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Abstract and Figures

Having depleted fish stocks in domestic waters, the fleets of many industrialised countries are now travelling further afield to meet the rising demand for seafood. Much of this distant-water fishing (DWF) takes place in the territorial waters of low-income countries. As well as competing against the interests of local people, DWF in low-income countries is often associated with unsustainable levels of extraction, and with illegal, unreported and unregulated (IUU) fishing activities.China’s DWF fleet is the largest in the world, and so is thought to have significant effects on the environment and socioeconomic impacts in developing countries. Although China’s DWF fleet is known to be large, there is little information available about its actual size and the scale of its operations. For instance, recent assessments have produced estimates ranging between 1,600 and 3,400 vessels. In addition, it is unclear whether the Government of China has a comprehensive overview of China’s DWF fleet; vessel ownership is highly fragmented among many small companies and the fleet includes vessels registered in other jurisdictions. With information from the Krakken®database (FishSpektrum, 2018) and automatic identification system (AIS) data for 2017 and 2018, we investigated the size and operations of China’s DWF fleet using big data analytic techniques, ensemble algorithms and geographic information systems (GISs).
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China’s distant-
water shing eet
Scale, impact and governance
Miren Gutiérrez, Alfonso Daniels, Guy Jobbins,
Guillermo Gutiérrez Almazor and César Montenegro
June 2020
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This work is licensed under CC BY-NC-ND 4.0.
Cover photo: Workers ofoad frozen, net-caught tuna onto waiting trucks from a reefer cargo vessel owned by a Chinese company (Manila,
Philippines). © Adam Dean
The authors are grateful to Roberto Mielgo for his generous assistance with data acquisition and
analysis, and the team at Vulcan’s Skylight for their support with data acquisition. All gures were
created by Guillermo Gutiérrez Almazor. Deusto University, Bilbao, allowed us to use its facilities
when we needed to meet in person. The authors gratefully acknowledge nancial support from the
Waterloo Foundation, which made this research possible. Finally, we would like to thank John Pearce,
from the Marine Resources Assessment Group (MRAG), for generously contributing his time and
expertise to review this report. All errors remain those of the authors.
Acknowledgements 3
List of boxes, tables and gures 5
Glossary 6
Acronyms 7
Executive summary 8
1 Introduction 10
2 Background 12
2.1 China as a global shing superpower 12
2.2 Knowledge gaps and questions 12
3 Data and methodology 14
4 Findings and implications 15
4.1 China’s DWF eet is 5–8 times larger than previous estimates 15
4.2 Trawlers are the most common DWF vessel, and most vessels are in the Northwest Pacic 16
4.3 Almost 1,000 Chinese DWF vessels are registered in other countries 21
4.4 The ownership and operational control of China’s DWF eet is both complex and opaque 23
4.5 At least 183 vessels in China’s DWF eet are suspected of involvement in IUU shing 26
5 Analysis: development implications 28
5.1 The scale, scope and impact of China’s DWF eet and activities 28
5.2 China’s DWF activities in a development context 30
5.3 IUU shing and its governance 31
6 Conclusions and key policy recommendations 33
6.1 Conclusions 33
6.2 Key policy recommendations 34
References 35
Annex 1 Methodology 41
Annex 2 Taxonomy of operations at sea 45
List of boxes, tables and gures
Box 1 Identifying China’s distant-water shing vessels 14
Box 2 The Chinese National Fisheries Corporation 25
Box 3 Poly Group Corp. 25
Box 4 China’s distant-water shing in Ghana 29
Table 1 Identifying China’s distant-water shing eet in the Krakken® database 15
Table 2 The composition of China’s distant-water shing eet 17
Table 3 Fishing operations observed in each global region during 2017 and 2018 18
Table 4 Distribution of owning and operating companies by eet size 24
Table 5 Largest six Chinese eets of distant-water shing vessels 24
Table 6 Suspected illegal, unreported and unregulated shing vessels per country ag 27
Table A1 Criteria for extractions from the Krakken® database 42
Figure 1 Type of vessel for a sample of 4,798 Chinese distant-water shing vessels 16
Figure 2 Intensity of shing activity by China’s distant-water shing eet 19
Figure 3 Intensity of trawling activity by China’s distant-water shing eet 19
Figure 4 Intensity of long-lining activity by China’s distant-water shing eet 20
Figure 5 Intensity of squid-jigging activity by China’s distant-water shing eet 20
Figure 6 The 10 most common foreign-ag states for Chinese distant-water shing vessels 21
Figure 7 Chinese distant-water shing vessels agged to African countries 22
Figure 8 Flags of convenience favoured by the Chinese DWF eet 23
Figure A1 Trawling by the Chinese DWF eet 46
Figure A2 Long-lining by the Chinese DWF eet 46
Figure A3 Squid-jigging by the Chinese DWF eet 47
Figure A4 Trap-setting by the Chinese DWF eet 47
Automatic identication system (AIS)
A ship-borne transponder sending signals on a vessel’s position, heading and speed.
The incidental or unintended capturing or killing of non-target species whileshingfor another species. By-catchcan
besh, but also includes dolphins, whales, turtles and birds caught byshinggear.
Distant-water shing (DWF)
The commonly accepted international denition of DWF covers activities outside a nation’s 200-mile exclusive
economic zone (EEZ), whether on the high seas or in another nation’s EEZ.
Exclusive economic zone (EEZ)
A sea area up to 200nautical milesfrom the coast, within which astateclaims exclusive rights over marineresources.
Flag of convenience
Describing the permitted registration by a state of a vessel owned by foreign nationals. Commonly used pejoratively to
denote ag states with low environmental, safety or labour standards.
Geographic information system(GIS)
A system that acquires, stores, collects, analyses, manages and visualises spatial orgeographic data.
Illegal, unreported and unregulated (IUU) shing
A range of offences covering shing without permission or in violation of regulations of the ag state or host nation,
misreporting or failure to report catches to relevant authorities where required to do so, shing vessels without a ag or
national registration, or shing on stocks without management measures in place.
International Maritime Organization (IMO) number
A vessel’s unique number, usually maintained throughout the vessel’s length of service. Not required for shing vessels,
but common on industrial shing vessels for reasons of security, taxes, certication and insurance.
Maritime Mobile Service Identity (MMSI)
A unique identication number used in radio communications. MMSI numbers are country specic, and in principle are
changed when a vessel is reagged.
Regional sheries management organisation (RFMO)
Multilateral organisations governing shing interests for a specic area and/or species. While some RFMOs have a
purely advisory role, most have management powers to set catch and shing-effort limits, technical measures and
control obligations.
1,000 kilograms.
AIS automatic identication system
CNFC Chinese National Fisheries Corporation
DGSANCO European Commission’s Directorate General for Health and Consumer Protection
DWF distant-water shing
EEZ exclusive economic zone
FAO Food and Agriculture Organization
GIS geographic information system
IMO International Maritime Organization
ITWF International Transport Workers’ Federation
IUU illegal, unreported and unregulated
MARA Ministry of Agriculture and Rural Affairs
MMSI Maritime Mobile Service Identity
PGC Poly Group Corp.
PSMA Port State Measures Agreement (Agreement on Port State Measures to Prevent, Deter
and Eliminate IUUFishing)
RCMF Rongcheng Marine Fishery Co. Ltd.
RFMO regional sheries management organisation
SME small- or medium-sized enterprise
UVI unique vessel identiers
VMS vessel monitoring system
WCPFC Western and Central Pacic Fisheries Commission
Executive summary
Having depleted sh stocks in domestic waters,
the eets of many industrialised countries are
now travelling further aeld to meet the rising
demand for seafood. Much of this distant-water
shing (DWF) takes place in the territorial
waters of low-income countries. As well as
competing against the interests of local people,
DWF in low-income countries is often associated
with unsustainable levels of extraction, and
with illegal, unreported and unregulated (IUU)
China’s DWF eet is the largest in the world,
and so is thought to have signicant effects on
the environment and socioeconomic impacts
in developing countries. Although China’s
DWF eet is known to be large, there is little
information available about its actual size and
the scale of its operations. For instance, recent
assessments have produced estimates ranging
between 1,600 and 3,400 vessels. In addition, it
is unclear whether the Government of China has
a comprehensive overview of China’s DWF eet;
vessel ownership is highly fragmented among
many small companies and the eet includes
vessels registered in other jurisdictions.
With information from the Krakken®
database (FishSpektrum, 2018) and automatic
identication system (AIS) data for 2017 and
2018, we investigated the size and operations
of China’s DWF eet using big data analytic
techniques, ensemble algorithms and geographic
informationsystems (GISs).
Key ndings
China’s DWF eet is 5–8 times larger than
previous estimates. We identied a total of
16,966 Chinese DWF vessels. These include
12,490 vessels observed outside internationally
recognised Chinese waters between 2017
Trawlers are the most common DWF vessel,
and most vessels are in the Northwest Pacic. We
identied 1,821 individual Chinese DWF vessels
as trawlers. This is more than double the largest
previous estimate of the number of trawlers in
China’s DWF eet. An analysis of 5,241 shing
manoeuvres for 1,878 vessels during 2017
and 2018 found that the most frequent area of
operations was the Northwest Pacic. However,
the most intense operations were squid sheries
in the Southeast Pacic and Southwest Atlantic.
Almost 1,000 Chinese DWF vessels are
registered in other countries. We identied 927
vessels with Chinese owners, operators or other
Chinese interests registered in other countries.
518 of these are agged to African nations, where
enforcement measures are generally limited,
and where shing rights are often restricted to
domestically registered vessels. Just 148 vessels
were registered in nations commonly regarded
as ags of convenience. This reects the limited
incentives for adopting ags of convenience given
the relatively lax regulation and enforcement of
Chinese authorities.
The ownership and operational control of
China’s DWF eet is both complex and opaque.
Analysis of a subsample of 6,122 vessels found
that just eight companies owned or operated
more than 50 vessels. The majority of vessels are
owned by small- or medium-sized enterprises
(SMEs). Many of these may be subsidiaries
of larger corporations for tax or regulatory
purposes. Labyrinthine company structures
and a lack of transparency are likely to hamper
monitoring and enforcement efforts, and efforts
to ensure those ultimately responsible for
malpractice are heldaccountable.
At least 183 vessels in China’s DWF eet are
suspected of involvement in IUU shing. Just 10
companies own almost half of these vessels, and
several are parastatal companies. This implies
that Chinese authorities have the opportunity to
target their enforcement efforts efciently and
lead by example when it comes to enforcing and
prosecuting IUU activities.
Conclusions and recommendations
Chinese DWF is not solely responsible for the
global sheries crisis: other countries are also
responsible for overshing. The international
community has also failed to ensure oversight
of international shing operations, such as
establishing a global, centralised database of IUU
vessels, and many governments in low-income
countries are either unwilling or unable to
monitor their waters.
However, the sheer size and global presence of
its DWF eet, as revealed in this report, means
China is the most signicant actor. This makes
the low levels of transparency and control over
the operations of its DWF eet of particular
concern. Improving the governance of this eet is
central to efforts to combat overshing and IUU
shing, and to prevent the degradation of global
sh stocks.
Our ndings suggest that China faces a
greater challenge than previously realised in
meeting its goal to reduce its DWF eet to
3,000 vessels. Our ndings also concur with
those of other researchers who have identied
signicant gaps in China’s capacity for governing
its DWF eet. However, China can take steps to
demonstrate global leadership on the governance
of DWF, sustainability of global sheries and
Steps would include:
improving the registration and transparency
ofDWF vessels, as well as owning and
operating companies;
adopting higher standards such as ratication
of the Port State MeasuresAgreement
(PSMA), as a ag state;
stricter regulation and enforcement of
DWFoperations; and
strengthening bilateral cooperation with states
where Chinese DWF vessels sh.
Our ndings also highlight the need for
more effective regional and global action.
International bodies and agencies can upgrade
capacity for monitoring, information sharing
and enforcement, take proactive measures to
disrupt IUU stocks from entering international
supply chains, and support governance capacity
in coastal developing states. Coastal developing
states that ratify international agreements
increase transparency over international shing
agreements, and upgrade enforcement measures
will be better able to combat resource theft
These ndings contribute to global work on
the scale, impacts and governance of China’s
DWF eet. More work is needed to explore
the ecological, social and economic impacts of
China’s DWF eet in developing countries, and
to investigate the behaviour of transnational
companies engaged in DWF, particularly those
registered in ag-of-convenience states and
1 Introduction
1 When referring to China, we mean the People’s Republic of China, excluding Chinese Taipei/Taiwan and the Special
Administrative Regions of Hong Kong and Macau.
