads are usually found in waters above
12°C (e.g. [53,54]), but acclimated adult loggerheads have been
observed in much colder waters [52]. Studies have shown thatloggerhead juveniles are more cold tolerant than adults, andhatchlings even more so, even without slow acclimation

J. R. Soc. Interface 18: 20200799

10.0
Japan Florida C Ver

100° E

140° E180°140° W 100° W

60° W

20° W

20° E

60° E

8

royalsocietypublishing.org/journal/rsif

70° N
50° N
30° N
10° N
10° S
30° S
50° S
70° S

Table 3. Two-dimensional median coordinates for dispersal distributions, including all non-stranded hatchlings (total dispersal) and ‘best-fed’ hatchlings for thethree thermal thresholds: 10°C, 12°C and 15°C. Italicized numbers indicate nesting sites where the change in thermal threshold signiﬁcantly changes the mediandispersal (ANOVA, F2,3 > 17, p < 0.001).

site no.

location

total dispersal(lat, lon)

10°C ‘best-fed’
dispersal (lat, lon)

12°C ‘best-fed’
dispersal (lat, lon)

15°C ‘best-fed’
dispersal (lat, lon)

1

Japan

37.1, 158.5

34.2, 171.5

33.9, 172.0

32.1, 150.2

2

Florida38.3, −58.7

37.3, −45.5

37.1, −45.7

35.2, −53.9

3
4

Cape VerdeOman

19.3, −33.2
16.79, 65.5

19.6, −30.5
16.1, 62.6

19.6, −30.5
16.1, 62.6

19.6, −30.5
16.1, 62.6

5
6

west Australia
east Australia−28.6, 109.6−34.6, 157.6−34.9, 113.3−37.6, 153.5−34.9, 113.4−37.6, 153.6−34.9, 113.4−37.4, 154,07

Brazil−26.2, −42.3−31.2, −45.3−31.2, −45.3−31.1, −45.2

8South Africa−36.4, 35.5

−39.3, 39.6

−38.1, 40.6

−34.6, 16.6

[55,56]. Moreover, pelagic-stage juveniles have been shown touse basking and other behavioural strategies that allow themto achieve body temperatures several degrees warmer than SST[17]. Thus, even the lowest threshold for ‘freezing’ used here
(10°C) might be overly conservative, and loggerhead hatchlings
may be more tolerant to life at the edge of the subpolar gyres than
we assumed. More in situ work is needed to assess the relative fitness of young juveniles in these cold regions, and how thischanges with size and age.
We note that the annual mean thermal range of less than
20°C indicating favourable habitat is consistent with TURTLEWATCH dynamic ocean management (e.g. [76]) efforts
in the North Pacific; the instantaneous 17.5–18.5°C isotherms
are used as a benchmark for avoiding fishery interactions
with adult loggerheads, constraining certain fishing gearwithin this thermal range [77]. The less than 20°C range isalso consistent with observations of tagged turtle temperature readings and models of habitat suitability in thisregion [25]. It is interesting to note that the thermal ranges
validated in the North Pacific for Japanese loggerheads areextendable globally to other populations associated withboundary currents. The results here suggest that similar management strategies, following the lessons learned in the North
Pacific, could be applied globally for minimizing fisheries
impacts on juveniles.

Food availability is a critical consideration in determining
the favourable pelagic habitat of loggerhead hatchlings. The
novelty of this study lies in the inclusion of a food proxy(bioC), computed from outputs of a biogeochemical model,
along with physical conditions (SST) in determining favourable habitat. In the Florida and Japan regions, food
limitation constrains the ‘best-fed’ dispersal envelope on thenortheastern and southwestern edges to a mostly zonal
strip along the gyre boundary. In these areas, food availability serves to concentrate favourable habitat to the centreof the total dispersal distribution. However, in other sites(e.g. Brazil, Australian sites), food limitation reduces habitat
wholly on one side (equatorward) of the total dispersal
zone; it is clear that assessing favourable habitat based on
physical characteristics alone would be insufficient. Despite
the coarse food proxy used in this study, our results highlightthe importance of including ecosystem variables in assessing
pelagic habitat, and that results of this inclusion vary acrossthe rookery sites. As global conservation efforts for large
pelagics progress, we suggest that an improved understanding of both the physical and ecological (food web)determinants of favourable habitat is critical for targeting
effective action and preserving key ecosystem services.
Young juvenile loggerheads have often been associatedwith pelagic Sargassum algae in the North Atlantic (e.g.

