VOL. 98, NO. 12, 2991–3251 ECOLOGY DECEMBER 2017
Physiological stress responses to natural variation in predation
risk: evidence from white sharks and seals
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Physiological stress responses to natural variation in predation risk:
evidence from white sharks and seals
SIMON MDUDUZI SEAKAMELA,
AND SCOTT CREEL
Department of Marine Ecosystems and Society, Rosenstiel School of Marine and Atmospheric Sciences,
University of Miami, Miami, Florida 33149 USA
Leonard and Jayne Abess Center for Ecosystem Science and Policy, University of Miami, Coral Gables, Florida 33146 USA
Branch: Oceans and Coasts, Department of Environmental Affairs, Private Bag X4390, Cape Town 8000 South Africa
Apex Shark Expeditions, Shop 3 Quayside Center, Simonstown Cape Town 7975 South Africa
Department of Ecology, Montana State University, Bozeman, Montana 59717 USA
Abstract. Predators can impact ecosystems through consumptive or risk effects on prey.
Physiologically, risk effects can be mediated by energetic mechanisms or stress responses. The
predation-stress hypothesis predicts that risk induces stress in prey, which can affect survival
and reproduction. However, empirical support for this hypothesis is both mixed and limited,
and the conditions that cause predation risk to induce stress responses in some cases, but not
others, remain unclear. Unusually clear-cut variation in exposure of Cape fur seals (Arcto-
cephalus pusillus pusillus) to predation risk from white sharks (Carcharodon carcharias) in the
waters of Southwestern Africa provides an opportunity to test the predation-stress hypothesis
in the wild. Here, we measured fecal glucocorticoid concentrations (fGCM) from Cape fur
seals at six discrete islands colonies exposed to spatiotemporal variation in predation risk from
white sharks over a period of three years. We found highly elevated fGCM concentrations in
seals at colonies exposed to high levels of unpredictable and relatively uncontrollable risk of
shark attack, but not at colonies where seals were either not exposed to shark predation or
could proactively mitigate their risk through antipredatory behavior. Differences in measured
fGCM levels were consistent with patterns of risk at the site and seasonal level, for both seal
adults and juveniles. Seal fGCM levels were not correlated with colony population size, density,
and geographic location. Investigation at a high risk site (False Bay) also revealed strong corre-
lations between fGCM levels and temporal variation in shark attack rates, but not with shark
relative abundance. Our results suggest that predation risk will induce a stress response when
risk cannot be predicted and/or proactively mitigated by behavioral responses.
Key words: antipredator behavior; apex predator; ecology of fear; ecophysiology; glucocorticoid; noncon-
sumptive effects; predation risk; risk effect; seal; shark; stress.
Apex predators can strongly alter ecosystems by affect-
ing the numbers, distribution and behavior of their prey
(Werner and Peacor 2003, Peckarsky et al. 2008). More-
over, such behavioral modifications in response to preda-
tion risk can manifest in physiological changes in prey
that carry fitness costs and affect population dynamics
(Peckarsky et al. 2010, Zanette et al. 2014). Together,
these predator effects can have cascading impacts on
other species (Schmitz et al. 1997, Brashares et al. 2010).
Two general hypotheses have been proposed for the
physiological mechanism underlying predation risk effects
on prey populations (outlined in Creel et al. 2009). The
predator-sensitive food hypothesis predicts that predators
constrain foraging activity or efficiency of their prey, thus
increasing energetic or nutritional constraints on prey
reproduction or survival (Sinclair and Arcese 1995). Many
studies across a broad range of taxa have found empirical
evidence in support of this hypothesis (Werner and Peacor
2003). Growing research has revealed that food-mediated
reactions of prey to predators (e.g., food–risk trade-offs)
are not simply an artifact of predator encounter rates and
often depend on predator hunting mode, anti-predator
behavior, and on landscape features that can influence the
probability of death given an encounter with a predator
(Schmitz 2008, Heithaus et al. 2009). The predation-stress
hypothesis predicts that exposure to risk causes increased
secretion of glucocorticoids (or other physiological stress
responses; Romero 2004). However, studies of this hypoth-
esis in natural settings have been limited and the results
mixed (Boonstra et al. 1998, Clinchy et al. 2004, Creel
et al. 2009, Sheriff et al. 2009). Moreover, most investiga-
tions of this hypothesis in the wild have generally
employed study designs for monitoring of potential stress
changes through time at a single site (Boonstra et al.
1998, Zanette et al. 2014); but few natural study systems
have been conducive to investigating the effects of risk on
Manuscript received 28 September 2017; accepted 6 October
2017. Corresponding Editor: John F. Bruno.
Ecology, 98(12), 2017, pp. 3199–3210
©2017 by the Ecological Society of America
stress responses in prey populations with replication
within both a low risk and high risk condition. Addition-
ally, many studies assume that risk effects are mediated by
fear of predation, which is manifested in stress; however,
anti-predatory behavioral responses to risk can arise
through mechanisms that do not involve a stress response.
For example, in the greater Yellowstone ecosystem, elk
(Cervus elaphus) forage in suboptimal habitats to reduce
their exposure to predation from wolves (Canis lupus;
Creel et al. 2005), which incurs physiological costs associ-
ated with lower nutritional intake, but does not result in a
stress response (Creel et al. 2009). Taken together, a key
question remains: under what conditions are risk effects
mediated by stress in the wild? This knowledge gap is lar-
gely driven by the inherent challenges of working with
predators and their prey in nature. Such studies are partic-
ularly important at this time given declines in predator
populations worldwide (Estes et al. 2011), together with
successful predator recovery programs in some ecosystems
(Marshall et al. 2016).
The waters off the Western Cape of South Africa pro-
vides an opportunity to study predator–prey interactions
involving white sharks Carcharodon carcharias and Cape
fur seals Arctocephalus pusillus pusillus, and an ideal sys-
tem to test the effects of predation risk on prey physiology
(Fig. 1A). Here, the population of Cape fur seals in the
region is segregated into discrete colonies that inhabit dif-
ferent inshore islands; but the seals from the different
island colonies move offshore to feed where they share
the same general foraging grounds (Rand 1959, 1967,
Oosthuizen 1991). White sharks only actively target cer-
tain seal colonies, creating a natural spatial variation in
seal colonies to threat of attack (Bonfil et al. 2005, Dud-
ley 2012, De Vos et al. 2015a, Andreotti et al. 2016). At
these locations, there also exists clear seasonal variation
in predation risk, as sharks only actively hunt Cape fur
FIG. 1. (A) Photograph of a white shark lunging toward a Cape fur seal at the edge of Seal Island (background) in False Bay,
South Africa. White sharks aggregate during the cool season at specific island colonies to hunt seals when they enter and exit the
water to and from offshore foraging. (B) A white shark patrols the border of a kelp bed that surrounds the seal colony at Geyser
Rock. The kelp is used by seals as refuge from sharks while traversing to and from the island. (C) Kelp and other high relief land-
scape features are absent from the waters around the island colony in False Bay, where attack rates on seals are 18 times higher than
at Geyser Rock. (D) A large seal bearing a fresh injury from a white shark attack hauls out on to Seal Island in False Bay where it is
investigated by a group of pups and juvenile seals. All images by C. Fallows. [Color figure can be viewed at wileyonlinelibrary.com]
3200 NEIL HAMMERSCHLAG ET AL. Ecology, Vol. 98, No. 12
seals during winter months (Hammerschlag et al. 2006,
Jewell et al. 2013, Towner et al. 2016). However, among
the different colonies targeted by sharks, predation risk to
seals can vary significantly due to landscape features that
either offer protection to seals traversing the gauntlet or
leave them exposed to unpredictable risk of attack (Wcisel
et al. 2015). For example, white shark attack rates on
seals at the seal colony in False Bay (1.97 attacks/h) are
18 times higher than at Geyser Rock (0.1 attacks/h),
because the latter is surrounded by dense kelp beds and
reefs that serve as a refuge from sharks when the seals tra-
verse from their colony (Wcisel et al. 2015; Fig. 1B). Such
landscape features are absent from False Bay (Fig. 1C),
where predation rates on seals average 6.7 attacks per day
during the cool season, with success rates as high as 0.55
kills per attack (Hammerschlag et al. 2006). Rarely do
spatially discrete natural prey populations share the same
general food supply, while being exposed to such distinct
variation in predation risk as in the current study system.
The purpose of this study was to test the predation-
stress hypothesis using this shark-seal system off South
Africa. First, we analyzed movement patterns of satellite
tagged white sharks to evaluate spatial and temporal pat-
terns of white shark residency and density at six seal colo-
nies that vary in risk from shark attack. Next, we
collected seal scat samples from these six seal colonies
over multiple years and seasons for measurements of fecal
glucocorticoid metabolites (fGCM) to evaluate if concen-
trations were associated with patterns of spatial and tem-
poral occurrence of white sharks. Finally, we conducted a
multi-year study at Seal Island in False Bay (a high risk
site), to test if seal fecal cortisol levels were correlated with
either relative abundance of white sharks or measured
attack rates by sharks on seals. We used these data to (1)
evaluate if seal colonies exhibit spatial and seasonal varia-
tion in fGCM concentrations consistent with patterns of
white shark predation risk, (2) test if fGCM levels in seals
correlate with shark relative abundance or measured sur-
face attack rates by sharks on seals in False Bay, (3) test if
differences in colony-specific landscape features that
influence the type and magnitude of shark predation risk
to seals are associated with differences in seal fGCM con-
centrations, and (4) determine whether fecal cortisol levels
differ in in adult seals vs. juveniles under risk of preda-
tion. Additionally, we tested the alternative hypotheses
that fGCM concentrations were associated with seal col-
ony population size, density and geographic location (and
associated variation in environmental factors).
MATERIALS AND METHODS
Cape fur seals exhibit high site fidelity to specific
inshore island colonies, which therefore remain fairly
discrete units (Rand 1959); however, seals from different
colonies share the same general offshore feeding grounds
as revealed through mark–recapture (Oosthuizen 1991).
Previous satellite and acoustic tracking of white sharks
within South Africa have demonstrated that sharks
aggregate at certain seal colonies during cool months of
the year to target Cape fur seals. These “high shark
abundance”seal colonies include False Bay, Mossel Bay,
and Geyser Rock, where shark habitat use and predation
has been relatively well studied (Martin et al. 2005,
Johnson et al. 2009, Fallows et al. 2012, Jewell et al.
2013, Kock et al. 2013, Towner et al. 2016, Wcisel et al.
2015). During warm months, white sharks shift the focus
of their hunting away from seals at the colonies, presum-
ably to feed on teleosts and elasmobranchs, resulting in
lower shark occurrence and predation pressure to seals
at these high shark abundance colonies during the sum-
mer (Hammerschlag et al. 2006, Kock et al. 2013, De
Vos et al. 2015a). There are also “low shark abundance”
seal colonies within the region that are not targeted by
sharks at any time of year (Bonfil et al. 2005, Kock et al.
2013, De Vos et al. 2015a). These spatiotemporal pat-
terns of white shark abundance have also been found
through region-wide survey data of white sharks
through standardized boat-based baited surveys as part
of a project to estimate population sizes of white sharks
in South Africa (Andreotti 2015, Andreotti et al. 2016).
In this study, we focused our investigation on six seal
colonies that varied in exposure to the seasonal presence
of hunting white sharks: three high shark abundance
colonies (False Bay, Mossel Bay, and Geyser Rock) and
three low shark abundance colonies (Bird Island in Lam-
bert’s Bay, Jutten Island, and Robbesteen; Fig. 2) during
both the “high predation season”(winter, June–Septem-
ber) and “low predation season”(summer, October–
May). However, to confirm this previously described
spatial and temporal variation in exposure of the six
focal seal colonies to white sharks during the study per-
iod, we analyzed white shark movement data that were
collected as part of a larger collaborative satellite tagging
project between the USA-based non-profit OCEARCH
and South African researchers.
White shark tracking
Between March and May of 2012, a total of 37 white
sharks (14 males, 23 females) were captured and tagged
at five different localities across the Western Cape of
South Africa: Algoa Bay, False Bay, Gansbaai, Mossel
Bay, and Struisbaai. Details on capture and handling
methods can be found in Wcisel et al. (2015). Briefly,
sharks were captured with baited barbless hooks and
carefully lead onto a hydraulic platform. One or two
hoses where then inserted into the shark’s mouth to
pump fresh oxygenated saltwater over the gills. Sharks
received antibiotics and electrolyte injections to enhance
recovery time. Smart Position-only and Temperature
Transmitting tags (SPOT5 tags; Wildlife Computers,
Redmond, Washington, USA ) were affixed to the dorsal
fin of sharks. Depending on their size, sharks were
tagged with either a small SPOT tag (2-yr battery life for
December 2017 SHARK PREDATION AND STRESS IN SEALS 3201
sharks <3 m total length) or a large SPOT tag (5-yr bat-
tery life for sharks >3 m total length).
Locations were acquired whenever the dorsal-fin
mounted SPOT tag broke the water surface and transmit-
ted a signal to a passing ARGOS satellite. Geographic
locations of SPOT tagged sharks were determined by
Doppler-shift calculations made by the ARGOS Data
Collection and Location Service (Argos CLS, Toulouse,
France ). Accuracy of position data is variable depending
on number of transmissions received by ARGOS and cat-
egorized into location classes (LC) as follows:
LC 3 <250 m, 250 m <LC 2 <500 m, 500 m <LC 1 <
1,500 m. The median error for LC 0, A, and B ranges
from 1 to 3 km. Class Z indicates that the location pro-
cess failed and estimates of position are highly inaccurate
and are removed before spatial analysis.
Seal fecal sample collection
Between 2012 and 2015, a total of 502 fecal samples
were collected and analyzed for fGCM, with at least two
collection periods in the high predation season and two
collection periods in the low predation season for each
colony (N=92 samples from Geyser Rock, N=44 from
Robbesteen, N=52 from Jutten Island, N=145 from
Lambert’sBay,N=114 from Seal Island in False Bay,
N=55 from Seal Island in Mossel Bay). At each sam-
pling occasion, ~20 g samples from clearly distinct
defecations by single seals were collected and placed in
50-mL screw-lid vials and frozen within 1–2 h of collec-
tion. Where possible, fecal samples could be assigned to
seal age classes (adult vs. juvenile) based on differences in
size (though no effect of age class was detected: see
Results). The juvenile category also included young-of-
the year seals. Based on direct observation, juvenile scats
ranged in size from 6 to 10 mm diameter; whereas adult
scats ranged in size from 15 to 20 mm diameter. Adult
scats could also be further distinguished based on a rela-
tively higher frequency of fish bones in the scat, which are
fewer in juveniles. Ambiguous samples and scats between
11 and 15 mm were not assigned to an age class.
Steroid hormone metabolites were extracted from
fecal samples by drying the scat and boiling a known
mass of dry feces in ethanol using methods that have
been described in detail previously (Monfort et al. 1997,
Creel et al. 2009).
We measured glucocorticoid metabolite concentrations
in fecal extracts (fGCM) using an enzyme-linked
immunoassay with a cortisol antibody (Enzo Life
Sciences ADI-900-071, Farmingdale, New York, USA))
that has broad cross-reactivity and has been procedurally
and biologically validated for assay of fecal extracts in a
broad range of species (Monfort et al. 1997, Creel et al.
Bird Island (LS)
Juen Island (LS)
Seal Island (HS)
Geyser Rock (HS)
Seal Island (HS)
FIG. 2. Locations of six focal colonies off the Western Cape of South Africa (inset). LS, low shark abundance colony; HS, high
shark abundance colony. [Color figure can be viewed at wileyonlinelibrary.com]
3202 NEIL HAMMERSCHLAG ET AL. Ecology, Vol. 98, No. 12
2009, 2013). We expressed fGCM concentrations as mil-
ligrams of cortisol immunoreactivity per gram of dry
feces. Antibody binding was parallel for a dilution series
of cortisol standards and seal fecal extracts diluted from
1:1 to 1:256 (log-linear slopes 0.011 and 0.014, respec-
tively). Quantitative recovery of cortisol added to seal
fecal samples was highly accurate (r
b=1.00 0.03 [mean SE]) for a range from 156 to
5,000 pg of cortisol added to fecal extracts at working
concentration. Assay sensitivity was several orders of
magnitude below the concentration of fecal extracts.
Based on preliminary analysis, we assayed extracts at
1:100 dilution to maximize sensitivity, assaying all sam-
ples in duplicate with a seven-standard curve, controls
and measures of total activity, zero-steroid binding, and
non-specific binding on each plate. Intra- and inter-assay
coefficients of variation from pooled fecal extracts were
13.36 and 13.71, respectively. The composition of scats
did not vary between sites or seasons, and we detected no
association between fGCM concentrations and the com-
position of scats, as measured by the proportions of water
and indigestible matter.
Seal population data
Aerial photographs of seal colonies from fixed wing
and helicopter aircrafts were taken at the peak of the seal
pupping season and the numbers of newborn pups of
the year were counted on the photographs. This is
because pups are confined to land (during their first
month of life) and their numbers can be used to infer
total population size of adults and pups, subject to cer-
tain assumptions (Kirkman et al. 2011). Because Jutten
Island is primarily a non-breeding colony where rela-
tively few pups are currently born, both pups and adult
seals were counted.
Aerial seal counts were conducted annually at all six
seal colonies between 2011 and 2014, excluding 2012 at
Mossel Bay and Lambert’s Bay and 2013 at Robbesteen,
Geyser Rock, False Bay, and Mossel Bay. Annual seal
counts were then averaged across the study period (here-
after referred to as colony population size). We also cal-
culated an estimate of seal density (seals/ha) at each
colony by dividing the number of seals counted by the
area of the island occupied by the seals (hereafter
referred to as colony density).
Shark predation and relative shark abundance
in False Bay
Between February 2014 and August 2015, standard-
ized surveys were conducted at Seal Island in False Bay
to evaluate for the potential differential effects of shark
occurrence vs. hunting behavior (i.e., components of pre-
dation risk) on seal fGCM concentrations.
Predation by white sharks on Cape fur seals was
recorded daily around the seal island colony in False
Bay for one week prior to fecal sample collection, which
occured on seven dates: 11 February, 25 April, 30 July,
and 12 September 2014 as well as on 19 March, 7 July,
and 12 August 2015. Previous laboratory studies that
have subjected sea lions (Eumetopias jubatus)toan
adrenocorticotropic hormone (ACTH) challenge found
a lag of up to 4 d between ACTH injection and peak
fGCM (Hunt et al. 2004). Accordingly, for one week
prior to collecting fecal samples on the dates specified
above, standardized observations for shark predation
events were performed from a research vessel daily
between 07:00 and 09:30, sea conditions permitting.
Monitoring of shark predations on seals were conducted
following the approach of Martin et al. (2005), and Fal-
lows et al. (2016). Here, sharks primarily attack Cape
fur seals at the surface via a vertical breach when seals
are surface porpoising to and from the Island. Attacks
are concentrated on the southern side of the Island, close
to shore (within 2 km). By positioning at the south end
of Seal Island where the majority of predatory activity
occurs, we were able to survey the waters surrounding
the island for predations up to a distance of at least
3 km, although the majority of predations occur within
400 m of southwest end of the island (Martin et al.
After about 09:30 , our research vessel anchored on
the southern side of Seal Island and conducted stan-
dardized boat-based baited surveys of white sharks
using an approach modified from Hammerschlag and
Fallows (2005). Between 10:00 and 12:00, sea conditions
permitting, sharks were attracted to the boat using a
large tuna head and seal decoy. Individual white shark
can be identified based on a combination of visual mak-
ers, including unique scarring, presence/absence of clas-
pers, and individual variation in pigmentation patters on
the gill flaps, pelvic fins, and caudal fins (Domeier and
Nasby-Lucas 2007). The duration of baited surveys were
recorded, along with the number of different individual
white sharks observed during this period. Using these
data, we calculated the number of different white sharks
observed per hour of baited survey as a metric of relative
White shark tracking analysis
SPOT satellite tagging data were downloaded from
ARGOS CLS. Given variable tag size (and thus battery
life) and possible issues related to biofouling with
increasing tag age, we included only positions within a
year of tagging for each individual shark. Given irregu-
lar transmissions and varying levels of position accuracy
(see Hammerschlag et al. 2011 for details), all SPOT
location data were interpolated and regularized to a con-
stant 6-h interval using a hierarchical, first-difference,
correlated, random-walk, switching (hDCRWS), state-
space model (SSM) described by Jonsen (2016). This
approach accounts for both the variability in geoposi-
tion accuracy provided through ARGOS location classes
and the irregularity of surfacing. Locations were not
December 2017 SHARK PREDATION AND STRESS IN SEALS 3203
interpolated for data gaps >14 d and for shark tracks
with fewer than 20 positions (per instructions by I. Jon-
sen). The SSM model also estimates a behavioral state
(bt) for each position ranging from one (transient,
migratory state) to two (resident, area-restricted state;
Jonsen 2016). Following Acu~
na-Marrero et al. (2017),
each position was classified as being either predomi-
nantly transient (bt <1.25) or predominantly resident
(bt >1.75). Given we were interested in predation risk
to seals from hunting sharks residing at the colonies,
subsequent analysis were restricted to 6-h interpolated
positions classified as predominately resident (bt >1.75)
and plotted in ArcMap 10.1 (ESRISA).
To examine relative differences in the spatial distribu-
tion of white sharks in relation to the focal seal colonies,
we applied kernel density analysis to the position data in
ArcMap 10.1. This calculated and plotted the number of
shark positions per km
using a kernel function (Silver-
man 1986). We then used ArcMap spatial analysis tools to
calculate the average kernel densities (KD) of white shark
positions within a 2 km radius of the high vs. low shark
abundance colonies. This analysis was conducted sepa-
rately for the warm (October–May) and the cool season
(June–September). To evaluate patterns of shark residency
at the colonies, we calculated the mean, minimum, and
maximum number of days individual white sharks spent
within 2 km of the high vs. low shark abundance colonies
within each season. We selected a 2 km radius given the
spatial accuracy of the SPOT data and also because white
sharks patrolling the colonies concentrate hunting effort
within 2 km of shore (Johnson et al. 2009, Fallows et al.
2012, Jewell et al. 2013, Towner et al. 2016).
In addition to colony-specific and seasonal variation
in predation risk to seals, differences in colony popula-
tion size and/or density could contribute to seal stress
levels. Moreover, given that colonies were widely dis-
tributed along the coast, differences in their geographic
locations (i.e., latitude and longitude) could potentially
expose the colonies to differences in environmental fac-
tors that could influence seal stress levels. Accordingly,
generalized linear models (GLiMs) were employed to
test the effects of these explanatory variables on mea-
sured fGCM concentrations, which included seal colony
(Jutten Island, Lambert’s Bay, Robbesteen, Geyser
Rock, Mossel Bay, False Bay), season (warm, cool), the
interaction between colony and season (colony 9sea-
son), colony population size, density, latitude, and longi-
tude. GLiMs were constructed with backward and
forward stepwise selection, starting with a model con-
taining all the plausible explanatory variables. Retention
or removal of variables were based on the Akaike infor-
mation criterion (AIC), with the lowest AIC suggesting
the best fitting model. Based on results of the GLiMs,
