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Abundance and distribution of the white shark in the Mediterranean Sea



Conservation of apex predators is a key challenge both in marine and terrestrial ecosystems. The white shark is a rare but persistent inhabitant of the Mediterranean Sea and it is currently assessed as “critically endangered” in the region. However, the population trends and dynamics of this species in the area are still unknown. Little is known about white shark distribution, habitat use and population abundance trends, aspects that are critical for conservation and management. In this study, we built the most comprehensive database of white shark occurrence records in the region. We collected 773 different records from different sources and used them to characterize the spatial and temporal patterns of abundance of Mediterranean white sharks between 1860 and 2016. We analysed these data by using generalized additive models and used spatially disaggregated information on human population abundance as a proxy of observation effort. Our results suggest a complex trajectory of population change characterized by a historical increase and a more recent reduction (61%, range 58%–72%) since the second half of the 20th century. In particular, analyses reveal a 52% (range 37%–88%) to 96% (range 92%–100%) overall decline in different Mediterranean sectors and a contraction in spatial distribution. Here, we provide the first reconstruction of abundance trends and offer new hypotheses regarding the drivers of change of white sharks in the Mediterranean. Our approach can be broadly applied to data‐poor contexts to reconstruct change and inform the conservation of endangered top predators in the Mediterranean Sea and other intensely used marine regions.
Fish and Fisheries. 2019;00:1–12.
  1© 2019 John Wiley & Sons Ltd
Received: 20 November 2019 
  Accepted: 22 November 2019
DOI : 10.1111/faf.124 32
Abundance and distribution of the white shark in the
Mediterranean Sea
Stefano Moro1,2 | Giovanna Jona-Lasinio2| Barbara Block3| Fiorenza Micheli3,4|
Giulio De Leo3| Fabrizio Serena5| Massimiliano Bottaro6| Umberto Scacco7|
Francesco Ferretti8
1Department of Environmental Biology,
Sapienza University of Rome, Rome, Italy
2Department of Statistical Sciences,
Sapienza University of Rome, Rome, Italy
3Hopkins Marine Station of Stanford
University, Pacific Grove, CA, USA
4Stanford Center for Ocean Solutions,
Pacific Grove, CA, USA
5Institute for Biological Resources and
Marine Biotechnology, National Research
Council (CNR-IRBIM), Mazara del Vallo, Italy
6Stazione Zoologica Anton Dohrn, Naples,
7Institute for Environmental Protection and
Research (ISPR A), Rome, Italy
8Department of Fish and Wildlife
Conser vation, Virginia Tech, Blackburg, VA,
Stefano Moro, Department of Environmental
Biology, Sapienza University of Rome,
Piazzale Aldo Moro 5, 00185 Rome, Italy.
Funding information
MIUR (Italian Ministr y of Education,
University and Scientific Research),
Grant/Award Number: 20154X8K23-
SH3; Lenfest Ocean Program; Bertarelli
Foundation; Schmidt Technology Partners;
MedReAct; Regione Lazio with the Grant
Programme “Torno Subito 2017
Conservation of apex predators is a key challenge both in marine and terrestrial eco-
systems. The white shark is a rare but persistent inhabitant of the Mediterranean
Sea and it is currently assessed as “critically endangered” in the region. However, the
population trends and dynamics of this species in the area are still unknown. Little is
known about white shark distribution, habitat use and population abundance trends,
aspects that are critical for conservation and management. In this study, we built the
most comprehensive database of white shark occurrence records in the region. We
collected 773 different records from different sources and used them to character-
ize the spatial and temporal patterns of abundance of Mediterranean white sharks
bet ween 1860 and 2016. We analysed these data by using generalized additive mod-
els and used spatially disaggregated information on human population abundance as
a proxy of observation effort. Our results suggest a complex trajectory of popula-
tion change characterized by a historical increase and a more recent reduction (61%,
range 58%–72%) since the second half of the 20th century. In particular, analyses
reveal a 52% (range 37%–88%) to 96% (range 92%–100%) overall decline in different
Mediterranean sectors and a contraction in spatial distribution. Here, we provide the
first reconstruction of abundance trends and offer new hypotheses regarding the
drivers of change of white sharks in the Mediterranean. Our approach can be broadly
applied to data-poor contexts to reconstruct change and inform the conservation of
endangered top predators in the Mediterranean Sea and other intensely used marine
Mediterranean Sea, observation effort, opportunistic and sparse data, spatio-temporal
patterns, standardized trends, white shark
The loss of top predators is one of the most challenging forms of
global environmental change, with still unrecognized and not well-
understood ecosystem effects (Estes et al., 2011). The decline of
large predators on land started approximately 50 kya with the great
demographic and geographic human expansion (Dirzo et al., 2014;
Ripple et al., 2014). In the oceans, recent increases in resource ex-
ploitation by high seas industrial fishers as well as artisanal fleets,
habitat degradation and climate change pose unprecedented chal-
lenges also to marine predators (Worm & Tittensor, 2011). In the
Mediterranean Sea, predator loss is more severe than other ocean
   MORO et al.
sectors due to thousands of years of human impact on marine com-
munities (Coll et al., 2010) and currently high cumulative human
pressure on marine ecosystems (Micheli et al., 2013). However, it is
only in the last 50 years that systematic data started to be gathered
to evaluate the impact of fishing on exploited marine populations
and ecosystems (Ferretti, Jorgensen, Chapple, Leo, & Micheli, 2015;
McClenachan, Ferretti, & Baum, 2012). This lack of historical base-
lines hampers our ability to fully understand the ecology of habitats
and species, and consequently, our ability to evaluate the conserva-
tion status of Mediterranean ecosystems and marine populations.
Among marine animals, sharks are one of the marine taxa with
the highest percentage of threatened species (Dulvy et al., 2014).
They are generally vulnerable animals, with very low resilience and
biological productivity, strongly susceptible to fishing pressure
(Ferretti, Worm, Britten, Heithaus, & Lotze, 2010; Queiroz et al.,
2019), though examples of sustainable shark fishery also exist (see
for details Simpfen dorfer & Dulvy, 2017). Because of these features,
in the past decades, many shark populations showed rapid declines
in multiple marine regions mostly because of the direct effect of tar-
geted and bycatch fisheries (Baum & Blanchard, 2010). An among
global ocean sectors, the Mediterranean Sea showed the worst
population declines and conservation statuses for many populations
(Cavanagh & Gibson, 2007; Ferretti, Myers, Serena, & Lotze, 20 08).
In 2016, the International Union for Conservation of Nature (IUCN)
compiled the second regional assessment of sharks and rays in the
Mediterranean Sea, reporting that after ten years the situation had
not improved and the conservation status of these species remained
probably the worst in the world (Dulvy, Allen, Ralph, & Walls, 2016).
In fact, 39 of the 73 assessed species are still threatened and 13
are still considered Data Deficient (Dulvy et al., 2016). Moreover,
for most non-data-deficient species, the risk assessment was based
on suspected trends and not adequately supported by quantitative
analyses. For instance, the conservation status of the white shark
(Carcharodon carcharias, Lamnidae) was raised from Endangered to
Critically Endangered in both Mediterranean and European Regional
Red Lists (Dulvy et al., 2016; Nieto et al., 2015) solely on the ground
of its current sporadic occurrence in the region and suspected
The white shark is one of the largest and most widespread top
predators in the ocean. It is broadly distributed between the sub-
polar and subtropics in both hemispheres, with major coastal ag-
gregation sites in temperate latitudes (Compagno, 2001). Most of
the biological and ecological research on white sharks have been
carried out in three coastal aggregation sites (Huveneers et al.,
2018): California (Chapple et al., 2011; Tinker, Hatfield, Harris, &
Ames, 2016), southern Australia (Bruce & Bradford, 2012) and South
Africa (Kock et al., 2013). Here, satellite and acoustic tagging, ge-
netics and isotopes analyses have deepened our ecological under-
standing of the species’ migrations, preferred habitats, population
structure, abundance and distribution patterns (Bruce & Bradford,
2012; Carlisle et al., 2012). Even if a general assessment of the
white shark abundance trends is challenging to achieve, there have
been several attempts in different areas to assess the status of the
sharks. Locally, different data sources and modelling approaches
have been adopted (Christiansen et al., 2014; Curtis et al., 2014;
Dudley & Simpfendorfer, 2006; Lowe et al., 2012; Reid, Robbins, &
Peddemors, 2011). Most of these attempts showed a slow increase
in white shark populations or subpopulations relative abundance in
recent years due to the presence of local protecting measures (Curtis
et al., 2014; Dudley & Simpfendorfer, 2006; Lowe et al., 2012; Reid
et al., 2011). By contrast, relative declines have been detected in
regions lacking these measures (Christiansen et al., 2014). Despite
both the protecting provisions existing and the actual conservation
status, no white shark population trend analyses have been carried
out in the Mediterranean basin, so far.
In the Mediterranean Sea, white sharks have been sporadi-
cally but regularly detected throughout history. Several authors
(Fergusson, 1996; Gubili et al., 2011) hypothesized the existence of
a distinct Mediterranean population, and phylogeographic analyses
showed a large genetic distance and scarce genetic flow between
the Mediterranean and north-western Atlantic white sharks (Gubili
et al., 2011, 2015). However, little is known about the ecology and
biology of the Mediterranean population. Studying white sharks in
the Mediterranean Sea is challenging because of the low population
density and the absence of conventional aggregation sites, such as
around pinnipeds colonies (Klimley & Anderson, 1996). This makes
it challenging to conduct monitoring studies with the use of elec-
tronic tagging, and limits the scope of genetic and isotopic analyses
(Gubili et al., 2011). However, opportunistic occurrence records exist
(Boldrocchi et al., 2017; De Maddalena & Heim, 2012; Fergusson,
1996; Serena, Mancusi, & Barone, 2008). Regional reviews of these
data generated interesting hypotheses on patterns in population
structure, movements and abundance. For example, several catches
2.1. Shark database construction and exploratory
2.2. Model framework 3
2.3. Collecting observation effort data 4
2.4. Estimating standardized shark sighting trends 4
2.5. Testing for spatial range contraction 5
3.1. Explorator y data analysis 5
3.2. Model fitting results 7
3.2.1. Temporal trends 7
3.2.2. Spatial patterns and distribution shrinkage 7
MORO et al .
of young-of-the-year white sharks reported for the Sicilian Channel
suggested the presence of a nursery area in this sector (Fergusson,
1996, 2002). The reduction in white shark sightings through the
years from areas with a parallel strong decline of tuna populations,
combined with recent and historical sightings in and around farm
pens and tuna traps (Galaz & De Maddalena, 2004; Storai et al.,
2011), suggested a close relationship between Atlantic Bluefin tuna
(Thunnus thynnus, Scombridae) and white shark occurrence in the
Mediterranean Sea (Boldrocchi et al., 2017; De Maddalena & Heim,
2012; Kabasakal, 2016). Yet, more research is needed to understand
population structure, size, movements and distribution within the
area and their relations with environmental and biological variables.