J. R. Soc. Interface 18: 20200799

Figure 5. Two-dimensional inter-quartile range plots for total dispersal (grey) and ‘best-fed’ distributions for the three thermal thresholds: 10°C (gold), 12°C (red)and 15°C ( purple). Circles mark median points; see table 3 for median values and significance testing. For Japan (site 1), Florida (site 2) and South Africa (site 8),
the thermal threshold significantly affects dispersal (table 3).

Narrow spatial corridors in dispersal pathways are regions ofenhanced vulnerability to anthropogenic and environmental
stressors, acting as a type of migratory bottleneck (e.g. [80]).
‘Best-fed’ distributions from boundary current rookeries exhibit these corridors close to the nesting site: narrow regions
close to the coast that hatchlings pass through during thefirst weeks of life (figures 1 and 3). These corridors are associated with the poleward and inshore flanks of WBCs, which
disperse these hatchlings to the high-biomass gyre boundaries. Dispersal corridors extend from rookeries to the point
where the current detaches from the coast, with significant
intersite differences in the length and narrowness (figures 1
and 3b). For the Brazil nesting site, this corridor extends
from 13° S to 30° S, almost 2000 km, a significant fraction of
the median dispersal distance (2410 km; table 2). In otherboundary current associated nesting sites, the corridor isof the order of hundreds of kilometres, often extending to1000 km. In all cases, when narrow dispersal corridors
exist, they represent a significant amount of timethat expected ‘best-fed’ hatchlings are in a narrow spatial
domain.
The narrow dispersal corridors found for many of theboundary current associated sites suggest a potential vulnerability for loggerhead hatchlings in their very early pelagicstage. Boundary currents are largely associated with the continental shelf break, such that their distance to shore iscontrolled by shelf width, which varies from basin to basin
and along the migratory bottleneck corridor extent for eachnesting site. Hatchlings using boundary currents that arecloser to the coast could be susceptible to higher rates ofnatural predation from both aquatic and avian species, aswell as anthropogenic stressors such as pollution (e.g.
[37,81,82]). Likewise, the length of the corridor will necessarily increase the probability of hatchlings’ vulnerability tothese threats. These narrow corridors are potentially very
fruitful regions for management efforts and could
potentially refine management regions currently in use [78].

3.5. Swimming and boundary currents
Within their thermal nesting range, sea turtles typically nestin greatest abundance where passive off-shelf dispersal is
optimized, e.g. where boundary currents are closest to
shore [11,40]. This is true for seven of the eight loggerhead
nesting sites modelled here, as well as Kemp’s ridley sea
turtle (Lepidochelys kempii) [69] and leatherback sea turtles(Dermochelys coriacea) [12]. The implications are that

3.6. Relative nesting site successSome combination of suitable nesting conditions and posthatchling survivability necessarily controls which nesting
beaches are the most successful [35,88]. Here, no significant
correlation was found between estimated nest abundance(e.g. [6,35,89]) and food proxies, median SST or dispersal distance (Pearson’s r < 0.6, p > 0.1, n = 8, for each metric). For
example, the two sites with the highest modelled bioC overthe first year (South Africa, site 8, and east Australia, site 6;
table 2) have estimated nesting populations one or twoorders of magnitude lower than Oman or Florida [6,35],
with temperature and dispersal distance in the middle
range of all nesting sites. These results suggest that other controlling factors are more important for nesting abundance on
a global scale.
We can speculate that factors such as habitat and predation pressure on nesting beaches, during oceanic dispersal
or where juveniles ultimately disperse to, are importantin ultimate nesting success. Many of the high-biomass
oceanic habitats favourable for juvenile turtles are also
likely to be favoured by their predators, not simulated here.
In the North Atlantic, hatchling and juvenile loggerheads
use floating Sargassum mats as refuge from predation; thisprotective mechanism may result in greater survivorshipfor hatchlings, e.g. from the Florida nesting site. An
additional potential factor is an oceanic distance from thenesting site at the end of the juvenile period, i.e. how easily
an individual can return to the nesting beach using ocean
currents [90–92]. Loggerhead females have high nesting fidelity to their natal beaches [20]; we may assume that, if there isa lower energetic swimming cost, nesting females are more
likely to successfully return to their natal beach. Moreover,

