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Juan-Jordá et al. 10.1073/pnas.1107743108 SI Text of immature yellowfin and bigeye (4). In the temperate fisheries, the purse seiners have also been increasingly catching 1. Background on Tunas and Their Relatives juveniles of Atlantic, Pacific, and Southern bluefin tunas to fulfill 1.1. . The family comprises 51 epipelagic the demand of the tuna farming industry, where tuna are fattened , commonly known as tunas, , Spanish before being sold in the global markets (5–7). At present, there (also known as seerfishes), and mackerels, which are distributed are more than 80 nations with tuna fisheries, and in the Indian throughout tropical and temperate oceans. The currently ac- and Pacific Oceans, tuna fisheries are still growing in many coastal cepted classification of the family Scombridae is largely based on developing countries (8). morphological studies, and it is composed of two subfamilies, four Spanish mackerels, bonitos, and mackerels are species with low tribes, 15 genera, and 51 species (Table S1). Fifty of these species economic value relative to the principal market tuna species and belong to the subfamily , which is divided into four are targeted largely by small-scale industrial and artisanal fisheries tribes Thunnini (tunas), Sardini (bonitos), Scomberomorini throughout their ranges. The small tunny species ( Thunnini (Spanish mackerels), and (mackerels) (1). The but- other than the principal market tunas), Spanish mackerels (tribe terfly kingfish (Gasterochisma melampus) comprises a monotypic Scomberomorini), mackerels (tribe Scombrini), and bonitos (tribe subfamily Gasterochismatinae. Sardini) are generally smaller coastal species associated with continental shelves. They are important forage fish that mediate 1.2. . Scombrid species have long been targeted mainly by the flow of energy from primary producers to top predators (9). artisanal fishing communities throughout the world, and until the The catches of scombrids other than the principal market tunas 1940s, most of the fishing occurred in coastal areas. The main have also increased significantly since the early 1950s. In the year industrialized fisheries for scombrids started between the 1940s 2008, around 5.2 mt of mackerels, Spanish mackerels, bonitos, and and 1960s, particularly targeting the tuna and species. small tunas were caught worldwide (Fig. 2A). The most important These fisheries expanded rapidly, operating nowadays in most species of scombrids other than the principal market tunas in latitudes of all oceans. The annual catches of scombrids have terms of weight are as follows: , japonicus grown continuously, rising from 1.1 million tonnes (mt) in 1950 to (∼2 mt); , Scomber scombrus (∼600,000 tonnes); 9.5 mt in 2008 (Fig. 2A). The tunas (tribe Thunnini) includes the Spanish mackerels, not specified (∼500,000 tonnes); , most economically important group of species, known as the brachysoma (∼310,000 tonnes); , not principal market tunas, which are ( alalunga), specified (∼300,000 tonnes); kawakawa, affinis (∼280,000 (Thunnus obesus), Atlantic bluefin tuna (Thunnus tonnes); Indian mackerel, Rastrelliger kanagurta (∼280,000 tonnes); thynnus), Pacific bluefin tuna (Thunnus orientalis), Southern longtail tuna, (∼277,000 tonnes); frigate and bullet bluefin tuna (Thunnus maccoyii), yellowfin tuna (Thunnus alba- tunas, thazard and Auxis rochei, respectively (∼230,000 cares), and (Katsuwonus pelamis). The principal tonnes); and narrow-barred , market tunas are oceanic and highly migratory, and they are commerson (∼220,000 tonnes) (10). These catches are possibly un- among the largest and fastest top predators of the high seas. derreported in all the taxonomic groups (11), particularly even more They are the most economically important species because of so for the small tunnies, bonitos, and Spanish mackerels. their predominance in the global fish exports and their intensive international trade for canning and (2). The catches of 1.3. Fisheries Management. Several and diverse international and principal market tunas have increased continuously from less intergovernmental organizations have been created to manage than 0.2 mt in the 1950s to over 4.2 mt in 2008 (Fig. 2A). scombrid species because of their highly migratory nature, their Skipjack and yellowfin tunas account for the greatest proportion widespread oceanic and coastal distributions, and their economic of the principal market tuna world catches in terms of yield (3.5 importance for many countries. There are currently five Regional mt in the year 2008), and most of these catches are directed to Fisheries Management Organizations (RFMOs) whose mandates the canning industry (3). Atlantic, Pacific, and Southern bluefin include the management and conservation of tuna and tuna-like tunas contribute little in terms of total catches in weight but are species in their areas of jurisdiction. The term “tuna and tuna-like” very important in terms of their individual economic value. The species includes the tunas (tribe Thunnini, which comprise the principal fishing methods used by the industrial fleets are purse principal market tunas and the small tunny species), the bonitos seine, longline, bait boat (or pole and line), and . Each (tribe Sardini), the Spanish mackerels (tribe Scomberomorini), type of gear is designed to target different species at different and the billfishes, which all belong to the suborder depths. Purse seine and bait boat are used to catch fish close to (12). Therefore, all the species of the family Scombridae, except the surface, for example, skipjack tuna or juveniles of yellowfin, the mackerels (tribe Scombrini), are considered tuna and tuna-like albacore, and bluefin tunas. The longline fisheries usually target species. The five RFMOs, also known as tuna commissions, are the the largest and oldest individuals found at greater depths, for International Commission for the Conservation of Atlantic Tunas example, adult bigeye, yellowfin, and bluefin tunas. In the recre- (ICCAT), the Tuna Commission (IOTC), the Inter- ational sector, the principal fishing methods used involve mostly American Tropical Tuna Commission, the Western and Central surface trolling and bait-boat fishing, whereas the artisanal fish- Pacific Commission (WCPFC), and the Commission for eries use a great variety of methods, such us gillnets, beach seines, the Conservation of Southern Bluefin Tuna (CCSBT). The bait boat, handlines, harpoons, and traps. In the tropical tuna CCSBT is the only tuna RFMO that is in charge of only a single fisheries, the catch by purse seiners using floating platforms to tuna species (the Southern bluefin tuna). In addition, the In- attract schools of tuna, called fish aggregating devices (FADs), has ternational Scientific Committee for tuna and tuna-like species in increased gradually since the 1990s, resulting in an increase in the the North Pacific Ocean conducts fisheries research on tuna and mortality of immature tunas globally. Although purse seiners us- tuna-like species in the North Pacific Ocean and cooperates with ing FADs mainly target skipjack tuna, they do not discriminate other tuna RMFOs in the region. Thus, the tuna commissions are among tropical tuna species, causing an increase in the mortality mandated to manage and conserve not only the principal market