Mediterranean white shark observation records are opportu-
nistic because they are often collected from fishers’ anecdotes or
newspaper articles (Pearce & Boyce, 2006), and, hence, obtained
without a specific and systematic sampling effort. Nevertheless, in
the absence of systematic surveys, opportunistic data provide valu-
able insights on species distribution, habitat requirements and pop-
ulation trends (Christiansen et al., 2014; Curtis et al., 2014; Ferretti
et al., 2015). For example, McPherson and Myers (2009) used white
shark sightings collected between 1868 and 2005 to infer popula-
tion changes in the Adriatic Sea. They estimated temporal trends of
occurrence records under different scenarios of observation effort
and estimated an 84% decline (CI: +27% and −98%). These estimates
were highly uncertain as the authors had no direct information on
observation effort but provided a first quantitative estimate of white
shark population change in a sector of the Mediterranean Sea. Here,
we expand on this approach to produce the first regional assessment
at the Mediterranean scale. We assembled the most comprehensive
database of white shark's occurrence records currently available for
the Mediterranean Sea and estimated trends controlling for obser-
vation effort, which was directly estimated with long-term trend
models of coastal human population censuses in the region. We used
these standardized records to infer trends in population abundance
and asked whether, how and how much the white shark population
has changed in abundance and spatial distribution over the last two
2.1 | Shark database construction and exploratory
We built a database containing all the white shark records in the
Mediterranean Sea using different sources and multiple search strat-
egies (Supporting Information), also including existing institutional
databases, such as MEDLEM (Mediterranean Large Elasmobranchs
Monitoring) currently under the auspices of the General Fisheries
Commission for the Mediterranean Sea (GFCM, Serena et al.,
2008). We followed through citations in the listed references to
delineate the history of each account and to determine whether
the record was original or redundant (reporting records from other
publications) (Ferretti, Morey Verd, Seret, Sulić Šprem, & Micheli,
2016). For each observation we recorded: date and location; total
length; weight; sex; age (adapted from Bruce & Bradford, 2012;
Supporting Information); record type (stranding, catch, sighting,
signs of predation on other marine animals); stomach contents; fish-
ing gear involved in the capture; and bibliographic reference for pub-
lished accounts. Then, we performed an exploratory data analysis in
order to evaluate the most immediate ecological information, such
as the sightings' temporal and spatial distribution, length frequency,
length–weight relationship and a qualitative stomach content analy-
sis (Supporting Information).
2.2 | Model framework
We stratified the Mediterranean sea in spatio-temporal statistical
units of different resolution (e.g. FAO or GFCM statistical sectors
and year) and following McPherson and Myers (2009)'s approach,
we assumed that the expected number of sightings per statistical
unit (year t and geographic se c tor s) was related to the fo llowi ng va ri-
ables: number of possible observers (observation effort), Ots, their
propensity to report a sighting, Pts, white sharks population abun-
dance, Nts, and shark detectability, Dts. In systematic and dedicated
surveys, these factors can be controlled. Conversely, this information
is incomplete for opportunistic data (McPherson & Myers, 2009). In
this work, we chose the human population size (Hts) as a proxy of ob-
servation effort. Therefore, we treated Ots and Pts as a joint process,
essentially assuming that all observers had a constant probability to
report a record (McPherson & Myers, 2009) and that the number of
observers is proportional to the human population size (Ots = cHts,
where c is constant). Hence, we assumed that detectability, Dts, has
a proportional relationship with abundance (Dts = kNts), assuming, in
other words, that a specific amount of observation effort is needed
to detect a fixed proportion of the individuals present in the study
area (McPherson & Myers, 2009). This represents the simplest pos-
sible scenario to infer standardized abundance trends of the shark
population. In fact, under these assumptions, the probability of a
recorded sighting depends only on Hts and Nts. We tested deviations
from such an assumption in the following inferential analysis.
Given that Mediterranean white shark sightings are rare and dis-
crete events, we assumed that the exp ec te d number of sharks per sta-
tistical unit follows either Poisson or Negative Binomial (NB, in case of
overdispersed data) distributions where their means are a function of
predictors describing Nts and Hts. However, it is important to note that
factors other than Hts can affect the obser vation effor t variabilit y over
space and time. For example, the marine area covered by the potential
observers and the technological innovations in fisheries and boating
may have played a pivotal role in changing the sightings probability
(fisheries have expanded in distance from shore and overall range over
time; Rousseau, Watson, Blanchard, & Fulton, 2019). So, the sighting
probability may have increased during the 20th century, but testing
this hypothesis was not possible with the available data. Therefore,
since this issue arises when interpreting the frequency of occurrence
   MORO et al.
of many other Mediterranean species, we explored the performance
of a single, readily available and systematic proxy of observation effort.
2.3 | Collecting observation effort data
In order to investigate trends in the spatio-temporal distribution
of our proxy of observation effort, we divided the Mediterranean
coastline into 202 coastal regions, belonging to 23 different coun-
tries and retrieved the human population in each coastal region
(Supporting Information) (Figure 1a,b). Historical time series of
the human population were collected for each coastal region over
a time range of 156 years (1860–2016). Multiple sources, such
as national census reports or international databases (Eurostat,
World Bank), were consulted to rebuild each human population
time series (Supporting Information). As not all considered regions
had annual census estimates for the whole time period, we inter-
polated missing years with a regression approach. Annual popula-
tion size estimates for each region were obtained by fitting GAMs
(Wood, 2011) and log-scale regressions to the historical popula-
tion censuses data. Then, we selected estimates according to the
best fitting model in each region (details are in the Supporting
2.4 | Estimating standardized shark sighting trends
In order to identify the spatial and temporal patterns characteriz-
ing the sighting data, we considered a time range of 156 years (be-
tween 1860 and 2016) and different levels of resolution for spatial
strata. We chose 1860 as our initial observation year because ear-
lier sightings were scarce and previous human population data in
most Mediterranean countries were unavailable. Observation ef-
fort and shark occurrences were spatially aggregated using both the
GFCM's Mediterranean Geographic Sub-area stratification (GSAs, aphic al-subar eas/en/)
(Figure 2a) and the coarser FAO Major Fishing Area 37's stratification
of eight divisions ( aphic al-
subar eas/en/) (Figure 3b). In order to find the best fitting model, we
tested multiple model structures (Supporting Information) with vari-
ous levels of temporal aggregation, functional relationships between
response and predictors (e.g. linear or more complex with polynomi-
als and splines) and the two statistical distributions of the response
variable (NB and Poisson). GAM s wi th 1-year time bins res ul te d as the
best model class in terms of AIC, fitting deviance and residuals analy-
sis. Model fits were performed by using the R package mgcv (Wood,
2011). We fitted a GAM with a Negative Binomial Distribution and a
log link function to the annual number of shark occurrences recorded
in each GSA , using the observation effort (annual number of peo-
ple for that GSA) as an offset term and the GSAs as spatial sectors
(hereby referred as GSA model). The model structure was
where zij is the ith observed number of sharks in year yi (i = 1, …, 156)
and GSA j, f is a smooth function estimated using penalized likelihood
maximization (with a smooth parameter estimated by Restricted
Maximum Likelihood) (Wood, 2011), [GSA]j is a factor with 27 levels
(j = 1, …, 27), corresponding to the GSAs), log (Hij) is the offset term and
is the error term for ith observation in GSA j, assu me d to be normally
distributed around 0 and with variance to estimate.
In our modelling exercises, we faced several issues. First, in order
to verify the assumption of a linear relationship between the re-
sponse variable and the offset term, we fitted a parallel model with
a spline on the human population abundance and compared the two
model's prediction errors through RMSEs (root mean square error,
Supporting Information). Second, although we could expect the
observation effort to increase with time, we supposed there could
be stages in our observation period where sighting effort changed
abruptly (i.e. star t of ocean use for bathing, intere st in marine scie nce,
conflicts and epidemics). Therefore, we tested for the effect of these
discrete important events dividing our temporal range in bins char-
acterized by different hypothetic sighting effort regimes (Supporting
Information). Finally, there was a trade-off between spatial and tem-
poral resolution. Because of the limited number of sightings from
specific Mediterranean sectors, the use of a complex spatial strati-
fication, such as the GSA scheme, with a high temporal resolution,
allowed us only to detect a common temporal trend throughout the
basin and a sector-specific spatial effect on shark's abundance. It was
where all terms are the same as in the GSA model except for fj, which
here is sector-specific ([FAO Division]j, with j = 1, …, 8). In this way, we ob-
tained subregional tempora l trends , thou gh with a lower spatial resolution.
However, this kind of model parametrization assigns the same number of
knots to each sub-regional curve via REML (restricted maximum likeli-
hood). In this way, the trajectories estimated for well-represented sectors
(with a high number of records) could have leverage on the others with
fewer occu rre nces reco rde d. Thus , in order to valida te the cur ves obtained
with the FAO model and to avoid the presence of artefacts related to the
sparse nature of data, we chose to fit, parallelly, a single-sector model for
each division (Supporting Information). Finally, we predicted the expected
number of sharks in each spatio-temporal model unit considering a fixed
amount of observation effort (five million people), in order to standardize
the shark abundance trend on easily interpretable values.
2.5 | Testing for spatial range contraction
Given its “Critically Endangered” status, it is expected the species
went through a range contraction together with a decline in popula-
tion abundance (Worm & Tittensor, 2011). To test for this scenario,
we aggregated the data in two main periods (1945–1975, 1976–2016)
deemed to have the most comparable regimes of observation effort.
