Estimating the Worldwide Extent of Illegal Fishing

Abstract

Illegal and unreported fishing contributes to overexploitation of fish stocks and is a hindrance to the recovery of fish populations and ecosystems. This study is the first to undertake a world-wide analysis of illegal and unreported fishing. Reviewing the situation in 54 countries and on the high seas, we estimate that lower and upper estimates of the total value of current illegal and unreported fishing losses worldwide are between 10bnand10 bn and 23.5 bn annually, representing between 11 and 26 million tonnes. Our data are of sufficient resolution to detect regional differences in the level and trend of illegal fishing over the last 20 years, and we can report a significant correlation between governance and the level of illegal fishing. Developing countries are most at risk from illegal fishing, with total estimated catches in West Africa being 40% higher than reported catches. Such levels of exploitation severely hamper the sustainable management of marine ecosystems. Although there have been some successes in reducing the level of illegal fishing in some areas, these developments are relatively recent and follow growing international focus on the problem. This paper provides the baseline against which successful action to curb illegal fishing can be judged.

Full text

Estimating the Worldwide Extent of Illegal Fishing
David J. Agnew
1
*, John Pearce
2
, Ganapathiraju Pramod
3
, Tom Peatman
2
, Reg Watson
3
, John R.
Beddington
1,4
, Tony J. Pitcher
3
1Division of Biology, Imperial College London, London, United Kingdom, 2MRAG Ltd, London, United Kingdom, 3Fisheries Centre, University of British Columbia,
Vancouver, British Columbia, Canada, 4United Kingdom Government Office for Science, London, United Kingdom
Abstract
Illegal and unreported fishing contributes to overexploitation of fish stocks and is a hindrance to the recovery of fish
populations and ecosystems. This study is the first to undertake a world-wide analysis of illegal and unreported fishing.
Reviewing the situation in 54 countries and on the high seas, we estimate that lower and upper estimates of the total value
of current illegal and unreported fishing losses worldwide are between $10 bn and $23.5 bn annually, representing
between 11 and 26 million tonnes. Our data are of sufficient resolution to detect regional differences in the level and trend
of illegal fishing over the last 20 years, and we can report a significant correlation between governance and the level of
illegal fishing. Developing countries are most at risk from illegal fishing, with total estimated catches in West Africa being
40% higher than reported catches. Such levels of exploitation severely hamper the sustainable management of marine
ecosystems. Although there have been some successes in reducing the level of illegal fishing in some areas, these
developments are relatively recent and follow growing international focus on the problem. This paper provides the baseline
against which successful action to curb illegal fishing can be judged.
Citation: Agnew DJ, Pearce J, Pramod G, Peatman T, Watson R, et al. (2009) Estimating the Worldwide Extent of Illegal Fishing. PLoS ONE 4(2): e4570. doi:10.1371/
journal.pone.0004570
Editor: Stuart A. Sandin, University of California San Diego, United States of America
Received December 4, 2008; Accepted January 15, 2009; Published February 25, 2009
Copyright: ß2009 Agnew et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the UK Department for Environment, Food and Rural Affairs and the UK Department for International Development. The
Sea Around Us project is supported by the Pew Charitable Trusts. The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: d.agnew@imperial.ac.uk
Introduction
It is widely accepted that there is a severe problem with future
global food security. Driven by substantial world population
growth, demand for fish protein continues to increase, but a large
number of the world’s fish stocks are currently depleted and
therefore not capable of producing their maximum sustainable
yield [1]. Illegal and unreported fishing (in this paper taken to
include illegal and unreported catches but to exclude discards and
artisanal unregulated catches) prejudices the managed recovery of
the world’s oceans from severe fish depletions [2–4]. It is reported
to lead to a loss of many billions of dollars of annual economic
benefits [5,6], creates significant environmental damage through
the use of unsustainable fishing practices [7] and has wider
consequences for food supply [8].
Estimating the level of illegal fishing is, by its very nature,
extremely difficult and has not previously been attempted on a
global scale. Fishing vessels, especially those fishing in high seas
waters and under third party access agreements to EEZ waters
(Exclusive Economic Zones, which can extend up to 200 nm from
the coast), are highly mobile. Although there are a number of
studies of the level of IUU (Illegal, Unreported and Unregulated)
fishing in individual fisheries (both EEZs and high seas) [3,9–16],
only two studies have attempted to estimate the impacts of IUU
over a whole region [5,6]. In this paper we set out, for the first
time, a detailed study which arrives at global estimates of current
and historical illegal and unreported catches.
