Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining — TEI-tagged view

Daniel PaulypersName, Dirk ZellerpersName (2016date). “Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining.” Nature Communicationstitle·j.

Object of study — global marine fisheries catchterm·dom trajectories from 1950date to 2010date, including officially reported and missing catchterm·dom components

Research question — How do reconstructed all-sector marine catchesterm·dom differ from FAO-reported landingsterm·dom in magnitude, peak, decline, spatial pattern, and sector composition?

Contribution — a country-by-country global catchterm·dom reconstruction that adds unreported sectors and discardsterm·dom to reported baselines and quantifies uncertaintyterm·mth

Full text — tagged

Catch reconstructionsterm·mth reveal that global marine fisheries catchesterm·dom are higher than reported and declining Abstract Fisheries data assembled by the Food and Agriculture Organization (FAOterm) suggest that global marine fisheries catchesterm·dom increased to 86 million tonnes in 1996, then slightly declined. Here, using a decade-long multinational ‘catch reconstructionterm·mth' project covering the Exclusive Economic Zonesterm·dom of the world's maritime countries and the High Seasterm·dom from 1950date to 2010date, and accounting for all fisheries, we identify catch trajectoriesterm·dom differing considerably from the national dataterm submitted to the FAOterm. We suggest that catchterm·dom actually peaked at 130 million tonnes, and has been declining much more strongly since. This decline in reconstructed catchesterm·dom reflects declines in industrial catchesterm·dom and to a smaller extent declining discardsterm·dom, despite industrial fishing having expanded from industrialized countries to the waters of developing countries. The differing trajectories documented here suggest a need for improved monitoring of all fisheries, including often neglected small-scale fisheriesterm·dom, and illegal and other problematic fisheries, as well as discarded bycatchterm·dom.

Marine fisheries are the chief contributors of wholesome seafood (finfish and marine invertebrates; here ‘fish'). In many developing countries (and likely also in many ‘transition‘ countries), fish is the major animal protein source that rural people can access or afford 1 ; and they are also an important source of micronutrients essential to people with otherwise deficient nutrition 2 . However, the growing popularity of fish in countries with developed or rapidly developing economies creates a demand that cannot be met by fish stocks in their own waters (for example, the EU, the USA, China and Japan). These markets are increasingly supplied by fish imported from developing countries, or caught in the waters of developing countries by various distant-water fleets 3 , 4 , 5 , with the consequences that: Foreign and/or export-oriented domestic industrial fleets are increasingly fishing in the waters of developing countries 5 , 6 , Industrially caught fish has become a globalized commodity that is mostly traded between continents rather than consumed in the countries where it was caught 7 , and The small-scale fisheriesterm·dom that traditionally supplied seafood to coastal rural communities and the interior of developing countries (notably in Africa) 8 are forced to compete with the export-oriented industrial fleets without much support from their governments.

The lack of attention that small-scale fisheriesterm·dom suffer in most parts of the world 9 manifests itself in potentially misleading statistics that are submitted annually by many member countries of the Food and Agriculture Organization of the United Nations (FAOterm), which may omit or substantially underreport small-scale fisheriesterm·dom data 10 . FAOterm harmonizes the data submitted by its members, which then becomes the only global data set of fisheries statistics in the world, widely used by policy makers and scholars 11 .

This data set, however, may not only underestimate artisanal (that is, small scale, commercial) and subsistence fisheriesterm·dom 10 , but also generally omit the catchterm·dom of recreational fisheries, discarded bycatchterm·dom 12 and illegal and otherwise unreported catchterm·dom, even when some estimates are available 13 . Thus, except for a few obvious cases of over-reporting 14 , the landingsterm·dom data updated and disseminated annually by the FAOterm on behalf of member countries may considerably underestimate actual fisheries catchterm·dom. While this underestimation is widely known among many fisheries scientists working with FAOterm catchterm·dom data, and is freely acknowledged by FAOterm, its global magnitude has not been explicitly presented until now.

Here we present the results of an approach called ‘catch reconstructionterm·mth' 15 , 16 that utilizes a wide variety of data and information sources to derive estimates for all fisheries components missing from the official reported dataterm. We find that reconstructed global catchesterm·dom between 1950date and 2010date were 50% higher than data reported to FAOterm suggest, and are declining more strongly since catchesterm·dom peaked in the 1990s. These findings and the country-specific technical work underlying these results will hopefully contribute to member countries submitting more accurate fisheries statistics to FAOterm. Such improved and more comprehensive data contribute a foundation that can facilitate the implementation of ecosystem-based fisheries managementterm·dom 17 , which is a component of the ‘ FAOterm Code of Conduct for Responsible Fisheries ' 18 .

Results Global pattern The sum of the reconstructed catchesterm·dom of all sectors in all Exclusive Economic Zonesterm·dom (EEZsterm·dom) of the world, plus the catchterm·dom of tuna and other large pelagic fishesterm·dom in the High Seasterm·dom leads to two major observations ( Fig. 1 ; Supplementary Table 1 ). First, the trajectory of reconstructed catchesterm·dom differs substantially from those reported by FAOterm on behalf of its member countries. The FAOterm statistics suggest that, starting in 1950date, the world catchterm·dom (actually ‘landingsterm·dom', as discarded catchesterm·dom are explicitly excluded from the global FAOterm data set) increased fairly steadily to 86 million tonnes (mt) in 1996, stagnated and then slowly declined to around 77 mt by 2010date ( Fig. 1 ). In contrast, the reconstructed catchterm·dom peaked at 130 mt in 1996 and declined more strongly since. Thus, the reconstructed catchesterm·dom are overall 53% higher than the reported data.

Trajectories of reported and reconstructed marine fisheries catchesterm·dom 1950date–2010date. Contrast between the world's marine fisheries catchesterm·dom, assembled by FAOterm from voluntary submissions of its member countries (‘reported') and that of the catchterm·dom ‘reconstructed' to include all fisheries known to exist, in all countries and in the High Seaterm·dom (‘reconstructed'=‘reported'+estimates of ‘unreported'). The mean weighted percentage uncertaintyterm·mth of the reconstructed total catchesterm·dom (over all countries and fisheries sectors) based on the quality scoresterm·mth attributed to each sector in each country and territory (dashed line) is also shown.