which revealed that the best explanatory model included
only the interactive effects of colony 9season, Tukey’s
standardized range (HSD) tests were used for pairwise
evaluations among colonies across both seasons.
For the high shark abundance colonies (False Bay,
Mossel Bay, Geyser Rock), analysis of variance
(ANOVA) was used to test for potential differences in
fGCM between seal age classes (adult vs. juveniles),
between seasons, and the interaction of these effects.
Tukey ’s HSD tests were then used for pairwise evalua-
tions between age classes among colonies.
For predation data recorded in False Bay, hourly attack
rates by white sharks on seals were averaged across the
seven days prior to each fecal sampling. Pearson’scorre-
lation was used to test if weekly shark attack rates were
correlated with associated fGCM concentrations. Simi-
larly, for shark survey data, hourly relative abundance of
white sharks were averaged across the seven days prior to
each fecal sampling and Pearson’s correlation was used
to test if shark relative abundance was correlated with
associated fGCM concentrations.
In addition to the GLiMs testing for effects of plausi-
ble explanatory variables on measured fGCM concen-
trations, we used Pearson correlations to separately test
for significant relationships between colony population
size and density on mean fecal cortisol concentrations.
Similarly, we used Pearson correlations to separately test
for potential significant relationships between latitude
and longitude on seal fGCM values in both the warm
and cool season.
All statistical analyses were conducted in SAS statisti-
Thirty-four tagged white sharks provided geoposition
data (three tags failed to report) for spatial analyses of
locations regularized to 6-h intervals using SSM. Sixteen
individual sharks provided resident positions (bt >1.75)
within 2 km of a high shark abundance colony (Geyser
Rock, Mossel Bay, and False Bay) in both the warm and
cool season. In contrast, no sharks provided resident
positions within 2 km of a low shark abundance colony
(Jutten Island, Lambert’s Bay, Robbesteen) in either sea-
son. In fact, no sharks tracked occurred within 2 km of
these colonies; the closest a resident individual came
within proximity of a low shark abundance colony was a
single individual 44 km off Jutten Island. Within 2 km
of the high shark abundance colonies, average density of
shark positions were 2.5 times higher in the cool season
(KD =0.35 km
) than warm season (KD =0.14 km
In terms of residency, sharks were resident 1.5 times
more days within 2 km of high shark abundance colo-
nies during the cool season than during the warm season
(Table 1). Moreover, the maximum number of days an
individual shark was resident at a high shark abundance
colony during the cool season was double that of the
warm season (Table 1).
Fecal GCM concentrations showed considerable vari-
ation, ranging from a minimum of 26.66 mg/g to a
3204 NEIL HAMMERSCHLAG ET AL. Ecology, Vol. 98, No. 12
maximum of 3,372.11 mg/g. The best fitting GLiM
included only the interactive effects of colony and season
(Colony 9Season) as an explanatory variable, which
was highly significant (P<0.0001; Appendix S1:
Table S1). Pairwise comparisons using Tukey’s HSD
Tests revealed fGCM concentrations were significantly
higher in samples from the high shark abundance colo-
nies in False Bay and Mossel Bay (Fig. 3; Appendix S1:
Table S2). While fGCM concentrations for these two
colonies did not differ from one another in the high pre-
dation season, both were significantly higher than from
collection made from those same colonies in the low pre-
dation season as well as significantly greater than those
from any other colony in either season, including the
high shark abundance colony at Geyser Rock (Fig. 3).
Concentrations of fGCM measured from the island
colonies in False Bay and Mossel Bay (1,737.8 689.16
SD mg/g) were on average 2.8 times greater than the
mean of all other colonies across both seasons
(627.26 523.88 mg/g), including Geyser Rock during
the high predation season (620.01 388.19 m/g).
For the high shark abundance colonies, there was a sig-
nificant interaction between season, seal age class, and
individual colony on measured fGCM values (ANOVA,
N=261, df =7, F=10.26, P<0.0001; Appendix S1:
Table S3). At these sites, fecal glucocorticoid metabolite
concentrations did not differ between adults and juveniles
in either the low or high predation season, but values for
both adults and juveniles were significantly higher in the
high vs. low predation season (Appendix S1: Table S4).
The exception was for Geyser Rock, in which there were
no differences in fGCM values between age classes during
the high vs. low predation season (Appendix S1: Table S4).
At Seal Island in False Bay, white shark predation rates
on seals were recorded on seven occasions during the
week prior to fecal sampling. Mean weekly predation
rates ranged from 0 attacks/h (4–10 February 2014) to
3.49 attacks/h (5–11 August 2015). Pearson correlation
revealed a strong positive linear correlation between mean
fGCM concentrations and mean predation rates (attacks/
h) over the prior week (r=0.96, P=0.0007; Fig. 4A). In
contrast, fGCM concentration were not correlated with
shark relative abundance (r=0.2, P=0.66; Fig 4B).
TABLE 1. Mean kernel density (KD) estimates of white shark
interpolated position per km
and the mean, minimum (min.)
and maximum (max.) number of days individual sharks were
resident within 2 km of a low shark abundance colony (Jutten
Island, Lambert’s Bay, and Robbesteen) or a high shark
abundance seal colony (Geyser Rock, Mossel Bay, and False
Bay) in the warm (low predation) and cool (high predation)
season within one year of tagging.
Low warm 0 0 0 0
Low cool 0 0 0 0
High warm 0.14 7.1 1 22
High cool 0.35 10.8 1 47
S.I. Mossel Bay
S.I. False Bay
S.I. Mossel Bay
S.I. False Bay
FIG. 3. A comparison of fecal glucocorticoid metabolite concentrations (fGCM) across all six seal colonies in both the low preda-
tion season and high predation season. Fecal samples were collected from each colony at least twice per season for at least two years
between 2012 and 2015. High shark abundance colonies are solid bars and low shark abundance colonies are vertical patterned bars.
Values are means and whiskers are 95% confidence intervals. Values with different letters denote statistical differences. HS, high shark
abundance colony; LS, low shark abundance colony; HP, high predation season; LP, low predation season; S.I., Seal Island.
December 2017 SHARK PREDATION AND STRESS IN SEALS 3205
Average counts of seals at each colony across the study
period and associated density can be found in App-
endix S1: Table S5. Model selection did not include these
explanatory variables in the final GLiM, and seal colony
population size and density was not correlated with mean
fGCM concentrations at that colony (Fig. 5A,B). More-
over, seal fGCM concentrations were not correlated with
either colony latitude or longitude in either the warm or
cold season (Fig. 5C–F).
The predation-stress hypothesis predicts that risk from
predators causes activation of physiological stress reac-
tions in prey, which can directly or indirectly reduce
reproduction and survival (Romero 2004, Clinchy et al.
2013). Observational and experimental studies have
found mixed evidence for such increases in stress hor-
mones of prey in response to predators or predation cues
(Boonstra et al. 1998, Clinchy et al. 2004, Creel et al.
2009, Sheriff et al. 2009) and to date there have been too
few studies of the predation-stress hypothesis in the wild
to infer general relationships (Clinchy et al. 2013). In this
study, we found that spatiotemporal patterns of stress in
Cape fur seals, measured by fGCM concentrations, were
consistent with predation risk from white sharks at the
site and seasonal level. In contrast, fGCM levels were not
detectably related to seal colony population size, density
and geographic location. Moreover, our subsequent study
in False Bay, revealed seal fGCM concentrations were
strongly positively correlated with temporal variation in
shark predation rates, but not with shark relative abun-
dance (Fig. 4). These findings provide empirical support
for the predation-stress hypothesis in the wild from a nat-
ural experiment involving large long-lived apex predators
and their prey. It is worth considering here that seals may
also incur costs consistent with the predator-sensitive
food hypothesis, which could be assessed through the
future research using energetic or nutritional indicators
(Gallagher et al. 2017a,b). The two mechanisms are not
mutually exclusive (Creel et al. 2009).
Below we separately discuss plausible alternative expla-
nations for the patterns found; however, it is likely that
some unmeasured variables (e.g., storms) are contributing
at least partly to the variation in measured fecal cortisol
levels, such as the seasonal difference in mean fGCM that
were found for the colony in Lambert’sBay.However,
the data gathered suggest that these factors are not the
primary drivers of the nearly quadrupling in fGCM levels
that occurred at the False Bay and Mossel Bay “high risk”
seal colonies during the high predation season. In con-
trast, we believe the majority of this variation is attributa-
ble to predation stress. While our data is correlative, our
inference is strengthened by the added results from the
False Bay study where the magnitude in variations of
fGCM levels were associated with recorded predation
rates on seals, measured on multiple occasions across dif-
ferent seasons over the course of two years (Fig. 4A).
The occurrence of some white sharks at the high shark
abundance colonies during the warm season, albeit lower
than during the cool season (Table 1), may seem difficult
to reconcile with the low fGCM stress levels found there,
which were comparable to the low shark abundance colo-
nies where no tracked sharks occurred. We suggest this is
because during the warm season at the high shark abun-
dance sites, white sharks are not actively hunting Cape
fur seals (Hammerschlag et al. 2006, Wcisel et al. 2015).
Corroborating these data is behavioral information previ-
ously gathered from Cape fur seals using acoustic teleme-
try in False Bay (De Vos et al. 2015a,b). For example,
seals engaged in safer behaviors, such as swimming in lar-
ger groups and avoiding deeper water, during the high
predation season and not during the low predation sea-
son (De Vos et al. 2015a,b).
Although exposed to hunting white sharks during the
cool season, seals at Geyser Rock did not exhibit signifi-
cant seasonal increases in fGCM levels in a manner simi-
lar to False Bay and Mossel Bay. This pattern can be
explained by the previously described variation in seals’
use of landscape features unique to the waters surround-
ing Geyser Rock. Specifically, these waters contain a
mosaic of structurally complex reef and dense kelp beds
that are used by seals as refugia from white sharks and
appear to effectively reduce attack rates on seals (Wcisel
et al. 2015). So while encounter rates between white
sharks and seals are high during the cool season at Gey-
ser Rock, the seals can behaviorally mitigate their expo-
sure to risk by using the reef and kelp as a relatively safe
0 0.5 1.0 1.5 2
Shark relative abundance (sharks/h)
P = 0.66
Predation rate (attacks/h)
P = 0.0007
FIG. 4. Correlation between fGCM concentrations and (A)
mean weekly predation rates (attacks/h) and (B) mean weekly
relative shark abundance (sharks/h) at Seal Island in False Bay.
Fecal sampling occurred on seven occasions between February
2014 and August 2015. Values are fGCM means SE.
3206 NEIL HAMMERSCHLAG ET AL. Ecology, Vol. 98, No. 12
underwater pathway to escape the immediate vicinity of
the colony (Wcisel et al. 2015; Fig. 1B). In comparison,
the waters in the immediate vicinity of the two other high
shark abundance colonies (Mossel Bay and False Bay)
are relatively deep and featureless, lacking landscape
characteristics that allow seals to proactively mitigate
their risk of attack (Fig. 1C). Indeed, recorded hourly
predation rates by white sharks on seals in False Bay are
more than 18 times higher than at Geyser Rock (Wcisel
et al. 2015). Moreover, the False Bay investigation
revealed strong positive correlations between seal fecal
stress levels and shark attack rates, but not with shark rel-
ative abundance. These results are consistent with grow-
ing theoretical and empirical predator–prey research
indicating that predator presence alone does not equate
to risk, as predator hunting mode, prey anti-predator
behavior, and habitat characteristics that mediate both
will influence risk (Schmitz 2008, Heithaus et al. 2009).
The finding from False Bay that seal fecal cortisol levels
were correlated with attack rates at a weekly scale suggests
seals can accurately assess and subsequently mount a
stress reaction in relation to the magnitude of actual risk
posed from shark predation. The base of information used
by seals leading to these responses might be obtained from
direct observations of daily shark attack rates around the
colony, by in-water encounter rates with attacking sharks,
or by on-island encounter rates with conspecifics bearing
fresh bite wounds (Fig 1D). It is likely that such informa-
tion could be socially transmitted at colonies or in water
among these highly social mammals.
High population density or crowding can impact stress
levels in animals and could have contributed in part to some
of the variation in glucocorticoid secretion measured among
colonies. However, it is unlikely that density differences
among colonies or between seasons was the primary driver
of fGCM patterns found, for several reasons. First, mean
fGCM values were not correlated with our measures of seal
0 20,000 40,000 60,000 80,000
B) Colony density r= -0.09
P = 0.87
0 5,000 10,000 15,000
A) Colony population size r= 0.63
P = 0.17
31.5 32.0 32.5 33.0 33.5 34.0 34.5 35.0
31.5 32.0 32.5 33.0 33.5 34.0 34.5 35.0
C) Warm season latitude r= 0.12
P = 0.82
16 18 20 22 24
16 18 20 22 24
E) Warm season longitude r= -0.71
P = 0.12
D) Cool season latitude r= 0.24
P = 0.65
F) Cool season longitude r= 0.44
P = 0.39
FIG. 5. Plots showing lack of correlation between fGCM concentrations and seal colony (A) population size, (B) density, (C)
latitude, with data in the warm season, (D) latitude, with data in the cool season, (E) longitude, with data in the warm season, and
(F) longitude, with data in the cool season. Values are fGCM means SE.
December 2017 SHARK PREDATION AND STRESS IN SEALS 3207
colony density or population size across the study period
(Fig. 5A,B). Second, as long-lived, k-selected species, female
Cape fur seals only give birth to one offspring per year
(Kirkman et al. 2011) and established colonies in the study
region do not exhibit significant monthly or seasonal fluctu-
ations in population size or density (Huisamen et al. 2011).
The only period during which the islands exhibit relatively
large changes in seal density is during the breeding season
(December); however, we did not collect fecal samples at
this time to avoid disturbing breeding animals.
Glucocorticoids often rise in late gestation of mam-
mals due to an increase in binding globulins (see Creel
et al. 2009 for a discussion), but this phenomenon can-
not explain the observed differences among colonies or
the correlation of fGCM with exposure to risk at the
weekly time scale in False Bay. Additionally, Jutten
Island is not a breeding colony.
While annual or seasonal changes in climate could
impact seal stress levels, this is unlikely to be the primary
driver of spatiotemporal variation in stress levels mea-
sured given that all the study islands occur within the
same region. Similarly, changes in food supply could be
expected to influence stress levels in the seals, but the
colonies examined shared a common food supply (Rand
1959, 1967, Oosthuizen 1991). Although colonies vary
geographically and thus could be exposed to an associ-
ated gradient in environmental factors that may influ-
ence seal stress levels, we found no correlation between
latitude and longitude on fGCM levels at the colonies.
Hypothesized conditions leading to stress-mediated
responses to risk
It has been previously suggested that differences in the
frequency and magnitude of predation risk may affect
whether prey mount a physiological stress response (Creel
et al. 2009). Seals at the high risk colonies of False Bay and
Mossel Bay may behaviorally reduce their individual level
of risk by employing grouping when in the water (dilution
effect and increased vigilance; Fallows et al. 2012) and/or
perhaps by shifting movements to the night (presumably to
benefit from the cover of darkness; Johnson et al. 2009,
De Vos et al. 2015b, Fallows et al. 2016). However, once
in the water and traversing the gauntlet, the seals cannot
reliably predict or detect a hunting shark prior to the
launch of an ambush attack (Martin et al. 2005). For
example, shark kill rate averages 0.48 per day in False
Bay, with frequency of attacks ranging from 0 to 45 per
day (Hammerschlag et al. 2006). Thus, when traversing
the gauntlet in False Bay and Mossel Bay, seals are
exposed to unpredictable, potentially lethal, and rela-
tively uncontrollable risk of attack, precisely the condi-
tions known to produce physiological stress in controlled
biomedical experiments (Weiss 1970, Romero 2004,
Sapolsky 2005). As discussed above, despite a high abun-
dance of hunting white sharks at Geyser Rock, relative
predation risk to seals is comparatively low due to land-
scape features permitting seals to proactively mitigate
risk of shark attack (Wcisel et al. 2015). Here again, the
ability to control exposure to a stressor is known to
reduce glucocorticoid responses in biomedical experi-
ments (Weiss 1970). A similar predator–prey scenario to
the one at Geyser Rock may exist between wolves and
elk in the Yellowstone ecosystem. Specifically, the pres-
ence of wolves has not been found to cause activation of
the fGCM stress response (Creel et al. 2009), likely
because elk can proactively mitigate their risk by altering
their patterns of habitat selection, grouping and behav-
ior, and wolves can be detected proactively using a com-
bination of vision, olfaction, hearing, and perhaps social
transmission of information (Creel and Winnie 2005,
Fortin et al. 2005, Christianson and Creel 2010).
In summary, our study had four primary results. First,
differences in measured Cape fur seal fGCM levels were
strongly associated with patterns of white shark predation
risk at the site and seasonal level, equally for both adults
and juveniles, based on multi-year sampling from six pop-
ulations. Second, seal fGCM levels were not correlated
with colony population size or density, nor with colony
geographic location (a proxy for geographic gradients in
environmental factors that might be expected to influence
stress levels). Third, within a high risk site (False Bay),
fecal cortisol concentrations across two years were strongly
correlated with temporal variation in shark attack rates on
seals at the weekly scale, but not with shark relative abun-
dance. Finally, seals from the Geyser Rock colony did not
sharks despite being exposed to high encounter rates with
sharks. However, in contrast to the other focal colonies tar-
geted by white sharks, seals at Geyser Rock can proactively
mitigate their risk behaviorally through use of subsurface
habitat refuges (Wcisel et al. 2015). Based on results from
the current shark–seal study system and in comparison to
other systems (e.g., elk exposed to wolves), we hypothesize
that predation risk will produce physiological costs, in the
form of a stress response, when risk cannot be adequately
predicted or mitigated by behavioral responses.
Glucocorticoid stress responses can carry fitness and
reproductive costs to individuals (Weiss 1970, Sapolsky
2005) and previous research has revealed that acute and
chronic physiological stress experienced by fur seals can
consequently result in mortality (Seguel et al. 2014).
Thus, future research is needed to determine the potential
differential contribution of various shark effects (e.g., pre-
dation mortality, physiological stress, foraging mediated
costs) and environmental variables (e.g., food limitation)
on seal fitness and population dynamics at the colonies.
This is especially important given recent conflicting data
on declining white shark populations in the study region
and associated concerns for the ecological consequences
(Towner et al. 2013, Andreotti et al. 2016).
Understanding the mechanisms and underlying
circumstances that can lead to differences in the occurrence,
3208 NEIL HAMMERSCHLAG ET AL. Ecology, Vol. 98, No. 12
magnitude, and type of prey response to a predator in
the wild is a challenge, but an important one given wide-
spread declines of top predators globally and associated
growing conservation recovery efforts and successes
(Myers and Worm 2003, Estes et al. 2011, Neubauer
et al. 2013, Marshall et al. 2016). It is probable that path-
ways leading to stress reactions of prey to predation risk
will vary among taxa, contexts, and systems, with differ-
ing consequences for prey population dynamics, as has
been found for food-mediated responses to risk (Schmitz
2008). The hypothesis presented here, describing the con-
ditions leading to physiological stress responses in prey,
provides a testable null model that may aid in future
empirical investigations of the physiological mechanisms
underlying predation risk effects on prey in the wild.
For providing satellite tagging data used in this study, we wish
to thank OCEARCH and collaborating researchers from the
OCEARCH South Africa Expedition, including Chris Fischer, Ali-
son Kock, Dylan Irion, Alison Towner, Enrico Gennari, Ryan
Johnson, and Malcolm Smale. For providing white shark survey
data throughout the Western Cape province of South Africa, we
are thankful to Sara Andreotti. Seal fecal samples were collected
under research permits from the South African National Parks
and the South African Department of Environmental Affairs
(DEA). For assisting with collection and organization of fecal sam-
ples, we are grateful to Yves Chesselet (Cape Nature), Deon Kotze,
Steven McCue, Laurenne Snyders, Bruce Dyer, Lieze Swart, and
several DEA interns. For assisting with predation data and field
work, thanks to Monique Fallows and Lacey Williams from Apex
Shark Expeditions. Thanks to Rachel Skubel and Emily Nelson
for helping with paper formatting. We thank John Bruno, Mark
Hebblewhite and the anonymous reviewers of our manuscript for
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St. George, Bermuda (August 9, 2016) – Underwater conservation initiative Project Baseline has completed the longest underwater video transect from the deep ocean to a shoreline in history. The world record transect recorded two and a half miles of ocean floor off the coast of Bermuda and was achieved through the collaboration of GlobalSubDive (GSD) manned submersibles and volunteer scuba divers trained by Global Underwater Explorers (GUE). The marine life samples and stereo-video footage will be used to establish the first baseline for the health of the Sargasso Sea in Project Baseline’s database of documentation of the world’s aquatic environments.
A human-occupied submersible piloted by Robert Carmichael, founder of GlobalSubDive, started the video transect of the deep ocean floor at a site called Spittal. A series of (3) 20-minute, horizontal transect dives were carried out at 1,000, 800, and 650 feet. At 300 and 200 feet, a team of GUE technical divers led by Dr. Todd Kincaid completed horizontal stereo video transects and marine life sample collection and then continued a vertical line transect to the shoreline. The transect was completed in one day’s worth of diving, making it the most ever accomplished in one day, at this depth, and of this length.
“We’re creating vertical and horizontal transects, which allows us to understand a cross section of this environment,” Robert Carmichael said. “That is not being done anywhere, uniting a skilled technical diver set with scientists and submersibles for the benefit of the ocean.”
Project Baseline places humans into depths from 1,000 feet to the shoreline to collect high quality imagery from two different angles, as opposed to using remote operated vehicles (ROVs). Horizontal recordings capture fish populations and related habitat structure, while vertical angles aid researchers in understanding benthic communities in greater detail than currently known.
The video transect data and sample are given to scientists aboard the Baseline Explorer who are a part of the XL Catlin Deep Ocean Survey / Nekton Mission in Bermuda. Collectively, the missions are creating a new standardized methodology for marine biologists to measure physical, chemical, and biological indicators to assess the function, health, and resilience of the deep ocean. The data will be released as part of the XL Catlin Deep Ocean Survey after the mission ends on August 14.
“Not only are we going places people have never really been before, but we are collecting data that is critical to establishing environmental baselines in Bermuda and influencing conservation policy,” said Dr. Todd Kincaid, Director of Science and Conservation for Project Baseline.
The data collection missions are launched from the 146-foot r/v Baseline Explorer, a mobile diving platform equipped with human-occupied submersibles and volunteer technical dive teams.
“We believe that everyone in the world can have a true understanding of what is going on in the underwater environment once we have something to compare it to, but first we need to establish a baseline,” said Carmichael.
Follow along on Facebook! facebook.com/ProjectBaseline