Results
The term ‘‘Illegal, Unreported and Unregulated’’ (IUU) fishing
can cover a wide range of issues [see discussion in 13,17–19]. We
confined our analysis to illegal and unreported catches (IU), namely
those taken within an EEZ which are both illegal and retained, and
which are usually unreported, and all unreported catches taken in
high seas waters subject to a Regional Fisheries Management
Organisation’s (RFMO) jurisdiction. We excluded discards and
unregulated artisanal catches, which will be analysed in a future
publication. With illegal and unreported catches rents are captured
by illegal fishermen but lost to legitimate fishermen and manage-
ment authorities. Note that the word ‘‘landings’’ is often used to
distinguish catches that are retained from catches that are discarded.
For simplicity, and to avoid confusion with the suggestion that fish
are necessarily landed in the country in whose waters they are
caught, we use the word catches here to mean catches that are
retained and discards to mean catches that are discarded.
In total, 54 EEZs and 15 high seas regions were analysed,
providing an estimate of global illegal and unreported catch for
292 case study fisheries which comprise 46% of the reported total
world marine fish catch. All data sources were combined to
provide upper and lower estimates of IU for each fishery. The total
catch of case study and non-case study fish from the EEZs and
high seas regions analysed comprises 75% of global catch.
There were significant differences in the level of illegal and
unreported catch and the trends in those catches between regions.
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The level of IU was highest in the Eastern Central Atlantic (Area
34) and lowest in the Southwest Pacific (Area 81) (Table 1). Since
the 1990s we estimate that the level of IU has declined in 11 areas
and increased in 5 (Table 2). We estimate that the overall loss from
our studied fisheries is 13–31% (lower and upper estimates) with a
mean of 18%, and that this was worth some $5-11 bn in 2003.
Regional trends reveal issues related to the quality of fishery
management. In the Northeast Atlantic, reasonable estimates of
the level of illegal fishing are available from various reports and
assessments conducted by the International Council for the
Exploration of the Sea, ICES [20]. These indicate that as pressure
on stocks increased following the end of the ‘gadoid outburst’
(exceptional recruitment from cod family fish between the mid
1970s to late 1980s) the level of illegal and unreported catch
increased, and has only recently improved. The decline in IU that
we show in the Western Central Atlantic is due to a reduction in
Table 1. Summary of regional estimates of illegal fishing, averaged over 2000–2003.
Region
Reported catch
of case study
species
Catch of case study
species as a percentage
of total regional catch
Lower
estimate of
illegal catch (t)
Upper
estimate of
illegal catch (t)
Lower
estimate of
value (US$m)
Upper
estimate of
value (US$m)
Northwest Atlantic 557,147 25% 22,325 82,266 20 74
Northeast Atlantic 6,677,607 60% 364.908 842.467 328 758
Western Central Atlantic 390,942 22% 21,745 58,514 20 53
Eastern Central Atlantic 1,154,586 32% 294,089 562,169 265 506
Southwest Atlantic 1,403,601 65% 227,865 673,712 205 606
Southeast Atlantic 1,351,635 79% 52,972 139,392 48 125
Western Indian 2,165,792 52% 229,285 559,942 206 504
Eastern Indian 2,263,158 44% 467,865 970,589 421 874
Northwest Pacific 7,358,470 32% 1,325,763 3,505,600 1,193 3,155
Northeast Pacific 196,587 7% 2,326 8,449 2 8
Western Central Pacific 3,740,192 36% 785,897 1,729,588 707 1,557
Eastern Central Pacific 1,374,062 73% 129,772 278,450 117 251
Southwest Pacific 451,677 61% 5,227 32,848 5 30
Southeast Pacific 9,799,047 73% 1,197,547 2,567,890 1,078 2,311
Antarctic 136654 100% 9593 9593 9 9
Total 39,021,155 46% 5,140,928 12,040,052 4,627 10,836
doi:10.1371/journal.pone.0004570.t001
Table 2. Trends in regional estimates of illegal fishing, averaged over 5 year periods 1980–2003.