Furthermore, since the year of peak catchesterm·dom in 1996, the reconstructed catchterm·dom declined strongly at a mean rate of −1.22 mt·per year, whereas FAOterm, at least until 2010date, described the reported catchterm·dom cautiously as characterized by ‘stability' 19 , 20 , though it exhibited a gradual decline (−0.38 mt·per year). The reconstructed total catchesterm·dom therefore represent a decline of over three times that of the reported data as presented by FAOterm on behalf of countries. A segmented regressionterm·mth 21 identifies two breakpointsterm in the catchterm·dom time series (that is, change in trend) of the reconstructed total catchesterm·dom as well as the reported catchesterm·dom. These are in 1967 as a result of a changing slope of the catchterm·dom time series from a stronger increase prior to 1967 (reconstructed catchesterm·dom=2.82 mt·per year; reported catchesterm·dom=1.88 mt·per year) to a slower increase after 1967 (reconstructed catchesterm·dom=1.86 mt·per year; reported catchesterm·dom=1.30 mt·per year). The second breakpointterm is in 1996 (the year of peak catchterm·dom), with a subsequently decreasing trend (that is, slope) of −1.22 mt·per year for reconstructed catchesterm·dom and −0.38 mt per·year for reported catchesterm·dom, as also presented for the simple regression above ( Fig. 1 ; see also Supplementary Table 2 ).

Note that the recent, stronger decline in reconstructed total catchesterm·dom is not due to some countries reducing catchterm·dom quotas so that stocks can rebuild. For example, a similar decline (−1.01 mt·per year) in reconstructed catchesterm·dom is obtained when the catchterm·dom from the Unites States, Northwestern Europe, Australia and New Zealand (that is, countries where quota managementterm·dom predominates) is excluded ( Fig. 2 ; Supplementary Table 3 ).

Trajectories of marine fisheries catchesterm·dom 1950date–2010date. Effects of removing discardsterm·dom on estimates of seafood caught per capita , and of removing the catchesterm·dom of the major countries using quota managementterm·dom (that is, USA, New Zealand, Australia and Western Europe) on reconstructed total catchesterm·dom.

Spatial pattern Closer examination of the reconstructed versus reported catchesterm·dom in each of the 19 maritime FAOterm statistical areas suggests that some of the areas where industrial fishing originated, such as the Northwest Atlantic (FAOterm area 21), are the first regions of the world to demonstrate declining catchesterm·dom ( Fig. 3 ). In contrast, lower-latitude areas demonstrate declines later, or still appear to have increasing catchesterm·dom, for example, the Indian and Western Central Pacific Oceans still showing generally increasing trends in reported catchesterm·dom ( Fig. 3 ).

Reconstructed and reported catchesterm·dom by FAOterm areas. Contrasting reconstructed and reported catchesterm·dom in the 19 maritime ‘Statistical Areas' which FAOterm uses to roughly spatialize the world catchterm·dom. Note that for Area 18 (Arctic), the reported catchterm·dom by the U.S. and Canada was zero, while only Russia (former-USSR) reported a small catchterm·dom in the late 1960s, even though the coastal fishes of the high Arctic are exploited by Inuit and others.

Catchesterm·dom by fishing sector We present, for the first time, global reconstructed marine fisheries catchesterm·dom by fisheries sectors ( Fig. 4 ; Supplementary Table 4 ). They are dominated by industrial fisheriesterm·dom, which contribute 73 mt of landingsterm·dom in 2010date, down from 87 mt in 2000 ( Fig. 4 ). At the global scale it is a declining industrial catchterm·dom (combined with the smaller contribution of gradually reduced levels of discarding) 12 that leads to declining global catchesterm·dom since 1996, while the artisanal sectorterm·dom, which generates a catchterm·dom increasing from about 8 mt·per year in the early 1950sdate to 22 mt·per year in 2010date, continues to show gradual growth in catchesterm·dom at the global scale ( Fig. 4 ).

Reconstructed global catchterm·dom by fisheries sectors. Reconstructed catchesterm·dom for all countries in the world, plus High Seasterm·dom, by large-scale (industrial) and small-scale sectors (artisanal, subsistence, recreational), with discardsterm·dom (overwhelmingly from industrial fisheriesterm·dom) presented separately.

Also noticeable is that the inter-annual variations (small peaks and troughs) in both reconstructed catchesterm·dom and reported catchesterm·dom ( Fig. 1 ) are mainly driven by industrial data, which are relatively well documented and reported in time series, while the small-scale sector data are smoother over time ( Fig. 4 ), and more strongly influenced by continuity assumptionsterm over time as part of the national reconstructions.

While some countries increasingly include subsets of artisanal catchesterm·dom in official catchterm·dom statistics provided to FAOterm, subsistence fisheriesterm·dom catchesterm·dom ( Fig. 4 ) rarely are 10 . Worldwide, subsistence fisheriesterm·dom caught an estimated 3.8 mt·per year between 2000 and 2010date ( Fig. 4 ; Supplementary Table 4 ). The current global estimate of just under 1 mt·per year of recreational catchesterm·dom is rather imprecise, and recreational fishing is declining in developed, but increasing in developing countries.

Discarded bycatchterm·dom, generated mainly by industrial fishing, notably shrimp trawling 22 , was estimated at 27 mt·per year (±10 mt) and 7 mt·per year (±0.7 mt) in global studies conducted for FAOterm in the early 1990s and 2000s, respectively 23 , 24 . However, these point estimates were not incorporated into FAOterm's global ‘capture' database, which thus consists only of landingsterm·dom. Here, these studies are used, along with numerous other sources, to generate time series of discardsterm·dom ( Fig. 4 ). Discardsterm·dom, after peaking in the late 1980s, have declined, and during 2000–2010date, an average of 10.3 mt·per year of fish were discarded.