Global shing effort has expanded rapidly since
the 1950s, fuelled by technological advances,
large public subsidies and increasing demand for
sh protein (Tickler et al., 2018). This expansion
has severely and negatively affected global sh
stocks; 90% of commercially exploited marine
sh stocks are now either overshed or shed to
their maximum sustainable limits (FAO, 2016a).
Fishing vessels now travel further in search of
declining catches. The average distance travelled
has doubled since the 1950s, with catches falling
from 25 kg per kilometre travelled to 7 kg per
kilometre over the same period (Tickler et al.,
2018). As shing eets have exhausted sh stocks
in the waters of advanced economies, they are
hunting further aeld, particularly in the waters
of low-income countries (Pauly, 2008). A recent
analysis found that in the exclusive economic
zones (EEZs) of low-income countries, 84%
of industrialised shing effort came from other
countries and 78% came from vessels agged
to higher- and upper-middle-income nations
(McCauley et al., 2018)
Distant-water shing (DWF) often competes
with the interests of people in low-income
nations (Toppe et al., 2017). Economically
weak countries in need of foreign currency, and
without their own industrial eets or scientic
advice on sustainable catch limits, often negotiate
disadvantageous sheries agreements (Belhabib
et al., 2014). Fragile governance and weak
enforcement mean that low-income countries
are also most at risk from widespread problems
of illegal, unreported and unregulated (IUU)
activities that accompany DWF eets (Agnew
et al., 2009; Daniels et al., 2016). For example,
20% of the global IUU catch is estimated to
come from just six contiguous West African
countries (Mauritania, Senegal, The Gambia,
Guinea-Bissau, Guinea and Sierra Leone).
The opportunity cost of IUU activities to the
economies of these six countries has been
estimated at $2.3 billion a year and 300,000
jobs (Daniels et al., 2016; Belhabib, 2017).
Assuch, DWF poses risks to the sustainable use
of marine resources in low-income countries,
and to the income, employment and food
security of people dependent on these resources
This report examines the size, composition and
operations of the Chinese eet capable of DWF.1
We focus on China as it is the dominant force
in the global shing industry, with the largest
domestic and DWF eets; China is also the
world’s largest producer of sh products (Pauly
et al., 2014; Mallory, 2012; 2013).
Despite the signicance of China’s shing
industry, assessment of its size and operations
is hampered by a lack of transparency and by
the limited availability of information in English
(Mallory, 2013). Even estimates of the size of
China’s DWF eet vary considerably: from under
2,000 vessels (Mallory, 2013) to around 3,400
vessels (Pauly et al., 2014). Information on the
geographic location, types of shing and catches
of the Chinese DWF eet is also limited.
The gaps in data on China’s DWF eet are
concerning. They constrain understanding and
mitigation of the ecological and socioeconomic
impacts of the eet’s activities in specic
territories and undermine effective global and
multilateral governance.
This report sets out to address some of these
knowledge gaps about the size and operations of
China’s DWF eet. We hope that our ndings will
be of interest to research and policy communities
aiming to improve the governance, monitoring,
surveillance and sustainability of global sheries.
We set out to answer four key questions:
1. How big is the Chinese DWF eet?
2. Where and how is it operating?
3. Where are these vessels registered, and who is
operating them?
4. What are the implications of the DWF eet’s
activities for sustainable development?
Chapter 2 gives more information on China’s
role and on previous studies. Chapter 3
summarises our methodology, followed by
Chapter 4, which presents our ve main ndings.
After a brief analysis of the development
implications of our ndings (Chapter 5),
we present our conclusions and key policy
recommendations inChapter 6.
2 Background
2.1 China as a global shing
China is a sheries superpower. It has the largest
shing eet and the largest DWF eet in the world.
In 2016, China captured 15.2 million tonnes
of sh – around 20% of the global total – and
consumed 38% of total global sh production.
China’s DWF caught two million tonnes, although
China provided details of species and shing
area for only those catches marketed in China,
representing 24% of the DWF catch (FAO,
2018a). In the same year, China exported sh and
sh products worth $20.1 billion – around 14%
of the total global trade (FAO, 2018a).
A relative latecomer to DWF, China began
overseas shing in 1985 when 13 vessels of the
China National Fishing Corporation set sail
for West Africa (Mallory, 2013). Since then,
the number of Chinese DWF vessels has grown
rapidly. As with other DWF eets, this growth is
driven by increasing demand for sh outstripping
local supply. By 2012, 30% of sheries in China
had collapsed, and 20% were considered over-
exploited (European Parliament, 2012).
Like those of other countries, China’s push
to expand its DWF eet has been fuelled by
tax exemptions and subsidies for fuel and ship
construction (Mallory, 2013; Kang, 2016). Fuel
subsidies have been a particularly important
component of this boom, given the long trips
from ports in China to distant shing waters
(Kang, 2016).
2.2 Knowledge gaps and questions
As mentioned in the introduction, understanding
of the size and operations of China’s DWF eet is
constrained by a range of issues. One is a lack of
transparency. For example, developing bottom-
up estimates of China’s DWF activities is difcult,
as bilateral shing agreements governing Chinese
vessels in the waters of other nations are rarely
publicly available (Pauly et al., 2014).
Conservation organisation Oceana has
described the lack of transparency in the
activities of China’s DWF vessels:
(They) operate largely without access
agreements or under access agreements
that are secret, thus we don’t even
know if their catch is legal or not …
There are good reasons to think that
China’s distant water eets, legally or
not, catch well above the surplus in the
countries where they operate. Chinese
authorities are not publishing catch
statistics or evaluations of the stocks
exploited by their eets. (Oceana, 2013)
Another key constraint is the limited availability
of information in English (Mallory, 2013).
In this section we summarise what is already
known about Chinese DWFs and provide an
overview of key knowledge gaps.
2.2.1 Fleet size
The size of China’s DWF eet has been reported
as: 1,899 and 1,989 vessels in 2010 and 2011
(Mallory, 2013); approximately 1,600 vessels
with over 30,000 crew in 2013 (European
Commission, 2016); and around 3,432 vessels
(Pauly et al., 2014) or 2,460 vessels (Greenpeace,
2016a) in 2014. In comparison, the European
Union’s DWF eet was 289 vessels in 2014, and
the United States had 225 large DWF vessels in
2015 (Kang, 2016). Estimates of China’s DWF
eet generally focus on Chinese agged vessels,
and there is limited data available on the number
of Chinese-owned or joint venture vessels agged
in other countries.
The Chinese government does appear to
recognise concerns about the size of its DWF
eet. At the 2017 World Trade Organization
summit in Buenos Aires, the Chinese government
announced plans to restrict the size of its
DWF eet to 3,000 vessels by 2020, and to
limit catches to 2.3 million tonnes per year
(Chun, 2018). This cutback is part of China’s
Thirteenth Five-Year Plan for Economic and
Social Development (2016–2020), which also
species reductions in diesel fuel subsidies and
the elimination of IUU shing (FAO, 2018a).
Another question is the extent to which the
government of China has a comprehensive
overview of the DWF eet. Some 70% of the
eet is now in private ownership, with the
majority of vessels owned by a proliferation of
small- or medium-sized enterprises (SMEs) rather
than large, state-owned rms (Mallory, 2013).
Fragmented ownership, joint venture operations
and reagging of vessels seem likely to challenge
the state’s ability to monitor the position and
activities of all vessels in China’s extensive eet.
2.2.2 Geographical presence
Information on the geographical presence of
China’s DWF is also limited. Mallory (2013)
developed a limited picture by compiling
information from various ofcial Chinese
public and industry sources. In this picture,
in 2010, 732 Chinese vessels operated in the
waters of eight Asian countries (mostly North
Korea, Indonesia and Myanmar) and 394
Chinese vessels operated in 11 African countries,
with larger eets in Mauritania, Guinea and
Morocco (Bureau of Fisheries, 2011, in Mallory,
2012). Another report from 2010 refers to 202
trawling vessels in West Africa (Supporting
and Strengthening Distant-water Fisheries
Task Force, 2011, in Mallory, 2012). Mallory
(2012) also refers to Chinese vessels operating
throughout the Pacic and Southwest Atlantic,
withoutgiving gures.
Taking a bottom-up approach, based on
Chinese vessels reported in different territories,
including in various bilateral sheries
agreements, Pauly and colleagues calculated
that China operated 2,745 DWF vessels in Asia,
mainly in the waters of Japan and South Korea,
and 393 vessels in West and East Africa, with
smaller numbers of vessels operating in Oceania,
Central and South America, and Antarctica
(Pauly et al., 2014). While Mallory’s and Pauly
et al.’s gures for vessels operational in Africa
are strikingly similar (394 vs 393), their gures
for DWF vessels in Asia are wildly different
2.2.3 Vessel types and target species
Information about the shing gear and target
species of China’s DWF eet is similarly
inconclusive. For example, various sources agree
that trawlers are the most common type of vessel,
but gures range from 40% (Pauly et al., 2014;
Agriculture Bureau of Fisheries, 2011, in Mallory,
2013) to 60% (Lam et al., 2011, in Pauly et al.,
2014). Estimates and reports for other types of
gear are similarly inconsistent, not helped by the
different systems used for classifying vessels.
3 Data and methodology
The methodology underlying this study
combines the use of big data analytic techniques,
ensemble algorithms and geographic information
We extracted data from the FishSpektrum
Krakken® database (FishSpektrum, 2018) on all
possible DWF vessels with connections to China
(Box 1). Annex 1 describes the methodology in
more detail. We developed our own database to
dene and categorise Chinese vessels capable of
DWF, and compared our data with ndings in
other expert literature.
We also used GIS software to visualise
automatic identication system (AIS) data and
identify shing manoeuvresaccording totheir
location and movement patterns (Annex 2).
Based on expert knowledge, these shing
manoeuvres were labelled to train algorithms
todetectpatterns in the location data. We
usedan ensemble oflearning algorithms to
identify where and how vessels operate when
shing. Finally, we combined all the analysis with
other sources on IUU shing.
Descriptive and dynamic data limitations
are the leading methodological constraint on
our ndings. The Krakken® dataset contains
gaps, including missing information on regional
sheries management organisation (RFMO)
registration, vessel type, International Maritime
Organization (IMO) and ownership. This implies
that our gure for the size of China’s DWF eet
may be an underestimate. Another possible cause
for an underestimate are gaps in the dynamic
data, with AIS data unavailable for 2,462
(14.5%) of Chinese-registered vessels.
Box 1 Identifying China’s distant-water
shing vessels
The DWF vessels of one country are those
operating within the EEZs of another
country, or further offshore on the high
seas (Oceana, 2013). However, identifying
which vessels are operating where is
To identify Chinese DWF vessels, we
looked at records of vessels: registered with
specic Chinese public agencies responsible
for regulating DWF; registered with
foreign governments; or inspected outside
Chinese waters. We also looked at vessels’
unique Maritime Mobile Service Identity
(MMSI) transponders being detected as
active outside Chinese waters on a sample
of dates during 2018. The methodology is
described in more detail in Annex 1.
4 Findings and
Our analysis of the data has identied ve key
1. China’s DWF eet is 5–8 times larger than
previous estimates.
2. Trawlers are the most common DWF vessel,
and most vessels are in the Northwest Pacic.
3. Almost 1,000 Chinese DWF vessels are
registered in other countries.
4. The ownership and operational control
of China’s DWF eet is both complex and
5. At least 183 vessels in China’s DWF eet are
suspected of involvement in IUU shing.
4.1 China’s DWF eet is 5–8 times
larger than previous estimates
We identied 16,966 vessels in the Krakken®
database as members of China’s DWF eet
(Table1). This is 5–8 times larger than the
estimates of 1,989 vessels provided by Mallory
(2013), 3,432 vessels by Pauly et al. (2014), or
2,460 vessels by Greenpeace (2016b).
The largest subgroup we identied was
of 12,490 vessels without IMO or RFMO
registrations but with active AIS signals
outside Chinese waters at some point between
1January2017 and 31 December 2018.