Region 1980–1984 1985–1989 1990–1994 1995–1999 2000–2003
Northwest Atlantic 26% 19% 39% 15% 9%
Northeast Atlantic 10% 10% 12% 11% 9%
Western Central Atlantic 16% 14% 14% 11% 10%
Eastern Central Atlantic 31% 38% 40% 34% 37%
Southwest Atlantic 15% 18% 24% 34% 32%
Southeast Atlantic 21% 25% 12% 10% 7%
Western Indian 31% 24% 27% 25% 18%
Eastern Indian 24% 29% 30% 33% 32%
Northwest Pacific 16% 15% 23% 27% 33%
Northeast Pacific 39% 39% 7% 3% 3%
Western Central Pacific 38% 37% 37% 36% 34%
Eastern Central Pacific 20% 17% 13% 14% 15%
Southwest Pacific 10% 9% 7% 7% 4%
Southeast Pacific 22% 21% 24% 23% 19%
Antarctic 0% 0% 2% 15% 7%
Average 21% 21% 21% 20% 18%
The figure given is the mid-point between the lower and upper estimates of illegal and unreported catch in the case study species, expressed as a percentage of
reported catch of case study species.
doi:10.1371/journal.pone.0004570.t002
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the upper bound of uncertainty over unreported tuna catches. The
introduction by the International Commission for the Conserva-
tion of Atlantic Tunas (ICCAT) of statistical document schemes
required for trade in tuna has significantly decreased the amount
of unreported tuna catch in the Central Atlantic [9]. In the
Eastern Central Atlantic there appears to have been a steady
increase in illegal fishing, which is at a much higher level than in
the western central Atlantic. This is a large area, covering many
states with a wide variety of fisheries and governance (Morocco to
Angola), some of which, such as Guinea, Sierra Leone and Liberia
suffered increasing illegal catches as a result of internal strife in the
1990s. We have increasing uncertainty about the level of illegal
fishing in the Soutwest Atlantic from the mid-1990s, but overall
the proportion of illegal catch appears to have increased at this
time, once again in response to declining resource status. In
contrast, the exclusion of foreign vessels from Exclusive Economic
Zones in the Southeast Atlantic, and the imposition of national
control in Southeast Atlantic coastal states from the late 1980s, led
to a marked reduction in illegal fishing at that time.
The decline of illegal fishing in the Western Indian Ocean
reflects gradually increasing control over time by coastal states,
particularly those in the extreme north and countries of the
Southern African Development Community, and a reduction in
the unreported catch estimated by the Indian Ocean Tuna
Commission (IOTC). The increase in estimated illegal fishing in
the Northwest Pacific is almost entirely due to the influence of
China and Russia, since estimates of illegal catch in other states in
the area are relatively small. However, the confidence in this
estimate is not as good as for other estimates in this analysis, which
is reflected in an increase in uncertainty in this region. Northeast
Pacific illegal catch is currently estimated to be low and to have
steadily declined over recent years, but, surprisingly, we were
unable to obtain good estimates from the USA. Western Central
Pacific data include coastal states of the western Pacific seaboard,
where the information available to us suggests that a relatively high
level of illegal and unreported catch has been present with little
change over the years. For instance, in Indonesia a huge amount
of unreported catch (over 1.5 million tonnes annually) has recently
been revealed by an FAO study of the Arafura Sea, much of this
illegal [21]. In the Eastern and Southeastern Pacific a similar
situation of low change exists, but with a much lower estimated
proportion of illegal fishing. In the Southwest Pacific increasing
control by coastal states has led to a significant reduction in illegal
fishing over the last 20 years.
Finally, in the Antarctic, the only illegal fishing issue is
unregulated and unreported fishing for toothfish, which peaked
in 1996 and has since significantly reduced.
As would be expected, the highest levels of illegal fishing are
associated with high value demersal fish, lobsters and shrimps/
prawns (Figure 1). It is somewhat surprising at first glance that the
proportion of illegal catch is low for tunas. The reason for this is
that most tuna catches are taken within the areas of RFMOs
where the small amounts of unreported fishing are generally
associated with large volume catches (for instance of yellowfin and
Figure 1. Illegal and unreported catch, expressed as a percentage of reported catch, by species group 2000–2003. Upper and lower
bounds are given.
doi:10.1371/journal.pone.0004570.g001
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bigeye tuna) and in some regions (e.g., the Inter-American
Tropical Tuna Commission and the IOTC) unreported catches
of tunas are now very small.
Taking the total estimated value of illegal catch losses and raising
by the proportion of the total world catch analysed in this paper,
lower and upper estimates of the total value of current illegal and
unreported fishing losses worldwide are between $10 bn and
$23.5 bn annually, representing between 11 and 26 million tonnes.
The estimates previously made by MRAG [6] ($9 bn) and Pauly et al.