Discussion Our reconstructed catchterm·dom data, which combines the data reported to FAOterm with estimates of unreported catchesterm·dom (that is, reconstructed data are ‘reported FAO dataterm+unreported catchesterm·dom') include estimates of uncertaintyterm·mth ( Fig. 1 ) associated with each national reconstruction. Note that many reconstructions are associated with high uncertaintyterm·mth, especially for earlier decades, for sectors such as subsistence which receive less data collection attention by governments, and for small countries or territories ( Fig. 1 ; Supplementary Table 5 ) 10 . We include uncertaintyterm·mth estimates here, despite the fact that reconstructions address an inherent negative biasterm·mth in global catchterm·dom data (that is, address the ‘accuracyterm·mth' of data) and not the replicability of catchterm·dom data collection (that is, the statistical ‘precisionterm·mth' of such estimates), which is what ‘uncertaintyterm·mth' estimates (for example, confidence limits) generally are used for. We do recognize that any estimates of unreported catchesterm·dom implies a certain degree of uncertaintyterm·mth, but so do officially reported data. Most countries in the world use sampling schemes, estimations and raising factorsterm·mth to derive their national catchterm·dom data they officially report domestically and internationally, all without including estimates of the uncertaintyterm·mth inherent in the numbers being reported as official national catchesterm·dom.

Our comparison of the reconstructed versus reported catchesterm·dom in each of the 19 maritime FAOterm statistical areas suggests that some of the lower-latitude areas still appear to have increasing reported catchesterm·dom. This generally increasing trend is most pronounced in the Indian and Western Central Pacific Oceans ( Fig. 3 ), where the reconstructed catchesterm·dom are most uncertain, as the statistics of various countries could only partially correct a regional tendency to exaggerate reported catchesterm·dom 5 . FAOterm's Indian and Western Central Pacific Oceans areas are also the only ones with an increasing FAOterm reported catchterm·dom, which, when added to that of other FAOterm areas, makes the FAOterm reported world catchterm·dom appear more stable than it is based on our global reconstructions.

Our data and analyses show that, at the global scale, it is a declining industrial catchterm·dom (plus a smaller contribution of gradually declining discardsterm·dom) 12 that provide for the declining global catchesterm·dom, while artisanal fishing continues to show slight growth in catchesterm·dom ( Fig. 4 ). Thus, the gradually increasing incorporation of artisanal and other small-scale catchesterm·dom in the officially reported data presented by FAOterm on behalf of countries is partly masking the decline in industrial catchesterm·dom at the global level. Since officially reported data are not (at the international level) separated into large-scale versus small-scale sectors 25 , this trend could not be easily documented until now. Obviously, these patterns may vary between countries. Furthermore, while parts of artisanal catchesterm·dom are increasingly included in official catchterm·dom statistics by some countries, non-commercial subsistence fisheriesterm·dom catchesterm·dom, a substantial fraction of it through gleaning by women in coastal ecosystems such as coral reef flats and estuaries 26 are generally neglected. The importance of subsistence fishing for the food securityterm·dom of developing countries, particularly in the tropical Indo-Pacific, cannot be overemphasized 10 , 27 .

Our preliminary and somewhat imprecise reconstruction of recreational catchesterm·dom indicates that this sector is largely missing from official reported dataterm, despite FAOterm's annual data requests explicitly allowing inclusion of recreational catchterm·dom data. This activity, however, generates an estimated 40 billion USD·per year of global benefits, involves between 55 and 60 million persons, and generates about one million jobs worldwide 28 .

Finally, our country-by-country reconstructed data supports previous studies illustrating that global discardsterm·dom have decreased 12 , 24 . Discarded catchesterm·dom should therefore be included in catchterm·dom databases, if only to allow for correct inferences on the state of the fisheries involved in this problematic practice.

The reconstructed catchterm·dom data presented here for the first time for all countries in the world can contribute to formulating better policies for governing the world's marine fisheries, with a first step being the recognition in national policies of the likely magnitude of fisheries not properly captured in the official national dataterm collection systems. This recognition will hopefully contribute to improvements in national dataterm collection systems, an aspiration that we share with FAOterm. For example, in Mauritania and Guinea Bissau, which, in large part as a result of the reconstructions 29 , 30 and our ongoing direct engagement with these countries, are now initiating national dataterm collection systems for recreational fisheries (a growth industry in both countries and missing from current data systems). It is hoped that this type of data, and other missing data (for example, subsistence catchesterm·dom) 10 , will be included in future national dataterm reports to FAOterm, as is the case for some other countries such as Finland 31 . The taxonomic composition of this reconstructed catchterm·dom (not presented here but available from the Sea Around Us and through the individual catch reconstructionterm·mth reports, see Supplementary Table 5 ) can also contribute to the development of more useful first-order indicators of fisheries status 32 , 33 , 34 than has been possible previously, especially in the absence of comprehensive stock assessments for all taxa targeted.

A policy change that would be straightforward for FAOterm to coordinate and implement with all countries around the world is to request countries to submit their annual catchterm·dom statistics separately for large-scale and small-scale fisheriesterm·dom 25 , which would be an excellent contribution towards the implementation of the ‘ Voluntary Guidelines for Securing Sustainable Small-scale Fisheriesterm·dom in the Context of Food Securityterm·dom and Poverty Eradication ' recently adopted and endorsed at the thirty-first Session of the FAOterm Committee on Fisheries and Aquaculture (COFI) in June 2014 (ref. 35 ). While we have found that many countries already have such data or data structure at hand, until all countries can implement such a data-change request, FAOterm could incorporate such a split into their internal data harmonization procedures, based, for example, on the same or similar information sources as used by the reconstructions.