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 1of21 tuna species but smaller tunny species, bonitos, and Spanish agement plans, possibly supported with stock assessments, and mackerels that are harvested within their jurisdiction. Commonly, (ii) which institutions were in charge of their evaluation, man- the tuna commissions concentrate most of their effort, resources, agement, and conservation. Next, to compile the most updated and personnel into managing the principal market tuna species stocks assessments and their respective reports, we contacted and billfishes, giving less priority to the rest of species. Although many institutions worldwide, from international to intergovern- the ICCAT and IOTC have working groups on the small tuna mental, as well as national fisheries institutions and individual species, the lack of fisheries data and insufficient biological scientists, which were in charge of the evaluations of any scom- knowledge generally paralyze any attempt to carry out stock as- brid species. There are several stock assessment modeling ap- sessment evaluations (12, 13). proaches varying in complexity and data requirements, ranging There are some exceptions in the use of the terms tuna and tuna- from simple surplus production models to sophisticated statisti- like species by the tuna RFMOs. The mandate of the WCPFC is cal catch-at-age models. Because we were interested in gathering such that it is the only commission to use the term “highly migratory population estimates of abundance at age, biomass at age, and fish stocks” instead of the term “tuna and tuna-like” species. The fishing mortality rates at age from the assessments, we limited our highly migratory fish stocks term refers to the species listed in data collation to only those stock assessments that used age- Appendix I in Article 64 of the United Nations Convention of the structured models, either of the virtual population analysis family Law of the Sea (UNCLOS). This term includes some of the (e.g., independent catch analysis, used for Northeast Atlantic scombrid species (the principal market tunas, blackfin tuna, mackerel) or statistical catch at age family (e.g., multifan-CL Thunnus atlanticus; , A. rochei; , A. thazard; applied to various tuna stocks). The standard biological reference , Euthynnus alletteratus; and kawakawa, E. affinis), ratios, the current adult biomass relative to which would provide fi fi bill shes, dolphin shes, oceanic , and sauries. The WCPFC the MSY (B/BMSY) and current fishing mortality relative to the is mandated to manage and conserve all species of highly migra- fishing mortality rate, which maintains MSY (F/FMSY), were also tory fish stocks within the convention area, except sauries. Thus, extracted from the stock assessments when available. the term highly migratory fish stocks does not include the bonitos, The data collection yielded stock assessments varying in Spanish mackerels, and some of the small tunnies (black skipjack, quality, methodology used, temporal coverage, and data avail- ; longtail tuna, T. tonggol; and slender tuna, ability. We did not include in our analysis stock assessments that Allothunnus fallai) that probably constitute “straddling stocks” (i) were considered unreliable by the scientist undertaking them, under the UNCLOS. Finally, all the tuna RFMOs recognize the (ii) were outdated (before 2000), (iii) were not carried out with obligation to manage and conserve the harvested species but also age-structured stock assessment models like biomass dynamic to conserve the associated and dependent species that are taken models, or (iv) provided estimates of population biomass for a incidentally during the tuna fishing activities (4). Small tunny time period shorter than 15 y. species, Spanish mackerels, and bonitos are commonly discarded by longliners and purse seine tuna fisheries (14). Finally, we would 2.2. Uncertainties and Caveats of Stock Assessments. Although data like to point out that there are other intergovernmental fisheries obtained from stock assessments are generally regarded as the organizations, such as the Caribbean Regional Fisheries Mecha- preferred source of information with which to assess the effects nism, which have defined strategic objectives and management of fishing on fish populations and ecosystems (15–18), there are plans and have recently started to evaluate the status of some many sources of uncertainty surrounding the stock assessment coastal scombrid species in the Caribbean Sea. models, which might create some unknown bias in the data Mackerel species are not under the mandate of any of the tuna outputs. The uncertainties surrounding stock assessments may RMFOs. The fisheries of mackerels are more localized. Often, arise by a combination of several factors, such as the variety of their distributions occur either in regions where the continental data sources used, the numerous inputs needed, or the limited shelf extends beyond the exclusive economic zone (EEZ) limit or knowledge about the dynamics of the population, all of which are in coastal regions where the productivity is very high (upwelling very complex to quantify. All this uncertainty is commonly regions), which extends their distributions into the high seas; characterized in observation errors and model errors, with both therefore, the mackerels are considered straddling stocks (and leading to estimation errors in the results of the stock assess- not highly migratory fish stocks). Straddling stocks under Article ments (19). Observation error may arise because of measure- 63 of the UNCLOS, are “the same stock or stocks of associated ment errors (e.g., in the weight and length of the catches) or species [which] occur both within the exclusive economic zone sampling errors (e.g., in the surveys). Model error may occur and in an area beyond and adjacent to the zone” (13). Therefore, because of the lack of knowledge of the biology of fish or the neighboring coastal states and fishing entities should coordinate inability of the models to model all the processes that affect the the management and conservation of these stocks, and in- dynamics of a fish stock. Many of these uncertainties can be tergovernmental regional organizations are usually set up for this identified and quantified in the stock assessment evaluations purpose. Although there are some intergovernmental regional using several types of models and their respective sensitivity organizations in charge of evaluating the stock status of mack- analyses to test different hypothesis and model assumptions. erels (e.g., the International Council for the Exploration of the Therefore, in any stock assessment evaluation, it is very common Sea, which provides scientific advice for the Northeast Atlantic to find the results of several models with their respective sensi- mackerel stock), most of the time, the mackerel species are tivity analyses, all of which attempt to characterize the status of evaluated separately by each individual country (e.g., Japan, a population and the associated uncertainty. During the data ). A combination of insufficient information with which to compilation of this study, when several stock assessment models delimit population distributions clearly and the lack of institu- and several variations of the models (sensitivity runs) were tional arrangements among neighboring countries to manage re- available for one population, we used the base-case model sources jointly leads individual states to carry out independent fish- specified in the stock assessment report to extract the estimates eries research for their fish populations in the best case scenarios. of biomass and fishing mortality over time or as advised by the stock assessment scientist. In our analysis, we did not take into 2. Stock Assessment Data account the uncertainties associated with the estimates of bio- 2.1. Data Sources and Data Selection. We conducted a global lit- mass, fishing mortality rates, and biological reference points erature search to locate the most important commercial fisheries extracted from the stock assessments. We merely summarize the for scombrid species, with the primary aim of identifying (i) which consensus choices of the stock assessment teams as to the best populations could potentially be under scientific review or man- parameter settings. Nonetheless, we acknowledge that the un-