We excluded from the analysis all the sightings from before 1945 in
order to minimize the bias linked to unaccountable variations of the
log (
MORO et al .
observation effort, such as the two World Wars presence. In addi-
tion, our aim was to test for a relatively recent decline associated
with a spatial range contraction. Hence, we fitted a negative binomial
generalized linear model (GLM) (R package MASS, Venables & Ripley,
2002) to the annual number of shark occurrences (considered as rep-
licates) for each time bin in each FAO division, still maintaining the
observation effort as an offset term. The model structure was.
where zij is the observ ed numb er of shark s in per iod Ti and FAO di visio n j,
β0 is the intercept, β
1–2 are regression coefficients, Ti is the time bin, [FAO
Division]j is a factor with eight levels (j = 1, …, 8, corresponding to the
spatial sectors), log (Hij) is the offset term and
is the error term for ith
observation in each FAO division j. Hence, we predicted the expected
number of sharks in each FAO division for each period considering a
fixed value of observation effort (five million people) and compared this
index for each sector between the two different time bins.
3.1 | Exploratory data analysis
We identified a total of 773 white shark records within the
Mediterranean Sea, spanning from the end of the Middle Ages
(1453) to 2016. However, 93% (718) of these occurred after 1860,
which is the period when we had the most reliable data and, con-
sequently, was used for our trend analyses. Fisheries catches
accounted for 66% of the records, 48% coming from tuna traps, fol-
lowed by gillnets (23.0%), hand lines (8%), harpoons (6.4%), purse
seines (5.6%) and longlines (5.2%) (Figure 1e). The remaining por-
tions came from strandings, sightings, recorded predation events
and bites to humans. Records were mainly distributed in the western
Mediterranean Sea, in particular, the Northern Adriatic sea (GSA 17,
20.9%), Ligurian and North Tyrrhenian Sea (GSA 9, 13.8%), Southern
Sicily (GSA 16, 9.5%) and off the Balearic Islands (GSA 5, 8.5%); and
pertained mainly to adults (42.8%), subadults (10.5%) and juveniles
(9.6%) (adapted from Bruce & Bradford, 2012) with the majority of
individuals of being from 4 to 6 m long (Figure 1b). However, it is im-
portant to emphasize that more than a third (32.8%) of records were
lacking length information and, consequently, we could not address
the age class. Sex ratio was biased towards women (64.1% of the
142 records having sex), and the individuals that had also informa-
tion on stomach contents (n = 122) suggested that bony fish were
the main prey (27.3%), followed by odontocetes (25.0%), scavenging
carcasses of other animals (principally farm animals, pets—5.7% and
humans—10.2%) and chelonians (6.8%) (Figure 1d).
Coastal human population increased six-fold since 1860, rising
from 29.6 million to 183.8 million in 2016, though this increase was
geographically heterogeneous (Figure 1a). The highest increases were
detected in the eastern basin sectors, with the maximum rise around
FIGURE 1 Observation effort and exploratory analysis. (a) Absolute variation of coastal regions human population size calculated
between 1860 and 2016 and expressed in logarithmic scale. The red dots correspond to the white sharks sighting locations. (b)
Length frequency. The absolute frequency is reported over each bar. (c) Sex distribution within age classes (YOY = young-of-the-year,
JUV = Juveniles, SUB = Subadults, ADL = Adults, UND = Undetermined). (d) Diet composition. The absolute frequency is reported over each
bar. (e) No. of specimens caught by each fishing gear category per age class
50 50
0−1 m1−2 m2−3 m3−4 m4−5 m5−6 m6−7 m>7m
Total length (m)
Relative frequency
Age class
N° of specimens
Female, n = 91
Male, n = 51
18 20
Trophic category
Relative frequency
GillnetHarpoon LineLongline Others Purse seineTrawl Tuna trap
Fishing gear
N° of specimen
YOY [n = 14]
JUV [n = 27]
SUB [n = 26]
ADL [n = 148]
UND [n = 30]
–10010 3020 40
Log (absolute
rate of increase)
   MORO et al.
FIGURE 2 Temporal and spatial changes of sighting rate estimated by the GSA model. (a) Temporal effect: expected shark sighting rate
between 1860 and 2016 predicted by using a fixed observation effort of five million people. Magnitude of the detected decline, starting
year and p-value for the smooth term is shown in the top-right corner. The red line is the overall mean sighting rate. (b) Spatial effect: dots
are the average variations in mean no. of shark detected in each GSA. Point colour matches colours in the map. Segments indicate the
confidence boundaries. (c) Spatial unit used in the model: GFCM Geographic Sub-Areas (as indicated in the Res. GFCM/33/2009/2). The
green dots in the map correspond to the white sharks sighting locations extracted from a variety of source observations
Nº of sharks per 5 million people
1860 1875 1890 1905 1920 1935 1950 1965 1980 1995 2010
Mean nº of sharks
–100 10 20 30 40
p−value = 2.47e−05
1975 − 61.5%
FIGURE 3 FAO model. (a) Mediterranean white shark temporal abundance trend (1860–2016) predicted by the FAO model in each FAO
division, considering a fixed observation effort value (five million people). The black dots represent the actual sighting rates (expressed as no.
of sightings per five million people) (b) Spatial unit used in the model: FAO Major Fishing Area 37 (Mediterranean and Black Sea) divisions.
The green dots in the map correspond to the white sharks sighting locations
2.2 − Ionian 3.1 − Aegean 3.2 − Levant 4.1 − Marmara Sea
1.1 − Balearic1.2 − Gulf of Lions 1.3 − Sardinia 2.1 − Adriatic
1860 1890 1920 1950 1980 2010 1860 1890 1920 1950 1980 2010 1860 1890 1920 1950 1980 2010 1860 1890 19201950 1980 2010
1860 1890 1920 1950 1980 2010 1860 1890 1920 1950 1980 2010 1860 1890 1920 1950 1980 2010 1860 1890 19201950 1980 2010
Nº of sharks per 5 millions people
–100 10 20 30 40
(a) (b)
MORO et al .
the Marmara Sea (319.4-fold). By contrast, the lowest rates of change
were observed in the western and central Mediterranean sectors,
such as the Northern Adriatic, Southern Sicily and Corsica, where the
human population doubled throughout the same period (Figure 1a).
3.2 | Model fitting results
3.2.1| Temporal trends
Shark observations increased throughout the period (Figure S2), but
when we controlled for changes in the potential number of observ-
ers (Figure 2a), we detected an initial increase, characterized by two
peaks in the 1880s and a higher one in the 1980s, followed by a 61%
(range 58%–72%) decline between 1975 and 2016. Similarly, to the
changes in the human population, this trajector y was not homogene-
ous throughout the basin. At the FAO divisions' level, the non-linear
smoothing term for year (Figure 3a–c) was significant for seven of
the eight considered sectors (five with α = 0.05 and two considering
α = 0.1) and five of these six significant trajectories ended in recent
declines (Figure 3b). These declines began earlier and were more
intense in the peripheral sectors, such as the Marmara Sea (1961 –
96.0%, range 92%–100%), Adriatic Sea (1883 94.1%, range 90%–
100%) and the Balearic (1954 – 82.5%, range 76%–98%) than central
Mediterranean sectors (Ionian from 1988 a 52.1% decline, range
37%–8 8% ; and Sardinia from 198 0 a 76.4% decl ine, ra nge 75%–91%).
3.2.2 | Spatial patterns and distribution shrinkage
Our standardized indices of shark abundance identified heteroge-
neous spatial distribution landscapes. The main hot spots were lo-
cated in the western Mediterranean sectors (Figure 2b), especially
in the Balearic Islands (0.73, CI 0.51–1.05), Maltese waters (0.37,
CI 0.21–0.64) and Corsica (0.34, CI 0.18–0.65). Shark abundance
cold spots were in all Eastern Mediterranean GSAs, except for the
Marma ra and Aege an Sea . When we ag gregated the rec ord s in t wo
time bins (1945–1980; 1980–2016), we detected a significant con-
traction of the species’ spatial distribution. All the Mediterranean
Sea peripheral sectors recorded a decrease in shark abundance
in the second period (Figure 4c), with the highest difference de-
tected in the Marmara Sea (−96.6%, CI −95.2% to −<99.9%), fol-
lowed by the Balearic (−73.1%, CI −72.5% to −74.7%) and the Gulf
of Lions (−38.0%, CI −41.4% to −18.3%). All the central sectors, in-
stead, highlighted an increase in the shark abundance (Figure 4c),
with the highest value detected in the Ionian division (+222.6%, CI
+191.6% to +322.4%).
Conservation actions and recovery plans for threatened and en-
dangered marine top predators are broadly limited by a lack of
information on the population status and trends at the scale of
whole ecor egions and over multi-deca dal time scales. By ana lysing
156 years of white shark records in the Mediterranean Sea, we
were able, for the first time, to estimate large-scale and long-term
trajectories of white shark abundance indices across the entire re-
gion. The use of all the available sources of information, integrated
with a proxy controlling for the observation effort change within
space and time, permitted us to standardize our trends. These
standardized indices of population abundance suggested that the
species went through a complex trajectory of change, character-
ized by an increasing phase followed by a sharp decline since the
198 0s. The re cent decl ine , toge t her wit h a dete c ted rang e contr ac-
ti on in the sp ati al dist r ibu t ion of recor ds ( Wo rm & Titten sor, 2011 ),
and stronger and more prolonged declines estimated in peripheral
regions compared to central sectors, suggest an overall rapid de-
cline of the white shark population in the region in the last 3–4
decades. Our results are in contrast with population abundance
increases inferred in other regions, such as California (Lowe et al.,
2012), north-western Atlantic (Curtis et al., 2014), South Africa
(Dudley & Simpfendorfer, 2006) and Australia (Reid et al., 2011).