The very high catchesterm·dom that were achieved globally in the 1990s were probably not sustainable. However, they do suggest that stock rebuildingterm·dom, as successfully achieved in many Australian and US fisheries, and beginning to be applied in some European fisheries, is a policy that needs wider implementation, and which would generate even higher sustained benefits than previously estimated from reported catchesterm·dom 36 . On the other hand, the recent catchterm·dom decline documented here is of considerable concern in its implication for food securityterm·dom, as evidenced by the decline in per capita seafood availability ( Fig. 2 ). Note that the recent, strong decline in reconstructed total catchesterm·dom is also evident if catchesterm·dom in countries with well-established quota managementterm·dom systems (United States, Northwestern Europe, Australia and New Zealand) are excluded ( Fig. 2 ). Low quotas are generally not imposed when a stock is abundant; rather low and reduced quotas in fully developed fisheries are generally a management intervention to reduce fishing pressure as a result of past overfishing. Similarly, it has been proposed that strongly declining catchesterm·dom in unmanaged, heavily exploited fisheries are likely a sign of overfishing 32 , 33 , 34 . The often raised suggestion that aquaculture production can replace or compensate for the shortfall in wild capture seafood availability, while being questionable for various reasons 37 , is not addressed here.

The last policy relevant point to be made here transcends fisheries in that it deals with the accuracyterm·mth of the data used by the international community for its decision making, and the generation of factual knowledge that this requires. After the creation of the United Nations and its technical organizations, including the FAOterm, a major project of ‘quantifying the world' 38 began to provide data for national and international agencies on which they could base their policies. As a result, large databases, for example on agricultural crops and forest cover, were created whose accuracyterm·mth is becoming increasingly important given the expanding exploitation of our natural ecosystems 39 .

Periodic validation of these databasesterm·mth should therefore be a priority to ensure they avoid producing ‘poor numbersterm·dom' 40 . For example, reports of member countries to FAOterm about their forest cover, when aggregated at the global level, suggest that the annual rate of forest loss between 1990/2000 and 2001/2005 was nearly halved, while the actual loss rate doubled when assessed by remote sensing and rigorous sampling 41 . Similarly, here we show that the main trend of the world marine fisheries catchesterm·dom is not one of ‘stability' as cautiously suggested earlier by FAOterm 42 , but one of decline. Moreover, this decline, which began in the mid-1990s, started from a considerably higher peak catchterm·dom than suggested by the aggregate statistics supplied by FAOterm members, implying that we have more to lose if this decline continues. Thankfully, this also means that there may be more to gain by rebuilding stocks.

For the global community, a solution could therefore be to provide the FAOterm the required funds to more intensively assist member countries in submitting better and more comprehensive fishery statistics, especially statistics that cover all fisheries components, and report data by sector 25 . Such improved statistics can then lead to better-informed policy changes for rebuilding stocks and maintaining (sea)food securityterm·dom. Alternatively, or in addition, FAOterm could team up with other groups (as was done for forestry statistics) to improve the fisheries statistics of member countries that often have fisheries departments with very limited human and financial resources.

Ultimately, the only database of international fisheries statistics that the world has (through FAOterm) can be improved. The more rapid decline of fisheries catchesterm·dom documented here is a good reason for this.

Methods Catch reconstructionterm·mth principles The catch reconstructionterm·mth approach rests on two basic principles 16 : When ‘no data are available' on a fishery that is known to exist, it is not appropriate to enter ‘NA' or ‘no data' into the database. Such entries will later be turned into a zero, which is a bad estimate of the catchterm·dom of an existing fishery. This concern about the problematic ‘elegance of the number zero' is also something that affects other scientific activities, such as climate modelling 43 ; Rather, a best estimateterm·mth should be inserted in all such cases, based on the fact that fishing is a social activity that is bound to throw a ‘shadow' on the society in which it is embedded, and from which an approximate and conservative (but better than zero) estimate of catchterm·dom can be derived if fishing of this type is known to occur (for example, from the seafood or the fuel consumed locally, or the number of vessels engaged in fisheries and the average catchterm·dom rate of vessels of this type and so on).

This approach addresses an inherent negative biasterm·mth in national and, by extension, global catchterm·dom data, although considerable uncertaintyterm·mth in catchterm·dom data is likely to remain.

Notably, when doing reconstructions, it became apparent that the perception of ‘no data' being available was not always correct: the ‘social shadowterm·mth' yields hundreds of articles in the peer-reviewed and report literature with catchterm·dom data, or data from which catchterm·dom rates could be inferred, even for remote islands 10 . Also, countries may sometimes send to FAOterm a stripped down version of the national catchterm·dom data their fisheries research institutes actually possess, and may even publish on their websites.

What is covered here are both ‘coastal' waters, defined as the waters within the EEZterm·dom ( Supplementary Fig. 1 ) that countries have claimed since this was allowed under the United Nations Convention on the Law of the Sea (UNCLOS), or which they could claim under UNCLOS rules, but have not (such as many countries around the Mediterranean), and the open oceans, or High Seasterm·dom, that is, the waters beyond national jurisdiction (that is, beyond the EEZsterm·dom). The delineations provided by the Flanders' Marine Institute (VLIZ, see www.vliz.be ) are used for our definitions of EEZsterm·dom. Countries that have not formally claimed an EEZterm·dom are assigned areas equivalent to EEZsterm·dom based on the basic principles of EEZsterm·dom as outlined in UNCLOS (that is, 200 nm and/or mid-line rules). Note that we (a) include territorial waters within our EEZsterm·dom; and (b) treat disputed zones (that is, EEZterm·dom areas claimed by more than one country) as being ‘owned' by each claimant with respect to their fisheries catchesterm·dom. We treat EEZterm·dom areas prior to each country's year of EEZterm·dom declaration as ‘EEZ-equivalent waters' (with open access to all fishing countries during that time). If the year of EEZterm·dom declaration could not be determined (and for ‘EEZsterm·dom' that were derived by us for non-claimant countries), we assign the year 1982 as declaration year, that is, the year of conclusion of UNCLOS.

We use different catch reconstructionterm·mth approaches for EEZsterm·dom (40% of the global ocean), and High Seasterm·dom (60%), where the catchesterm·dom are mainly large pelagic fishes (notably tuna). Note that we also exclude the Caspian Sea from all considerations.