9

J. R. Soc. Interface 18: 20200799

3.4. Dispersal corridors and endangered populations

proximity to currents favourable for dispersal is a leadingorder constraint on nesting habitat for sea turtles in general.
Given that fitness is increased for turtles that can reachnursery grounds with limited energy expenditure, and thatmature turtles return to the vicinity of their natal site tonest, beaches where hatchling movement is consistently facilitated by ocean currents will tend to have relatively highnesting populations [11]. It also follows that turtle populations nesting at sites less favourable for the transport ofhatchlings may undergo strong natural selection for oriented
swimming towards these favourable dispersal corridors; evidence strongly suggests that this is the case [37,40,83,84].
Moreover, it is likely that, for all turtle populations, swimming behaviour that increases the chances of young turtles
reaching favourable oceanic habitats will be selected for,such as orienting to magnetic map cues [38,85]. A tracking
experiment of less than 1-year-old loggerheads from Brazil
and simultaneously deployed drifters indicated that largescale patterns in movements followed the prevailing directionof current flow and that oriented swimming helped turtles
maintain their position within currents [86]. Similarly, a tracking experiment with wild-caught, 1- to 2-year-old Kemp’s
ridley and green sea turtles (Chelonia mydas) indicated thatoriented swimming behaviour contributed significantly totheir movements and habitat selection in the Gulf of Mexico[87]. Accounting for such behaviour in our model would
probably not change the favourable habitat regions found
here, but increase the overall fraction of hatchlings reaching
this favourable habitat [22,40].

royalsocietypublishing.org/journal/rsif[15]), such that Sargassum is used to define critical habitat in
US waters [78]. However, Sargassum is endemic to the North
Atlantic and without parallel in other ocean basins. Though
we have not modelled the role of Sargassum here, it is likelythat high bioC is a necessary condition for early juvenile feeding success and thus fitness globally, whether or not
Sargassum is present. It is interesting to note that observed
and modelled climatologies of Sargassum in November [79]are high in the Gulf Stream Extension, across the North
Atlantic towards the Azores, in a similar distribution to the‘best-fed’ turtles simulated here. This Sargassum abundance
appears driven by in situ growth and not transport [79],suggesting that Sargassum is benefiting from the sameprocesses driving high bioC in this simulation.

10

We have found that the largest rookeries in each subpopulation fall into two classes: those that are closest to major
boundary currents that allow easy dispersal to high-biomass
regions, and lower dispersal sites in exceptionally productive
tropical biomes. In both cases, nesting sites are optimized foreasy transport to the most productive open ocean habitat
within loggerhead hatchlings’ thermal range. Hatchlings
with higher potential fitness, determined by their exposure
to a simulated food biomass proxy, were associated withcolder, more productive waters. Many boundary current
associated nesting sites require long transit of hatchlings
through narrow coastal migratory corridors with a high likelihood of anthropogenic impacts. Dispersal distance during
the first year varied greatly between nesting sites, as did theoceanographic distance from both suitable pre-maturity foraging habitat and nesting beaches at the end of the first year.
The results here are derived from global ocean models,and as such need to be further validated to be applied for loggerhead conservation. This study points the way forward forboth observational and directed regional modelling studies
to further hone our understanding of what determines
favourable pelagic habitat and which hatchlings are themost likely to survive. For example, comparative fitness
studies of juvenile turtles in subtropical–subpolar gyreboundaries with juveniles in warmer waters, along with simultaneous forage abundance estimates in each biome, would
help constrain the relative effects of forage availability andtemperature-dependent growth rates.
While simulated dispersal studies are excellent tools fordeveloping hypotheses, there is much work to be done. Thisocean model simulation does not have extreme weather
events, which are known to impact turtle dispersal and strandings [98,99]. Ocean models with better near-shore resolution
are needed to constrain the early days of the first year, in particular the relative potential for stranding and success of frenzy
swimming among the nesting sites. Additionally, ocean
models poorly constrain zooplankton food sources for higher
trophic level studies, especially biogeochemistry components
of Earth system models which are largely designed to study
the carbon cycle. In particular, more effort is needed to represent zooplankton functional groups, and in particulargelatinous zooplankton for sea turtle life-history simulations.
Finally, the relative impact of passive versus active dispersal
on fitness, along with temperature-dependent growth, needs
to be determined with a realistic bioenergetic model.
Data accessibility. The Community Earth System Model is freely available at https://www.cesm.ucar.edu. Simulated turtle tracks,
including along-track temperature and food data, and sample plotting scripts are available on Open Science Framework (OSF) at
doi:10.17605/OSF.IO/YJWK8.