Conversely, they are in line with regions where the white shark
occurrence data are sparse and infrequent, such as the Northwest
Pacific Ocean (Christiansen et al., 2014). These results confirmed
earlier evidence of regional declines provided by McPherson and
Myer s (20 09), Bol dro cchi et al., (2017 ) and Fer ret ti et al. (20 0 8) for
a larger taxonomic group, but scaled-down recent Red List assess-
ments carried out by the IUCN, which classified the white shark
as critically endangered in the Mediterranean Sea and European
waters (Dulvy et al., 2016; Nieto et al., 2015). Our results suggest
instead an overall decline of 61.5% over the last 10 years or three
generations, which would classify the species as endangered (EN)
“if the reduction causes may not have ceased or well understood,”
as stated in IUCN Criteria Version 3.1 (A2-bc). Taken together,
our results and those of studies conducted elsewhere highlight
the importance of regional analyses and the risk of extrapolating
trends across different geographies. It is easily perceivable that
each region has peculiar characteristics, history of human impact
and drivers of change. An informative regional assessment would
prevent wastage of both conservation efforts and resources.
Similarly, we confirmed previous evidence of the prevalence
of Mediterranean white sharks in western sectors (Boldrocchi
et al., 2017), characterized by distinct bioecological and physical
oceanographic characteristics from the Eastern Mediterranean.
The west–east temperature (Bosc, Bricaud, & Antoine, 2004) and
productivity (Coll et al., 2010) gradients would make the warmer
Eastern Mediterranean waters a suboptimal habitat for adult en-
dothermic white sharks (Carey et al., 1982). By contrast, the colder
and productive western sectors could represent resource hot
spots for the species. These are in fact important breeding and
feeding ground for bluefin tunas (Cermeño et al., 2015) and small
cetaceans (Gnone et al., 2011; Lauriano, Pierantonio, Donovan,
& Panigada, 2014), which are important food items for the white
sharks (Figure 1d, Boldrocchi et al., 2017). This result highlights
   MORO et al.
the critical importance of the western sectors for the persistence
of white shark populations.
Th e whi t e shark eco l ogy in the Medi ter r anean Se a is stil l po orly
characterized and these analyses are a step forward addressing
this important issue. Among the multiple hypotheses that may ex-
plain the estimated trajectories of change, we highlight three po-
tential drivers. First, over the last 200 years, coastal fishing in the
Mediterranean Sea has notably increased and expanded through-
out the region (Piroddi et al., 2015) impacting both juvenile and
adult white sharks, but contemporarily increasing the number of
occurrence records. Young-of-the-year and juvenile white sharks
are vulnerable to inshore gears such as trammel or gill nets (Bruce
& Bradford, 2012; Curtis et al., 2014; Lowe et al., 2012), which
have been massively used all along the Mediterranean shores also
for targeting sharks (Ferretti, Osio, Jenkins, Rosenberg, & Lotze,
2013). Adult individuals were frequently reported in tuna traps
(>50% of catches on record, Figure 1e), which were fixed gears
historically used to catch bluefin tunas on their migratory routes
in the Mediterranean Sea (Bombace & Lucchetti, 2011) and could
have represented a source of mortality for white sharks for centu-
ries. Since the 1960s, tuna traps ceased to be profitable and most
have been closed as an effect of tuna overexploitation by indus-
trial purse seining and other pelagic fisheries (Fromentin & Powers,
2005; ICCAT, 2017; Rouyer et al., 2018). This may have reduced
the impact on adult white sharks as well as the number of catches
we had on record. Meanwhile, white sharks began to be exposed
to offshore fishing, especially tuna and swordfish longlining, which
greatly escalated in the region during the last 50 years (Ferretti
et al., 2008). In this period, white sharks were exposed to both
inshore and offshore fishing and could not benefit from sheltering
offshore which was practically unexploited historically (Ferretti
et al., 2008). Similar patterns have been observed in South Africa
and Australia (Dudley & Si mpfendor fer, 2006; Ferretti et al., 2010 ;
Reid et al., 2011).
It is also possible that Mediterranean white sharks have fol-
lowed the population trajectory of Bluefin tuna, one of their most
frequent prey in the region (Boldrocchi et al., 2017; De Maddalena
& Heim, 2012; Kabasakal, 2016). In our data, 27.3% of the white
sharks with stomach content data ate bony fish and 47% of these
fishes were tunas (Figure 1d, Table S6). Tunas are suitable prey for
white sharks (Hussey et al., 2012) and the bluefin tuna's overex-
ploitation in the last 50 years may have reduced one of the most
FIGURE 4 Spatial range contraction. Predicted mean annual no. of sharks every five million people for each FAO division in time
intervals: (a) 1945–1975, (b) 1976–2016. The red dots in the maps show the white sharks sighting locations in each period. (c) Variation
between 1945–1975 and 1976–2016 time bins. Red sectors correspond to abundance rise, while blue sectors correspond to abundance
n°of sharks
n°of sharks
0 10 20 30
Change in the
number of
sharks records
(a) (b)
MORO et al .
imp ort ant prey resources for this species in the area (ICCAT, 2017;
Rouyer et al., 2018). The long-ter m trajec tory we estimated for the
white shark records has a temporal phase similar to the tim e series
of Mediterranean bluefin tuna abundance estimated from centu-
ries of tuna trap data (Ravier & Fromentin, 2001). The bluefin tuna
decline detected in recent decades (Fromentin & Powers, 2005;
Rouyer et al., 2018) coincides with the recent decline of the white
shark sighting rate, supporting the plausibility of a predator–prey
dynamic between the two species. Yet tuna overexploitation also
caused the end of the tuna trap fishery. Therefore, it is unclear
whether such a contemporar y decline in sighting rate has been
caused by the end of an important source of white shark mortality
in the region (i.e. decline in catch records from tuna traps), or by
an underlining population decline through indirect bottom-up ef-
fect s (be cause of the declin e of an important prey), or both fa ctors
combined. However, no differences in GAM’s trajectories were
detected by fitting the FAO model with and without the tuna trap
catches (Supporting Information, Figure S9) in all sectors but the
Balearic (Division 1.1), a piece of evidence against the decline in
catch record hypothesis. Whereas, the predator–prey hypothesis is
cor ro borate d by the fact that adult white sharks’ preferential prey,
such as pinnipeds and whale carcasses (Hussey et al., 2012), have
been much scarcer or essentially absent in the Mediterranean Sea
for most of the period considered in this analysis. The only pinni-
ped in the region, the monk seal (Monachus monachus, Phocidae),
has small remnant populations only in the Eastern Mediterranean
sectors (Karamanlidis & Dendrinos, 2015) and was considered
rare (heavily depleted by centuries of overhunting) in most of the
Mediterranean Sea by the 18th centur y (Johnson, 2004). Whale
abundance is also much lower than in other ocean sectors where
white sharks occur (Notarbartolo di Sciara, 2002). It is, therefore,
possible that adult white sharks adapted to feed mainly on tunas
in the Mediterranean Sea; a hypothesis that would make this pop-
ulation unique respec t other global populations and should be for-
mally tested in future research.
The above explanations are confounded by the change in ob-
servation effort expected from the spatial and temporal expan-
sions of fisheries and other factors affecting the probability to
detect records. We used trajectories of human population change
along the Mediterranean coasts as a single and practical proxy of
observation effort, but human population abundance is one of its
multiple components. For example, linguistic barriers and politi-
cal instability may have limited the number of records we found
in North African and Middle Eastern regions, as well as the two
World Wars and the 1918 Flu Pandemic may have acted simi-
larly in Europe during these periods (D’Ancona, 1949; Thurstan,
Brock i n g ton, & Ro ber ts , 20 10). In ad dit i o n , epis o d i c event s , su ch as
a 19th-cen tur y rew ard pro gram me iss ued by th e Imper ial Ma riti me
Austrian Government to cull white sharks in the Adriatic Sea (De
Marchesetti, 1882), could have boosted the probability to have
occurrence records independent of human population changes.
Similarly, the expansion of the use of the Internet and social net-
works in the last 20 years has likely increased the probability that
a record of a white shark capture is reported. International (CITES,
CSM, Barcelona and Bern Conventions) and national legislation (in
Malta, Israel, Croatia, Montenegro and Slovenia) to protect this
species may have deterred Mediterranean fishermen in reporting
catches, fearing disruptive or legal consequences for their activ-
ities. Although these factors may have acted in different direc-
tion (i.e. biasing upward or downward the estimated trends), the
probabilistic distribution we used to handle the response variable
allows clustered observations, quantifying these sources of bias
is now a top priority to further explaining and reducing uncer-
tainty of the general large-scale spatial and temporal patterns we
identified. Nevertheless, our modelling approach represents an
innovation in analysing opportunistic data, by testing observation
effort regimes that are not simulated, as done so far (Christiansen
et al., 2014; Curtis et al., 2014; McPherson & Myers, 2009), but
quantitatively estimated through the use of a proper observation
effort proxy. Indeed, most of the cited features affecting obser-
vation effort are in some ways related to demographical changes
of the human population (i.e. fishing pressure, technological de-
velopment). Hence, adopting an observation effort proportional
to the human population mitigates the confusing effects of the
mentioned factors.
Reconstruction of the Mediterranean white shark spatio-tem-
poral patterns of abundance, obtained by using all available occur-
rence records, generated new hypotheses on the species’ population
structure and predator–prey dynamics in the region. Testing these
hypotheses with further dedicated research will further contribute
to reconstruct population baselines of this species and deepen our
understanding of its life history, ecology and biogeography. These
aspects are crucial to ensure the conservation of white sharks in
the region and across the planet. We also identified occurrence hot
spots that would represent important sampling locations for collect-
ing high-quality biological data, including tracking data to directly
assess distribution, foraging and habitat use. These field studies are
expensive and require careful planning on where and when white
sharks are most likely detected.
Globally, there are multiple species of conservation concern
with a similar scantiness of abundance data that would benefit from
our approach of combining all available occurrence data. Our study
shows that a careful examination of these data, even if opportunis-
tic, can reveal important ecological patterns, particularly regarding
trends in abundance and spatial distribution, that are critical to in-
form adequate conser vation actions and science-based recovery
This work is part of the Global Shark Abundance Baselines funded
by the Lenfest Ocean Program. Dr. Stefano Moro was partially
supported by the PRIN2015 supported-project "Environmental
processes and human activities: capturing their interactions via sta-
tistical methods (EPHAStat)" funded by MIUR (Italian Ministr y of
Education, University and Scientific Research) (20154X8K23-SH3).