Domestic catch reconstructionterm·mth method Reconstructing time series of fisheries catchterm·dom for all countries of the world from 1950date (the first year that FAOterm published its ‘Yearbook' of global fisheries statistics) to 2010date was undertaken by fisheries ‘sectors'. However, because a standardized global definition of fishing sectors based on vessel size does not exist (for example, a vessel considered large-scale (industrial) in a developing country may be considered small-scale (artisanal) in developed countries), reconstructions utilize each country's individual definitions for sectors, or a regional equivalent. These are described in each country reconstruction publication underlying this work. We consider four sectors: Industrial: large-scale fisheries (using trawlers, purse-seiners, longliners) with high capital input into vessel construction, maintenance and operation, and which may move fishing gear across the seafloor or through the water column using engine power (for example, demersal and pelagic trawlers), irrespective of vessel size. This corresponds to the ‘commercial' sectors of countries such as the USA; Artisanal: small-scale fisheriesterm·dom whose catchterm·dom is predominantly sold (hence they are also ‘commercial fisheries'), and which often use a large variety of generally static or stationary (passive) gears. Our definition of artisanal fisheries relies also on adjacency: they are assumed to operate only in domestic waters (that is, in their country's EEZterm·dom). Within their EEZterm·dom, they are further limited to a coastal area to a maximum of 50 km from the coast or to 200 m depth, whichever comes first. This area is defined as the Inshore Fishing Area (IFA) 44 . Note that the definition of an IFA assumes the existence of a small-scale fishery, and thus unpopulated islands, although they may have fisheries in their EEZterm·dom (which by our definition are industrial, whatever the gear used), have no IFA; Subsistence: small-scale non-commercial fisheries whose catchterm·dom is predominantly consumed by the persons fishing it, and their families (this may also include the ‘take-home' fraction of the catchterm·dom of commercial fishers, which usually by-passes reporting systems); and Recreational: small-scale non-commercial fisheries whose major purpose is enjoyment.

In addition to the reconstructions by sector, we also assign catchesterm·dom to either ‘landingsterm·dom' (that is, retained and landed catchterm·dom) or ‘discardsterm·dom' (that is, discarded catchterm·dom), and label all catchesterm·dom as either ‘reported' or ‘unreported' with regards to national and FAOterm data. Thus, reconstructions present ‘catchterm·dom' as the sum of ‘landingsterm·dom' plus ‘discardsterm·dom'.

Discarded fish and invertebrates are generally assumed to be dead, except for the US fisheries where the fraction of fish and invertebrates reported to survive is generally available on a per species basis 45 . Due to a distinct lack of global coverage of information, we do not account for so-called under-water discardsterm·dom, or net-mortality of fishing gears 46 . We also do not address mortality caused by ghost-fishing of abandoned or lost fishing gear 47 .

For commercially caught jellyfishes (particularly Rhizostomeae, but also other taxa), it has been shown that over 2.5 time more are caught than reported to FAOterm (mostly as ‘ Rhizostoma spp.') 48 . This factor is used to estimate missing catchesterm·dom of unidentified jellyfish. However, this additional catchterm·dom is, pending further study, not allocated to any specific country or FAOterm area, and is thus counted only in the world's total catchterm·dom.

We exclude from consideration all catchesterm·dom of marine mammals, reptiles, corals, sponges and marine plants (the bulk of the plant material is not primarily used for human consumption, but for cosmetic or pharmaceutical use). In addition, we do not estimate catchesterm·dom made for the aquarium trade, which can be substantial in some areas in terms of number of individuals, but relatively small in overall tonnage, as most aquarium fish are small or juvenile specimens 49 .

Most catch reconstructionsterm·mth consist of six steps 15 : (1) Identification, sourcing and comparison of baseline catch times seriesterm·mth, that is, (a) FAOterm reported landingsterm·dom data by FAOterm statistical areas, taxon and year; and (b) national or regional data series by area, taxon and year. Implicit in this first step is that the spatial entity be identified and named that is to be reported on (for example, EEZterm·dom of Germany in the Baltic Sea), something that is not always obvious, and which poses problems to some of our external collaborators, notably those in countries with a claimed EEZterm·dom overlapping with that of their neighbour.

For most countries, the baseline data are the statistics reported by member countries to FAOterm. We treat all countries recognized in 2010date (or acting like independent countries with regards to fisheries) by the international community as having existed from 1950date to 2010date. This is necessary, given our emphasis on ‘places', that is, on time-series of catchesterm·dom taken from specific ecosystems. This also applies to islands and other territories, many of which were colonies, and which have changed status and borders since 1950date.

For several countries, the baseline data are provided by international bodies. In the case of EU countries, the baseline data originate from the International Council for the Exploration of the Sea (ICES), which maintains fisheries statistics by smaller statistical areas, as required given the Common Fisheries Policy of the EU. A similar area is the Antarctic waters and surrounding islands, whose fisheries are managed by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), where catchterm·dom data are available by relatively small statistical areas 50 .

When FAOterm data are used, care is taken to maintain their assignment to different FAOterm statistical areas for each country ( Supplementary Fig. 1 ), as they often distinguish between strongly different ecosystems. For example, the Caribbean Sea versus the coast of the Eastern Central Pacific in the case of Panama, Costa Rica, Nicaragua, Honduras and Guatemala. For each maritime country, the area covered extends from the coastline to the edge of the EEZterm·dom, including any major coastal lagoons connected to the sea, and the mouths of rivers, that is, estuaries. However, freshwaters are excluded.

(2) Identification of sectors (for example, subsistence, recreational), time periods, species, gears and so on, not covered by (1), that is, missing data componentsterm·mth. This is conducted via literature searches and consultations with local experts. This step is one where the contribution of local co-authors and experts is crucial. Potentially, all four sectors defined by us can occur in the marine fisheries of a given coastal country, with the distinction between large-scale and small-scale being the most important 25 . For any entity, we check whether catchesterm·dom originating from the four sectors were included in the reported baseline of catchterm·dom data, notably by examining their taxonomic composition, and any metadata, which were particularly detailed in the early decades of the FAOterm ‘Yearbooks' 51 .