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 2of21 certainties in model outputs may be creating some unknown several stock assessment methods specific for data-poor stocks biases in our results. We therefore highlight the importance of (22, 23). consulting the original assessment reports when seeking in- The mackerels (tribe Scombrini) include the temperate mack- formation on the uncertainties surrounding the status of the erels (Scomber sp.) that are usually evaluated with formal quan- individual stocks. titative stock assessments, whose status is generally known, and We also attempted to compile the most recent available stock the tropical mackerels (Rastrelliger sp.) that are either not evalu- assessments for scombrid populations around the world. How- ated or evaluated with simple stock assessments methods; there- ever, we are aware that some populations have been reevaluated fore, their status is generally unknown or highly uncertain. The throughout the development of the present work. In the case of temperate mackerel species sustain one of the largest commercial the biological reference points, we extracted them from the most fisheries worldwide, particularly the chub mackerel, which is recent stock assessments up to February 2011 to present the most among the 10 most fished species in the world (3). Consequently, updated exploitation status of tunas and their relatives (Table S2). some temperate mackerel populations have been relatively well We definitely encourage future studies to update this work every monitored and evaluated by national and intergovernmental few years, including the most updated information possible, to fisheries organizations. We were able to obtain reliable age- reassess the global status of scombrids. Perhaps the consortium of structure stock assessments for five mackerel populations (Table tuna RFMOs under the Kobe agreement could be responsible for S2). In addition to the mackerel populations included in our continuously updating this type of analysis for the species under analysis, it is worth mentioning other temperate mackerel pop- their mandate. ulations that are currently being managed with age-structured stock assessments but, for several reasons, were not included in 2.3. Description of Stock Assessment Data and Identification of Data our analysis. First, we did not include in the analysis two blue Gaps. After the data screening, we ended up with stock assessments mackerel populations (Scomber australasicus) distributed along for 26 populations (11 species) of scombrids, composed of the the coastal waters of Japan (Japanese and Tsush- following: 17 principal market tunas (7 species), five mackerels (2 ima Current blue mackerel) because the population assessment species), and four Spanish mackerels (2 species) of a total of 51 evaluation covered less than 15 y of data (24, 25). Second, we did species of scombrids that we included in our analysis (Table S2). not include the Northwest Atlantic mackerel population (Scomber By geographic regions, we were able to obtain information for 11 scombrus) distributed along the eastern coast of the United States populations in the , 12 populations in the Pacific and Canada. In the recent past, the US and Canadian govern- Ocean, 2 populations in the Indian Ocean, and 1 population in the ments have evaluated this population separately (26, 27). How- Southern Ocean (Fig. 1). The small number of exploited species ever, the population is currently being assessed as a larger evaluated with age-structure stock assessments in the Indian geographic unit in a joint assessment between the US and Ca- Ocean stands out because 34 species of scombrids are found in the nadian governments. The joint stock assessment report only be- Indo-Pacific region and 23 of those are endemic to the region. came available after this paper was written (28). Finally, we are Next, we summarize the data availability and accessibility by not aware of any formal quantitative stock assessment evaluations taxonomic group. for any of the tropical mackerel species (Rastrelliger sp.) in the Among the four major taxonomic groups of scombrids, the Indian Ocean. However, the data availability and status of some tunas (tribe Thunnini), particularly the principal market tunas, mackerel fisheries have recently been evaluated with simple stock have been largely assessed and their status is generally known. assessment methods in several countries in the There are 23 populations of principal market tunas (7 species) region (22, 23). managed by the five tuna RFMOs. Seventeen of the 23 pop- The Spanish mackerels (tribe Scomberomorini) have the ulations are currently evaluated with age-structure stock assess- largest number of species (18 species), and with some notable ment models (Table S2). The rest of the stocks (i) are evaluated exceptions, the status of the large majority of the species is very with surplus production models (Indian Ocean albacore tuna uncertain or little known. For our analysis, we were only able to and East and West Atlantic skipjack tuna stocks), (ii) are eval- collect reliable quantitative stock assessments for four Scom- uated based on several indicators of stock status because of the beromorus populations (2 species) that sustain important fish- difficulties of developing proper stock assessment models for eries on the southeastern coast of the United States (29, 30). these populations (Indian Ocean and East Pacific skipjack tuna This is worrying, given the importance of the Spanish mackerel stocks), or (iii) have not been evaluated yet (Mediterranean al- fisheries worldwide, especially in the Indo-West Pacific region, bacore tuna population, although its assessment is planned for where 11 of the 18 species are found and sustain important the year 2011). fisheries throughout their distributions (31). Although we were We are not aware of any formal quantitative stock assessment not able to obtain reliable and complete formal quantitative evaluations using age-structured models for any of the rest of stock assessment evaluation for four Scomberomorus pop- the tuna species. In general terms, the status of the small tunny ulations, it is worth mentioning several cases in which Spanish species is poorly known around the world. The fisheries targeting mackerel species have been evaluated in the past or are currently small tunny species usually involve mostly developing countries, being evaluated at least in some regions throughout their dis- which have limited resources for research, monitoring, and tributions. First, there are several populations of the narrow- management capacity (13). However, we would like to highlight barred Spanish mackerel (S. commerson) and spotted mackerel recent efforts to evaluate the status of several coastal scombrids (Scomberomorus munroi), the most important commercial with simpler stock assessment models. First, the blackfin tuna Spanish mackerel species in , that are currently being stock distributed off the coast of Brazil has recently been eval- assessed with age-structure stock assessment models (32–35). uated (20). Second, the longtail tuna stock distributed off the However, these populations were not included in our analysis northern coast of Australia has also been evaluated (21). Third, because they did not provide the type of data needed for our the United Nations Food and Agricultural Organization has analysis or the time coverage of the assessment data was too recently carried out two workshops to review fisheries data and short or not available to us. Second, there are several species of to update and carry out stock assessments for fish resources in Spanish mackerels (S. commerson, Scomberomorus niphonius, the South and Southeast Asia regions. During these workshops, and Scomberomorus brasiliensis) whose stocks have been evalu- many coastal small tunny species (e.g., Auxis sp. and Euthynnnus ated in the past with simple stock assessment methods, for ex- sp.), tropical mackerel species (Rastrelliger sp.), and tropical ample, in Thailand (36), the Southeast Asia region (22, 23), Spanish mackerels (Scomberomorus sp.) were evaluated using India (37, 38), Oman (39, 40), the southern Arabian Gulf (41),