Additional funders are as follows: Lenfest Ocean Program, Bertarelli
   MORO et al.
Foundation, Schmidt Technology Partners, MedReAct and Regione
Lazio with the Grant Programme “Torno Subito 2017”. We Thank
Annie Adelson for help in bulding the sighting database.
The data that support the findings of this study are available from
the corresponding and senior authors (stefano.moro@uniroma1.
it and upon reasonable request.
Stefano Moro
Baum, J. K., & Blanchard, W. (2010). Inferring shark population trends
from generalized linear mixed models of pelagic longline catch
and effort data. Fisheries Research, 102(3), 229–239. https ://doi.
org/10.1016/j.fishr es.2009.11.006
Boldrocchi, G., Kiszka, J., Purkis, S., Storai, T., Zinzula, L., & Burkholder,
D. (2017). Distribution, ecology, and status of the white shark,
Carcharodon carcharias, in the Mediterranean Sea. Reviews in Fish
Biology and Fisheries, 27(3), 515–534. https ://
Bombace, G., & Lucchetti, A. (2011). Elementi di biologia della pesca.
Bologna, Italy: Edagricole.
Bosc, E., Bricaud, A., & Antoine, D. (2004). Seasonal and interan-
nual variabilit y in algal biomass and primary production in the
Mediterranean Sea, as derived from 4 years of SeaWiFS observa-
tions. Global Biogeochemical Cycles, 18(1), GB1005. https ://doi.
org/10.1029/2003G B002034
Bruce, B. D., & Bradford, R. W. (2012). Habitat use and spatial dynamics
of juvenile white sharks, Carcharodon carcharias, in eastern Australia.
In M. L. Domeier (Ed.), Global perspectives on the biology and life his-
tory of the white shark (pp. 225–254). Boca Raton, FL: CRC Press.
Carey, F. G., Kanwisher, J. W., Brazier, O., Gabrielson, G., Casey, J. G.,
& Pratt, H. Jr (1982). Temperature and activities of a white shark,
Carcharodon Carcharias. Copeia, 1982(2), 254–260.
Carlisle, A. B., Kim, S. L., Semmens, B. X., Madigan, D. J., Jorgensen, S. J.,
Per le , C. R., … Block, B. A. (2012). Using st ab le isotope anal ys is to un-
derstand the migration and trophic ecology of northeastern pacific
white sharks (Carcharodon carcharias). PLoS ONE, 7(2), e30492. https
:// al.pone.0030492
Cavanagh, R. D., & Gibson, C. (2007). Overview of the conservation sta-
tus of cartilaginous fishe s (Chrondrichthyans) in the Mediterranean Sea.
Gland, Switzerland: IUCN.
Cermeño, P., Quílez-Badia, G., Ospina-Alvarez, A ., Sainz-Trápaga, S.,
Boustany, A. M., Seitz, A. C., Block, B. A. (2015). Electronic tag-
ging of Atlantic bluefin tuna (Thunnus thynnus, L.) reveals habitat use
and behaviors in the Mediterranean Sea. PLoS ONE, 10(2), e0116638.
https :// al.pone.0116638
Chapple, T. K., Jorgensen, S. J., Anderson, S. D., Kanive, P. E., Klimley,
A. P., Botsford, L. W., & Block, B. A. (2011). A first estimate of
white shark, Carcharodon carcharias, abundance off Central
California. Biology Letters, 7(4), 581–583. https ://
Christiansen, H. M., Lin, V., Tanaka, S., Velikanov, A., Mollet, H. F., Wintner,
S. P., … Hussey, N. E. (2014). The last frontier: catch records of white
sharks (Carcharodon carcharias) in the Northwest Pacific Ocean. PLoS
ONE, 9(4), e94407. https :// al.pone.0094407
Coll, M., Piroddi, C., Steenbeek, J., Kaschner, K., Ben Rais Lasram,
F., Aguzzi, J., Voultsiadou, E. (2010). The biodiversity of the
Mediterranean Sea: estimates, patterns, and threats. PLoS ONE, 5(8),
e11842. https :// al.pone.0011842
Compagno, L. J. (2001). Sharks of the world. An annotated and illustrated
catalogue of shark species known to date, vol 2. Bullhead, mackerel and
carpet sharks (Heterodontiformes, Lamniformes and Orectolobiformes).
FAO Species Catalogue for Fishery Purposes, 1, viii+ 1–269.
Curtis, T. H., McCandless, C. T., Carlson, J. K., Skomal, G. B., Kohler, N.
E., Natanson, L. J., … Pratt, H. L. Jr (2014). Seasonal distribution and
historic trends in abundance of white sharks, Carcharodon carcharias,
in the Western North Atlantic Ocean. PLoS ONE, 9(6), e99240. https
:// al.pone.0099240
D’Ancona, U. (1949). Rilievi statistici sulla pesca nell’alto Adriatico. Atti
Istituto Veneto Scienze Lettere Ed Arte, 10 8, 41–53.
De Maddalena, A ., & Heim, W. (2012). Mediterranean great white sharks:
A comprehensive study including all recorded sightings. Jefferson, NC:
De Marchesetti, C. (1882). La pesca lungo le coste orientali dell’Adria.
Herrmanstorfer. Tipografia di Lod.
Dirzo, R., Young, H. S., Galetti, M., Ceballos, G., Isaac, N. J. B., & Collen,
B. (2014). Defaunation in the anthropocene. Science, 345(6195), 401.
https :// ce.1251817
Dudley, S. F. J., & Simpfendorfer, C. A. (20 06). Population status of 14
shark species caught in the protective gillnets off KwaZuluNatal
beaches, South Africa, 1978–2003. Marine and Freshwater Research,
57(2), 225–240.
Dulvy, N. K ., Allen, D. J., Ralph, G. M., & Walls, R. H. L. (2016). The con-
servation status of sh arks, rays and Chim aeras in the Mediterranean Sea.
Malaga, Spain: IUCN.
Dulvy, N. K., Fowler, S. L., Musick, J. A., Cavanagh, R. D., Kyne, P. M.,
Harrison, L. R., … Francis, M. P. (2014). Extinction risk and conserva-
tion of the world’s sharks and rays. Elife, 3, e00590.
Estes, J. A., Terborgh, J., Brashares, J. S., Power, M. E., Berger, J., Bond,
W. J., … Wardle, D. A. (2011). Trophic downgrading of planet earth.
Science, 333(6040), 301. https :// ce.1205106
Fergusson, I. K. (1996). Distribution and autecolog y of the white shark
in the eastern North Atlantic Ocean and the Mediterranean Sea. In
A. P. Klimley, & D. G. Ainley (Eds.), Great White Sharks: The biology
of Carcharodon carcharias (pp. 321–345). San Diego, CA: Academic
Fergusson, I. K. (2002). Occurrence and biolog y of the great white shark,
Carcharodon carcharias, in the Central Mediterranean Sea: A review.
Proc. 4th European Elasmobranch Association Meeting Livorno,
Italy, 7–23.
Ferretti, F., Jorgensen, S., Chapple, T. K., De Leo, G., & Micheli, F.
(2015). Reconciling predator conser vation with public safety.
Frontiers in Ecology and the Environment, 13(8), 412–417. https ://doi.
org /10.1890/15010 9
Ferretti, F., Morey Verd, G., Seret, B., Sulić Šprem, J., & Micheli, F. (2016).
Falling through the cracks: The fading history of a large iconic pred-
ator. Fish and Fisheries, 17(3), 875–889. https ://
Ferretti, F., Myers, R. A ., Serena, F., & Lotze, H. K . (2008). Loss of large
predatory sharks from the Mediterranean Sea. Conservation Biology,
22(4), 952–964. https ://
Ferretti, F., Osio, G. C., Jenkins, C. J., Rosenberg, A. A., & Lotze, H. K.
(2013). Long-term change in a meso-predator community in response
to prolonged and heterogeneous human impact. Scientific Reports, 3,
10 5 7.
Ferretti, F., Worm, B., Britten, G. L., Heithaus, M. R., & Lotze, H.
K. (2010). Patterns and ecosystem consequences of shark de-
clines in the ocean. Ecology Letters, 13(8), 1055–1071. https ://doi.
org /10.1111/j.1461-0248. 2010.01489.x
Fromentin, J.-M., & Powers, J. E. (2005). Atlantic bluefin tuna: Population
dynamics, ecolog y, fisheries and management. Fish and Fisheries, 6(4),
281–306. https ://
Galaz, T., & De Maddalena, A. (2004). On a Great White Shark,
Carcharodon carcharias(Linnaeus, 1758), trapped in a tuna cage
MORO et al .
off Libya, Mediterranean Sea. Annales Series Historia Naturalis, 14,
15 9–1 6 4 .
Gnone, G., Bellingeri, M., Dhermain, F., Dupraz, F., Nuti, S., Bedocchi,
D., … Wurtz, M. (2011). Distribution, abundance, and movements of
the bottlenose dolphin (Tursiops truncatus) in the Pelagos Sanctuary
MPA (north-west Mediterranean Sea). Aquatic Conservation: Marine
and Freshwater Ecosystems, 21(4), 372–388. https ://
aqc .1191
Gubili, C., Kalkan, E., Ünsal, K. S., Jones, C. S., Sims, D. W., Hakan, K.,
… Noble, L . R . (2011). Antipodean white sharks on a Mediterranean
walkabout? Historical dispersal leads to genetic discontinuity and an
endangered anomalous population. Proceedings of the Roya l Society B:
Biological Sciences, 278(1712), 1679–1686. https ://
Gubili, R. C. E. C., Cliff, G., Wintner, S. P., de Sabata, E., De Innocentiis,
S., … Jones, C. S. (2015). DNA from historical and trophy samples
provides insights into white shark population origins and genetic di-
ver si ty. Endangered Species Research, 27(3), 233–241.
Hussey, N. E., McCann, H. M., Cliff, G., Dudley, S. F., Wintner, S. P., & Fisk,
A. T. (2012). Size-based analysis of diet and trophic position of the
white shark (Carcharodon carcharias) in South African waters. Global
Perspectives on the Biology and Life History of the White Shark, 27–49.