Atlantic Weather Is Bringing Fish Decline
The fish decline associated with the striped bass had been successfully combated back in the 1980s by setting stringent rules which forbade overfishing. But the low rate of the marine animal this time round could be much more serious as the scientists now suspect that the weather brings fish decline as well. The Atlantic weather is bringing fish decline fears Bob Wood, a biologist attached with the ‘National Oceanic and Atmospheric Administration’.
Wood is now conducting a research into the cause of the fish decline which hopes to establish the fact that it is the weather behind the decline of fish. A study of the AMO or the ‘Atlantic Multidecadal Oscillation’ will take us closer to the truth feels Wood.
The AMO is known to have affected marine life whenever the shift in winds and oceanic current takes place. The phenomenon is known to occur every 35 years at the North Atlantic region causing a substantial fish decline in the area. The AMO is also known to affect the local weather along the coasts of Atlantic, states Ed Martino an associate of Wood.
The changes in temperature and precipitation is one of the predominant factors of fish decline explains Martino reiterating the fact that such climatic changes could play havoc with the saline levels of the sea thereby striking at the very base of the food chain, the Plankton. It is these tiny marine creatures that are consumed by the Striped Bass. The loss of Planktons caused by the AMO shift results in fish decline corroborates the two biologists.
Image Courtesy: porroa.com