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 3of21 Djibouti (42), Japan (43), and Brazil (44). However, we did not revenues has been reversed in the Mediterranean and Black Seas use these stock assessment evaluations because (i) they were very (46), as is probably the case for many other regions of the world. outdated (before 2000), (ii) the results were highly uncertain, Coastal scombrids, although low in economic value for the global (iii) they were not evaluated with age-structure models, or (iv) markets, sustain and feed many of the coastal fishing economies they were inaccessible. The development of age-based stock as- in many developed and developing countries around the world. sessment models would particularly benefit and ease the man- Therefore, a review of existing frameworks and their suitability agement of Spanish mackerels because many of the species can for the needs of some species might be needed to identify gaps in reach relatively large sizes and are relatively long-lived compared the mandates of existing management bodies, identify opportu- with other scombrid species, such as the tropical mackerels and nities for further collaboration across states and fisheries or- the small tunny species. ganizations, and promote international efforts to quantify better Lastly, the status of the bonitos (tribe Sardini), composed of the status and outlook for more coastal scombrids other than seven coastal species, is unknown throughout the world. We are the principal market tuna species. We highlight the present col- not aware of any stock status evaluations of any type for any of the laborations between the ICCAT and the Caribbean Regional species distributed around the world. Fisheries Mechanism and between the ICCAT and the General Based on our global literature search and findings, we can Fisheries Commission for the Mediterranean to improve the conclude that accurate and reliable formal quantitative stock as- knowledge on the sustainable exploitation of small scombrid sessment evaluations and fisheries advice are unknown or highly fisheries. uncertain for most of the scombrid species, with the notable ex- An issue of open access is also of relevance here. Stock ception of the principal market tunas and some temperate assessments or catch statistics could not be obtained for some mackerel species. We are aware that the coverage of this study, in stock assessments for which they are known to exist. Contacts with terms of the number of commercially important populations the relevant scientific or management bodies proved unsuccessful. identified and number of stock assessments obtained, is not ex- One of the major impediments to global analysis is that there are haustive. However, to our knowledge, we identified and compiled no global repositories of fisheries data under common formats the majority of formal quantitative age-structured assessments and containing the multiple sources of information related to expanding at least 15 y of data available worldwide for scombrid fishing (e.g., catch statistics, stock assessment inputs and outputs, populations. Nevertheless, the compilation is evolving and new economic data) as is the case for many biological and physical assessments will be incorporated into the dataset for future oceanographic datasets (e.g., World Ocean Database). The analysis. We welcome institutions and individual scientists wishing creation of global fisheries repositories has been proposed many to contact us and share information about the status of scombrid times (e.g., 47), with no immediate measurable results; however, species not covered by this study. there are some recent ongoing initiatives to compile all fish stock assessments globally (16, 18). In addition, the five tuna RFMOs 2.4. Major Conclusions on Stock Assessment Data Compilation and have started a dialogue to create common initiatives to organize Recommendations. We summarize the global status and biomass and standardize several types of fisheries data from all the tuna trajectories of 26 populations (11 species) of scombrids using commissions into common formats to facilitate the accessibility population estimates from age-structured models prepared by of data to all the stakeholders and exchange of knowledge (48). stock assessment scientists. By limiting the data to age-structured These types of initiatives and others should be pursued in the models, we could evaluate the effects of fishing on the adult short term. Large, global, unbiased fisheries datasets would biomass of scombrid populations over time but at the cost of being definitely benefit and motivate more analyses needed to evaluate able to include only the most important commercial species of the global status of marine fish resources and quantify impacts of scombrids. Thus, some of the taxonomic groups, the Spanish fishing on marine species and ecosystems. mackerels and the bonitos, and many regions are clearly un- derrepresented in the analysis. However, the 26 populations of 3. Statistical Analysis scombrids included in this analysis expanded the number and 3.1. Data Assumptions. We quantified fishing impacts on adult coverage of scombrids previously accounted for in past studies biomass from 1954 to 2006 because the majority of the data (16, 18, 45). available started after the 1950s and finished in 2006 (Fig. 1B). The 26 populations of 11 species of scombrids evaluated with However, an approach was needed to estimate the adult biomass formal quantitative age-structure stock assessments collated in for those populations for which biomass started after 1954 and/ this study seems small, given the fact that scombrid species sustain or finished before 2006. For those time series starting after 1954, some the largest fisheries in the world. All the species of we extended the adult biomass backward using the mean of the scombrids, except slender tuna (Allothunnus fallai), plain bonito first 3 y of data. Thus, we assumed that from 1954 to the first year (), and butterfly kingfish (Gasterochisma with data, there have been no major fisheries targeting these melampus), are targeted by industrial and/or small-scale fisheries populations; therefore, the adult biomass has not changed over throughout their ranges. The disparity between the existing time. This is a conservative approach in which we are likely number of populations being exploited and those that could be underestimating some of the impacts of fishing, because fishing included in this analysis can be attributed to two reasons. First, began long before the start of many of the time series summa- there are a large number of scombrid populations for which rized here. The first year in a stock assessment does not usually virtually no data are available and for which no scientific advice correspond with the start of the fishery; thus, stock assessments or analysis of their status is currently being carried out. Second, may often not capture past declines well. some of these data are not openly available and some of them For those time series finishing before 2006, we extended them are simply not open to scrutiny and analysis in the case of both forward to 2006 using two different approaches. For most pop- fisheries data and assessment results. ulations, we only needed to extend them for a few years, 1 or 2 y in It appears that the current structure of tuna RFMOs might not the majority of cases. In the first approach, we used an average of be appropriate or might be lacking in capacity to provide quan- the past 3 y to project the biomass forward up to 2006, therefore titative scientific advice for many small tunas, bonitos, and Spanish assuming no change in biomass. In the second approach, we used mackerels, and some of them might not even be under the remit of the model-estimated average annual rate of change of each in- any international organization despite populations that usually dividual population to project the adult biomass forward; there- stretch across national boundaries. The widespread perception fore, assuming biomass of the past few years follows a trend based that small tuna fisheries are irrelevant in terms of catches or on past data. Both assumptions are plausible because recent