Table 1 Identifying China’s distant-water shing eet in the Krakken® database
Extraction 1 2 3 4.1 4.2 4.3 6.1 6.2 6.3 6.4
Registered IMO or RFMO number ✓ ✓ ✓ ––––
Registered RFMO number ✓ ✗ –––––––
Registered with Chinese DWF
–– ––––––
AIS signal outside Chinese EEZ in
2017 or 2018
– – –––––––
Currently flagged to China ✓ ✓ ✗ ✗ ✗ ✗
Not currently flagged to China – – ✓✓✓ ––––
Previously flagged to China –––––
Never flagged to China – – – – – –––
Inspected by Chinese authorities
outside Chinese waters in 2018
– – – – – – – –
Exported or impounded by Customs – – – – – – –
Built in China – – ✓ ✗ ––––
Related to Chinese interests ✓ ✓ –––
Number of vessels 2,076 575 12,490 431 92 86 318 379 82 437
Source: elaborated from FishSpektrum (2018).
Weassume that this remote observation of a
vessel’s presence overseas grants high condence
that it is engaged in DWF operations. If we
consider only this group – discounting all other
results – the gure of 12,490 vessels is still 3.5
times larger than the estimate of Pauly etal.(2014).
We also identied 3,541 vessels with either
a registered intention to sh overseas or in
contact with Chinese enforcement agencies in
circumstances that strongly imply engagement
in DWF shing. These included Chinese-agged
vessels: with IMO numbers (Extraction 1),
registered with RFMOs (Extraction 2), registered
with the Chinese DWF association (Extraction
6.4), inspected by Chinese authorities outside
Chinese waters during 2018 (Extraction 6.2),
or registered as exported or seized by Chinese
customs agents (Extraction 6.3).
Additionally, we identied 927 vessels agged by
other countries that have associations with China
that we assume are signicant. These include
vessels built in or previously agged to China, or
with a Chinese interest, meaning that they have
a current or previous Chinese name, operator
or owner. These vessels may be agged to other
nations but were operated by Chinese businesses
or their subsidiaries, contributing to China’s supply
chains and international shingeffort.
Our identication of vessels as members of the
DWF eet does not imply that all are operating
currently, simultaneously or consistently in
foreign or international waters. This is partly
due to gaps in the available data, and partly due
to the criteria used to identify the DWF eet.
Krakken®s records are not updated in real time
and do not reect the current status of some
vessels. For example, Krakken® may record a
vessel as being operational during 2017, but not
record that it was decommissioned in early 2018.
There are 58 Chinese vessels whose last record
in Krakken® was ‘active and operational’ before
1989; these vessels may no longer be operational.
4.2 Trawlers are the most common
DWF vessel, and most vessels are in
the Northwest Pacic
4.2.1 Numbers of DWF trawlers
Krakken® contains details on the type of vessel
for 4,798 of the DWF vessels we identied. Of
these, 1,821 (38%) were trawlers, 993 (20.7%)
were long-liners, 625 (13%) were squid-jiggers,
358 (7.5%) were seiners, and 334 (7%) were gill-
netters. A further 667 vessels (13.9%) were of
other types or served in support roles (Figure 1).
Figure 1 Type of vessel for a sample of 4,798 Chinese distant-water shing vessels
Trawler (1,821) 37.95%
Longliner (993) 20.70%
Squid-jigger (625) 13.03%
Seiner (358) 7.46%
Gill-netter (334) 6.96%
Carrier (207) 4.31%
Reefer (150) 3.13%
Multipurpose (136) 2.83%
Others (174) 3.63%
Source: elaborated from FishSpektrum (2018).
This picture contrasts with the current
composition of the global high seas eet, in which
59% of vessels are thought to use long-lines (Sala
et al., 2018). However, the proportions in our
sample are reasonably consistent with previous
estimates of the composition of the Chinese DWF
eet as shown in Table 2, all of which conclude
that trawlers are the dominant type of gear carried.
As we cannot assume that our sample is
representative of China’s DWF eet, we have not
extrapolated these results. The gure of 1,821
trawlers is therefore highly conservative; the
actual number of trawlers in China’s DWF eet
may be considerably higher.
Despite this uncertainty, our subsample of
1,821 trawlers is still more than double the
largest previous estimate, in Mallory (2013).
Trawlers are of particular interest, as one form
of trawling – bottom-trawling – is a highly
destructive shing technique. Bottom-trawling is
unselective and produces excessive by-catch. It is
associated with long-term damage to ecosystems
in and around the seaoor (Gianni et al., 2016;
Sana, 2016; WWF, 2019). While we do not
know how many of these 1,821 Chinese DWF
2 Just 13% of the vessels with active AIS signals had sufcient data to detect clear shing manoeuvres. This may be because
vessels shing on the high seas may be undetected by AIS receivers, and/or vessels may deactivate or tamper with their AIS
transponders (Gutierrez et al., 2018).
trawlers are engaged in bottom-trawling, there
is evidence that it is a common practice for
Chinese trawlers in West Africa (e.g. Greenpeace,
2016b; EJF, 2018a). That China may have well
over 1,000 DWF trawlers more than previously
recognised heightens concerns about the eet’s
global ecological impact.
4.2.2 DWF vessels in the Northwest
Based on AIS position data, we detected 5,241
individual shing manoeuvres for 1,878 vessels
during 2017 and 2018.2 This allowed us to assess
their areas of operations with a high degree of
certainty, and also to classify their behaviour
using algorithmic methods. The majority of these
vessels were active in different areas of the Pacic,
particularly the Northwest, Western Central and
Southeast Food and Agriculture Organization
(FAO) regions. Table 3 summarises the behaviour
exhibited by vessels in each FAO shing area.
The number of vessels present in an area does
not necessarily indicate the intensity of shing
effort taking place, however. Using the density
of AIS signals as a proxy for shing effort by the
Table 2 The composition of China’s distant-water shing eet
Source Sample
Trawlers Tuna
Others Criteria
ODI, based on
FishSpektrum (2018)
4,798 625
NR 358
Chinese DWF vessels for
which there is data on
gear type
Lam et al. (2011), in
Pauly et al. (2014)
444 NR 269
Chinese DWF vessels
Pauly et al. (2014) 900 NR 359
Chinese DWF vessels
operating in EEZ (and
adjacent high sea)
(2000–2011), excluding
vessels in Japan and
South Korea
Ministry of Agriculture
Bureau of Fisheries
(2011), in Mallory (2013)
1,800 500
– 100
Chinese DWF vessels
(approximate numbers,
Source: elaborated from AIS data provided by Vulcan’s Skylight.
1,878 vessels shows that shing effort is most
intense in the Southwest Atlantic and Southeast
Pacic regions (Figures 2,3,4,5). These two
areas, and particularly the Southeast Pacic, are
associated with nutrient-rich cool-water currents
and productive squid sheries (FAO, 2005)
(Figure 5). Trawling is widespread, but mostly
of low intensity, and is clearly taking place in
deep offshore areas as well as areas vulnerable to
bottom-trawling (Figure 3).
This sample of 1,878 vessels represents only
around 11% of the total DWF eet identied in
our study, so is not necessarily representative.
However, the concentration of individual vessels
in the Northwest Pacic (Table 3) and the
extensive presence in the Yellow and East China
Seas (Figure2) are consistent with expectations.
These ndings are also broadly consistent with
those of Pauly and colleagues (2014), who found
that the majority of Chinese DWF vessels operate
in Korean and Japanese waters.
3 These vessels have no IMO registration number, and are not registered with an RFMO or the Chinese DWF association.
Different denitions of national and distant
waters could be one possible factor underlying
the large discrepancy between the 16,966 Chinese
DWF vessels we have found and the much
smaller numbers offered by the Government
of China and other reports. China claims large
areas in the Yellow, South and East China seas
as national waters. These areas and claims are
not internationally recognised as part of China’s
EEZ. China does not consider shing operations
outside its EEZ but within these claimed areas to
be DWF, and so does not include them in reports
on its DWF eet or operations (Zhang, 2015).
However, one criterion for inclusion in our DWF
list (as described in Chapter 3 and Annex1)
was a detectable AIS position outside China’s
internationally recognised EEZ during 2017 or
2018. For this reason alone, 12,490 Chinese-
agged vessels were added to our list.3 However, it
seems unlikely that different denitions of shing
areas account for the whole disparity.
Table 3 Fishing operations observed in each global region during 2017 and 2018
Region FAO code Trawling Long-lining Squid-
fishing operations
Pacific, Northwest 61 1,277 684 1,018 2,979
Pacific, Western Central 71 182 133 252 567
Pacific, Southeast 87 142 119 163 424
Atlantic, Southwest 41 102 98 181 381
Pacific, Eastern Central 77 63 66 69 198
Indian Ocean, Western 51 54 45 104 203
Atlantic, Eastern Central 34 43 31 54 128
Indian Ocean, Eastern 57 32 18 58 108
Atlantic, Southeast 47 17 17 37 71
Atlantic, Western Central 31 15 15 12 42
Pacific, Southwest 81 12 18 21 51
Atlantic, Northeast 27 10 8 18 36
Mediterranean and Black Sea 37 7 2 22 31
Atlantic, Antarctic 48 4 2 4 10
Arctic Sea 18 1 1 1 3
Atlantic, Northwest 21 1 0 4 5
Indian Ocean, Antarctic and Southern 58 1 1 2 4
Note: we did not detect any Chinese shing in Area 88 (Pacic, Antarctic).
Figure 2 Intensity of shing activity by China’s distant-water shing eet
Low density areas
Transition areas from low to high density
High density areas
Coastline and FAO regions (black)
China’s exclusive economic zone (EEZ) boundaries (red)
Source: elaborated from AIS data provided by Vulcan’s Skylight.
Source: elaborated from AIS data provided by Vulcan’s Skylight.
Figure 3 Intensity of trawling activity by China’s distant-water shing eet
Low density areas
Transition areas from low to high density
High density areas
Coastline and FAO regions (black)
China’s exclusive economic zone (EEZ) boundaries (red)
Figure 4 Intensity of long-lining activity by China’s distant-water shing eet
Low density areas
Transition areas from low to high density
High density areas
Coastline and FAO regions (black)
China’s exclusive economic zone (EEZ) boundaries (red)
Source: elaborated from AIS data provided by Vulcan’s Skylight.
Figure 5 Intensity of squid-jigging activity by China’s distant-water shing eet
Low density areas
Transition areas from low to high density
High density areas
Coastline and FAO regions (black)
China’s exclusive economic zone (EEZ) boundaries (red)
Source: elaborated from AIS data provided by Vulcan’s Skylight.
4.3 Almost 1,000 Chinese DWF
vessels are registered in other
4.3.1 Registration of Chinese vessels to
other countries
Of the 16,966 vessels in China’s DWF eet,
16,039 (94.5%) sail under a Chinese ag and
only 927 (5.5%) are agged to a third country or
no country (Figure 6).4 Although 927 is a large
number, it is a relatively small proportion of the
global eet; around 20% of the world’s shing
vessels are registered in states to which they have
no other connection (DeSombre, 2006).
The Chinese DWF eet includes vessels agged
to 56 countries outside China. The ve most
frequent non-Chinese ags states – Ghana,
Mauritania, Côted’Ivoire, Fiji and Panama
– account for almost half the total (48%, or
4.3.2 Chinese vessels agged to Africa
Of the 927 vessels agged in countries other
than China, we found 518 Chinese DWF vessels
registered in African nations. The vast majority
of them – 92.7% (480 vessels) — y the ags of
countries on Africa’s west coast between Gabon
4 Krakken® does not show ag data for 15 of the DWF vessels.
and Morocco (Figure 7). More than half of
these vessels are registered in just two countries:
Ghana and Mauritania.
Registration in Ghana most likely reects
a technical compliance with laws restricting
industrial and semi-industrial shing in Ghanaian
waters to Ghanaian-agged vessels that are
not owned or part-owned by foreign interests,
except in the case of tuna trawling (Republic of
Ghana,2002). (For more information on this, see
the box in Chapter 5 of this report.) Similarly,
Chinese rms are alleged to reag vessels in
Mauritania as part of private agreements
brokering investment for access to sheries
resources (Transparent Sea, 2012; Marti, 2018).
Of the 518 Chinese DWF vessels registered
in Africa, 82% (426 vessels) are trawlers. Some
authors have alleged that restrictions by Chinese
authorities on trawlers have encouraged Chinese
trawlers to relocate to waters with weaker
enforcement capacity (e.g. Chimtom, 2016;
Ogundeji, 2019).