From the richness of the Coral Sea to underwater volcanoes, photographer Alexis Rosenfeld will travel the seas of the planet under the sponsorship of Unesco, a 10-year mission in images intended to raise awareness of the “dramatic” situation of oceans.
“The situation of the Ocean is dramatic, biodiversity suffers a lot, but people see it less than what is happening in their garden”, explains to AFP Vladimir Ryabinin, executive secretary of the Intergovernmental Oceanographic Commission of Unesco , which sponsors this operation “1 Ocean, the great testimony on the ocean”.
“There is a proverb which says: far from the eyes, far from the heart. It is an important project because it is an answer to this problem”, continues the Russian scientist.
The project, which is part of the United Nations decade for ocean sciences in the service of sustainable development (2021-2030), wants to “highlight the wealth and threats weighing on the ocean through 1,000 photographs”.
A bit like the adventure “Earth seen from the sky” by photographer Yann Arthus-Bertrand, but under the sea. And “with a more scientific and more committed dimension”, comments Alexis Rosenfeld.
Before exhibitions planned later around the world, a first dive into this universe will be unveiled on the forecourt of the Gare de Lyon in Paris from March 4. Like the images of a first mission in the Coral Sea National Park, off the coast of New Caledonia, interrupted by the Covid in 2020.
“It’s an incredible place. The quantity of animals per cubic meter is worthy of a cartoon, of the imagination of Jules Verne”, tells AFP the photographer-diver who displays on the counter “more than 10,000 hours below the surface “.
“It is the area considered to be the most pristine and the richest in the world,” he continues, seeing it as a means of “demonstrating the importance of marine protected areas”.
The ocean, increasingly ill with the absorption of CO2 generated by human activities, is at the heart of the planet’s climate challenges, but also threats to biodiversity.
This great testimony “above all photographic” will focus in particular on the means of making the corals more resistant to warming, on the “ghost” fishing nets which continue to fish after being lost at sea, on the little known underwater volcanoes. or the proliferation of Sargassum algae.
Operation “1 Ocean” will also include texts and “making of” videos, as well as testimonials from personalities from the world of art, science or sports who will talk about their relationship with the ocean.