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 4of21 fishing mortality for the majority of the populations has not been within each species was too low (a maximum of 4 populations per reduced over the past few years. In addition, by projecting forward species). To estimate trends in the average annual rate of change using the average rate of change of each population, we are also of adult biomass from 1954 to 2006 within species, we first es- assuming that the statistical properties, such as the mean and timated the average of the annual rates of change in adult bio- variance of the rate of change, do not themselves change over mass from 1954 to 2006 for each population using a generalized time, which might not be the case in some of the time series. least-squares model of the form Yi =bo +ei (SI Text, Section Therefore, this second approach might have created some bias in 3.2). Second, we combined the single population average annual the estimated declines, although such bias would be small, because rate of change estimated in the first step within each species we are projecting forward only for a few years into the future. This using weights according to the inverse of the SEs of the esti- assumption would not have been appropriate for medium- and mates (Fig. S2A). long-term projections but seems reasonable enough in this case. We obtained very similar results using both approaches; therefore, 3.5. Estimation of the Average Mortality over Time Across All our results are robust to the choice of method. the Populations. To estimate what percentage of tunas and their relatives are caught each year by fisheries, we used the matrices of 3.2. Estimation of the Average Annual Rate of Change in Adult fishing mortality at age over time for each population from the Biomass Across All Populations over Time. We tested if the aver- stock assessments. For each population, we then calculated the age annual rate of change in adult biomass across all of the weighted average fishing mortality across all ages, using the populations (global estimate) was accelerating or decelerating abundances by age. We then estimated an average annual fishing over time using a submodel of the full mixed model (full model mortality rate across all the populations (Foverall) by taking a shown in the main text). The submodel consisted of keeping the weighted average of the average annual fishing mortality rates of covariate X (year) and eliminating the covariate W from the full each population, weighting them by the total number of in- mixed model. By keeping the covariate X (year) in the model, we dividuals in each population. Finally, we used the estimated av- are interested in the overall global trend and could test if the erage annual fishing mortality rate across all the populations covariate year is significantly different from zero. A slope sig- (Foverall) to calculate the annual percent removal of fish attrib- nificantly different from zero indicates that the average annual utable to fishing using the Baranov catch equation, (F/(F + rate of change in biomass has been changing over time, either M))·(1 − exp(−(F+M))), where F is the instantaneous fishing accelerating and becoming more negative (negative rate) or ac- mortality rate and M is natural mortality rate (Fig. 4B). We es- celerating and becoming more positive (positive trend) over timated that fisheries currently catch around 10–15% of the tu- time. Our data suggest that the global rate has been constant nas and their relatives each year globally (F2003–2005 = 0.16 and − over time (γ10 = −0.00027, P = 0.19); therefore, it has neither using a natural mortality rate of 0 0.85; Fig. 4B). The complete decreased nor increased across all the populations. At present, matrix of fishing mortality at age over time was only available for the majority of populations have been fished roughly around 21 of the 26 populations under study. The matrix of fishing MSY levels (Fig. 4A); therefore, the majority of the populations mortality at age over time was not available, or harvest rates were are currently fully exploited. We would expect in the near future provided instead, for the following populations: Pacific bluefin to see a deceleration in the average annual rate of decline to tuna, Japanese chub mackerel, Tsushima Current chub mackerel, fulfill the international biodiversity commitments and fisheries and Southern bluefin tuna. Therefore, these populations were targets of maintaining populations at MSY and, when necessary, not included in the analysis. to halt and reverse declines and recover populations to the level that would generate MSY. 4. Population Trajectories in Adult Biomass and Their Current Management Status 3.3. Estimation of the Average Annual Rate of Change and Extent of 4.1. Current Management Status of Tunas and Their Relatives Ac- Decline in Adult Biomass for Each Population. We estimated the cording to the Reference Points (B/BMSY and F/FMSY). The biological average of the annual rates of change in adult biomass across all reference points, B/BMSY and F/FMSY, were available for 21 of the years for each population using a generalized least-squares the 26 populations of tunas and their relatives (15 tuna pop- model of the form Yi =bo +ei.Yi, the dependent variable, is the ulations, 4 Spanish mackerel populations, and 2 mackerel pop- annual (i) rate of change in adult biomass of each population; b0, ulations) (Table S2). For the remainder of the populations, these the intercept, is interpreted as the average annual rate of change reference points were either not estimated as part of the as- in adult biomass across all the years (Fig. S5A); and ei is the sessment process (some mackerel populations) or were consid- residual error. For these analyses, we used the raw time series of ered highly uncertain by the assessment scientists and were not adult biomass of each population; therefore, the time series of included (Pacific bluefin tuna and North Pacific albacore tuna). each population differs in time coverage and time span (Fig. 1B). We define “overfished” to mean that the biomass of the population We used maximum likelihood to fit all the generalized least- has been reduced to a level less than that which would provide the square models using the gls function in the NLME package in R MSY (B < BMSY)and“overfishing” to mean that a population (49). We examined the residuals of all the models and corrected is being subjected to a fishing effort greater than that required to for temporal autocorrelation with AR1 and AR2 processes when produce the MSY (F > FMSY), a definition used by the majority necessary. In addition, we estimated the extent of decline for of the tuna RFMOs (50). According to the biological reference each individual population as follows: (1 − exp(bo·n))·100, where points, the current status of the four Atlantic Spanish mackerels fi bo is the model estimated average annual rate of change for each is healthy with adult biomasses above BMSY and current shing individual population and n is the length of the time series of mortalities below FMSY (Fig. 4A and Table S2). Among the 15 each individual population (Fig. S5B). tuna populations with biological reference points, 8 populations are sustainably exploited with biomasses above BMSY and fishing 3.4. Estimation of the Average Rate of Change in Adult Biomass mortality lower than FMSY. Only the West Pacific bigeye tuna is Within Species. Although we used mixed-effects models to per- being subjected to a fishing effort greater than that required to form a metaanalysis of population trends in adult biomass to produce the MSY. Four tuna populations, all temperate tunas, estimate annual rates of change globally, within oceans, within the are overexploited, with current biomasses being below BMSY, main taxonomic groups, and within distinct life history strategies, and experiencing excessive fishing mortality rates (F > FMSY). we did not use mixed-effect models to estimate the average rates Finally, 2 tuna populations, the South Atlantic albacore tuna and of change within species, because the number of populations Atlantic yellowfin tuna, are overfished with current biomasses