The absence of a taxon known to be caught in a country or territory from the baseline data (for example, cockles gleaned by women on the shore of an estuary) 26 can also be used to identify a fishery that has been overlooked in the official data collection scheme, as can the absence of reef fishes in the coastal data of a Pacific Island state 10 . To avoid double counting, tuna and other large pelagic fishesterm·dom, unless known to be caught by a local small-scale fishery (and thus in the past not likely reported to a Regional Fisheries Management Organizationterm or RFMO), are not included in this reconstruction step (see below under ‘High Seasterm·dom and other catchesterm·dom of large pelagic fishes').

Finally, if gears are identified in national dataterm, but a gear known to exist in a given country is not included, then it can be assumed that its catchterm·dom has been missed, as documented for weirs ( hadrah ) in the Persian Gulf 52 .

(3) Sourcing of alternative information sourcesterm·mth on missing sectors identified in (2), via literature searches (peer-reviewed and grey) and consultations with local experts. Information sources include social science studies (anthropology, economics and so on), reports, data sets and expert knowledge. The major initial source of information for catch reconstructionsterm·mth is governments' websites and publications (specifically their Department of Fisheries or equivalent agency), both online and in hard copies. Contrary to what could be expected, it is often not the agency responsible for fisheries research and initial data collection that supplies the catchterm·dom statistics to FAOterm, but other agencies, for example, statistical office or agency. As a result, much of the granularity of the original data (that is, catchterm·dom by sector, by species or by gear) may be lost even before data are prepared for submission to FAOterm. Furthermore, the data request form sent by FAOterm each year to each country does not encourage improvements or changes in taxonomic composition, as the form that requests the most recent year's data contains the country's previous years' data in the same composition as submitted in earlier years. This encourages the pooling of detailed data at the national level into the taxonomic categories inherited through earlier (often decades old) FAOterm reporting schemes, as was discovered, for example, for Bermuda in the early 2000s (ref. 53 ). Thus, by getting back to the original data, much of the original granularity can be regained during reconstructions.

Additional sources of information on national catchesterm·dom are international organizations such as FAOterm, ICES or SPC (Secretariat of the Pacific Community), or a Regional Fisheries Management Organizationterm (RFMO) such as NAFO (Northwest Atlantic Fisheries Organization), or CCAMLR 54 , or current or past regional fisheries development and/or management projects (many of them launched and supported by FAOterm), such as the Bay of Bengal Large Marine Ecosystem project (BOBLME). All these organizations and projects issue reports and publications describing—sometimes in considerable details—the fisheries of their member countries. Another source of information is the academic literature, now widely accessible through Google Scholar.

A good source of information for the earlier decades (especially the 1950sdate and 1960s) for countries that were part of former colonial empires (especially British or French) are the colonial archives in London (British Colonial Office) and the ‘Archives Nationales d'Outre-Mer', in Aix-en-Provence, and the publications of ORSTOM (Office de la recherche scientifique et technique d'outre-mer), for former French colonies. A further source of information and data are non-fisheries sources, including household and/or nutritional surveys, which are occasionally used for estimating unreported subsistence catchesterm·dom. Our global network of local collaborators is also crucial in this respect, as they have access to key data sets, publications and local knowledge not available elsewhere, often in languages other than English.

Supplementary Figure 2 shows a plot of the publications used for slightly over 110 reconstructions against their date of publication. Although, recent publications predominate, older publications firmly anchor the 1950sdate catchterm·dom estimates of many reconstructions. On average, around 35 unique publications were used per reconstruction (not counting online sources and personal communications).

Potential language bias is taken seriously in the Sea Around Us , to ensure that data are collated in languages other than English. Besides team members who read Chinese, others speak Arabic, Danish, Filipino/Tagalog, French, German, Hindi, Japanese, Portuguese, Russian, Spanish, Swedish and Turkish. To deal with other languages, research assistants are hired who speak, for example, Korean or Malay/Indonesian. We also rely on our multilingual network of colleagues and friends throughout the world, for example, for Greek or Thai. While it is true that English has now become the undisputed language of science 55 , other languages are used by billions of people, and assembling knowledge about the fisheries of the world is not possible without the capacity to explore the literature in languages other than English.

(4) Development of data ‘anchor pointsterm·mth' in time for each missing data item, and expansion of anchor pointterm·mth data to country-wide catchterm·dom estimates. ‘Anchor' points are catchterm·dom estimates usually pertaining to a single year and sector, and often to an area not exactly matching the limits of the EEZterm·dom or IFA in question. Thus, an anchor pointterm·mth pertaining to a fraction of the coastline of a given country may need to be expanded to the country as a whole. For expansion, we use fisher or population density, or relative IFA or shelf area as raising factorterm·mth, as appropriate given the local condition. In all cases, we consider that case studies underlying or providing the anchor pointterm·mth data may had a case-selection bias (for example, representing an exceptionally good area or community for study, compared with other areas in the same country), and thus use raising factorsterm·mth very conservatively.

(5) Interpolation for time periods between data anchor pointsterm·mth, either linearly or assumption based for commercial fisheries, and generally via per capita (or per fisher) catchterm·dom rates for non-commercial sectors. Fisheries are often difficult to govern, as they are social activities involving multiple actors. In particular, fishing effort is often difficult to reduce, at least in the short term. Thus, if anchor pointsterm·mth are available for years separated by multi-year intervals, it usually will be more reasonable to assume that the underlying fishing activity continues in the intervening years with no data. We tread this ‘continuity' assumption as a default proposition. Exceptions to such continuity assumptionsterm are major environmental impacts such a hurricanes or tsunamis 56 , or major socio-political disturbances, such as military conflicts or civil wars 57 , which we explicitly consider with regards to the use of raising factorsterm·mth and the structure of time series estimates. In such cases, our reconstructions mark the event through a temporary change (for example, decline) in the catchterm·dom time series, which is documented in the text of each catch reconstructionterm·mth. At the very least, this provides pointers for future research on the relationship between fishery catchesterm·dom and natural catastrophes or conflicts. We note that the absence of such signals (such as a reduction in catchterm·dom for a year or two) in the officially reported catchterm·dom statistics for countries having experienced a major natural or socio-political disturbance can be a sign that their official catchterm·dom data may not accurately reflect what occurs on the ground. This contributes to the emergence of ‘poor numbersterm·dom' 40 . Overall, our reconstructions assume—when no information to the contrary is available—that commercial catchesterm·dom (that is, industrial and artisanal) can be linearly interpolatedterm·mth between anchor pointsterm·mth, while non-commercial catchesterm·dom (that is, subsistence and recreational) can generally be interpolated between anchor pointsterm·mth using non-linear trends in human population numbers or number of fishers over time (via per capita ratesterm·mth).