Elizabeth Wallace, Ph.D., 2020
Jeffrey Donnelly, Advisor
Little is known about how Atlantic hurricane activity changes on long timescales. This thesis uses proxy development and proxy-model integration to constrain the spatiotemporal variability in hurricane activity in the Bahama Archipelago over the past millennium. I present annually-resolved archives of storm activity derived from sediment cores from blue holes on three islands in the Bahama Archipelago: South Andros, Long Island, and Middle Caicos. Dramatic differences between these records suggest localized controls on the hurricane patterns observed by each island. Thus, compiling these records together more accurately captures regional variations in hurricane strikes. Integrating our new Bahama Archipelago compilation with compiled paleohurricane records from the U.S. coastline indicates shifting patterns of hurricane activity over the past millennium between the Gulf Coast and the Bahama Archipelago/New England. Finally, I address whether variability in hurricane strikes observed in Bahamian paleohurricane records is related to climate or random variability using hurricane model output. The signal observed in any individual record of paleohurricane activity from the Bahama Archipelago is driven more by random variability in hurricane tracks than by climate. This thesis lays the groundwork for creating high-resolution paleohurricane records from blue holes and using hurricane models to inform our interpretations of these records.


Oceanic and atmospheric modes play a key role in modulating climate variations, particularly on interannual and interdecadal scales, causing an indirect response of regional climate to external forcings. This study comprehensively investigated the time-varying linkages among dominant oceanic and atmospheric modes of the Pacific and Atlantic areas on different timescales using the scale space multiresolution correlation analysis. For the Pacific Ocean, the Interdecadal Pacific Oscillation (IPO) shows closer matches with the El Niño-Southern Oscillation (ENSO) than with the Pacific Decadal Oscillation (PDO). This indicates that the ENSO dominates climate variability of the whole Pacific Ocean not only on interannual but also on interdecadal scales. Interdecadal variations of the IPO appear to be more closely linked to southern Pacific Ocean climate before ∼1940, but become more closely linked to northern Pacific Ocean after ∼1940. The shifts on interdecadal connections among northern, tropical and southern parts of the Pacific Oceans seems to be related to the phase shifts of the IPO/PDO, which may contribute to the cooling trend from 1940s to 1970s. For the Atlantic Ocean, the Atlantic Multi-decadal Oscillation (AMO) is closely linked to the North Atlantic Oscillation (NAO) on the interdecadal scale before ∼1940.
- Climate teleconnection
- Scale space multiresolution analysis
ASJC Scopus subject areas
- Earth-Surface Processes