4.3.3 Foreign-registered vessels under ags
of convenience
Of the 927 foreign-registered Chinese vessels,
148 are registered in countries considered to
be providing ags of convenience, including
Figure 6 The 10 most common foreign-ag states for Chinese distant-water shing vessels
Mauritania (132) 14.24%
Ghana (137) 14.78%
Côte d’Ivoire (69) 7.44%
Fiji (55) 5.93%
Panama (52) 5.61%
Cambodia (27) 2.91%
Argentina (34) 3.67%
Russian Federation (42) 4.53%
Senegal (32) 3.45%
Morocco (46) 4.96%
Others (301) 32.47%
Source: elaborated from FishSpektrum (2018).
Panama, Cambodia, Belize, Vanuatu, St Vincent,
Honduras and Liberia (Figure 8).5 Flags of
convenience have legitimate uses, but are also
routinely used by ship owners to evade taxes
and regulations of their home state, such as
for safety and environmental standards and/or
Flags of convenience can also help to protect
vessel owners from legal action or scrutiny,
particularly by obscuring who actually owns
vessels engaging in illicit activity (Brush,
2019). Several of these ag-of-convenience
nations – particularly Panama, Belize, Liberia
and St Vincent – are also recognised tax havens
(discussed in Section 4.4).
4.3.4 Chinese DWF vessels retaining
Chinese ags
More than 90% of China’s DWF vessels y the
Chinese ag. Why do so few Chinese vessels
register with ags of convenience or ags of
other nations? One answer may be that there are
limited incentives to do so, as China’s regulation
of its DWF activities is notably less vigorous
5 Based on the list of ags of convenience issued by the International Transport Workers’ Federation (ITWF) in 2019
(ITWF, 2019).
6 These are: the International Commission for the Conservation of Atlantic Tunas, the WCPFC, the Inter-American Tropical Tuna
Commission, the Indian Ocean Tuna Commission, the South Pacic Regional Fisheries Management Organization, the North
Pacic Fisheries Commission and the Commission for the Conservation of Antarctic Marine Living Resources (MARA, 2019).
than the regulation of its own domestic sheries
(Mallory, 2013); China is effectively its own ag
of convenience.
As a ag state, China does not have a
particularly strong record of engaging with the
international community and complying with
RFMO obligations (Hosch, 2019; Macfadyen
etal., 2019). Half of China’s DWF vessels
are believed to operate in areas governed by
RFMOs. These regional organisations are
typically established to manage migratory species
that move across national jurisdictions and
international waters and therefore require global
management to prevent overshing (Kang, 2016).
However, China has joined only seven RFMOs,6
while, in comparison, the EU participates in 17
such organisations.
China has also been accused of attempting to
set high historical shing records, which would
then serve as a basis to allocate national shares
of sh stocks, taking advantage of the fact that
RFMOs are usually governed by consensus (Pew,
2012). This ‘race to sh’ happened, for example,
during negotiations of the South Pacic albacore
Figure 7 Chinese distant-water shing vessels agged to African countries
Ghana (137) 26.45%
Mauritania (132) 25.48%
Côte d’Ivoire (69) 13.32%
Morocco (46) 8.88%
Senegal (32) 6.18%
Madagascar (17) 3.28%
Guinea (14) 2.70%
Sierra Leone (15) 2.90%
Mozambique (14) 2.70%
Gabon (8) 1.54%
Others (34) 6.56%
Source: elaborated from FishSpektrum (2018).
shery, under the remit of the Western and
Central Pacic Fisheries Commission (WCPFC)
(Kang, 2016). During the WCPFC 2014 annual
meeting, the Chinese delegates insisted on
increasing the Chinese DWF eet in the area
from 100 to 400 vessels before agreeing to any
limits, despite scientists’ concerns over the status
of the albacore population (Kang, 2016).
China has failed to endorse some fundamental
marine conventions, such as the Fund for
Compensation for Oil Pollution Damage of
1992 (International Chamber of Shipping,
2019), the Forced Labour Convention (1930)
and the Freedom of Association and Protection
of the Right to Organise (1948) (ILO, 2017).
As of March 2020, China had still not ratied
the legally binding Agreement on Port State
Measures to Prevent, Deter and Eliminate IUU
Fishing (PSMA), unlike other signicant sheries
powers such as the EU and the United States
(FAO, 2019a). This agreement was approved
by the FAO Conference in 2009 and came into
force in 2016, aiming to strengthen controls in
ports where the sheries catches are landed and
reported, and denying access to vessels suspected
of IUU activity (FAO,2019b).7
Further, China has been criticised for
insufcient action to sign, ratify and enforce
7 Some requirements of the PSMA are included as membership obligations of certain RFMOs. For example, member states
of the Indian Ocean Tuna Commission are bound by Resolution 16/11 on PSMA.
international agreements and standards
aimed at tackling IUU shing (Mallory,2013;
Macfadyenet al., 2019), poor working conditions
and human slavery (Global Slavery Index, 2018)
and non-compliance with reporting requirements
(Blomeyer et al., 2012; Mallory,2013).
Thesepositions by the Chinese state confer
technical and nancial advantages to the owners
and operators of Chinese vessels, reducing
their incentives to re-register vessels to ag-of-
convenience nations.
4.4 The ownership and operational
control of China’s DWF eet is both
complex and opaque
4.4.1 Information on ownership of China’s
DWF eet
The Krakken® shipping database offers
information on the most recent operators and
owners of 6,122 vessels of the 16,966 in the
Chinese DWF eet. Krakken® lists 2,228 rms
that own and/or operate these 6,122 vessels.
Most rms own or operate a small number of
vessels each. Atotal of 1,631 owners and/or
operators (72.3% of these rms) possess and/or
operate just a single vessel, and over half (57.8%)
Figure 8 Flags of convenience favoured by the Chinese DWF eet
Panama (52) 35.14%
Cambodia (27) 18.24%
Belize (21) 14.19%
Vanuatu (11) 7.43%
Saint Vincent and
the Grenadines
(10) 6.76%
Honduras (10) 6.76%
Liberia (8) 5.41%
Georgia (2) 1.35%
Others (7) 4.73%
Source: elaborated from FishSpektrum (2018).
of these vessels are owned and/or operated by
the 95.7% of companies with eets of 10 vessels
or fewer (Table 4).
While our sample is not representative of
the wider Chinese DWF eet, these gures
suggest that Mallory’s (2013) assessment that
70% of Chinese DWF businesses are SMEs
may be an underestimate. Alternatively, some
of these small companies may be owned
by larger conglomerations, with individual
companies registered for each boat for tax or
On the other hand, there is a relatively small
number of very large companies that own or
operate extensive eets. The 10 largest rms
own or operate 898 vessels (14.7% of these
vessels) between them. Table 5 lists information
on the largest six eets. The largest eet of 257
vessels is owned by the China National Fisheries
Corporation (CNFC) (Box 2), while Poly Group
Corp. (PGC) owns 128 (Box 3).
There is little publicly available information
on the ownership of Chinese DWF vessels by
companies. Efforts to cross-reference data from
Krakken® with corporate websites and publicly
available information suggests that patterns of
ownership and operation are complex, but also
perhaps more consolidated than appears when
looking only at the names of registered owners.
Aside from the 7.5% of vessels operated by
companies other than their owners, many of the
rms in our sample are subsidiaries within larger
corporate frameworks.
For example, China National Fisheries Yantai
Marine Fisheries Corp., for which we have
data on 66 vessels, is a subsidiary of the CNFC
(FIS,2019a). Krakken® also records seven vessels
as owned by Zhoushan Marine Fisheries Co. Ltd,
which may be the same as (CNFC) Zhoushan
Marine Fisheries Co. Ltd, a subsidiary of CNFC
according to FIS (2019b).
Similarly, Rongcheng Rong Yuan Fishery Co.
Ltd (68 vessels) is a subsidiary of the Jinghai
Group Co.Ltd which has a further six vessels
Table 5 Largest six Chinese eets of distant-water
shing vessels
Name Location Owned/
China National (Overseas) Fisheries Corp.
(CNFC) / Zhong Yu Global Seafood Corp.
中国水产总公司 / 中渔环球海洋
Beijing 257
Poly Group Corp. / Poly Technologies Inc.
/ Fuzhou Hong Dong Yuan Yang Pelagic
Fishery Co. Ltd – 宏东渔业股份有限
公司 / 福州宏东远洋渔业有限公司
Beijing 128
Fujian Province Pingtan County Heng Li
Fishery Co. Ltd – 福建省平潭县恒利
Dalian Chang Hai Yuan Yang Pelagic
Fishery Co. Ltd / Dalian Chang Hai Ocean
Going Fisheries Co. Ltd – 大连长海远
Rongcheng Rong Yuan Fishery Co. Ltd –
Shandong 68
China National Fisheries Yantai Marine
Fisheries Corp. / Yantai Marine Fisheries
Co. Ltd – 烟台海洋渔业有限公司 /
Shandong 66
Source: elaborated from FishSpektrum (2018).
Table 4 Distribution of owning and operating companies by eet size
Companies Vessels
Vessel number
Total Running total Cumulative
Total Running total Cumulative
1 1,631 1,631 73.2% 1,631 1,631 26.6%
2–10 502 2,133 95.7% 1,909 3,540 57.8%
11–20 50 2,183 98.0% 722 4,262 69.6%
21–50 37 2,220 99.6% 1,060 5,322 86.9%
51–100 6 2,226 99.9% 415 5,737 93.7%
100+ 2 2,228 100.0% 385 6,122 100.0%
Total 2,228 6,122
Source: elaborated from FishSpektrum (2018).
8 Dalian Lian Run Overseas Oceanic Pelagic Fisheries Co. Ltd – 大连连润远洋渔业有限公司 registered in Las Palmas, Spain.
9 Based on ‘The Council conclusions on the revised EU list of non-cooperative jurisdictions for tax purposes’, Council of
the European Union, 2020 (
in the Krakken® database. The Jinghai Group’s
website mentions several other subsidiaries,
including Shandong Shawodao Fishery
Co.Ltd and Shandong Haiyu Ocean shery
Co.Ltd, for which we have no additional data
4.4.2 International ownership and operation
of China’s DWF vessels
Krakken® lists 840 vessels owned and/or operated
by 258 rms registered outside China. In Ghana, for
example, 48 non-Chinese rms owned or operated
142 Chinese DWF vessels, while in Mauritania 23
companies owned or operated 122 Chinese DWF
vessels. There are several plausible reasons why
owners may choose to register ownership outside
China and use non-Chinese operating rms. As
mentioned in Section 4.3, countries such as Ghana
reserve shing rights in their EEZ to national
rms; re-registering ownership of a vessel is one
way to circumvent these regulations. As another
example, we identied 26 vessels agged by China,
but with registered ownership in Spain. Of these,
24 are operated by rms registered in Guinea and
the remaining two by the same Spanish company,8
perhaps to access EU shing rights in Guinea’s EEZ.
Another reason for international registration
is to take advantage of preferential tax regimes.9
We found 41 vessels with owners or operators
registered in countries commonly regarded as tax
havens, including Fiji (21 vessels), Panama (9),
Vanuatu (6 vessels), Seychelles (2), Trinidad and
Tobago (2) and Samoa (1).
In some countries, Chinese DWF vessels
are owned by different companies registered
at the same street address or post-ofce (PO)
box. For example, Krakken® contains details
of: two companies owning or operating 258
vessels registered at the same Beijing address;
two companies owning or operating 81 vessels
registered at the same Cheng Shan (Shandong
province) address; two companies owning or
operating 52 vessels registered at the same
Shanghai address; and, in Fiji, ve companies
owning or operating 25 vessels registered at
Box 2 The Chinese National Fisheries
The CNFC was China’s original state-owned
DWF eet, which set sail in 1985 with
ve vessels. By 1999, private vessels made
up around 70% of the eet, and CNFC
owned 556 vessels (Mallory, 2013). With its
subsidiaries, CNFC remains a publicly listed
state company and China’s largest DWF
operation, with ofces in Spain, Morocco,
Guinea-Bissau, India, Yemen, Saudi Arabia,
Hong Kong and Australia (FIS, 2019a).