[5] ($25 bn) fall at either end of this range. Estimates of losses from
illegal logging are of the same magnitude, roughly 10% of world
timber trade with illegal products worth at least $15 bn a year [22].
Since there are strong economic drivers for illegal fishing [3,4]
and it occurs in situations of poor fisheries management and
control [2,6], we might expect that the level of illegal fishing would
be related to fish price, governance and indicators of the control
problem, such as the area of a country’s EEZ and the number of
patrol vessels at its disposal. We found no significant relationship
between illegal fishing and the price of fish or the size of the EEZ
or the fishery in our study, but we did find a significant
relationship with World Bank governance indicators measured
in 2003 [23], which was strongest with the log of illegal fishing
level. This relationship was significant for the whole dataset
(Figure 2) (R
2
0.400, p,0.001, n = 54), for Africa, Europe and
Asia separately (R
2
0.393, 0.375, 0.429, p,0.01, 0.05 and 0.01
respectively, n = 16 in each case), and with different indicators of
governance such as the Corruption Perceptions index [24] (R
2
0.371, p,0.001, n = 50).
Discussion
This is the first time, to our knowledge, that a significant
relationship has been demonstrated on a global scale between the
level of illegal and unreported fishing and indices of governance,
and it points to the benefits of improving governance. This is not to
say that developing countries with poor governance records are
necessarily to blame for illegal fishing, but that they are more
vulnerable to illegal activities, conducted by both their own fishers
and vessels from distant water fishing nations. In Africa, for
instance, many coastal states licence vessels from distant water
fishing nations such as China, Taiwan, Korea, the EU and Russia to
fish in their waters, and there is a significant illegal fishing problem
from many of these vessels [6]. This represents a failure of control on
behalf of the flag state as well as the coastal state. Furthermore,
many vessels engaged in IUU activities are registered with so-called
‘flag of convenience’ states, and whilst these are mostly developing
countries the vessels themselves are usually owned and operated by
developed country companies [25].
On a world scale, poor performance in the control of illegal
fishing is pervasive. In a recent review [26] over half of the
countries (30/53 top fishing countries) assessed for compliance
with illegal and unreported fishing in the FAO (UN) Code of
Conduct for Responsible Fisheries [27,28; Article 6.10; Articles
7.6.1, 7.7.1, 7.7.5, and 7.8.1] were awarded fail grades (less than
4/10). Only a quarter (16/53) were rated as ‘passable’ (6/10 or
more). Moreover, implementation of ecosystem-based manage-
ment requires control of illegal fishing, and here again almost half
of the countries surveyed failed (16/33), while only two received a
‘good’ rating [29].
Illegal and unreported fishing can have very significant effects
on stocks. For instance, unreported catches of bluefin tuna from
the Mediterranean (estimated by the International Commission for
the Conservation of Atlantic Tunas to have been 19,400 t in 2006
and 28,600 in 2007; 30) have significantly contributed to the rapid
decline in the stock, and a failure by the European Union to
control unreported catches led to a failure to generate any
Figure 2. Relationship between the amount of illegal fishing (expressed as a proportion of the reported catch that is additionally
taken as illegal and unreported catch) and an average of four World Bank indices of governance (Government Effectiveness,
Regulatory Quality, Rule of Law and Control of Corruption, measured in 2003;
23
). Although there is a significant linear relationship
between governance and the proportion of IU, the log-linear relationship shown above is a better fit to the data and has R
2
= 0.4081, p,0.001 with 53
degrees of freedom. The broken lines are 95% confidence intervals.
doi:10.1371/journal.pone.0004570.g002
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recovery in North Sea cod until very recently [31]. There is a
correspondence between our regional estimates of illegal and
unreported fishing and the number of depleted stocks in those
regions. For instance out of 53 demersal stocks recognised in the
eastern central Atlantic, 32 of which could be assessed, 60% were
overexploited in the early 2000s [32] compared to 30% of EU
stocks and 15% of New Zealand stocks [2]. Thus out of these three
areas those with the highest and lowest proportion of depleted
stocks also had the highest and lowest levels of illegal fishing
(Table 1). This may be both because illegal and unreported fishing
is contributing to overexploitation of stocks, and because the
general management of stocks (including the quality of research,
for instance) is likely to be better in areas of higher quality
governance. Illegal fishing in regions with poor governance has
often been linked to organised crime [25,33], but where fish have a
high value, this can be an issue even in countries with good
governance [34].