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 5of21 below BMSY but are not experiencing overfishing (F < FMSY). populations, mostly tropical tunas and Spanish mackerels, that Therefore, three distinct exploitation categories are evident in are healthy with biomass levels above target levels (B > BMSY) “ ” the tuna populations (Fig. S6). On one extreme, the good and fishing mortality rates not exceeding FMSY (F < FMSY). category comprises moderately exploited and successfully man- These healthy exploited populations have decreased at a rate of − aged populations: West Pacific skipjack and South Pacific alba- −1.1% y 1 (95% CI: −2.1 to −0.1) and have declined, on aver- core. On the other extreme, the “ugly” category comprises the age, by 43.9% since 1954 (Figs. S4C and S5C). The overall extent populations that are overexploited and managed poorly: Eastern of decline in total adult biomass in these 12 healthy populations and Western Atlantic bluefins and Southern bluefin. Finally, in has been 42.8% since 1954 (Fig. S5D). Finally, there are 6 the “fully exploited” category separating these two extremes, the populations of tunas and mackerels that either have biomasses majority of the populations circle MSY. The reference points of below healthy levels or fishing mortality rates exceeding healthy fi fi fi 2 tuna populations, the Paci c Blue n tuna and the North Paci c levels but not both (B < BMSY or F > FMSY). These populations − albacore tuna, were considered highly uncertain by the assess- have decreased at a rate of −2.1% y 1 (95% CI: −3.7 to −0.6) ment scientists and were not included. Finally, only 2 of the 5 and have experienced an average decline of 67.7% since 1954 mackerel populations had estimates of biological reference (Figs. S4B and S5C). They have also experienced an extent of points. The Northeast Atlantic mackerel is considered healthy decline in total adult biomass of 58.7% since 1954, similar to that fi with current biomass at BMSY and shing mortality rates lower exhibited by the overexploited populations (Fig. S5D). than FMSY (51). The current biomass of the Chilean chub We found that the link between the trajectories of adult bio- fi mackerel is above BMSY, and the current shing mortality rates mass and their current management status remains at the pop- are higher than FMSY (52). The reference points BMSY and FMSY ulation levels (Fig. S5 A and B). However, there are some were not estimated as part of the stock assessment process for discrepancies between the trajectories of the individual pop- fi the Japanese chub mackerel and the Northeast Paci c chub ulations and their current management status; populations ex- mackerel. However, since 2003, there have been measures to fi hibiting the largest declines are not always currently considered reduce shing mortality rates and recover the Japanese chub as being unsustainably exploited, and vice versa. First, two chub mackerel population to healthy levels (53). For the Northeast mackerels (the Chilean and the Northeast Pacific populations) Pacific mackerel, the exploitation rate is currently low. This fi have experienced the steepest and most variable declines, yet shery collapsed in the 1960s and recovered afterward. The their exploitation statuses are not currently considered over- current biomass still remains very low relative to its historical exploited. In the case of the Chilean chub mackerel, the most peaks because of a combination of historical fishing pressure and recent current biomass (2006) was still considered within safe unfavorable oceanographic conditions (54). levels but close to unsuitable levels if the exploitation rates were We would like to highlight that the current exploitation status not reversed (52). For the Northeast Pacific mackerel, the ex- of tuna populations and their relatives can be easily categorized ploitation rate is currently low because of the collapse of the according to their standard biological reference points, although fi it is important to take into account two points. First, there is important commercial shery it once supported. Although the uncertainty associated with the estimated reference points. stock collapsed in the mid-1960s and recovered afterward, the current biomass still remains very low relative to its historical Second, the reference points for the majority of tunas and their fi relatives, despite their assigned exploitation status, are roughly at peaks as the result of a combination of historical shing pressure and unfavorable oceanographic conditions (54). Second, the MSY. Most of the populations are considered fully exploited; fi thus, the expansion of the catches in these fisheries is limited. South Paci c albacore is deemed healthy, despite having expe- rienced one of the largest declines. The large declines may be 4.2. Link Between Population Trajectories and their Current Manage- partly spurious, attributable to a poorly fit stock assessment ment Status. There is a consistent link between the population model resulting in overestimates of the adult biomass in the trajectories in adult biomass and their current exploitation status earlier periods (55). Last, the current management status for the (Figs. S4 and S5). First, there are a total of 4 overexploited Eastern Atlantic bluefin tuna is overexploited, despite relatively populations, all temperate tunas, with current biomasses below small declines in adult biomass compared with the other over- target levels (B < BMSY) and experiencing excessive fishing exploited populations. This may be attributable to a shifted mortalities (F > FMSY). These overexploited populations have baseline perspective, because the population estimates start only − exhibited the steepest rate of decline, −3.7% y 1 (95% CI: −5.2 in the 1970s. The Eastern bluefin tuna has a long history of ex- to −2.1) and, on average, have declined by 85.7% from 1954 to ploitation and mismanagement accompanied by substantial 2006 (Figs. S4A and S5C). These overexploited populations have quantities of illegal, unreported, and unregulated fishing in re- also experienced a large extent of decline in total adult biomass, cent history, which makes it difficult to estimate the historical 84.8% since 1954 (Fig. S5D). Second, there are 12 healthy population trajectory (56, 57).

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Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 7of21 Fig. S1. Trajectories of adult biomass (1,000 tonnes) for 26 populations of tunas and their relatives (11 species). The values indicate initial and final adult biomass estimates. The horizontal gray lines delineate a biomass of zero. Abbreviations for population names: E., east; G.O.M., Gulf of Mexico; N., north; N.E., northeast; S., south; T.C., Tsushima Current; U.S., United States; W., west. Population trajectories are colored according to their exploitation status. Red populations are overfished (B < BMSY) and experiencing overfishing (F > FMSY). Orange populations are overfished or experiencing overfishing (B < BMSY or F > FMSY but not both). Green populations are not overfished (B > BMSY) and are not experiencing overfishing (F < FMSY). Population trajectories for which reference points were unavailable are colored in gray (SI Text, Section 4.1). Populations are plotted in descending rank order of abundance at former levels, with the least abundant at the bottom.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 8of21 Fig. S2. Metaanalysis of fishing impacts on adult biomass globally, within major oceans, within the major taxonomic groups, within ecological groups, within species, and within life history strategies using maximum body size as a proxy. (A) Average annual rates of change in adult biomass (average % per year ± 95% CIs) from 1954 to 2006. (B) Overall extent of decline or recovery in total adult biomass from 1954 to 2006. The number of populations within each category is shown between parentheses. Albacore and bluefin tunas are considered temperate tunas, and skipjack, yellowfin, and bigeye tunas are considered tropical tunas. Species were grouped according to their maximum body size [large, >2 m fork length (FL); medium, >1 m and <2 m FL; small, <1 m FL), which we used as a proxy to describe life history strategies. The maximum body size of species is provided in Table S1.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 9of21 Fig. S3. Box plots of the annual rates of change (ri) in adult biomass for the 26 populations of tunas and their relatives. Mackerel populations exhibit greater interannual variability. Fig. S7 shows the time series of the annual rates of change (ri) for each population. Abbreviations for population names: E., east; GOM, Gulf of Mexico; N., north; N.E., northeast; S., south; T.C., Tsushima Current; U.S., United States; W., west.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 10 of 21 Fig. S4. Relative adult biomass trajectories (thick solid line) of tunas and their relatives within each exploitation status category, which was standardized to 1 in 1954. Faint and dashed lines show the effect of excluding one population at a time from the overall trend and recalculating the relative adult biomass. Dashed lines delineate the most influential populations. Trajectories are colored according to the exploitation status of populations. Red populations are overexploited; they are overfished (B < BMSY) and experiencing overfishing (F > FMSY). Orange populations are overfished or experiencing overfishing (B < BMSY or F > FMSY but not both). Green populations are healthy; they are not overfished (B > BMSY) and are not experiencing overfishing (F < FMSY). E., east; N.E., northeast; W., west.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 11 of 21 Fig. S5. Population trajectories in adult biomass and link with their current exploitation status. (A) Average annual rate of change in adult biomass (mean ± 95% CIs) for each population, including the entire time span of the time series (time span in Fig. 1B). (B) Overall extent of decline or recovery in adult biomass for each population from the first year to the last year of available data (SI Text, Section 3.3). (C) Average annual rate of change in adult biomass (mean ± 95% CIs) from 1954 to 2006 within each exploitation status category. (D) Overall extent of decline or recovery in total adult biomass from 1954 to 2006 within each exploitation status category. The vertical dashed line in B delineates an extent of decline of 85%. Population trajectories are colored according to their ex- ploitation status. Red populations are overfished (B < BMSY) and experiencing overfishing (F > FMSY). Orange populations are overfished or experiencing overfishing (B < BMSY or F > FMSY but not both). Green populations are not overfished (B > BMSY) and are not experiencing overfishing (F < FMSY). Population trajectories for which reference points were unavailable are shown with white solid circles and lines (SI Text, Section 4.1). Abbreviations for population names: E., east; GOM, Gulf of Mexico; N., north; N.E., northeast; S., south; T.C., Tsushima Current; U.S., United States; W., west.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 12 of 21 Fig. S6. Current adult biomass relative to BMSY (x axis) vs. current exploitation rate relative to FMSY (y axis) reference points for tuna populations. Codes follow Fig. 1 and Table S2. Colors represent the density of the points (the probability of occurrence) as calculated with a kernel density function. Red populations are overfished (B < BMSY) and experiencing overfishing (F > FMSY). Orange populations are overfished or experiencing overfishing (B < BMSY or F > FMSY but not both). Green populations are not overfished (B > BMSY) and are not experiencing overfishing (F < FMSY). The reference points of two tuna populations were not available: Pacific bluefin tuna and North Pacific albacore tuna (SI Text, Section 4.1). E., east; Pac., Pacific; S., south; W., west.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 13 of 21 Fig. S7. (Continued)