If you follow food issues, one of the topics that surfaces again and again is how exactly we’re going to feed a planet expected to exceed 9 billion hungry mouths by 2050.
Experts talk about crop yield and study ways to increase animal production. Others predict future food shortages will eventually require us to adapt to a vegetarian lifestyle. Mmmm … kale.
But an oft-overlooked part of the sustainable protein conversation is aquaculture. This has less to do with farmed bluefin tuna and farmed Atlantic salmon — which both have serious sustainability issues — and more to do with oysters, clams and mussels.
Bivalves are the darlings of the sustainable seafood world. They’re filter feeders that clean the water as they grow. They don’t require supplemental feed. No pesticides or antibiotics are used in their cultivation. There are virtually no issues with escapement. They’re a delicious, affordable source of protein. Every way you look at it, they could become an important part of the solution of how to feed the planet. There’s just one problem with all of this: It’s called ocean acidification.
The world’s oceans are changing. Not only are sea levels rising and ocean water getting warmer, but the sea has been acting as a huge sponge, soaking up our excess carbon dioxide.
Unfortunately, it’s being dissolved into the ocean, making our waters acidic, and it’s happening at an alarming rate. For oysters, and other creatures that make calcium carbonate shells, the ocean’s changing pH levels mean tiny larvae have a hard time creating the shells they require to survive.
Right now, this change is primarily visible in the Pacific Northwest (although seafood-watchers on the East Coast are worried too — the Washington Post just published this story on how acidification is affecting Maryland’s treasured blue crabs). Hardest hit are oyster companies like Taylor Shellfish Farms and Whiskey Creek Shellfish Hatchery that produce the seed aqua-farmers up and down the West Coast use to grow oysters.
Scientists are beginning to take a closer look off our own San Diego shoreline.
“We’re not immune to ocean acidification. The pH of our waters offshore are changing here as well,” said Dennis Peterson, biologist and director of science at Carlsbad Aquafarm, which produces the Carlsbad oysters that appear on raw bar menus and at dollar oysters nights across San Diego. (They’re also the only oyster farm in Southern California.)
While Peterson says ocean acidification hasn’t caused massive oyster die-offs at the Carlsbad farm yet, he is worried about the company’s mussel production.
“The byssus thread is what I’m really worried about. I lose a lot of product in the summer already, and if it gets worse, I could see that as a real problem,” he said.
That byssus thread is the fiber mussels produce to cling to rocks. As mussels mature, they get heavier. When the byssus thread is weak, it makes it hard for the bivalve to stay attached to its growing surface. Whether pH changes in the water are impacting the development of the byssus thread is still uncertain, but Peterson said there’s cause for concern.
“It’s important that we tease apart what’s ocean acidification, what’s global warming and what’s La Nina,” he said.
To help solve the mystery, Peterson connected with Gretchen Hoffman, a marine scientist from the University of California, Santa Barbara. Hoffman and her team have been placing monitoring equipment up and down the coast of California to track ocean acidification levels.
“We want to learn what’s going on in the water at economically important sites,” she said. “We want to understand which species are more resilient, and to identify those that are sensitive. Without a doubt, San Diego is an important region for us.”
While ocean acidification may make it difficult for oysters to form shells, mussels to form healthy byssus threads or may eventually impact species like rock fish or other economically important fisheries; some species like sea urchin, seem to be more resilient. At least so far.
The California Ocean Protection Council has formed a working group to monitor the effects of ocean acidification and to develop recommendations, similar to the way Washington state created a Blue Ribbon Panel on the issue, Hoffman said.
“We’re trying to do for California what Washington did, and to understand the science,” she said.


Southwest Florida Shoreline Studies
Come study SW Florida's bays and beaches with us....
SW Florida Shoreline Studies
SW Shoreline News
This blog is dedicated to the environmental well-being of our Florida coastal habitat.
This blog is
dedicated to the environmental well-being of coastal habitat.
Sunday, January 13, 2013
Warm Weather Question
Hey you, READER, what are the effects of the current exceptionally warm weather on Sarasota's Shoreline?