Illegal fishing creates significant collateral damage to ecosys-
tems. Illegal fishing, by its very nature, does not respect national
and international actions designed to reduce bycatch and mitigate
the incidental mortality of marine animals such as sharks, turtles,
birds and mammals. Such practices are common: examples are
illegal fishing in marine reserves in west Africa [6,7] and the
bycatch of albatross in illegal and unreported longline and gillnet
operations in the Antarctic [11,35]. Only a solution of the illegal
fishing problem will generate the compliance with these wider
ecosystem management measures. Moreover, as part of the move
to explore ecosystem-based management, estimates of unreported
catches have proved to be necessary to balance ecosystem models
[36]. Where unreported extraction of fish from major stocks is not
included this can bias both single species stock assessment and
ecosystem-based analyses in a dangerous direction of allowing
more fishing than would otherwise be thought sustainable.
Clearly some progress has been made in some areas over the last
decade; our study identifies reductions in illegal fishing in 11 areas
since the early 1990s and indeed this trend has continued in the
years since 2003. The worst period for illegal and unreported
fishing world wide appears to have been the mid-1990s, driven by
a combination of factors: a growing world demand for fish and
significant overcapacity of the world’s fishing fleet set against
increasing limitation of access to distant water fishing nations and
a lack of new or alternative fishing opportunities [1,37].
The solutions most often proposed to eliminate illegal fishing
are associated with increased governance and the rule of law -
increased cooperation between regional management authorities
in management and control activities, increased capacity to
undertake surveillance and enforcement of port state control
[38], and other means of reducing the economic incentives to
engage in IUU fishing, such as increased sanctions and trade
measures [4,39]. Recent successes emphasise this. There has been
a significant reduction in illegal and unreported catches of cod
from 50% to 20% of the reported catch in the Barents Sea
following cooperative port state controls implemented by the states
party to the Northeast Atlantic Fisheries Commission [40] and in
the Antarctic IUU catches have been reduced from 33,700 t in
1996/97 to 3,600 t in 2006/07 through cooperative international
and state action [36].
These activities are encouraging, but set in the context of
burgeoning demand for food and particularly protein, there will
continue to be enormous pressure on fish stocks over the next 50
years and it is essential that the international community address
effectively the large illegal and unreported catch of fish reported in
this paper. Given the recent change in political will to tackle the
issue of illegal fishing, [e.g. 38], further improvements might be
expected to come from legally mandating compliance with the
FAO (UN) Code of Conduct for Responsible Fisheries [25], which
would provide countries with an international legal basis for
economic and other sanctions that discourage illegal fishing. Some
countries already include some of the provisions of the Code of
Conduct in their national legislation (for example in Australia,
South Africa, Norway, Namibia, Malaysia). Others, such as the
EU, are now proposing to implement much stronger import
controls and sanctions to restrict trade in IUU fish. This paper
provides the baseline against which action to curb illegal fishing
can be judged.
Methods
We used the ‘‘anchor points and influence table’’ approach of
Pitcher et al. [13] which employs detailed reports (from published
scientific literature and in-country specialist studies) to establish
point estimates and upper and lower bounds of the level of illegal
fishing in different fisheries, and identifies changes to these levels
over time based on historical data or likely trends based on known
changes in management regime. In the source studies a number of
different methods have been used to estimate the level of illegal
fishing, including surveillance data, trade data, stock assessments
based on fishery-independent (survey) data and expert opinion [7].
Some of these methods deliver a point estimate of the level of
illegal fishing, some deliver statistical estimates with confidence
intervals, and some deliver upper and lower bounds. We took the
approach that, when trying to integrate the results of these various
estimation methods with their differing levels of reliability, using
the extreme upper and lower limits produced less variation than
trying to make a point estimate. Where it was available the point
estimate was used to set initial bounds for a percentage figure, but
we used expert opinion to guide the upper and lower limits, and
did not treat them as two point estimates.
Countries were selected based on the volume (tonnage) of
catches reported to have been taken in their EEZ in order of
magnitude (i.e., their importance as fishing areas). A few additional
countries with smaller catches (5 in all, 1.4% of world catch) were
included because of their importance in understanding the
distribution of illegal fishing. All Regional Fishery Management
Organisations (RFMO) were examined. Because data were
required by EEZ rather than FAO area, and in order to keep
catches consistent with FAO totals, catch data for each EEZ
selected and for each high seas FAO region were extracted from
the Sea Around Us project database of estimated catches (41;
www.seaaroundus.org). The Sea Around Us project has attributed
FAO catches reported to EEZs and High Seas by means of a
geospatial algorithm [41]. Within each study, catches and IUU
fishing (discarded and illegal assembled separately) of the four
highest volume (i.e., tonnage caught) species were estimated from
the source studies (seven countries only had three species listed).