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 14 of 21 Fig. S7. (Continued)

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 15 of 21 Fig. S7. Time series of adult biomass on the logarithmic scale (Left; y axis, blue solid line) and time series of the annual rates of change (year-on-year rate of change) in adult biomass (Right; y axis, green solid line) of populations of temperate tunas (A), populations of tropical tunas (B), and populations of mackerels and Spanish mackerels (C). We converted the time series of adult biomass of each population to annual rates of change (ri)asri = ln(ABi+1/ABi), where ABi is adult biomass in year i, to allow for nonlinear trends and reduce autocorrelation. The annual rate of change in adult biomass, ri, was the dependent variable in the analyses of biomass trends. The model-estimated average annual rate of change (brown solid line) and its CIs (shaded brown polygon) are also shown. Abbreviations for population names: E., east; GOM, Gulf of Mexico; N., north; N.E., northeast; S., south; T.C., Tsushima Current; U.S., United States; W., west.

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 16 of 21 Fig. S8. Results and validation analysis from the metaanalysis of trends in adult biomass across tuna populations and their relatives (global estimate) usinga mixed-effects model. (A) Solid and dashed black lines indicate the overall fixed-effect average annual rate of change and 95% CIs, respectively, in adult biomass across all 26 populations. Gray lines represent the time series of annual rates of change for the 26 populations. (B–E) Validation plots of the final model. Autocorrelation function with 95% confidence intervals (dashed blue horizontal lines).

Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 17 of 21 unJráe al. et Juan-Jordá Table S1. List of scombrid species (family Scombridae) with their maximum body sizes (cm fork length) and geographic distributions Subfamily and Tribe Latin name Common name Maximum size (cm) Geographic distribution

Subfamily Scombrinae Thunnus alalunga* Albacore tuna 140 Cosmopolitan Tribe Thunnini (tunas) Thunnus albacares* Yellowfin tuna 239 Cosmopolitan www.pnas.org/cgi/content/short/1107743108 Thunnus atlanticus Blackfin tuna 108 Western Atlantic Ocean Thunnus maccoyii* Southern bluefin tuna 245 Southern Oceans Thunnus obesus* Bigeye tuna 228 Cosmopolitan Thunnus thynnus* Atlantic bluefin tuna 426 Atlantic Ocean Thunnus orientalis* Pacific bluefin tuna 300 Pacific Ocean Thunnus tonggol Longtail tuna 145 Indian Ocean, Indo-Pacific region, Western Pacific Ocean Katsuwonus pelamis* Skipjack tuna 110 Cosmopolitan Euthynnus affinis Kawakawa 100 Indian Ocean, Indo-Pacific region Euthynnus alleteratus Little tunny 106 Atlantic Ocean, including the Mediterranean and Black Seas Euthynnus lineatus Black skipjack 84 Eastern Pacific Ocean Auxis rochei Bullet tuna 50 Cosmopolitan Auxis thazard Frigate tuna 65 Cosmopolitan Allothunnus fallai Slender tuna 105 Southern Oceans

Subfamily Scombrinae Cybiosarda elegans Leaping bonito 45 Indo-Pacific region Tribe Sardini (bonitos) Gymnosarda unicolor 248 Indian Ocean, Indo-Pacific region. The distribution is disjoint, found primarily around reefs. Orcynopsis unicolor Plain bonito 130 Eastern Atlantic Ocean including Mediterranean Sea australis 180 Indian and Pacific Oceans Eastern Pacific bonito 102 Eastern Pacific Ocean Sarda orientalis Indo-Pacific bonito 102 Indian Ocean and Western Pacific Ocean Sarda sarda 91 Atlantic Ocean including Mediterranean Sea

Subfamily Scombrinae Acanthocybium solandri 239 Cosmopolitan Tribe Scomberomorini (Spanish mackerels) Scomberomorus brasiliensis 125 Western Atlantic Ocean Scomberomorus cavalla King mackerel 173 Western Atlantic Ocean Scomberomorus commerson Narrow-barred king mackerel 240 Indian Ocean and Western Pacific Ocean. Recently found in Mediterranean Sea along the Northern African countries. Scomberomorus concolor Monterey Spanish mackerel 77 Eastern Central Pacific Ocean Scomberomorus guttatus Indo-Pacific king mackerel 76 Indian Ocean and Western Pacific Ocean Scomberomorus koreanus Korean seerfish 150 Indian Ocean and Western Pacific Ocean Scomberomorus lineolatus Streaked seerfish 80 Indian Ocean and Indo-Pacific region Scomberomorus maculatus Atlantic Spanish mackerel 91 Western Atlantic Ocean Scomberomorus multiradiatus Papuan seerfish 35 Restricted to the Gulf of Papua and Timor Sea in the Indo-Pacific Scomberomorus munroi Australian spotted mackerel 104 Indo-Pacific region restricted to Northern Australia and Papua New Guinea Scomberomorus niphonius Japanese Spanish mackerel 100 Northwest Pacific Scomberomorus plurilineatus Kanadi kingfish 120 Western Indian Ocean along the Eastern African Coast 8o 21 of 18 unJráe al. et Juan-Jordá Table S1. Cont. Subfamily and Tribe Latin name Common name Maximum size (cm) Geographic distribution