Hawaii Locals Tee
Hawaii - respect the local wildlife. This vintage-inspired beachy graphic supports Ocean Conservancy, an organization working to protect our oceans and all the creatures within it.
- Unisex sizing for a relaxed, comfy fit
- Heavy wash jersey
- 100% cotton, garment-washed for softness
- Model wears a size small


Mote Marine Laboratory will host a five-day coral restoration workshop in the Florida Keys, providing hands-on intensive training in Mote’s signature coral fragmentation process, along with knowledge about coral larval settlement and survival in a land-based nursery and proper monitoring of outplanted coral. Dr. David Vaughan, Executive Director of Mote’s Elizabeth Moore International Center for Coral Reef Research and Restoration and Manager of Mote’s Coral Reef Restoration Program, will lead the coral restoration workshop starting March 25, ending March 29 and geared toward those with an interest in conducting their own restoration projects.
Vaughan most notably pioneered implementation of coral fragmentation techniques to re-skin massive coral species for reef restoration. Vaughan’s first workshop late last year was designed to share best practices with other coral restoration enthusiasts. “We had students from all around the globe come to our facility to learn our methods of restoration. Many already had restoration efforts underway in their parts of the world and were interested in implementing new key knowledge and understanding how to scale-up their production,” said Vaughan. The first workshop was deemed such a success by the attendees that Vaughan decided to host another workshop this March. “The knowledge transfer with other coral restoration stewards is so important as we all continue to face similar impacts to our marine environment,” added Vaughan.
Workshop Schedule (some activities are weather-dependent):
Monday, March 25: Orientation & tour of the facility; History of massive and staghorn coral restoration
Tuesday, March 26: Massive coral species production and land-based nursery training; Participant presentation of current projects/interests; micro-fragmentation lab & fusion
Wednesday, March 27: Field nursery dive or snorkel, nursery gear manufacturing and site selection
Thursday, March 28: Research project presentations/review; coral sexual reproductions opportunities and settlement; early juvenile care, genotype testing and tracking; data collection, scale-up and economics
Friday, March 29: Land-based system design, planning and construction; field trip to outplant site
The cost of the workshop is $1,400 and includes meals and accommodations at the facility. Each participant is responsible for providing their own snorkel and/or dive equipment. For more information or to register, click here. If you are interested in learning more about coral restoration workshops and volunteer opportunities, visit: https://docs.google.com/forms/d/115hrupqiN6l5gJAdEjrZdx6im7lJ3M8BNUFqOG5ckno/viewform?ts=58cae651&edit_requested=true.


THE OFFICIAL BLOG OF NORTHEAST MARITIME INSTITUTE
Blue Stream Shellfish, LLC – A Morning in the Life of an Oyster Aquaculture Crew
There is a growing demand for more sustainable food sources on our planet. Aquaculture poses one of the more promising ways to meet this objective. Not only does aquaculture provide sustainable seafood, but also ecological, environmental, economic, and societal benefits to our world.
The 2018 Massachusetts Division of Marine Fisheries annual report stated that the Massachusetts Oyster industry was valued at $27.5 million. The Massachusetts aquaculture industry is still in its infancy and is predicted to develop and continue to grow exponentially.
In our developing Restorative Aquaculture program at Northeast Maritime Institute, we have been collaborating and gaining aquaculture experience with our industry partners and Nasketucket Bay, Fairhaven sea farming neighbors like Blue Stream Shellfish LLC. (BSS).
What follows is one of my typical mornings when I intern with the crew at Blue Stream Shellfish to learn the ropes in oyster aquaculture.
Every Tuesday morning, I join the morning shift with the crew at Blue Stream Shellfish in Fairhaven, MA. I take a final left hand turn across from Hoppy’s Landing before the West Island causeway and into the West Island Marina parking lot. I put on my rain bibs, my boots, and my gloves, grab my water bottle and head toward the Blue Stream Shellfish docks. I am here to learn the ins and outs of oyster aquaculture. After teaching nautical science and sailing for the past 40 years, I realize that it is much more effective to teach a subject that you have gained experience in!
I join some of the BSS crew in the 25’ Carolina work skiff. We motor out to the farm site in Nasketucket Bay. We haul lantern nets, pull bags full of oysters from bottom cages and floating oyster “condos” (wire mesh cages that contain multiple bags of oysters in racks within the cage). The oyster bags get piled into the skiff. We return to the processing barge, the bags and nets are opened, and loaded into the sorting hopper. A conveyor system pulls oysters from the hopper bin into a slow spinning cylindrical drum where the oysters are cleaned and tumbled to develop shape before they are cleaned, sorted, and sized on the culling table.
Four to six BSS crew process the oysters on the culling tables. Each oyster is externally cleaned (of marine growth) by hand, and then sized as “Grande”/4+ inches extra-large, “Market”/3 inches, “Petite”/2.5-3 inches, “put-backs”/(go back into the cages to grow) or “boxes”/shell only. This processing goes on all morning with a break midway. Other tasks are taking place simultaneously while the sorting goes on. Emptied bags and nets are power washed of barnacles, tunicates, sponges and other marine growth and then readied to be redeployed. Market oysters are counted and bagged to make up outstanding orders to be delivered or picked up.
So… what have I learned from my Tuesday morning sea farming on-the-job training? I’ve learned by hands-on experience the intricacies of culturing oysters from seed to market. There is a great deal of labor and care that goes into an oyster that is ready for the consumer to enjoy. Oyster farming like all farming is demanding, repetitive, and physical. It is fulfilling work to provide locally grown seafood to the community to enjoy and sustain them. It is a blessing to work on the sea in a setting as lovely as Nasketucket Bay, Fairhaven Massachusetts. It makes me proud to work shoulder to shoulder with such a fun loving, hardworking, smart, capable, sterling Blue Stream Shellfish oyster farming team!
Click here to learn more about NMI’s Office of Restorative Aquaculture.


For more than 80 years grey seals (Halichoerus grypus) were assumed to be extinct in the German Baltic Sea. The reasons for their disappearance were hunt, loss of habitats and massive pollution of the Baltic Sea causing infertility. In the 1980s the Baltic grey seal was threatened with extinction while the number of seals collapsed. The number decreased from originally more than 100.000 Baltic grey seals to only 2.000 remaining individuals.
Over the last decade grey seals were sighted again year round in the German Baltic Sea. The number of seals increased steadily with seasonal fluctuations. The return to their historical sites is a highly sensitive period. For the future management of this protected species, the knowledge about potential anthropogenic disturbance is critically needed.
This research project analyses potential disturbances to grey seals as well as their habitat use and site fidelity in the German Baltic Sea. Main focus are abundance estimation, establishing quality criteria of haul-out sites, temporal and spatial distribution of seals in the research area and the effects of disturbance.
The project utilizes several techniques:
- Photo-id allows for the identification of grey seals and enables long-term abundance estimations. Data is collected during periodic counts.
- Additionally, webcams and wildlife cams along the coastline provide continuous data for photo-id. Moreover, these non-invasive camera systems give an insight into the seals’ lives and records their behavior and reactions to interfering sources, for examples boats.
- An underwater noise recorder will document the noise emissions at one haul-out site.
The results of the project serve for reporting requirements and will influence the development of indicators of the marine strategy framework directive (MSRL) and corset indicators (HELCOM). The results will feed into further international protection agreements. Furthermore, this project serves as a scientific basis for the management of grey seals in the Baltic Sea.
The project is funded by the Federal Agency for Nature Conservation.


LOS ANGELES, May 31 (UPI) -- Changes have been made in shipping lanes along the California coast to give whales a break, a shipping industry association said Friday.
In an effort to reduce collisions between freighters and whales, routes within the Channel Islands National Marine Sanctuary, near the Los Angeles and Long Beach ports, have been changed, as well shipping lanes in national marine sanctuaries near San Francisco Bay and the Santa Barbara Channel, the Los Angeles Business Journal reported.
The Pacific Merchant Shipping Association said the new routes are effective Saturday.
Airplanes will also be used to spot migrating whales, the newspaper said.
The new routes will affect shipping companies that are members of the trade group and other commercial vessels.
The action follows recommendations made by the Channel Islands National Marine Sanctuary Advisory Councils and other organizations, with input from the National Oceanic and Atmospheric Administration, National Marine Fisheries Service, the U.S. Coast Guard, biologists, researchers and other environmental groups, the newspaper said.
The changes were approved by the International Marine Organization.
"We are in full agreement with the shipping changes as they will help assure the protection of both human and marine life and the continued safe and efficient flow of commerce in and out of California ports," association Vice President TL Garrett said the adjustments will be good for both shippers and whales.
said in a statement.


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This loop of GOES-9 visible imagery shows ship condensation trails ("ship tracks") off the California coast on 15 July 1998. These features were being distorted as they were carried southward by northerly winds within the marine boundary layer. Note the cloud-free regions downwind of the islands off southern California -- these result from the the islands acting as a barrier to the winds and stratocumulus clouds within the marine layer. Aslo evident are the snow-capped Sierra Nevada Mountains in central California.