CNFC vessels catch tuna in the western
central Pacic, squid in the southeast Atlantic
(Harkell,2019) and krill in the Antarctic (Liu
and Brooks, 2018). Of the 257 CNFC DWF
vessels we could identify in Krakken®, 192 are
agged to China, with the rest in Senegal (31),
Mozambique (12), Mauritania (9), unknown
(7), Belize (2) and 1 each in Comoros,
Morocco, Panama and St Kitts and Nevis.
Box 3 Poly Group Corp.
Of the vessels in our sample, 128 are owned
directly by PGC – a large corporation with
wide-ranging interests across different sectors
of China’s economy, including defence
manufacturing, real estate and engineering.
PGC has been described as a commercial
arm of the Chinese People’s Liberation Army
(Welker,1997; Bickford, 1999; Busch,2019).
The corporation encompasses a wide network
of subsidiaries and afliates, the structures of
which are difcult to establish. In 2010, PGC
signed an agreement with Mauritania granting
access for 50 vessels to Mauritanian marine
resources for 25 years in exchange for $100
million of investment (Transparent Sea, 2012).
Of the 128 PGC vessels in our sample, 24 were
agged in Mauritania.
the same PO box. It is not clear what the legal
relationships between these companies may
be, if any; the address may be that of a lawyer
or shipping agent acting on behalf of multiple
companies. Several of these rms operate vessels
owned by the others, further suggesting that actual
distinctions between them may be blurred.
There are legitimate reasons for registering
businesses in tax havens, and it is not unusual
to register vessels in ag-of-convenience nations
(Section 4.3). As a package, however, registering
ownership in a tax haven that is also a ag of
convenience offers the possibility of enabling the
laundering of prots from illegal shing (Blaha,
2018) and of hiding wealth from legal operations
(Alstadsæter et al., 2018). Krakken® identies
22 Chinese DWF vessels agged to nations
of convenience and with owners or operators
registered in tax havens (15 companies). Of these,
eight vessels agged in Panama are owned by
companies registered in Panama, and four vessels
agged in Vanuatu are owned by companies
registered in Vanuatu. The others are all owned
in one country and agged in another.
A lack of transparency, labyrinthine corporate
structures, and the complexity of a vessel’s identity
– in terms of ag state, operators and registered
owners – can make it extremely challenging to
identify who ultimately owns and benets from
vessels involved in DWF shing. Using ags of
convenience and shell companies in tax havens
offers further opportunities for obscurity to those
who might want it. While there can be legitimate
reasons for engaging in these practices, they also
shelter those engaged in transnational criminal
activity, such as IUUshing.
The proliferation of SMEs has already been
recognised as a challenge to the Government of
China’s capability to control the Chinese DWF
eet effectively (Mallory, 2013). Our ndings
suggest that authorities can make signicant
impact by initially focusing efforts on a relatively
small number of very large rms and their
subsidiaries that control a large number of vessels,
their agents, and the sheries organisations where
they work. That the largest companies are also
state owned provides an opportunity for the
authorities to demonstrate the Government of
China’s commitment to setting standards and
combatting IUU in the DWF eet. Investigating
the ultimate beneciaries of vessels owned by
companies registered in tax havens may also be of
interest to the Chinese authorities.
4.5 At least 183 vessels in
China’s DWF eet are suspected of
involvement in IUU shing
Krakken® lists 183 Chinese DWF vessels in
connection with IUU shing activities. This
includes vessels appearing in public IUU
registries, reports on suspected IUU vessels,
and records of convictions for IUU shing,
including Macfadyen et al. (2019), the
Environmental Justice Foundation (EJF 2018a;
2018b), Sea Shepherd (2017) and Greenpeace
This does not imply that other Chinese DWF
vessels we have identied are not involved in
IUU activities. The involvement of China’s
DWF eet with rule-breaking is undoubtedly
more extensive. An investigation in Ghana, for
example, found dozens of Chinese DWF vessels
not listed in Krakken® engaged in IUU shing
(EJF, 2018a). However, Krakken® has records of
just four Ghanaian-agged Chinese DWF vessels
suspected of involvement in IUU shing. This
gap implies that 183 is likely to be a signicant
under-representation the total number of Chinese
DWF vessels involved in IUU shing.
Of the 183 IUU Chinese DWF vessels
identied in Krakken®, 89 are long-liners, and
58 are trawlers. This type distribution contrasts
with Krakken’s® baseline data for long-liners
and trawlers in Chinese DWF eet, where 38%
are trawlers and 20.7% are long-liners. This
may reect more effective IUU listing processes
among tuna RFMOs. The IUU list also contains
17 reefers, nine seiners, four squid-jiggers, three
support vessels, one carrier, one multipurpose
vessel and one pole-and-line vessel.
Compared to the baseline for China’s DWF
eet, a relatively large proportion of these vessels
are agged overseas (100 vessels, 54.6%), to
18 non-Chinese nations. The most frequent
non-Chinese ag nations are Fiji (40vessels)
and Senegal (13 vessels) (Table 6). Flag-of-
convenience nations account for 24 vessels,10
with Panama (8) and St Vincent and the
Grenadines (7) the mostcommon.
There are 50 vessels owned by companies
registered in recognised tax havens, with 40
in Fiji, eight in Panama and two in Vanuatu.
This may imply that many of these vessels are
engaging in IUU opportunistically, and that – at
least in terms of IUU activities – reagging and
foreign registration of companies is related
more to proximity of and access to resources
than to permissive standards and enforcement
of the agging state. The high proportion of
vessels registered in Fiji may well represent an
10 Panama (8), St Vincent and the Grenadines (7), Honduras and Vanuatu (2 each), Belize, Democratic People’s Republic of
Korea, Equatorial Guinea, Liberia and Marshall Islands (1 each).
above-average detection rate, rather than a unique
concentration of IUU activity.
By cross-referencing the lists of IUU vessels
with Krakken®s records on operators, several
companies emerge as repeat suspects and
offenders. Just 10 companies own 46% of the
suspect vessels. The CNFC owns and operates 15
vessels. The Dalian Lian Run Overseas Pelagic
Fisheries Co. owns 15 vessels operated by ve
different rms registered in Guinea. The Sunshine
Fisheries Co. operates seven vessels in Fiji, and
shares the same Fijian PO box number with three
companies that operate four further vessels owned
by Sunshine. The Zhonshui Ocean Shipping
Corp. owns eight, and Hangton Pacic, based in
Fiji, owns seven. Two other rms own 13 vessels
operated by ve rms registered inGuinea.
This implies that, to tackle large companies
that are repeat offenders, the Chinese authorities
may be able to focus their enforcement efforts
efciently. That CNFC is a state company
also presents an opportunity for the Chinese
authorities to lead by example.
However, monitoring foreign-agged Chinese-
owned vessels presents Chinese authorities with
a different challenge. When China is not the
ag state, China’s responsibility for these vessels
is moral rather than legal. Simply providing
information on vessels suspected of IUU shing
to developing-country governments is unlikely to
result in action. Even when aware of violations,
many nations in West Africa do not have the
equipment and personnel to enforce the law
effectively, and nd limited support from
sheries powers to upgrade enforcement capacity
(Daniels, 2019).
The Chinese authorities’ ability to monitor and
enforce foreign-agged Chinese vessels is limited,
as this may constitute interfering with ag-state
operations. However, where Chinese agencies
have no authority to inspect Chinese vessels ying
foreign ags in foreign waters, there are options
for China to support local enforcement through
technical assistance and capacity-building.
Table 6 Suspected illegal, unreported and unregulated
shing vessels per country ag
Flag Number
China 83
Fiji 40
Senegal 13
Panama 8
Kiribati 8
St Vincent and the Grenadines 7
Sierra Leone 4
Ghana 4
Papua New Guinea 3
Vanuatu 2
Honduras 2
Russian Federation 2
Belize 1
Equatorial Guinea 1
Liberia 1
Marshall Islands 1
Democratic People’s Republic of Korea 1
Philippines 1
Marshall Islands 1
Source: elaborated from FishSpektrum (2018).
5 Analysis: development
5.1 The scale, scope and impact of
China’s DWF eet and activities
Our results suggest that the scale, scope and
impact of China’s DWF activities are signicantly
larger than has been previously understood. At
16,966 vessels, we estimate that the Chinese
DWF eet is 5–8 times larger than previous
studies suggest. The Chinese government has
not revealed the size and composition of its
DWF eet but it did, in 2017, announce plans
to restrict the size of this eet to 3,000 vessels
by 2020. This stated ambition suggests that the
government recognises gures that are similar to
those in previous studies.
As discussed in Section 4.2, one possible
reason for such a large discrepancy in DWF eet
numbers may be that China does not consider
shing activity outside its EEZ but within disputed
areas of the Yellow, South and East China Seas as
DWF shing (Zhang, 2015: 8). If so, our ndings
suggest that researchers using data from the
government to analyse China’s DWF eet should
treat that data with additional caution.
Although we have no evidence on catch data,
our ndings clearly imply that China’s DWF eet
is exerting greater pressure on global sh stocks
than is currently recognised. The greenhouse
gas emissions and other adverse environmental
impacts of China’s DWF eet activities – such as
levels of waste, oil spills and pollution – are also
likely to be higher than currently understood.
Recent research has shown that China subsidises
shing through tax exemptions, particularly on
fuel, to the value of $16.5 billion per year, or
47% of total global shing subsidies (Arthur
et al., 2019). Our ndings suggest the extent
to which these incentives have enabled DWF
operations. Our ndings also indicate that a
large proportion of these vessels are active in the
Northwest Pacic region, and that the Southeast
Pacic and Southwest Atlantic are regions with
a high intensity of shing activity, where China’s
DWF eet may be having the most signicant
environmental impacts.
The relatively high proportion of trawlers
in several of our subsamples is another cause
for concern, given the high level of ecological
damage associated with bottom-trawling.
Indeed, China has announced plans to restrict
the production of new trawlers and increase
regulation of trawling within its EEZ (Zhang,
2015; Jiang et al., 2018). YetChina’s DWF
eet contains an unusually high proportion of
trawlers. For example, of the 518 Chinese DWF
vessels agged in African countries, 82% are
trawlers (Section 4.3). This implies a signicant
export of ecological risk to developing-country
waters, despite increasing regulation and
restrictions on trawling in countries where these
vessels are registered, including Ghana and
Mauritania (Republic of Ghana, 2002; Tavares,
2003; McConnaughey et al., 2019). Box 4 gives
more information on the situation in Ghana.
In recent years, the Government of China
has become more sensitive to national and
international debates about environmental issues,
and mounting domestic concerns over food
safety (Godfrey, 2019a). In particular, China has
become more sensitive to accusations that it is
contributing to the collapse of global sh stocks,
and has acknowledged the need to restrict the
size and operations of the DWF eet.
The 13th Five-Year Plan for National Ocean
Fisheries Development (MARA, 2017) made
commitments to improve regulation of the
DWF eet. Alongside measures to encourage
consolidation and streamlining of eet
ownership, the plan committed to tackling IUU
shing by establishing a blacklist, improving
monitoring, increasing inspections on the high
seas, and implementing the PSMA. Other
commitments include requiring DWF vessels to
register with authorities, reviewing regulations
governing overseas shing, and cutting fuel
subsidies underpinning DWF operations by 60%
(Jacobs, 2017; Godfrey, 2019b).
In February 2018, a Ministerial Circular
reported that 264 vessels from 78 ‘offshore
shing enterprises’ had been punished for
Box 4 China’s distant-water shing in Ghana
With 137 ships, Ghana has the largest registry of Chinese DWF vessels outside China; 121 of
these are trawlers. More than a quarter of those on our list of Chinese DWF vessels that are
agged to African countries y the Ghanaian ag. Marine resources are important to livelihoods
and food security in Ghana, and over two million people depend directly or indirectly on marine
sheries for income and employment (FAO, 2016b). However, the country’s rich shing grounds
have come under increasing pressure from industrial shing, particularly from DWF vessels from
China and elsewhere. The incomes of local artisanal shers have fallen by around 40% since the
turn of the century, reecting greater competition with industrial vessels for increasingly scarce
resources (Republic of Ghana, 2016).
In 2014, a total of 107 industrial trawlers were reported to be operating in Ghanaian waters
(EJF, 2018a). Some experts regarded this as well above pressure the shery could sustain, and
industrial shing was directly linked to overshing of Ghanaian waters where key species like
sardinella, a crucial source of protein for people living in coastal communities, are on the brink
of collapse (Lazar et al., 2018).