Huveneers, C., Apps, K., Becerril-García, E. E., Bruce, B., Butcher, P. A.,
Carlisle, A. B., … Werry, J. M. (2018). Future research directions on
the “Elusive” White Shark. Frontiers in Marine Science, 5, 455. https ://
ICCAT (2017). Report of the 2017 ICCAT Bluefin Tuna Stock A ssessment
Meeting (No. Document SCRS/2017/10; p. 106). Retrieved from ICCAT,
Madrid, Spain 20–28 July, 2017. https :// ents/
Johnson, W. M. (2004). Monk seals in post-classical history. The
Netherlands Commission for International Nature Protection,
Mededlingen, 39, 91.
Kabasakal, H. (2016). Historical dispersal of the great white shark,
Carcharodon carcharias, and bluefin tuna, Thunnus thynnus, in the
Turkish waters: Decline of a predator in response to the loss of its
prey. Annales Series Historia Naturalis, 26, 213.
Karamanlidis, A., & Dendrinos, P. (2015). Monachus monachus. The IUCN
Red List of Threatened Species.
Klimley, A. P., & Anderson, S. D. (1996). Residency patterns of white
sharks at the South Farallon Islands, California. In A. P. Klimley, &
D. G. Ainley (Eds.), Great White Sharks: The biolog y of Carcharodon
carcharias (pp. 365–373). San Diego, C A: Academic Press.
Kock, A., O’Riain, M. J., Mauff, K., Meÿer, M., Kotze, D., & Griffiths,
C. (2013). Residency, habitat use and sexual segregation of white
sharks, Carcharodon carcharias in False Bay, South Africa. PLoS ONE,
8(1), e55048. https :// al.pone.0055048
Lauriano, G., Pierantonio, N., Donovan, G., & Panigada, S. (2014).
Abundance and distribution of Tursiops truncatus in the Western
Mediterranean Sea: An assessment towards the Marine Strategy
Framework Directive requirements. Large Marine Vertebrates as
Sentinels of GES in the European MSFD, 10 0, 86–93. https ://doi.
org/10.1016/j.maren vres.2014.04.001
Lowe, C. G., Blasius, M. E., Jarvis, E. T., Mason, T. J., Goodmanlowe, G.
D., & O’Sullivan, J. B. (2012). Historic fishery interactions with white
sharks in the Southern California Bight. In M. L. Domeier (Ed.), Global
perspectives on the biology and life history of the white shark (pp. 169
186). Boca Raton:CRC Press.
McClenachan, L., Ferretti, F., & Baum, J. K. (2012). From archives to con-
servation: Why historical data are needed to set baselines for marine
animals and ecosystems. Conservation Letters, 5(5), 349–359. https :// .0 0253.x
McPherson, J. M., & Myers, R. A. (2009). How to infer population trends
in sparse data: Examples with opportunistic sighting records for
great white sharks. Diversity and Distributions, 15(5), 880–890.
Micheli, F., Halpern, B. S., Walbridge, S., Ciriaco, S., Ferretti, F., Fraschetti,
S., Rosenberg, A. A. (2013). Cumulative human impacts on med-
iterranean and black sea marine ecosystems: Assessing current
pressures and opportunities. PLoS ONE, 8(12), e79889. https ://doi.
org/10.1371/journ al.pone.0079889
Nieto, A., Ralph, G . M., Comeros-Raynal, M. T., Kemp, J., García Criado,
M., Allen, D. J., & Williams, J. T. (2015). European Red List of marine
fishes. Luxembourg: Publications Office of the European Union.
Notarbartolo di Sciara, G. (2002). Cetacean species occurring in the
Mediterranean and Black Seas. In G. Notarbartolo di Sciara (Ed.),
Cetaceans of the Mediterranean and Black Seas: State of knowledge
and conservation strategies (p. 17). A report to the ACCOBAMS
Secretariat, Monaco, Februar y 2002.
Pearce, J. L., & Boyce, M. S. (2006). Modelling distribution and abundance
with presence-only data. Journal of Applied Ecology, 43(3), 405–412.
https :// .1111/j.1365-2664.2005.01112.x
Piroddi, C., Gristina, M., Zylich, K., Greer, K., Ulman, A., Zeller, D., & Pauly,
D. (2015). Reconstruction of Italy’s marine fisheries removals and
fishing capacity, 1950–2010. Fisheries Research, 172, 137–147. https
:// es.2015.06.028
Queiroz, N., Humphries, N. E., Couto, A., Vedor, M., da Costa, I., Sequeira,
A. M. M., … Sims, D. W. (2019). Global spatial risk assessment of
sharks under the footprint of fisheries. Nature, 572(7770), 461–466.
https ://
Ravier, C., & Fromentin, J.-M. (2001). Long-term fluctuations in the east-
ern Atlantic and Mediterranean bluefin tuna population. ICES Journal
of Marine Science, 58 (6), 1299–1317.
Reid, D. D., Robbins, W. D., & Peddemors, V. M. (2011). Decadal trends
in shark catches and effort from the New South Wales, Australia,
Shark Meshing Program 1950–2010. Marine and Freshwater Research,
62(6), 676–693.
Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C., Ritchie, E. G.,
Hebblewhite, M., Wirsing, A. J. (2014). Status and ecological ef-
fects of the World’s Largest Carnivores. Science, 343(6167), 1241484.
https :// ce.1241484
Rousseau, Y., Watson, R. A., Blanchard, J. L., & Fulton, E. A. (2019).
Evolution of global marine fishing fleets and the response of
fished resources. Proceedings of the National Academy of Sciences,
116(25):12238–12243. https ://
Rouyer, T., Kimoto, A., Kell, L., Walter, J. F., Lauretta, M., Zarrad, R., …
Sharma, R. (2018). Preliminary 2017 stock assessment results for
the Eastern and Mediterranean Atlantic bluefin tuna stock. ICCAT
Collective Volume of Scientific Papers, 74 , 3234–3275.
Serena, F., Mancusi, C., & Barone, M. (2008, September 15). The MEDLEM
database application: A tool for s toring and sharing data about by-catch
and incidental catches of large cartilaginous fishes in the Mediterranean
basin (p. 12). Rome, Italy: FAO HQs.
Simpfendorfer, C. A., & Dulvy, N. K. (2017). Bright spots of sustain-
able shark fishing. Current Biology, 27(3), R97–R98. https ://doi.
Storai, T., Zinzula, L., Repetto, S., Zuffa, M., Morgan, A., & Mandelman, J.
(2011). Bycatch of large elasmobranchs in the traditional tuna traps
(tonnare) of Sardinia from 1990 to 2009. Fisheries Research, 109(1),
74–79. https :// es.2011.01.018
Thurstan, R. H., Brockington, S., & Robert s, C. M. (2010). The effects of
118 years of industrial fishing on UK bottom trawl fisheries. Nature
Communications, 1, 15.
Tinker, M. T., Hatfield, B. B., Harris, M. D., & Ames, J. A. (2016). Dramatic
increase in sea otter mortality from white sharks in California. Marine
Mammal Science, 32(1), 309–326.
Venables, W. N., & Ripley, B. D. (2002). Modern applied s tatistics with S.
New York: Springer-Verlag.
Wood, S. N. (2011). Fast stable restricted maximum likelihood and marginal
likelihood estimation of semiparametric generalized linear models.
   MORO et al.
Journal o f the Royal Statistica l Society: Ser ies B (Statistical M ethodolog y),
73(1), 3–36. https ://
Worm, B., & Tittensor, D. P. (2011). Range contraction in large pelagic
predators. Proceedings of the National Academy of Sciences, 108 (29),
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article: Moro S, Jona-Lasinio G, Block B,
et al. Abundance and distribution of the white shark in the
Mediterranean Sea. Fish Fish. 2019;00:1–12. h t t p s : / / d o i .
org /10.1111/f af.12432
... This makes the Mediterranean Sea one of the areas with the world's highest percentage of threatened shark spe-cies (Walls & Dulvy 2020). Pelagic shark populations showed declines up to 98−99% over the last 50−200 yr (Ferretti et al. 2008, Moro et al. 2020, and there is a long list of coastal and demersal species that are on the edge of local extinction, such as the angelsharks (Squatina spp.) (Fortibuoni et al. 2016) and the sand tiger shark Carcharias taurus (Bargnesi et al. 2020a), or have even already been extirpated from the area , Lawson et al. 2020. ...
... They can identify critical habitats and ongoing threats ). Range contraction and area of occupancy fragmentation can identify population declines (Mace et al. 2008, Worm & Tittensor 2011, Moro et al. 2020). Yet locations where species are still present can indicate conservation opportunities and important habitats acting as strongholds from which endangered species could be preserved and potentially recovered. ...
... This condition has also impaired research on the biology and ecology of many species, even for broad-ranging and widely distributed species such as large pelagic sharks. Life histories, population structure, abundance, and spatial ecology of many of these species are still hypothesized in the Mediterranean Sea (Damalas & Megalofonou 2012, Moro et al. 2020, as is the role of this region for their ecology. For example, it has been proposed that the Mediterranean Sea may host important nursery areas for pelagic sharks (Costantini & Affronte 2003, Soldo 2005, Megalofonou et al. 2009, Jambura et al. 2021. ...
... This makes the Mediterranean Sea one of the areas with the world's highest percentage of threatened shark spe-cies (Walls & Dulvy 2020). Pelagic shark populations showed declines up to 98−99% over the last 50−200 yr (Ferretti et al. 2008, Moro et al. 2020, and there is a long list of coastal and demersal species that are on the edge of local extinction, such as the angelsharks (Squatina spp.) (Fortibuoni et al. 2016) and the sand tiger shark Carcharias taurus (Bargnesi et al. 2020a), or have even already been extirpated from the area , Lawson et al. 2020. ...
... They can identify critical habitats and ongoing threats ). Range contraction and area of occupancy fragmentation can identify population declines (Mace et al. 2008, Worm & Tittensor 2011, Moro et al. 2020). Yet locations where species are still present can indicate conservation opportunities and important habitats acting as strongholds from which endangered species could be preserved and potentially recovered. ...