“Working in ocean conservation, I can teach people about something that I care about deeply with the hopes that it will inspire others to care just as much as I do.”
Eva Touhey grew up immersed in the island life. Growing up in Portsmouth, Rhode Island on Aquidneck Island, she’s lived within minutes of the coast and surrounded by the waters of the Ocean State, so protecting and preserving ocean health is a topic near and dear to her.
Eva earned her bachelor’s degree in biology in 2015 from Hobart and William Smith (HWS) Colleges, located in the heart of New York State’s Finger Lakes region. Before coming to Clean Ocean Access (COA), Eva gained experience working as an animal caretaker assistant at the HWS biology department and an aquarist intern with Save The Bay.
She first discovered COA through a beach cleanup in her hometown and quickly became inspired to advance the budding organization’s mission. Eva began interning with COA in the fall of 2015, working to organize and analyze the Seaweed Nutrient Analysis Program (SNAP) two-year raw data set. She led presentations about the watershed, sources of pollution in the watershed, and pollution prevention. She later joined the team as an education coordinator, helping to develop hands-on environmental curriculum for elementary school students across Aquidneck Island.
“We didn’t have an office and I met with Dave in coffee shops to discuss the project I was working on,” recalls Eva. “In the three years I have been involved with COA, we have grown a lot as an organization. We now have an office, a solid work team and great interns.”
Eva is now COA’s program manager and oversees the organization’s programming, volunteer management, and advocacy efforts. “I am motivated to stay with COA because we have so much potential to do more great work, and I really am interested and excited to see where it takes us,” she adds.
As she works to finish her master’s degree in marine affairs at the University of Rhode Island this year, Eva aims to educate Rhode Islanders about the importance of having policies to protect the environment, though she is hopeful that environmental protection can be achieved without strict policies, but instead through instilling environmentally-responsible behavior in the community.
Eva’s master’s thesis, entitled “The Influence of Plastic Bag Bans on Pro-environmental Behaviors in Rhode Island Coastal Communities,” analyzes the effects of plastic bag bans on individual behaviors, and takes an in-depth look at people’s awareness of and involvement in environmental groups, their awareness of plastic bag bans in their community and their general support for a state-wide plastic bag ban. She will be presenting on her research as part of COA’s Ocean Science Speaker series in spring 2019.
Where did you grow up?
I grew up in Portsmouth attending the Portsmouth public school system and am now living in Newport. Aquidneck Island is home!
What is your first memory of the ocean?
I am not sure what my first memory of the ocean is, but I remember taking family summer vacations to York Beach, Maine and spending time looking for sand dollars along the beach. My parents started bringing me to the beach at a very young age and I have memories of swimming with my dad and playing in the sand.
What is your favorite ocean activity?
Being a beach bum. I can go to the beach for hours on end and sit, read a book, go for a swim, take a nap and repeat. I am dive certified and would love to dive more often than I get to right now. I also really like looking in tide pools and seeing what little critters are there.
What motivates you to work in ocean conservation?
Growing up on Aquidneck Island, the ocean has always been home. I can’t really imagine living anywhere that’s not within minutes of the coastline. Working in ocean conservation is very personal and I can’t “sea” (haha) myself doing anything else. By working in ocean conservation, I can teach people about something that I care about deeply with the hopes that it will inspire others to care just as much as I do. We take a lot of the benefits from the marine environment for granted, and if we keep abusing this, we are going to be in much deeper trouble in the future.


AKA: sand perch
Description: The fish has a greenish-blue back with bright silver or brassy sides and belly. It can be distinguished from other drums and croakers by its terminal mouth, five to six chin pores, lack of chin barbels and strong spines on the gill cover.
Size: Silver perch grow to 9 inches.
Sometimes confused with: croaker, juvenile weakfish, spotted seatrout or kingfish
Habitat: Silver perch are found inshore in sea grass beds, tidal creeks, rivers and marshes.
Eating habits: Silver perch feed on small crustaceans, silversides, anchovies and herring.
Life cycle: Spawning occurs in the late spring or early summer, beginning later and having shorter duration at higher latitudes. Off North Carolina, spawning lasts from April through August.
Fishing tips: Silver perch are often taken by hook and line as incidental catches and used as live bait for bluefish, mackerels and striped bass.
N.C. Saltwater Fishing Tournament
No award given for this species.
Persons engaged in recreational fishing in North Carolina coastal waters are required to possess a Coastal Recreational Fishing License in accordance with G.S. 113-174.2.


We’re traveling Antarctica on Silversea Cruises. Today, we sailed the Drake Passage on our way to the Falkland Islands. Since there’s not much to report, here’s a little information about the passage and surrounding seas.
It takes nearly two days to sail from Elephant Island to the Falkland Islands though the Drake Passage or Mar de Hoces. This crossing will be our second. (our first was on day 2.) The Drake Passage spans between Cape Horn in Chile and the South Shetland Islands of Antarctica. It connects the South Atlantic and the South Pacific.
The 600 miles of the Drake Passage are some of the most treacherous and unpredictable in the world. When the cold South Atlantic water mixes with the warm water of the South Pacific, it creates choppy seas of large currents and swells. And there is no land to slow the currents down.
The passage gets its name from the 16th century English explorer, Sir Francis Drake. With only one ship left from his original fleet, he was blown south after passing through the Strait of Magellan in 1578. As a result, he was the first to suggest there was an open connection between the Atlantic and Pacific Oceans.
Half a century earlier, the Spanish navigator Francisco de Hoces was pushed south from the Strait of Magellan. He surmised there might be safe passage between the oceans, but he had no factual base for it. Some Spanish and Latin American historians give Mr. Hoces the nod for being first to discover the passage. But today the most common name is the Drake Passage.
Neither Francisco de Hoces nor Sir Frances Drake navigated all the way through the Drake Passage. In 1616, Dutch navigator Willem Cornelisz Schouten on the Eendracht recorded the first voyage through the passage. In the process he named Cape Horn after the other ship in his expedition, which sank earlier.
The boundary between the South Atlantic and the South Pacific extends from Cape Horn to Snow Island in the South Shetland Islands. We sailed from Snow Island to Elephant Island, and now we’re headed to the Falkland Islands. It is a voyage of 800 miles taking two full sea days.
There are two other passages around Cape Horn, but they’re both more treacherous. The narrow Magellan Strait and Beagle Channel easily entrap large ships in ice. For more about being icebound, read up on Sir Ernest Shackleton and his Endurance.
Antarctic Circumpolar Current
No significant land masses impede the currents in the Drake Passage. The Antarctic Circumpolar Current (ACC) is an ocean current that flows unimpeded by land clockwise, from west to east, around Antarctica. The ACC keeps warm waters away from Antarctica, enabling the continent to maintain its huge ice sheet.
The ACC is a massive flow of water that acts as a barrier separating the Southern Ocean from the Pacific and Atlantic oceans. The current extends from the sea surface to depths of more than 2.5 miles and is approximately 120 miles wide. The current is very cold ranging from slightly below freezing to just over freezing depending on the time of the year. The current is very strong and is constantly circulating.
The ACC carries an estimated 5.8 to 6.4 billion cubic feet of water every second. This is the equivalent of 43.3 to 47.8 billion gallons of water every second.
The mixed water moves onward to the other oceans through the Drake Passage. The AAC also moves around steep undersea mountains that restricts its path and steers it north and south across the Southern Ocean.
The AAC carries a huge volume of water around Antarctica. It flows at 600 times the Amazon River. So, it’s no wonder that the Drake Passage is so rough. Traveling north we haven’t seen any land or icebergs. With temperatures in the 40-degree range, it’s too warm for ice.
Sailing the Passage
The Drake Passage opened 41 million years ago. Scientists found fish teeth in sedimentary rock and dated it. Before the passage, the Atlantic and Pacific Oceans were separate. Back then, Antarctica was much warmer, and there was no ice cap. When the passage opened, the two oceans joined and started the AAC, which has provided air conditioning for the Antarctic region ever since.
The Silver Cloud has large stabilizers and usually cruises at 15 knots. But the side-to-side motion of the ship brings motion sickness to many. Madeline suffered during our first time across the Drake Passage, going from Ushuaia to Antarctica. And she suffered worse sailing back to the Falklands. And she’s not alone. The previously well attended science and history lectures now seated far fewer passengers. Since passengers can watch lectures from their suites, many stayed in their cabins—and near the bathroom.
We’re eating regularly from room service until the seas calm down. Room service on the Silver Cloud is easy and tasty. Richard, our butler, and Rebecca, our suite attendant, showed concern for us and tried their best to help. Thank you, guys!
I roamed the Silver Cloud without difficulty. I left the room this morning to ready our equipment for arrival in the Falklands. It’s a biological safety check to ensure we aren’t bringing onboard foreign material like plants, seeds and animal excrement. Silversea’s expert expedition staff check out boots, poles, gloves, parkas and hats. I did this solo because Madeline wasn’t moving beyond the couch.
Some people have no trouble with choppy water. The ones that do try remedies like scopolamine, ginger, pressure bands, Dramamine and others. The best advice we have is to go to a lower deck in the ship. The lower you go, the less you feel the wave movement.
Last night, I went to a Venetian Society cocktail party on the 8th deck. Compared to our suite on the 5th deck (lower), the rocking was more noticeable. Even staff were leaning against something for support!
The Drake Passage is a must to experience Antarctica; you’ll get two opportunities to experience it. But afterward, you’ll carry your Drake Passage badge of honor with pride.
I heard staff say that the megaships and tankers can’t go through the Panama Canal to avoid the Drake Passage. They must run the gauntlet, just like we did. But those that crew one of those tankers are happy to do so. They want to experience one of the most notorious sea crossings in the world. Those of us on the Silver Cloud have no choice. Our terrific captain and crew minimizing the waves as much as they can and are safely getting us to our next destination.
We thank them and all the service staff looking after us every day.
In tomorrow’s post I'll talk about the Falkland Islands, where we hear it's warm, sunny and calm.
That's it for Day 12 of our trip to Antarctica. More tomorrow!
Tips: You can learn how we planned our trip by reading Planning Our Antarctica Trip. Learn what we read to prepare at Reading Antarctica. And you can find out what we packed at Packing for Cruising Antarctica on Silversea.