Ghana has taken steps to regulate industrial shing, and to ensure that it returns more benet
to Ghana’s economy. Ghana’s Fisheries Act of 2002 limits shing licences for semi-industrial and
industrial shing vessels to those ying a Ghanaian ag. Licences – with the exception of those
for tuna vessels – must also be entirely owned by Ghanaian companies (Republic of Ghana,
2002). Ghana’s 2015–2019 National Fisheries Management Plan also set out to reduce shing
days for the industrial trawl eet by 50% by 2018 (Republic of Ghana, 2015).
A 2018 report by the Environmental Justice Foundation alleges that Chinese DWF rms use
Ghanaian ‘front companies’ to circumvent these regulations. Registering Ghanaian subsidiaries
and working with Ghanaian operations rms, Chinese businesses import their vessels and secure
licences. However, the vessels remain ‘almost exclusively’ operated by Chinese rms (EJF, 2018a).
For example, the EFJ report concludes that the Chinese company Rongcheng Marine Fishery
Co. Ltd (RCMF) operates 15 Ghanaian-agged trawlers (EJF, 2018a). Krakken® lists these
vessels and 10 further Ghanaian-agged RCMF-owed ships. These are the Lu Rong Yuan Yu
219, 926, 927, 928, 929, 956, 959, 981, 982 and 988. Collectively, these 25 vessels represent
almost a fth of all the Ghanaian-agged Chinese DWF vessels we have identied.
The 137 vessels we have identied as Ghanaian-agged Chinese DWF vessels support the
EJF’s claim. All of these vessels were constructed in China, previously agged in China, and/or
have Chinese names such as Dalian, Guo Jin, Lian Run, and Zhong Yuan Yu. Most of the vessels
we identify are both owned and operated by Ghanaian-registered rms. Five vessels appear to
be in breach of the 2002 Fisheries Act: four trawlers (Zhong Lu Yu 1003 and 1004, and Lian
Run 29 and 30) are owned by Chinese rms, two of which are operated by Ghanaian rms, and
the fth (Lian Run 14) is a trawler owned and operated by a Spanish company. Two further
Chinese-owned and operated vessels are listed as pole-and-line shers rather than trawlers, and
may well be hunting tuna within the rules of the 2002 Fisheries Act.
violations in 2017, and that 15 company ofcials
and sheries employees had been added to a
blacklist (MARA, 2018). Punishments included
loss of a year’s fuel subsidies, and suspension
of shing licences and enterprise qualications.
Included on the list were vessels found guilty
of: illegal sheries transshipments at sea, using
illegal gear, illegal operations in foreign waters,
shing in protected areas, misreporting catches,
and health and safety violations. Among others,
the Dalian Lian Run Ocean Fishery Co. Ltd.’s
DWF certicate – for an enterprise with 28
vessels recorded in Krakken® – was revoked for
IUU violations in Ghana (see Box 4) after being
reported by Greenpeace (Greenpeace, 2018).
A revised Fisheries Law regulating China’s
shing industry is also expected to come into
force later in 2020. This would increase penalties
for IUU shing, restrict reagging of vessels,
require registration of port movements and
develop a blacklist system (Godfrey, 2019b;
Chun, 2020). Also, the central government is
expected to introduce measures to strengthen
monitoring of China’s DWF eet, with
punishments for any vessel that removes or turns
off its vessel-monitoring system (Chun, 2020).
However, meeting these commitments is
likely to be a challenge, requiring signicant
institutional development and reform to
implement policies and enforce them effectively
(Chun, 2020). It is also not clear whether the
efforts reported in the 2018 Circular have
persisted; we found no similar reports of IUU
enforcement during 2018 or 2019. According to
Godfrey (2019a), most central government action
to date has concentrated on tackling illegal
aquaculture ponds and shing within China,
rather than tackling the DWF eet.
Even achieving the ambitious goals for the
DWF eet may not go far enough. Reducing
fuel subsidies by 60% would still leave China
with the highest level of harmful shing
subsidies in the world (Arthur et al., 2019).
The Environmental Justice Foundation has
challenged the Government of China to improve
transparency of its DWF eet operations,
especially by making data more robust and
accessible (EJF, 2018a). DWF sheries and
business interests have considerable political and
economic weight in China; our ndings suggest
that the scale of these interests may have been
underestimated by previous studies.
The Government of China itself may not
be fully aware of the scale of the governance
challenge it faces. Incomplete data on a large,
complex and fragmented sheries sector makes
monitoring and enforcement a challenge
for all parties. There are additional policy
challenges posed by the different interest
groups in the shing sector. One challenge is
the proliferation of many small owning and
operating companies (approximately 75% of all
companies). Even if these are ultimately owned
by larger conglomerates, effectively regulating
a large number of small companies with
limited capacity presents certain logistical and
By contrast, our evidence suggests that a large
number – perhaps even the majority – of DWF
vessels are owned by a relatively small number
of companies, with state-owned corporations
chief among them. Focusing enforcement efforts
on these companies may be an effective means
of reaching a large proportion of the eet. The
revocation of the DWF licence of the Dalian
Lian Run Ocean Fishery Co. Ltd in 2018 shows
that the Chinese authorities have been willing
to take such measures in the past. Focusing on
IUU activities by larger public and semi-public
enterprises is an opportunity for regulatory
authorities to demonstrate the state’s willingness
to lead by example.
5.2 China’s DWF activities in a
development context
Our ndings suggest that the negative impacts
of China’s DWF eet on developing countries
is more signicant than has been realised to
date. These concerns arise partly from reports
about the arrival of large numbers of industrial
vessels that compete with local shers, asset-
strip natural resource bases and undermine
local environmental security, food security and
livelihoods (Clover, 2016; Daniels, 2018).
Many of the agreements governing Chinese
DWF in developing countries’ waters are
framed in terms of economic development.
Chinese vessels gain access to marine resources
in exchange for inward investment, industrial
development and the generation of exports for
the host country (Dahir, 2018; Mallory, 2012;
Transparent Sea, 2012). However, in practice
these deals are often poorly structured for the
host nation. Deals may see more catch licensed
than stocks can stand, local shers lose income
and local governments can lose tax revenue
if landings and catches are not appropriately
measured (Clover, 2016).
Based on the review of several studies, Mallory
concluded in 2012 concerning China that
‘sheries access agreements, on the whole, have
led to unsustainable use of sheries resources
and have negatively impacted the socioeconomic
development of host countries’ (Mallory, 2012).
A case study in Mauritania, for example, found
that, although a shing deal with PGC offered to
create 2,463 jobs for Mauritanians, job losses in
traditional shing totalled 13,000 during 2014
alone, at least partly caused by competition from
foreign industrial vessels (Sherpa, 2014).
Our ndings suggest that Chinese DWF
activities may have greater impacts in developing
countries than is currently understood. The
number of vessels active in the Northwest Pacic
region underlines the conicts reported by shers
from Viet Nam, the Philippines and Cambodia
(Fache and Pauwels, 2016; Meick et al., 2018;
Wesley-Smith and Potter, 2010). Widespread
trawling behaviour, particularly off Africa, and
intense squid-jigging off the coasts of South
America all imply competition with shers from
other countries.
5.3 IUU shing and its governance
Our ndings provide new evidence on the scale
of Chinese interests in IUU shing activities.
In total, we identied 183 Chinese vessels
in Krakken® that were either suspected or
conrmed to be involved with IUU shing.
To give some context, the largest list of global
IUU vessels – aggregated from RFMOs and
INTERPOL – lists a total of 311 vessels (Trygg
Mat Tracking, 2020). China’s role in IUU shing
is, therefore, clearly signicant. The IUU vessels
we have identied include vessels owned by some
11 The vessels North Ocean, West Ocean, Shun Chang No. 2 and Soleil Nos. 7, 8, 9, 10, 11, 12, 51, 61, 65, 66, 67 and 68.
of China’s largest, state-owned DWF companies,
as well as 104 vessels agged outside China.
Chinese engagement in IUU activities is
most probably more extensive, and Krakken®’s
dataset on IUU shing is not exhaustive. Several
of the companies covered in our analysis have
vessels allegedly engaging in IUU activities not
recorded in Krakken®. For instance, in 2016,
the Argentinian coastguard sank a vessel owned
by the CNFC, for allegedly shing illegally in
its territorial waters (CNN, 2016). At least 15
other vessels from this corporation are listed
in Krakken® as suspected or convicted of IUU
practices in different episodes.11 The scale and
extensive global operations of China’s DWF eet
poses a signicant challenge to those engaged in
combatting IUU shing.
Our identication of 927 Chinese-owned,
foreign-agged vessels highlights a further
obstacle for enforcement. Under international
law, China is not responsible for the standards
under which these vessels operate. Nor, in
principle, can Chinese authorities inspect
foreign-agged vessels in foreign waters without
the cooperation of the host nation, even if
those vessels are ultimately owned by Chinese
businesses. Yet many developing coastal states
lack the equipment and other resources required
for investigation and enforcement at sea. As
a result, many of these vessels are able to
operate without close surveillance. Expanding
its activities in sheries technical cooperation
to include capacity-building for enforcement
would demonstrate China’s commitment
to the good governance of its corporations’
Other advanced economies can also help to
improve maritime law-enforcement capacity in
coastal developing states and ag states, and
to improve enforcement cooperation between
ag, coastal and port states. For example,
EU regulations require sh imports to be
accompanied by-catch certicates issued by the
ag state.
However, it is not only foreign-agged vessels
that are at fault. Almost half the 183 IUU
suspects we identied were agged in China.
As we have already discussed, the Chinese
authorities face considerable challenges with
enforcing – and gaining compliance with –
existing policies and regulations. China is
ranked as the worst-performing nation on the
IUU Fishing Index, which looks at coastal, ag
and port state responsibilities, among other
indicators (Macfadyen et al., 2019). The size and
extent of the Chinese eet’s activities around the
world make this task even more daunting for
Some companies, including the CNFC and
PGC, appear to be repeat IUU offenders. Large-
scale, repeat offenders are obvious targets for the
focus of enforcement agencies. As such offenders
are also often either state-owned or linked to
the state, focusing on them also provides the
authorities with the opportunity to establish
their credibility as enforcement agencies – and to
demonstrate the depth of China’s commitment
and leadership on this issue. China can support
international enforcement efforts by improving
the transparency of its registry, particularly by
listing the ultimate owners of vessels rather than
just the name of the immediate company (which
is often a subsidiary).
This is an issue for action by not only Chinese
and developing-country authorities. Krakken®
records show that 32 of the vessels we have
identied as IUU vessels remain registered
with the European Commission’s Directorate
General for Health and Consumer Protection
(DG SANCO), despite their involvement with
IUU shing. This means that they are allowed
to continue exporting to the EU. Of these 32
vessels, 15 belong to Dalian Lian Run Overseas
Oceanic Pelagic Fisheries Co. Ltd., 11 to CNFC
subsidiary Zhong Yu Global Seafood Corps and
two to Ocean Harvest (Fiji) Ltd. The DG SANCO
should be more proactive about de-listing suspect
vessels. This also demonstrates the generally
poor coordination between IUU registries and
investigations and the bodies responsible for
maintaining standards andenforcement.
6 Conclusions and key
policy recommendations
6.1 Conclusions
The cultural, economic and political importance
of the sheries sector in China, booming
economic growth and demand for sh protein,
and the strategic policy of ‘going out’ has created
the conditions for an extraordinary boom in
China’s DWF activities. The eet has grown from
13 vessels in the mid-1980s to as many as 16,966
vessels today, operating all over the world.
The number of SMEs engaged in DWF has
proliferated, and the structures and tax affairs
of large corporate eets are now managed with
much greater sophistication.
This boom has beneted China, Chinese
consumers and Chinese business. However, the
majority of social, environmental and economic
costs have been borne by developing coastal states,
who have not shared equally in thebenets.
The rapid growth of China’s DWF has not
been matched by capacity of the Chinese state
to govern its operations. China has not acceded
to a range of pertinent international agreements,
and does not require high standards from its
registered vessels. As a consequence, Chinese
DWF companies are left to police themselves
and negotiate access to the sheries resources
of developing coastal states. This contrasts with
the EU’s policy of reducing its shing eet and
exerting greater control over its global operations.
The Chinese DWF vessels are often shielded from
public scrutiny, and frequently take advantage of
weak regulatory and governance structures in the
regions where they operate.
The Chinese DWF is not solely responsible
for the global sheries crisis. Other eets are
also responsible for overshing, and many
governments in developing countries are either
unable or unwilling to monitor their waters.