... This condition has also impaired research on the biology and ecology of many species, even for broad-ranging and widely distributed species such as large pelagic sharks. Life histories, population structure, abundance, and spatial ecology of many of these species are still hypothesized in the Mediterranean Sea (Damalas & Megalofonou 2012, Moro et al. 2020, as is the role of this region for their ecology. For example, it has been proposed that the Mediterranean Sea may host important nursery areas for pelagic sharks (Costantini & Affronte 2003, Soldo 2005, Megalofonou et al. 2009, Jambura et al. 2021. ...
In the last 50 yr, shark populations showed steep declines in the Mediterranean Sea. The IUCN lists most Mediterranean species as Endangered (55%), while considering 27.5% of them Data Deficient. Here, sharks are currently one of the rarest and more elusive groups of animals, and data from fisheries and scientific monitoring still insufficiently support robust abundance and distribution assessments. New technologies can fill this data gap by linking people and scientists through new monitoring strategies. SharkPulse, an international collaborative project, aims at creating a large world database of shark occurrence records by mining images on the web, social networks, and private archives. Here we analyzed 1186 sharkPulse records from the Mediterranean Sea. We collected records to characterize spatio-temporal patterns on 37 species, highlighting distribution changes for 5, and, by using generalized linear models, estimating trends in sighting for the most abundant species. With 273 records, Hexanchus griseus had the most sighting records since the beginning of the series. We identified pupping areas and aggregation sites for immature Prionace glauca and Isurus oxyrinchus; pinpointed strongholds of the Critically Endangered Squatina squatina to focus conservation efforts; and identified broader than previously reported regional distribution ranges for Alopias superciliosus, Dalatias licha, Heptranchias perlo, H. griseus, Oxynotus centrina, and P. glauca. We confirmed that fishing is still the major threat for Mediterranean sharks and call for a greater effort in controlling the emerging patterns with efficient conservation effort indexes. If properly standardized, opportunistic data can efficiently and cost-effectively advance our understanding of shark abundance, distribution, and conservation status.
... Known as wideranging carnivores in mostly temperate waters of both the northern and southern hemispheres, white sharks are true superpredators, and perhaps the most formidable of the present-day, fish-like vertebrates (Compag-no 1984). Carcharodon carcharias is currently recognised as an uncommon but persistent inhabitant of the Mediterranean Sea (e.g., Boldrocchi et al. 2017;Moro et al. 2020;Serena et al. 2020) -one that is currently assessed as critically endangered in the region (Gubili et al. 2011;Soldo et al. 2016). ...
The white shark, Carcharodon carcharias (Linnaeus, 1758), is a fairly uncommon and somewhat enigmatic inhabitant of the present-day Mediterranean Basin. In this broad region, fossil teeth of C. carcharias are known from the lower Pliocene onwards, but definite Pleistocene records concentrate in a few southern Italian localities along the Ionian and Tyrrhenian coasts. Here, we report on new and historical specimens of C. carcharias from the Quaternary of Tuscany (central Italy), which provide valuable data on the post-Pliocene history of white sharks in the southern Ligurian Sea (a north-western Mediterranean quarter where white sharks are currently rare). Some of these finds come from mollusc-bearing sands that were quarried at Torre del Lago (Lucca Province). Originally regarded as “Versilian” (latest Pleistocene to Holocene) in age, these largely immature white shark teeth date back to the mid-Holocene (Northgrippian, roughly corresponding to the last phases of the Holocene Climate Optimum). A new dental specimen of C. carcharias originates from Lower Pleistocene (Calabrian, ?Emilian) sediments cropping out at Montalto, near Fauglia (Pisa Province). Among many other fossils, the Montalto locality has also yielded a monk seal calcaneum, thus hinting at a possible predator-prey relationship between the shark and the pinniped. An additional record comes from the Meloria Shoals, off Leghorn. It likely derives from the shallow-marine, Upper Pleistocene (Tyrrhenian) fossiliferous deposits that are locally exposed at the seafloor. Together with previous Pleistocene finds from southern Italy, these Tuscan fossils highlight the ecological plasticity of the Mediterranean white sharks, which persisted through the fairly massive climatic and environmental perturbations that characterised the Quaternary Period without obvious connections with their adjacent Atlantic conspecifics.
... Fishing mortality varies widely among cartilaginous fish species depending to gear and metier varieties. For example, pelagic longlines pose the main threat to sharks and pelagic rays in the world's oceans (Beerkircher et al., 2002;Gallagher et al., 2014;Kroodsma et al., 2018, Queiroz et al., 2019, including areas of the Mediterranean Sea (Ferretti et al., 2008;Megalofonou et al., 2005;Moro et al., 2019). Set gillnets and trammel nets tend to catch large numbers of sharks and rays (Benjamins et al., 2010;Coelho et al., 2005;Perez & Wahrlich, 2005;Scacco et al., 2012;Thorpe & Frierson, 2009;Valenzuela et al., 2008), as do the drift nets (McKinnell & Seki, 1998;Tudela et al., 2005). ...
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Based on an explorative but rigorous elicitation framework, we obtained the bycatch fishing probability at the fishing fleet segment level using expert estimates. Based on the knowledge of three scientific experts, we developed a new and creative structured method for smart and fast fishery-related risk assessments for species of high conservation concern. In order to test the method here propose, we applied it to 76 cartilaginous fish species (included in the IUCN Red Lists) and on five different fishing segments at both Italian and Mediterranean scale. The method produced qualitative results specific to the threat posed by fishing for each species and each segment with information between and within the segments. Based on the interpretation of resilience–disturbance interactions developed for ecological systems, the quantitative results provided reliable cumulative metrics, measuring the extinction risk due to fishing and the response to overfishing for the species considered. Additionally, the results highlight that the method perform best on a small geographic scale. Therefore, the application of this new method on other subregional or local scales where very few data are available (e.g., fishing effort) could be a valuable tool for the preliminary assessment for species of conservation concern. In fact, despite the absence of detailed catch data at local geographic scales, the flexibility of this method could help to highlight potential fishery-related conservation problems and thus redirect conservation strategies for threatened marine species such as many sharks and rays species. K E YWORDS elasmobranchs, fishing fleet's segments, IUCN red lists, priority species, risk assessment
... Fishing mortality varies considerably among elasmobranch species as fishing gear and métiers vary. For instance, pelagic longlines represent the main threat to pelagic sharks and rays in the world's oceans [13][14][15][16][17], including the Mediterranean areas [3,18,19]. Fixed gill and trammel nets tend to catch a large number of sharks and rays [20][21][22][23][24][25], as well as drift nets [26,27]. Small-scale fishery impacts cartilaginous coastal-dependent species, as it usually uses passive fishing gears within coastal waters [28][29][30][31]. ...
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Elasmobranchs are priority species for conservation due to their rapid decline determined by the unbalanced struggle between a fragile bio-ecology and strong anthropogenic impacts, such as bycatch from professional fishing. In this context, measuring species resistance to catch of poorly selective gear is of paramount importance. During June–October 2022, five experimental fishing campaigns were carried out in the Asinara Gulf (northern Sardinia) through 35 geographically and bathymetrically representative hauls of an area between 30 and 600 m in depth. Skates prevailed over sharks in the number of species, with seven and five species, respectively. We first evaluated the status of each individual with respect to stress due to the trawl’s catch using a three-graded scale. We also recorded individual biometrics (total and disk length, weight and sex, and maturity for males) on board by implementing the best practices in manipulating individuals for physiological recovery and release at sea. After capture, skates resulted in generally better conditions than sharks, although deepwater species of both groups exhibited a worse state than coastal species. The estimated vitality rates also depended on the size of the individuals. This work provides standardized data on the intermingled effect of size, species type, and inhabited depth on the resistance response of some elasmobranch species against capture by trawl fishery activities.
... Larger predators have a disproportionate impact on food web structure due to their higher consumption rates and their preference for larger consumers (DeLong et al., 2015). Fishing has highly reduced the biomass of carnivorous fish at a regional level both in the Mediterranean Sea and the north-east temperate Atlantic Ocean (Christensen et al., 2003;Piroddi et al., 2015), and several high trophic level carnivores, such as seals and coastal sharks, are very scarce or regionally ex-Food web structure in marine protected areas 13 tinct in the western Mediterranean Sea (Sala, 2004;Coll et al., 2012;Moro et al., 2019;Nuez et al., 2021). Thus, total fishing prohibition and protection of the adjoining rocky habitats would certainly increase the biomass of carnivorous fish at the MPAs studied here, but it is unlikely that this would restore the original diversity of highly mobile, high trophic level carnivores at a local scale if they are scarce at a regional scale (D'Agata et al., 2016;Roff et al., 2016;McClanahan et al., 2019). ...
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Here, we assess whether fishery exploitation affects the trophic structure of carnivorous fish. We censused fish and analysed the stable isotope ratios of C and N of species targeted by fishermen in areas open to fishing and marine protected areas (MPAs) in the Mediterranean Sea and the north-eastern Atlantic Ocean. Results demonstrated a major impact of fishing on the biomass and size structure of nektobenthic carnivorous fish. However, those changes did not modify the diversity of the trophic resources used by the assemblage, the pattern of resource partitioning between species, or the degree of trophic redundancy. These results add to recent evidence suggesting that MPAs implemented in fished seascapes may fail to restore the original structure of the food webs that once existed in pre-fished ecosystems because regional decimation and extinction of highly mobile predators prevent recovering the original diversity of predators at local scales, even in no-take areas. If so, more strict local fishing regulations are unlikely to restore the original diversity of high trophic level carnivores and restoration goals should be reframed in terms of an objective that is less unrealistic than restoring the pre-fished condition while still recovering aspects of the historical trophic structure.
... Historical accounts may be extremely useful to add new data to past shark occurrence and distribution, especially in poorly studied regions such as the waters of the Eastern Mediterranean [7,22]. This allow us to better understand temporal changes in species diversity and population trends, in a location where vast declines and local extinctions are taking place [16,23,24]. ...