Scomberomorus queenslandicus Queensland school mackerel 100 Indo-Pacific region restricted to Northern Australia and Papua New Guinea www.pnas.org/cgi/content/short/1107743108 Scomberomorus regalis 164 Western Atlantic Ocean Scomberomorus semifasciatus Broad-barred king mackerel 120 Indo-Pacific region restricted to Northern Australia and Papua New Guinea Scomberomorus sierra Pacific sierra 99 Eastern Pacific Ocean Scomberomorus sinensis Chinese seerfish 218 Western Pacific Ocean Scomberomorus tritor West African Spanish mackerel 98 Eastern Atlantic Ocean including the Mediterranean Sea bicarinatus mackerel 112 Indo-Pacific region Grammatorcynus bilineatus Double-lined mackerel 100 Indian Ocean and Indo-Pacific region. It is not clear if the distribution is continuous, at least around the Indian Ocean.

Subfamily Scombrinae Rastrelliger brachysoma Short mackerel 35 Indo-Pacific region Tribe Scombrini (mackerels) Rastrelliger faughni Island mackerel 20 Indo-Pacific region Rastrelliger kanagurta Indian mackerel 35 Indian Ocean and Western Pacific Ocean Scomber australasicus Spotted chub mackerel 44 Indo-West Pacific region Scomber japonicus Chub mackerel 62 Indian and Pacific Oceans Scomber scombrus Atlantic mackerel 60 North Atlantic Ocean Scomber colias 63 Atlantic Ocean including Mediterranean Sea

Subfamily Gasterochismatinae Gasterochisma melampus Butterfly kingfish 164 Southern Oceans

*Principal market tunas. 9o 21 of 19 Table S2. Populations of tunas and their relatives analyzed and sources of stock assessments and management reference points Source of Source of the stock the reference

Code Ocean Taxonomic group Species Latin name Population common name assessments B/BMSY F/FMSY points

1 Atlantic Mackerels Scomber scombrus Atlantic mackerel, North East (1) 1.13 1.07 (2) 2 Atlantic Spanish mackerels Scomberomorus cavalla King mackerel, Gulf of Mexico (3) 1.50 0.83 (4) 3 Atlantic Spanish mackerels Scomberomorus cavalla King mackerel, U.S. Atlantic (5) 1.34 1.00 (4) 4 Atlantic Spanish mackerels Scomberomorus maculatus Spanish mackerel, Gulf of Mexico (5) 1.07 0.60 (5) 5 Atlantic Spanish mackerels Scomberomorus maculatus Spanish mackerel, U.S. Atlantic (5) 1.44 0.65 (5) 6 Atlantic Tunas Thunnus alalunga Albacore tuna, North Atlantic (6) 0.62 1.04 (7) 7 Atlantic Tunas Thunnus alalunga Albacore tuna, South Atlantic (6) 0.91 0.63 (7) 8 Atlantic Tunas Thunnus thynnus Atlantic bluefin tuna, East (8) 0.35 2.90 (9) 9 Atlantic Tunas Thunnus thynnus Atlantic bluefin tuna, West (8) 0.15 1.88 (9) 10 Atlantic Tunas Thunnus obesus Bigeye tuna, Atlantic (10) 1.01 0.95 (11) 11 Atlantic Tunas Thunnus albacares Yellowfin tuna, Atlantic (12) 0.96 0.86 (12, 13) 12 Indian Tunas Thunnus obesus Bigeye tuna, Indian (14) 1.20 0.79 (15) 13 Indian Tunas Thunnus maccoyii Southern bluefin tuna (16) 0.17 1.91 (16) 14 Indian Tunas Thunnus albacares Yellowfin tuna, Indian (14) 1.11 0.99 (15) 15 Pacific Mackerels Scomber japonicus Chub mackerel, Chilean (17) 2.78 2.07 (17) 16 Pacific Mackerels Scomber japonicus Chub mackerel, Japanese (18) 17 Pacific Mackerels Scomber japonicus Chub mackerel, North East Pacific (19) <1 <1 (20) 18 Pacific Mackerels Scomber japonicus Chub mackerel, Tushima Current Pacific (21) 19 Pacific Tunas Thunnus alalunga Albacore tuna, North Pacific (22) 20 Pacific Tunas Thunnus alalunga Albacore tuna, South Pacific (23) 2.44 0.29 (24) 21 Pacific Tunas Thunnus obesus Bigeye tuna, East Pacific (25) 1.33 0.88 (26) 22 Pacific Tunas Thunnus obesus Bigeye tuna, West Pacific (27) 1.34 1.41 (28) 23 Pacific Tunas Thunnus orientalis Pacific bluefin tuna (29) 24 Pacific Tunas Katsuwonus pelamis Skipjack tuna, West Pacific (30) 2.67 0.34 (30) 25 Pacific Tunas Thunnus albacares Yellowfin tuna, East Pacific (31) 1.05 0.94 (32) 26 Pacific Tunas Thunnus albacares Yellowfin tuna, West Pacific (33) 1.64 0.58 (34)

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Juan-Jordá et al. www.pnas.org/cgi/content/short/1107743108 20 of 21 30. Hoyle S, Kleiber P, Davies N, Harley S, Hampton J (2010) Stock assessment of skipjack tuna in the Western and Central Pacific Ocean. Scientific Committee, Sixth Regular Session (Western and Central Pacific Fisheries Commission, August 10–19 2010, Nuku’alofa, Tonga). 31. Maunder MN, Aires-Da-Silva A (2008) Status of Yellowfin Tuna in the Eastern Pacific Ocean in 2007 and Outlook for the Future (Inter-American Tropical Tuna Commission, La Jolla, CA). 32. Maunder MN, Aires-da-Silva A (2010) Status of Yellowfin Tuna in the Eastern Pacific Ocean on 2009 and Outlook for the Future (Inter-American Tropical Tuna Commission, Scientific Advisory Committee, La Jolla, CA). 33. Langley A, Hampton J, Kleiber P, Hoyle S (2007) Stock assessment of yellowfin tuna in the Western and Central Pacific Ocean, including an analysis of management options (Western and Central Pacific Fisheries Commission, Scientific Committee, Third Regular Session, August 13–24, 2007, Honolulu, HI). 34. Langley A, et al. (2009) Stock assessment of yellowfin tuna in the Western and Central Pacific Ocean (Western and Central Pacific Fisheries Commission, Scientific Committee, Fifth Regular Session, August 10–21, 2009, Port Vila, Vanuatu).

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