Radical and rapid effort reductions as a result of an intentional policy decision and implementation do not occur widely. One example we are aware of is the trawl ban of 1980 in Western Indonesia 58 . The ban had little or no impact on official Indonesian fisheries statistics for Western Indonesia, another indication that these statistics may have little to do with the realities on the ground. FAOterm hints at this being widespread in the Western Central Pacific and the Eastern Indian Ocean (the only FAOterm areas where reported catchesterm·dom appear to be increasing) when they note that ‘while some countries (i.e., the Russian Federation, India and Malaysia) have reported decreases in some years, marine catchesterm·dom submitted to FAOterm by Myanmar, Vietnam, Indonesia and China show continuous growth, i.e., in some cases resulting in an astonishing decadal increase (e.g., Myanmar up 121 percent, and Vietnam up 47 percent)'. 42 (6) Estimation of total catch times seriesterm·mth. A reconstruction is completed when the estimated catchterm·dom time series derived through steps 2–5 are combined and harmonized with the reported catchterm·dom of step 1. Generally, this results in an increase of the overall catchterm·dom, but several cases exist where the reconstructed total catchterm·dom is lower than the reported catchterm·dom. The best documented case of this is that of mainland China 14 , whose over-reported catchesterm·dom for local waters in the Northwest Pacific are compensated for by under-reported catchesterm·dom taken by Chinese distant water fleets fishing elsewhere. In the 2000s, Chinese distant water fleets operated in the EEZsterm·dom of over 90 countries, that is, in most parts of the world's oceans 5 . Harmonizing reconstructed catchesterm·dom with the reported baselines goes hand-in-hand with documenting the entire reconstruction procedure. Thus, every reconstruction is documented and published, either in the peer-reviewed scientific literature, or as detailed technical reports in the publicly accessible and indexed Fisheries Centre Research Reports series or the Fisheries Centre Working Paper series, or other regional organization reports ( Supplementary Table 5 ).

Several reconstructions were conducted in the mid- to late 2000s, when official reported dataterm (that is, FAOterm statistics or national dataterm) were not available to 2010date (refs 15 , 59 ). All these cases are updated to 2010date, in line with each country's individual reconstruction approach to estimating missing catchterm·dom data. Thus, all reconstructions are brought to 2010date to ensure identical time coverage ( Supplementary Table 5 ).

Since these six points were originally proposed, a seventh point has come to the fore that cannot be ignored 10 : (7) Quantifying the uncertaintyterm·mth associated with each reconstruction. In fisheries research, catchterm·dom data are rarely associated with a measure of uncertaintyterm·mth, at least not in the form resembling confidence intervals. This may reflect the fact that the issue with catchterm·dom data is not a lack of precisionterm·mth (that is, whether we could expect to produce similar results upon re-estimation), but about accuracyterm·mth, that is, attempting to eliminate a systematic bias, a type of error which statistical theory does not really address.

We deal with this issue through a procedure related to ‘pedigreesterm·mth' 60 and the approach used by the Intergovernmental Panel on Climate Change to quantify the uncertaintyterm·mth in its assessments 61 . The authors of the reconstructions are asked to attribute a ‘score' expressing their evaluation of the quality of the time series data to each fisheries sector (industrial, artisanal and so on) for each of the three time periods (1950date–1969, 1970–1989 and 1990–2010date). These ‘scores' are (1) ‘very low', (2) ‘low', (3) ‘high' and (4) ‘very high' ( Table 1 ). There is a deliberate absence of an uninformative ‘medium' score, to avoid the effective ‘non-choice' that this option would represent. Each of these scores is assigned a percentage uncertaintyterm·mth range ( Table 1 ). Thereafter, the overall mean weighted percentage uncertaintyterm·mth (over all countries and sectors) was computed ( Fig. 1 ).

Scoring system for deriving uncertaintyterm·mth bands for the quality of time series data of reconstructed catchesterm·dom.

Foreign catchesterm·dom We define foreign catchesterm·dom as taken by vessels of a maritime state in the EEZterm·dom, or EEZ-equivalent waters of another coastal state. Based on our definition of sectors, all foreign fishing in the waters of another country is deemed to be industrial in nature. As the High Seasterm·dom legally belong to no one (or to everyone), there can be no ‘foreign' catchesterm·dom in the High Seasterm·dom. Prior to UNCLOS, and the declaration of EEZsterm·dom by maritime countries, foreign catchesterm·dom were illegal only if conducted without explicit permission within the territorial waters of such countries (generally 12 nautical miles). Since the declarations of EEZsterm·dom by the overwhelming majority of maritime countries, foreign catchesterm·dom are considered illegal if conducted within the EEZterm·dom but without access being granted by the coastal state. A distinct exception is the EU, whose waters are managed by a ‘Common Fisheries Policy', which implies a multilateral ‘access agreement'.

Access permission can be tacit and based on historic rights (‘observed' access), or more commonly in the form of explicit access agreements and involving compensatory payment for the coastal state. The Sea Around Us , building on previous work by FAOterm 62 , has created a database of such access and agreements, which is used to allocate the catchesterm·dom of distant-water fleets to the waters where they were taken.

This information is then harmonized with the catchesterm·dom reported by FAOterm for countries fishing outside their country's ‘home' FAOterm areas, which always identifies this catchterm·dom as distant-water industrial catchterm·dom (see below for tuna catchesterm·dom reported to RFMOs).