This led to 292 separate fishery estimations per year. Percentage
trends for IUU in each five year block were multiplied by the
annual reported catch data to form overall annual estimates,
separated into illegal catches and discards (including other
unreported fish catch such as recreational and legal but
unreported artisanal catches).
EEZs selected for the main time-trend analysis were: Angola,
Argentina, Australia, Bangladesh, Brazil, Canada, China, Den-
mark, Ecuador, Faeroe Islands, France, Germany, Ghana,
Iceland, India, Indonesia, Iran, Ireland, Italy, Japan, Republic of
Korea, Latvia, Malaysia, Mexico, Morocco, Mozambique,
Myanmar, Namibia, Netherlands, New Zealand, Nigeria, Nor-
way, Pakistan, Peru, Philippines, Poland, Portugal, Russia,
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Senegal, South Africa, Spain, Sri Lanka, Sweden, Thailand,
United Kingdom, Tanzania, Yemen. RFMOs analysed for time
trends of illegal and unreported catches were: Northwest Atlantic
Fisheries organisation (NAFO), Northeast Atlantic Fisheries
Commission (NEAFC), the Commission for the Conservation of
Antarctic Marine Living Resources (CCAMLR), the Inter
American Tropical Tuna Commission (IATTC), the International
Commission for the Conservation of Atlantic Tuna (ICCAT), the
Indian Ocean Tuna Commission (IOTC), the Western and
Central Pacific Fisheries Commission (WCPFC) and the Com-
mission for the Conservation of Southern Bluefin Tuna (CCSBT).
Our primary data sources were several key composite studies
[6,20,42–44], supplemented by country-specific studies
[15,19,33,45–86].
In order to estimate the global level of illegal and unreported
catches (IU) a single estimate for the price of a tonne of fish each year
was used. The price data used were those reported by FAO [87].
For some countries a historical time series of estimates of IU
could not be derived from available data sources, although data
were available from the early 2000s from MRAG [6] (Guinea,
Kenya, Liberia, Papa New Guinea, Seychelles, Sierra Leone,
Somalia). While they have been included in the analysis of
governance relating to illegal fishing, these data do not contribute
to the table showing the trends in illegal catch over time by region.
For each case study and species the analysis generated the
following
T
cy
total reported tonnage of all wild fish caught in the case
study EEZ/RFMO area cin year y
t
csy
reported tonnage of fishery sin case study c
U
csy
upper bound estimate of illegal catch
L
csy
lower bound estimate of illegal catch
The estimate of illegal catch as a proportion of reported catch
for a case study and year was calculated as pyc~Ucy zLcy
ðÞ
2tcy where
Ucy~P
4
s~1
Ucsy, and so on.
Regional estimates were developed by combining the high seas
estimates along with EEZ estimates within that region. Where an
EEZ was covered by a number of different FAO regions, these
EEZs were where possible divided into two separate estimates
(e.g., the estimate for the Russian EEZ was broken down by for the
Atlantic and Pacific catches, and Canada and Mexico for west and
east coasts). If this was not possible, the data reported by FAO area
and recorded in the FAO FISHSTAT database were used to
determine the approximate percentage of catches taken in each
area and the estimates distributed uniformly with reported catches
(e.g., South Africa, Australia and USA).
The confidence intervals shown in Figure 2 were created by
estimating the confidence intervals for 1000 simulated datasets
where, for each country, the level of IU was sampled from a
uniform distribution defined by our upper and lower estimates of
IU, and governance was sampled from a gaussian distribution with
mean and standard deviation as presented in Lambsdorff [24].
The confidence intervals plotted in the paper are the maximum
upper 95% and minimum lower 95% limits from the 1000
simulations.
Acknowledgments
We are grateful to numerous colleagues who commented on earlier drafts
and reports, in particular Darius Campbell from the UK Department for
Environment, Food and Rural Affairs and Tim Bostock from the UK
Department for International Development who provided support
throughout the project.
Author Contributions
Conceived and designed the experiments: DA. Performed the experiments:
DA JP GP. Analyzed the data: DA JP GP TP TP. Contributed reagents/
materials/analysis tools: DA GP RW JB TP. Wrote the paper: DA JP TP
TP.
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