Collectively, the international community has
failed to establish global, centralised databases of
DWF or IUU vessels. IUU shing has still not been
declared as a transnational crime.
However, China is the world’s largest exporter
and consumer of shing products, and has the
world’s largest DWF eet. Its authorities have an
interest in leading the ght against overshing and
IUU shing globally, and in managing effectively
the operations of its massive DWF eet. This is
not yet happening. This inaction has led some
to criticise the Government of China’s efforts to
regulate shing in domestic waters as playing
the role of ‘an environmentalist at home while
plundering abroad’ (Godfrey,2018;2019a).
The Chinese government may be increasingly
sensitive to international concerns about
the expansion and behaviour of its DWF
eet. In 2017, it announced plans to restrict
the number of DWF vessels to 3,000 by
the year 2020. An announced review of the
Administration of Offshore Fisheries, which
regulates overseas shing, is expected to set
higher nes and constrain the reagging of
However, the central government faces
opposition from provinces reluctant to lose the
economic boost provided by the DWF eet.
Both Fujian and Shandong, for example, have
ambitiously expanded their DWF eets over the
last ve years (Kang, 2016). Proposals are afoot
to devolve responsibility for sheries-sector
development to regional governments. This
would make the central government’s intention
of reducing the number of vessels and addressing
the drivers of expansion – including cutting
subsidies – much more challenging (Kang, 2016).
Our research ndings suggest that the
Government of China’s goal in limiting the
DWF sector to just 3,000 vessels and exerting
tighter control over its operations will be
even more difcult to achieve than has been
previously recognised. The scale of the DWF
eet, its complex global operations and business
structures, and the lack of coherent, transparent
data, are all major challenges Achieving that goal
will require systematic reform of the DWF sector
and its governing institutions.
6.2 Key policy recommendations
6.2.1 Government of China
Our ndings suggest that the scale of the task
China faces in meeting its goal to reduce its DWF
eet to 3,000 vessels is greater than previously
realised. Our ndings also concur with those of
other researchers, who have identied signicant
gaps in China’s capacity for governing its DWF.
China can take the following signicant steps to
demonstrate global leadership on the governance
of DWF, sustainability of global sheries and
combatting IUU:
requiring all DWF vessels to enter a
centralised, publicly and internationally
accessible registry, including details on
holding companies as well as immediate
adopting higher standards as a ag state
with obligations for its DWF eet, including
signing, ratifying and implementing the
PSMA, and joining all appropriate RFMOs
and enforcing compliance with their
targeting monitoring, compliance and
enforcement efforts on larger, particularly
state-owned, companies with the most
extensive DWF operations;
strengthening bilateral cooperation and
capacity-building for sheries enforcement in
coastal developing states where the Chinese
DWF is active;
enforcing regulations on bottom-trawling
within China’s EEZ and in waters claimed
by China in the Yellow, South and East
introducing disincentives for bottom-trawling
on all Chinese-agged vessels.
6.2.2 Coastal developing-country states
Coastal developing states can support global
efforts to combat IUU shing and enhance the
governance of DWF eets by:
enforcing existing regulations on registration
and tackling ‘phony agging’ of DWF vessels;
making all international sheries agreements,
including those with China’s DWF, publicly
signing, ratifying and implementing the PSMA
designed to tackle global IUU shing.
6.2.3 International bodies and agencies
Global governance of DWF and IUU activities
needs more effective regional and global capacity.
RFMOs, national governments, multilateral
agencies and international development donors,
can contribute by:
monitoring, information-sharing and
prosecution of vessels and companies suspected
of IUU activities;
monitoring the presence and activities of
Chinese shing vessels outside China’s EEZ in
the Yellow, South and East China Seas;
taking proactive measures to de-list IUU vessels
and companies from import/export agreements;
supporting coastal developing states to combat
IUU activities in their own waters.
6.2.4 Researchers
Our ndings contribute to global work on the
scale, impacts and governance of China’s DWF.
Suggestions for future research include:
more research and analysis on China’s eet
to rene estimates of the scale, extent and
activities of China’s DWF;
research on the ecological, social and economic
impacts of China’s DWF eet, particularly in
the Northwest Pacic, Western Central Pacic,
Southeast Pacic and Southwest Atlantic
regions and in WestAfrica;
more research on the activities of transnational
companies engaged in DWF, particularly those
operating in ag-of-convenience states and tax
extending the methods employed in this paper
to the DWF eets of other nations, and over
longer timeframes.
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Annex 1 Methodology
Our study combines big data analytic techniques, ensemble algorithms and GIS. The methodology
involves both dynamic (tracking) data and static (descriptive) data.
A1.1 Dynamic data
We obtained dynamic data from Vulcan’s Skylight for 2017 and 2018 (24 months). Using the AIS data
from the vessels in our database, we were able to visualise the positions and behaviour of possible
shing vessels for those cases with sufcient data density. Using GIS software, we extracted metadata
from these time series to visualise the Chinese DWF vessels’ operations and movements, based on
their geographic location and other information, including the depth in which they operated (using
bathymetry maps) and geographic information of shing areas provided by the UN FAO.
A1.2 Static data
We obtained static data for this study from the November 2018 version of the FishSpektrum
Krakken® database (FishSpektrum, 2018). Krakken® is the world’s largest database on shing vessels,
using unique vessel identiers (UVIs). Krakken® accounts for some 1.5 million historical references
representing more than 800,000 vessels, offering more than 100 specic information items per vessel,
with historical data going back to 2009.
We performed 10 rounds of extractions to mine the data on every Chinese vessel in Krakken®
capable of DWF. Specically, we extracted data on vessels that: have been registered with a unique
IMO number; are registered with a RFMO; have an MMSI number shown to be active outside the
Chinese EEZ during 2018; have been inspected by the Chinese Fisheries Authorities in waters of a
country other than China; are registered as exported or impounded by the Chinese customs during
2018; or are registered with China’s Distant Water Fisheries Association and are therefore able to
operate abroad. Chinese names in Krakken® follow a coherent transcription system and have either a
unique IMO number or other identication numbers employed to identify them to avoid duplication.
We consider the Chinese DWF eet to be composed of the aggregate of groups formed by data
Extractions 1, 2, 3, 4 and 6 of the 10 rounds of data extractions from the Krakken® database.
TableA1 shows the inclusion criteria for all Chinese DWF vessels that we have used in all the
extractions. In the extractions, we consider that a current or previous Chinese name, operator or
benecial owner is an indication of Chinese interest. We have included all vessels in Krakken® that
show traces of a Chineseinterest.
To describe the Chinese DWF eet, we examined the vessels’: ags; IMO numbers; names; RFMOs
they are registered in; year and place of construction; primary and secondary gear (e.g. trawler net);
type of vessel (e.g. trawler); tonnage (e.g. ton gross tonnage); length, breadth and draught; engine
power; sh-hull volume; status (e.g. sold or renamed); owner and operator and their addresses;
AIS type (e.g. cargo, trawler); and IUU shing metadata. We disregarded the information on
vesselmonitoring system (VMS) and communication system aboard as not relevant or redundant. We
discarded any data marked as ‘unreliable’ in Krakken®.
A1.2.1 Extractions from the Krakken® database
The rst group includes all vessels agged to China with an IMO number. We assume that Chinese ship
owners and operators that register their vessels with a unique IMO number intend to operate them in
distant waters at some point. We discarded vessels with invalid IMO numbers (e.g. numbers that do not
include the three letters ‘IMO’ followed by seven digits, of which the latter is a validation number).12
The second group includes all vessels agged to China with no IMO number but registered with an
RFMO. We assume that Chinese ship owners and operators that register their vessels with an RFMO
intend to operate them outside China’s EEZ. However, some of them do not have an IMO number but
operate within an RFMO. It is not clear why these vessels are not registered with an IMO number, since
they can operate in the RFMO’s designated areas outside the Chinese EEZ.
The third group includes all vessels agged to China with no IMO number and registered in no
RFMO, but with an MMSI number, which have shown to be active outside the Chinese EEZ during
2018. We requested AIS positions of these vessels (amounting about 100,000 MMSI numbers) from
the Krakken® database to nd those operating outside Chinese waters in 2018.
The fourth group (gathering Extractions 4.1, 4.2 and 4.3) includes vessels with an IMO number but not
currently agged to China. We consider that these are industrial vessels because they are registered at IMO.
They are divided into those: built in China (4.1); not built in China and previously agged to China (4.2);
not built in China, never agged to China but related to Chinese interests (4.3). Vessels that include only
Chinese characters are not easily bought by non-Chinese companies, according to sources from the industry.
The fth group consists of non-Chinese reefers or large processing and sh-cargo vessels for
validation purposes. These vessels are not part of the Chinese DWF eet.
The sixth group (gathering Extractions 6.1, 6.2, 6.3 and 6.4) includes vessels without an IMO
number, which are not part of any of the previous extraction groups. This group includes vessels: never
agged to China but showing Chinese interests (6.1); agged to China and inspected by the Chinese
Fisheries Authorities (CFAs) in waters of a country other than China (6.2); agged to China and
12 The reliability of an IMO number can be conrmed using itscheck digit,which is the rightmost digit. This is done ‘by
multiplying each of the leftmost six digits by a factor corresponding to their position from right to left, and adding those
products together; the rightmost digit of this sum is the check digit’ (Port Klang Net Technical Working Committee, 2019).
Table A1 Criteria for extractions from the Krakken® database
Criteria Total
Extraction Currently
flagged to
flagged to
1YES N/A YES N/A N/A N/A N /A N/A N/A N/A 2,076
2YES N/A NO YES N/A N/A N/A N/A N /A N/A 575
3YES N/A NO NO YES N/A N/A N/A N/A N /A 12,49 0
4.1 NO N /A YES N/A N/A YES N/A N /A N/A N/A 431
4.2 NO YES YES N/A N/A NO N/A N /A N/A N/A 92
5N/A N/A N/A N/A N /A N/A N /A N/A N/A N /A
6.1 NO N /A N/A N /A N/A N/A YES N/A N/A N/A 318
6.2 YES N/A N /A N/A N/A N /A N/A YES N/A N/A 379
6.3 YES N/A N /A N/A N /A N/A N/A N /A YES N/A 82
6.4 YES N/A N/A N/A N/A N/A N/A N /A N/A YES 437
Total 16,966
Notes: N/A, not applicable due to being outside the criteria for this extraction; CHN, China.
Source: elaboration on information from the Krakken® database.
registered as exported or impounded by the Chinese customs (CC) during 2018 (6.3); agged to China
and registered with China’s Distant Water Fisheries Association (known as CNDWF) (6.4).
We then ltered the vessels in each extraction according to their last known status in Krakken®.
We removed 177 vessels recorded as ‘laid-up, scrapped, lost, sunk or decommissioned’ and one vessel
recorded as a ‘cancelled order’. This left only the 16,966 vessels last recorded as ‘active’.
A1.2.2 Algorithmic methods
We initially applied several learning models with associated learning algorithms that analyse data for
classication and regression analysis. However, we decided that random decision forests are the most
appropriate method here. Random decision forests are an ensemble learning method using decision trees
to improve machine learning results by combining multiple models. Machine learning is an approach to
data analysis that automates the development of analytical models, using software to explore data and
identify patterns (Cukier,2014; Marr, 2018).
To create automatic models able to detect shing manoeuvres, we rst examined a random selection of
boats for each manoeuvre. Following the manoeuvre descriptions (detailed in Annex 2), the manoeuvres
were identied and labelled by a sheries expert. We used 500 models for each shing manoeuvre:
trawling, long-lining, squid-jigging and trap-setting. We used machine-learning approaches to examine
and classify patterns of shing behaviour.
We pre-processed data to avoid drawbacks that can arise during the early, training phase of modelling.
Overtting, for example, is the generation of a modelthat corresponds too closely or exactly to a
particular set of data, and may therefore fail to t additional data or predict future observations reliably.
Overtting can result in a model that learns about shing areas or shing schedules instead of the
manoeuvres themselves – predicting that every boat crossing through an area frequented by trawlers
is also a trawler, for example. The model could also wrongly learn that trawling manoeuvres are more
likely to happen following the north–south axis, if training examples perform every manoeuvre oriented
that way.
To avoid these drawbacks, our dataset had to be independent of position, time and orientation.