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The lack of historical data on shark presence, distribution, and status in the Eastern Mediterranean undermines efforts to manage and protect their populations. An exhaustive review of anecdotal references related to shark presence during the early and development phase of Greek fisheries (1883–1983) was conducted. In the early-20th century (1912), the first sighting of the presence of a dead shark was reported in the Ionian Sea. Later on, the presence of sharks gradually increased up to 1969, with most records being more frequent for the Aegean Sea, whereas the number of sharks being sighted declined leading up to the middle of 1980s. The increase in shark attacks during the mid-20th century led to a calling for culling of sharks in co-operation with the competent authorities promoting the permission to hunt sharks with firearms and offering rewards for killed individuals. A high number of these observations potentially resulted from shark attacks on people, whereas this is not currently evident. This is an indicator of the lower abundance of sharks in modern times and subsequently an alteration in the way that our current modern society is approaching the protection of such vulnerable species.
... ; doi: bioRxiv preprint 2021). Similarly, a recent study on white sharks in the Mediterranean Sea analyzed encounter data using generalized additive models and information on human population abundance as a proxy of observation effort; however, they did not account for environmental variation within their models, although they suggest temperature and productivity for potential reasons for fluctuations in abundances (Moro et al. 2020). Nevertheless, other studies have successfully examined shark protection and conservation, while also accounting for environmental variability. ...
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Several studies have found predictable relationships between the behavior of planktivores and environmental conditions, suggesting that planktivores may be especially sensitive to environmental change. However, many studies to date are based on limited observations, include few of the many environmental covariates which could influence planktivores, and do not occur over long enough time periods to make inferences about the potential effects of environmental change. As such, long term datasets on planktivores are necessary to disentangle the potential impacts of oceanographic and environmental variability. In this study, to elucidate the relationship between plankivores and environmental variability, we use data obtained over the last 28 years by a small group of divemasters at Cocos Island, Costa Rica, one of the oldest marine reserves in the world. We found that, in general, for planktivorous elasmobranchs, several environmental variables, such as, chlorophyll A, lunar cycle, and salinity have clear influences on their occurrence and relative abundances. We found that in the phases of lower illuminations, there were significant increases in abundance of mobula rays. Specifically, a 0.10 mg/m ³ increase in Chlorophyll A correlated with 26% decrease in whale sharks. We found that increases in salinity correlated with increases in mobula abundance but did not correlate with observations of mantas or whale sharks. We also found that omission of environmental covariates can lead to overprediction and underprediction of relative abundances. Our findings highlight the need to take environmental conditions into account when evaluating the efficacy of marine protection.
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The white shark (Carcharodon carcharias) is a globally distributed, ecologically important top predator whose biology and population dynamics are challenging to study. Basic biological parameters remain virtually unknown in the Mediterranean Sea due to its historically low population density, dwindling population size, and lack of substantial sightings. White sharks are considered Critically Endangered in the Mediterranean Sea, and recent analyses suggest that the population has declined by 52% to 96% from historical levels in different Mediterranean sectors (Moro et al., 2020). Thus, white shark sightings dating back to 1860 are being used to estimate population trajectories throughout the entire region. Though the population size is unknown, remaining individuals are thought to be primarily restricted to a handful of hotspots deemed important for their reproduction and foraging. One of these hypothesized hotspots is the Sicilian Channel, which accounts for 19% of total historical sightings.
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This Collective Article presents new information about the occurrence of 21 taxa that belong to six Phyla: one Cnidaria, one Ctenophora, two Annelida, four Mollusca, two Arthropoda, and eleven Chordata. These records were reported from ten countries from the western to the eastern Mediterranean Sea as follows: Spain: early colonization signs of the Mar Menor lagoon by the cigar jellyfish Olindias muelleri; France: second record of the sea chub of the genus Kyphosus in French Mediterranean waters; Italy: first record of the marbled crab Pachygrapsus maurus in Sardinian waters; first records of the polychaetes Malmgrenia polypapillata and Levinsenia tribranchiata in the Tyrrhenian Sea; new record of the deep-sea squid Ancistrocheirus lesueurii in the Tyrrhenian Sea; first record of the pignosed arrowtooth eel Dysomma brevirostre in the Adriatic Sea; Tunisia: first documented record of the blue butterfish Stromateus fiatola and new record of the iconic great white shark Carcharodon carcharias in the Gulf of Gabes; Slovenia: first records of the sea slug Diaphorodoris alba and the sharpnose sevengill shark Heptranchias perlo; Montenegro: new record of the rare tope shark Galeorhinus galeus; Greece: new records of the rabbitfish Chimaera monstrosa and the electric ray Tetronarce nobiliana; first published record of the nuribranch Discodoris rosi; first record of the goblin shark Mitsukurina owstoni, unreported so far from the entire Mediterranean; Turkey: first record of the ctenophore Hormiphora plumosa at country level; first records of the anomuran decapod Munida speciosa and the Mediterranean tripodfish, Bathypterois mediterraneus from the Levantine Sea; Cyprus: first documented record of the nuribranch Scyllaea pelagica; Lebanon: first record of the killer whale Orcinus orca from the Levantine Sea.
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The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous marine animal populations have declined, yet it remains unclear whether these trends are symptomatic of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of threat for a globally distributed lineage of 1,041 chondrichthyan fishes-sharks, rays, and chimaeras. We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing (targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher than for most other vertebrates, and only one-third of species are considered safe. Population depletion has occurred throughout the world's ice-free waters, but is particularly prevalent in the Indo-Pacific Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is urgently needed to avoid extinctions and promote population recovery.
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Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management.
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White sharks, Carcharodon carcharias, are often described as elusive, with little information available due to the logistical difficulties of studying large marine predators that make long-distance migrations across ocean basins. Increased understanding of aggregation patterns, combined with recent advances in technology have, however, facilitated a new breadth of studies revealing fresh insights into the biology and ecology of white sharks. Although we may no longer be able to refer to the white shark as a little-known, elusive species, there remain numerous key questions that warrant investigation and research focus. Although white sharks have separate populations, they seemingly share similar biological and ecological traits across their global distribution. Yet, white shark's behavior and migratory patterns can widely differ, which makes formalizing similarities across its distribution challenging. Prioritization of research questions is important to maximize limited resources because white sharks are naturally low in abundance and play important regulatory roles in the ecosystem. Here, we consulted 43 white shark experts to identify these issues. The questions listed and developed here provide a global road map for future research on white sharks to advance progress toward key goals that are informed by the needs of the research community and resource managers.
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The occurrence of the white shark, Carcharodon carcharias, in the Mediterranean Sea has been reported since the Middle Ages (476–1453). Several studies have documented its presence in various areas of the basin, but no comprehensive review of the distribution and status of this species is available for the area. We compiled a total of 628 white shark records from 476 to 2015. Data suggests that the white shark is more common in the western Mediterranean Sea, especially in the Adriatic Sea and in the Sicilian Channel and is more frequently observed during summer months. However, analysis using night-time satellite imagery showed the existence of an anthropogenic bias in the distribution of white sharks. All size classes have been recorded in the region. However, the highest occurrence of young of the year has been recorded in the Sicilian Channel, in the Adriatic Sea and in the Aegean Sea, in summer, suggesting these areas might serve as nursery grounds. In the Mediterranean Sea, the white shark exhibits a broad diet. The most common prey found include small cetaceans (Tursiops truncatus, Stenella coeruleoalba), tuna (Thunnus spp.), swordfish (Xiphias gladius) and loggerhead sea turtle (Caretta caretta). A total of 53 white shark records refer to interactions between sharks and humans that resulted in a detrimental impact on humans, which include 42 bites and 11 reports of the presence of human remains in the stomach of captured animals. Analysis of the temporal variation in mean total lengths of white sharks found a decreasing trend from 1913 to 2012. The decreasing length of white sharks suggests this species might be declining in the Mediterranean Sea.
Technical Report
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An analysis of threat levels across all sharks, rays and chimaeras has revealed the Mediterranean Sea as a key hotspot of extinction risk1. Seventy seven species are recorded from the Mediterranean Sea, however of these, four species are considered to be either vagrant or probably vagrant, or Lessepsian immigrants from the Red Sea; they are the Spinner Shark (Carcharhinus brevipinna), the Reticulate Whipray (Himantura uarnak), the Great Hammerhead (Sphyrna mokarran) and the Scalloped Hammerhead (Sphyrna lewini). These four species have been excluded as Not Applicable for the Mediterranean region. Three species are endemic to the Mediterranean Sea and found nowhere else – Maltese Skate (Leucoraja melitensis; CR), Rough Skate (Raja radula; EN), and the Speckled Skate (Raja polystigma; LC). More than half of the species assessed, 39 of 73 species, are regionally threatened; 31 are most imperilled in the Critically Endangered (20 species) and Endangered (11) categories (Figure 1). On a global scale, of the 20 species of sharks, rays and chimaeras that have been assessed as Critically Endangered, seven have some part of their distribution in the Mediterranean Sea. Of the other 13 regionally CR species, the Mediterranean Sea part of their population is more threatened than the remainder of their global range.
Significance We independently reconstructed vessels number, engine power, and effort of the global marine fishing fleet, in both the artisanal and industrial sectors. Although global fishing capacity and effort have more than doubled since 1950 in all but the most industrialized regions, the nominal catch per unit of effort (CPUE) has comparatively decreased. Between 1950 and 2015 the effective CPUE, among the most widely used indicator to assess fisheries management and stocks well being, has decreased by over 80% for most countries. This paper highlights the large differences in the development of sectorial fishing fleets regionally. This detailed paper empowers future exploration of the drivers of these changes, critical to develop sector and regionally specific management models targeting global fisheries sustainability.
Sharks, rays and chimeras (class Chondrichthyes; herein ‘sharks’) today face possibly the largest crisis of their 420 million year history. Tens of millions of sharks are caught and traded internationally each year, many populations are overfished to the point where global catch peaked in 2003, and a quarter of species have an elevated risk of extinction [1–3]. To some, the solution is to simply stop taking them from our oceans, or prohibit carriage, sale or trade in shark fins [4]. Approaches such as bans and alternative livelihoods for fishers (e.g. ecotourism) may play some role in controlling fishing mortality but will not solve this crisis because sharks are mostly taken as incidental catch and play an important role in food security [5–7]. Here, we show that moving to sustainable fishing is a feasible solution. In fact, approximately 9% of the current global catch of sharks, from at least 33 species with a wide range of life histories, is biologically sustainable, although not necessarily sufficiently managed.