In line with INTERPOL and others 63 , we define illegal fishingterm·dom as foreign fishing within the EEZterm·dom waters of another country without a permission to access these resources. We do not treat domestic fisheries' violations of ‘fishing regulations' as ‘illegal'. In general, our reconstruction method cannot readily distinguish between legal and illegal foreign fishing, as we do not necessarily know about all access agreements 5 , 6 . Thus, our data only pertain to ‘reported' versus ‘unreported' status, irrespective of legality of foreign fleets in a host country 5 . However, for around two dozen countries (mainly in West Africa) where the number of illegally operating vessels could be inferred, the fleet size can be multiplied by appropriate catchterm·dom per unit of effort rates, leading to an estimate of illegal catchterm·dom in these EEZsterm·dom.

Industrial catchesterm·dom of large pelagic fishes Nominal landings dataterm . To date, there is no single, publicly available data set presenting industrial landingsterm·dom of tuna and large pelagic fishes for the entire world that is separate from the amalgamated FAOterm statistics, despite these fisheries being among the most valuable in the world 64 . Here, we first compile nominal industrial landingsterm·dom of tuna and other large pelagic fishterm·dom caught either in the High Seasterm·dom or within EEZsterm·dom by fishing gear, taxon, countries and statistical reporting areas from data published by Regional Fisheries Management Organizationsterm. Second, we use partially spatialized landingsterm·dom data provided by staff of the French ‘Institut de recherche pour le développement' to spatially pre-assign the nominal landings dataterm derived from RFMOs ( Supplementary Table 6 ).

For each ocean, the nominal landings dataterm are spatialized according to reported proportions in the previously spatialized data ( Supplementary Table 6 ). For example, if the nominal data reports France catching 100 tonnes of yellowfin tuna ( Thunnus albacares ) in 1983 using longlines, but the spatial data only present 85 tonnes of yellowfin tuna reported in 1983 by France using longlines in four separate statistical cells, the nominal 100 tonnes for France are split into these four spatial cells according to their reported proportion of catchterm·dom in the spatial dataset. This matching of the nominal and spatial records is done over a series of successive refinements, with the first being the best-case scenario, in which there are matching records for year, country, gear and taxon. The last refinement is the worst-case scenario, in which there are no matching records except for the year of catchterm·dom. For example, if Sri Lanka reports 100 tonnes of yellowfin tuna caught in 1983 using longlines, but there are no spatial records for any country catching yellowfin tuna in 1983, the nominal 100 tonnes for Sri Lanka are split into spatial cells according to their reported proportions of total catchterm·dom of any species and gear in 1983. The end result is a baseline landingsterm·dom database containing all matched and spatialized catchterm·dom records, which sum to the original nominal catchterm·dom tonnages.

Discardsterm·dom . A review of the literature for each ocean provided limited country- and fleet-specific discardterm·dom data. Therefore, we average the discardterm·dom rates across the entire time period and apply these to the region of origin of the fleet (for example, East Asia or Western Europe), rather than the actual country of origin of the fleet. Discardsterm·dom were spatialized in conjunction with nominal landings dataterm.

Assembly of total catchesterm·dom Ultimately, the total catchterm·dom extracted from a given area, such as a given EEZterm·dom or EEZ-equivalent waters, or high seasterm·dom waters within a given FAOterm area is computed as the sum of three data layers: (1) the reconstructed domestic catchesterm·dom within home EEZsterm·dom (‘Layer 1' data); (2) the derived catch by foreign fleetsterm·dom (‘Layer 2' data); and (3) the tuna and other large pelagic fishesterm·dom caught in the High Seasterm·dom and in EEZsterm·dom (‘Layer 3' data).

Documentation of the catch reconstructionsterm·mth The references and web-links of the contributions documenting the catch reconstructionsterm·mth that went into the re-estimation of the global catchterm·dom of marine fisheries are documented in Supplementary Table 5 . Altogether, 273 EEZsterm·dom (or EEZterm·dom ‘components') were covered in 247 catch reconstructionsterm·mth, which had 103 unique first authors and 279 unique co-authors in over 50 countries.

All data presented here are also deposited in the Dryad Digital Depository (DOI: 10.5061/dryad.4s4t1).

Analyses To examine if significant breakpointsterm exist in the catchterm·dom data time series of both reconstructed total catchesterm·dom and reported catchesterm·dom that may illustrate a change in trends of catchesterm·dom over time (that is, a change in the slope), we analyse the time series trajectories using segmented regressionterm·mth 21 . For both the reconstructed as well as reported time series, we identify two breakpointsterm, being 1967 and 1996, respectively ( Supplementary Table 2 ). These breakpointsterm suggest a change in regression slope, with the second breakpointterm suggesting a trend reversalterm·dom. This was validated by testing for a significant difference-in-slope parameter using the Davies testterm·mth 65 , which tests for a non-zero difference-in-slope of a segmented regressionterm·mth relationship.

Additional information How to cite this article: PaulypersName, D. & ZellerpersName, D. Catch reconstructionsterm·mth reveal that global marine fisheries catchesterm·dom are higher than reported and declining. Nat. Commun. 7:10244 doi: 10.1038/ncomms10244 (2016).

Supplementary Material Supplementary Figures 1-2, Supplementary Tables 1-6 and Supplementary Acknowledgements Acknowledgments The Pew Charitable Trusts, Philadelphia funded the Sea Around Us from 1999 to 2014, during which the bulk of the catch reconstructionterm·mth work was performed. Since mid-2014, the Sea Around Us has been funded mainly by The Paul G. Allen Family Foundation and assisted by the staff of Vulcan, Inc., with additional funding from the Rockefeller, MAVA, and Prince Albert II Foundations. We thank our many collaborators, as listed in the Supplementary Acknowledgements, and also numerous additional colleagues who assisted in various aspects of this work over the last 15 years.

Footnotes References Associated Data Supplementary Materials Supplementary Figures 1-2, Supplementary Tables 1-6 and Supplementary Acknowledgements