We transformed: position information into distance travelled between two consecutive points, date
information into time elapsed between consecutive points, and orientation information into change
of boat orientation between consecutive points.These transformations result in variables that contain
valuable information, from which we can infer what manoeuvre is being performed, while avoiding
After this preprocessing phase, we used labelled manoeuvres to train a random forest algorithm
composed of 500 decision trees for each specic manoeuvre. This resulted in a group of automatic
labellers that we later used to provide shing information for some of the studies in this report. To
determine whether one AIS data point belongs to a shing manoeuvre, we considered not only the
particular information of the point but also a window of previous and subsequent data points that varies
depending on the type of manoeuvre.
To validate thefunctional generalisation capabilitiesof the algorithm – that is, the opposite of
overtting – we tested the models with a selection of boats that were not involved in the training process.
Theensemblealgorithm and the preprocessing algorithms will be provided to authorities in developing
countries with limited monitoring and enforcement capabilities, and that are interested in understanding
the operations of foreign vessels in their waters.
Looking at the ship tracks on a map, a sheries expert identied whether each ship was in transit
(going straight from point A to B at a constant speed) or shing. If the ship was shing, the expert
determined whether it was trawling (dragging a conical net), long-lining (hauling a line with baited
hooks), purse-seining (creating a round net cage around the sh) or engaged in other types of
shing.Annex 2 describes these manoeuvres in more detail, and includes information on speed, duration
and depth for different shing manoeuvres.
Our model labels positions that are part of a shing manoeuvre with a condence percentage ranging
from 0 to 1. For this paper, we created a score to understand the Chinese DWF’s shing activity: each
time a vessel’s position is labelled as being part of a trawling, long-lining, squid-jigging or trap-setting
operation, with condence greater than or equal to 0.75, it scores 1 point. Scores are spread over time
in slots of one whole hour. Thus, a vessel’s score in a time slot tells us how many positions have been
labelled as being part of a particular shing technique in that slot.
Annex 2 Taxonomy of
operations at sea
13 A knot is a speed of 1 nautical mile per hour or 1.852 kilometres per hour.
This taxonomy is offered as a tool for further studies and policy-making. We used it in this study to
develop ensemble learning algorithms to identify how vessels operate and to identify common shing
manoeuvres. A vessel’s speed and pattern of movement can indicate its activity. Speed is especially
signicant, as most of the methods to discriminate between shing and non-shing motion depend
on the analysis of speed proles (Bez et al., 2011). This can be based on either statistical and data
approaches or expert knowledge. To increase accuracy, this study incorporates other indicators,
including: spatial–temporal movement patterns, bathymetric charts, on-board gear, identication of the
type of vessel and pictures of individualvessels.
A2.1 Trawling
Trawlinginvolves dragging a shing netthrough water. Trawlers range from small, undecked boats,
powered by outboard engines, to factory trawlers of up to 3,000 gross tonnage, with up to 8,000
horsepower engines (Pusceddu et al., 2014; FAO, 2018a). Trawling can involve one or more ships
working cooperatively, known as pair-trawling.
Speed: Trawling should happen at constant speeds of 1–7 knots, and usually 3–5 knots13 (FAO,
2018b; de Souza et al., 2016). This is to maintain vessel alignment in pair trawling. Speed depends on
the catch species: from 1.5–2 knots for shrimp and small bottom-dwelling species, to about 5 knots
for mid-sized pelagic sh (FAO, 2018b).
Depth: Efcient trawling takes place at a constant depth or pressure. This is why we used
bathymetric charts showing submerged terrain in this study, to analyse trawling operations. Bottom
trawlers typically work along a chasm, where there is high biodiversity because of temperature
differences, following sh banks and tracing courses that look straight and parallel (FigureA1).
Datacannot distinguish between bottom or mid-water trawling.
Duration: The duration of a tow depends on the outline of the sea bottom, the slope in the shing area
and the likely concentration of sh. It can last from 10–15 minutes to 10–12 hours, with around 3–5
hours most common (FAO, 2018b).
A2.2 Seine-shing
Seine-shing(or seine-haul shing) uses anetcalled a seine that dangles vertically in the water. The
bottom edge, or lead-line, is held down by weights and the top edge is buoyed by oats (FAO, 2018b;
Stündl, 2013).
Speed: Vessels involved in seine-shing show different speed patterns depending on the length of the
net, the diameter of the circle that the vessel draws, the species and the time taken to draw aring.
Duration: Half an hour for a school of about 100 metric tonnes of Bluen tuna, for example,
according to industry experts consulted for thisreport.
Depth: 200 to 300 metres.
Types: Seiners employ two main types of net:purse seinesandDanish seines. A Danish seine (or anchor
seine) is a conical net with two long wings with a bag where the sh collect. It is similar to a small trawl
net. A purse seine’s lead-line is held by purse rings hanging from the lower edge of the gear; a purse line
drawn through the rings gathers the net to contain the sh (FAO, 2018a). This is the most efcient gear for
catching large and small pelagic species that shoal, such as tuna.
The authors could not identify any purse-seining by the Chinese eet; only 7.3% of the Chinese DWF
eet are seiners.
A2.3 Long-lining
Long-lining vessels launch a series of long shing lines tted with hundreds or thousands of baited hooks
(FAO, 2018b; Stündl, 2013). The number of lines depends on the size of the ship, the number of crew
members and the kind of mechanisation and automation available on the ship. Long-lines can be left
drifting for pelagic shing or set on the bottom for bottom species, or maintained at a certain depth by
regularly spaced oats.
Speed: A constant 4–6 knots, depending on the crew (both setting and gathering the line).
Duration: When the last hook is in the water, the line is left hanging from a oating buoy, with a light, in
the water for some hours, while the vessel either drifts slowly together with the line or sets other lines nearby
(FAO, 2018b; Stündl,2013). The vessel then reverses along the line at a mostly constant speed, although this
can change depending on the catch and the crew. The whole operation can take up to a day but the median
set time estimated from one examination of 16 vessels was 6.5 hours (de Souza et al., 2016).
Length: Up to 100 kilometres (de Souza etal.,2016).
Mapping spatial–temporal movement patterns, as shown in Figure A2, is useful in comparing and
identifying long-lining. Long-lining typically presents as complex movements as vessels lay out multiple
lines and/or drift in currents, and reverse to recover lines.
A2.3.1 Chinese multipurpose vessels
These vessels combine long-lining with trawling. The Krakken® database describes 137 Chinese vessels as
multipurpose vessels.
Figure A2 Long-lining by the Chinese DWF eet
Source: elaborated from FishSpektrum (2018).
Figure A1 Trawling by the Chinese DWF eet
Source: elaborated from FishSpektrum (2018).
The Chinese multipurpose vessel is a new type, derived from the traditional dry cargo ship. It retains
the characteristics of traditional dry cargo ships, with low speed and good manoeuvrability, but has
improved layout to expand cargo adaptability and loading efciency (EWorldship,2016).14
A2.4 Squid-jigging
Squid-jigging involves a group of shhooks fastened together with radiating points for catching squid
(Bjarnason, 1992). Jigs of various types, makes and colour are attached to a hand-line at intervals
of 70 cm–90 cm. One line often holds as many as 8–12 jigs, and many more are used on automated
squid-reeling systems (Bjarnason 1992). Squid-jigging often takes place at night, with bright lights to
attract the squid, with groups of vessels. It requires little modication to general hand-line gear and
can be a seasonal activity to supplement existing hand-line operations or any other traditional shing
(Bjarnason, 1992). The FAO characterises squid-jigging as ‘pole and line (mechanised)’.
Speed: Engine off and drifting, as shown in Figure A3.
A2.5 Trap-setting
Traps are simple, passive shing gear that allow sh to enter and then make it hard for them to escape.
Some traps include chambers or pots that can be closed once the sh enter (Slack-Smith, 2001).
FigureA4 shows trap-setting, which typically involves vessels moving efciently around a grid to set
and recover traps.
14 Translated by the authors.
Figure A3 Squid-jigging by the Chinese DWF eet
Source: elaborated from FishSpektrum (2018).
Figure A4 Trap-setting by the Chinese DWF eet
Source: elaborated from FishSpektrum (2018).
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... And thirdly, China as a flag State does not hold legal entitlement to intervene in foreign coastal jurisdiction on operative matters, such as TAC, fishing gear, and onboard inspection at sea. Even if it intends to discharge certain "moral" accountability to the harvested area, nowadays 70% of the Chinese DWF fleet is composed of privately own vessels (Gutiérrez et al., 2020). Unlike stateowned enterprises' diligent execution of government policy, resource conservation is not an accepted priority of most profitdriven firms. ...
... However, like the EU, China was considered to have significantly underreported local catches to the FAO, including from both legal and illegal sources (Belhabib et al., 2015). A deficit in accountability to partner African countries triggered pervasive conflicts, legal violations, and even violence in distant waters where Chinese vessels operated from time to time (Li and Amer, 2015;Gutiérrez et al., 2020). The current input-based regulatory framework thus prompts us to explore innovative and effective countermeasures to assist in empowering China's fisheries management in the implementation phase afterward. ...
... Apart from technological and institutional breakthroughs, there is also the need to mainstream sustainability literacy in one of the world's biggest seafood markets. China's DWF expansion has generated worldwide concerns and alerts (Pauly et al., 2014;Gutiérrez et al., 2020). It comes with the imperative to ensure the transparency and legal credibility of the supply chain reaching numerous Chinese retailers and consumers. ...
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While the ecological impacts of fishing the waters beyond national jurisdiction (the “high seas”) have been widely studied, the economic rationale is more difficult to ascertain because of scarce data on the costs and revenues of the fleets that fish there. Newly compiled satellite data and machine learning now allow us to track individual fishing vessels on the high seas in near real time. These technological advances help us quantify high-seas fishing effort, costs, and benefits, and assess whether, where, and when high-seas fishing makes economic sense. We characterize the global high-seas fishing fleet and report the economic benefits of fishing the high seas globally, nationally, and at the scale of individual fleets. Our results suggest that fishing at the current scale is enabled by large government subsidies, without which as much as 54% of the present high-seas fishing grounds would be unprofitable at current fishing rates. The patterns of fishing profitability vary widely between countries, types of fishing, and distance to port. Deep-sea bottom trawling often produces net economic benefits only thanks to subsidies, and much fishing by the world’s largest fishing fleets would largely be unprofitable without subsidies and low labor costs. These results support recent calls for subsidy and fishery management reforms on the high seas.
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'Fisheries in the Pacific: The Challenges of Governance and Sustainability' is a multidisciplinary book, which examines various aspects of coastal and oceanic fisheries in Pacific waters. These interrelated fisheries sectors are critical for regional food security and also represent a reserve of food resources for the rest of the world. The introduction and eight chapters highlight that both these sectors raise major economic and ecological issues while revealing significant social changes, political asymmetries and alliances, geostrategic rationales, developments in legislation, customary dynamics, and conservation challenges. Through complementary approaches and interpretations of both quantitative and qualitative data, this book aims to contribute to a better understanding of the current situation of fisheries in the Pacific. It also responds to the compelling need to establish a constructive and ongoing dialogue on the matter between social scientists and environmental scientists, based in Europe and in the Pacific Islands, and between these experts and the various stakeholders and policy-making institutions involved in the Pacific region.
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A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.
The paper first briefly describes the negotiation process of Marine Protected Areas (MPAs) in the Southern Ocean. Then it examines China's changing position towards the establishment of a Ross Sea MPA, as proposed by the United States and New Zealand in the Commission for Conservation of Antarctic Marine Living Resources. Finally, the paper explores how China's position towards or against Southern Ocean MPAs implies China's future role in Antarctic governance.
Drawing on newly published macroeconomic statistics, this paper estimates the amount of household wealth owned by each country in offshore tax havens. The equivalent of 10% of world GDP is held in tax havens globally, but this average masks a great deal of heterogeneity-from a few percent of GDP in Scandinavia, to about 15% in Continental Europe, and 60% in Gulf countries and some Latin American economies. We use these estimates to construct revised series of top wealth shares in ten countries, which account for close to half of world GDP. Because offshore wealth is very concentrated at the top, accounting for it increases the top 0.01% wealth share substantially in Europe, even in countries that do not use tax havens extensively. It has considerable effects in Russia, where the vast majority of wealth at the top is held offshore. These results highlight the importance of looking beyond tax and survey data to study wealth accumulation among the very rich in a globalized world.