Authors’ contributions. C.S.H., J.Y.L., N.F.P. and M.C.L. designed theresearch. C.S.H., J.Y.L., M.C.L., Q.L., P.S., J.S. and K.K. performed
the research and analysed the data. C.S.H., J.Y.L., N.P. and K.K.
wrote the paper.

Competing interests. We declare we have no competing interests.
Funding. C.S.H. and M.C.L. acknowledge support from the National
Science Foundation (NSF) (OCE-1048926) and NASA (OBBNNX14AM36G). The National Center for Atmospheric Research(NCAR) is supported by the NSF. The CESM project is supportedby the NSF and the Office of Science of the US Department ofEnergy. Computing resources were provided by the Climate Simulation Laboratory at NCAR’s Computational and Information

J. R. Soc. Interface 18: 20200799

4. Conclusion and future outlook

royalsocietypublishing.org/journal/rsif

nest counts do not entirely correspond to population abundance because some females may lay multiple clutches in ayear and not all females in the population nest each year.
Clutch frequency and remigration interval are likely to berelated to foraging conditions for adult females, and changes
through time can produce wide differences in estimatedpopulation sizes [93]. For instance, in some loggerhead populations individuals may nest eight times in a year [94]. How
biogeographic variation in these two aspects of sea turtle
physiology contributes to differences in nest counts acrosswidely separated areas is not known, but may be a large confounding factor in attempting to relate relative population
abundance in loggerhead turtles to hatchling dispersal at a
global scale [95].
Nonetheless, at both regional and global scales, some sites
are better than others for setting up juveniles for success after
the first year and ultimately supporting return of nestingfemales to the nesting site. For the boundary current associated sites, ultimate dispersal fate varies greatly. For
example, while temperatures, dispersal distance and foodavailability are similar for the Florida and Japan nestingsites (table 2 and figure 3), habitat availability at the end of
the first year is divergent. Loggerheads dispersing from Florida are transported to the Azores archipelago [96], which iswell known to be a favourable habitat for juvenile turtles[14]. These hatchlings have a suite of behavioural adaptations
to make efficient use of the Gulf Stream System with abundant food and Sargassum habitat along the way, ultimately
arriving at excellent island habitat at the end of the firstyear [4]. By contrast, loggerhead hatchlings from Japan aretransported to the central North Pacific, with the closest
coastal foraging habitat still thousands of kilometres away
in all directions. These differences in habitat at the end of
the first year likely contribute to the ultimate success ofhatchlings from the US East Coast in general, and the large
number of nests there relative to other boundary current
sites [6,35]. There is also a large difference in the oceanographic distance back to the nesting sites for mature turtles
between the North Atlantic and North Pacific first-year dispersal fate. Transit times around the North Atlantic gyreare only a few years [15,97]. Transit times across the North
Pacific are longer [27], and the energetic costs to return tothe nesting site are likely to be much higher.
In contrast with other boundary current sites, mean dispersal distance from Oman is low (810 km; table 2 andfigure 4); here no juveniles disperse far from their natal site,
spending their first year in a region with persistently warm,
productive ocean conditions. It is possible that these favourable conditions lead to higher survivability not only in thefirst but also in subsequent years when juveniles are moreable to control their dispersal through swimming. The
added benefit of low dispersal and high food availability isthat loggerheads can spend their entire lives close to theirnatal sites, likely contributing to the high nest abundance inthis subpopulation [6,35]. Similarly, hatchlings from theCape Verde site encounter very high food levels near their
nesting site, which along with low dispersal leads to cumulative bioC levels significantly higher than for Florida
hatchlings, and similar to hatchlings from Brazil and Japan(figure 4a). Despite their transport into the less productive
subtropical gyre towards the end of the first year, thesehatchlings could be aided in later stages by encountering
Sargassum habitat not resolved in this simulation [79].

Systems Laboratory (CISL), sponsored by the NSF and otheragencies.
their constructive and valuable input, and Vincent Saba, who

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Acknowledgements. The authors thank three anonymous reviewers forprovided comments that improved a previous version of thispaper. Oceanographic colourmaps from the Python package cmocean were used for visualization (https://matplotlib.org/cmocean/;[100]).

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