Fisheries Science and Its Environmental Consequences
Summary and Keywords
Fisheries science emerged in the mid-19th century, when scientists volunteered to conduct conservation-related investigations of commercially important aquatic species for the governments of North Atlantic nations. Scientists also promoted oyster culture and fish hatcheries to sustain the aquatic harvests. Fisheries science fully professionalized with specialized graduate training in the 1920s.
The earliest stage, involving inventory science, trawling surveys, and natural history studies continued to dominate into the 1930s within the European colonial diaspora. Meanwhile, scientists in Scandinavian countries, Britain, Germany, the United States, and Japan began developing quantitative fisheries science after 1900, incorporating hydrography, age-determination studies, and population dynamics. Norwegian biologist Johan Hjort’s 1914 finding, that the size of a large “year class” of juvenile fish is unrelated to the size of the spawning population, created the central foundation and conundrum of later fisheries science. By the 1920s, fisheries scientists in Europe and America were striving to develop a theory of fishing. They attempted to develop predictive models that incorporated statistical and quantitative analysis of past fishing success, as well as quantitative values reflecting a species’ population demographics, as a basis for predicting future catches and managing fisheries for sustainability. This research was supported by international scientific organizations such as the International Council for the Exploration of the Sea (ICES), the International Pacific Halibut Commission (IPHC), and the United Nations’ Food and Agriculture Organization (FAO).
Both nationally and internationally, political entanglement was an inevitable feature of fisheries science. Beyond substituting their science for fishers’ traditional and practical knowledge, many postwar fisheries scientists also brought progressive ideals into fisheries management, advocating fishing for a maximum sustainable yield. This in turn made it possible for governments, economists, and even scientists, to use this nebulous target to project preferred social, political, and economic outcomes, while altogether discarding any practical conservation measures to rein in globalized postwar industrialized fishing. These ideals were also exported to nascent postwar fisheries science programs in developing Pacific and Indian Ocean nations and in Eastern Europe and Turkey.
The vision of mid-century triumphalist science, that industrial fisheries could be scientifically managed like any other industrial enterprise, was thwarted by commercial fish stock collapses, beginning slowly in the 1950s and accelerating after 1970, including the massive northern cod crisis of the early 1990s. In the 1980s scientists, aided by more powerful computers, attempted multi-species models to understand the different impacts of a fishery on various species. Daniel Pauly led the way with multi-species models for tropical fisheries, where the need for such was most urgent, and pioneered the global database FishBase, using fishing data collected by the FAO and national bodies. In Canada the cod crisis inspired Ransom Myers to use large databases for fisheries analysis to show the role of overfishing in causing that crisis. After 1980 population ecologists also demonstrated the importance of life history data for understanding fish species’ responses to fishery-induced population and environmental change.
With fishing continuing to shrink many global commercial stocks, scientists have demonstrated how different measures can manage fisheries for species with different life-history profiles. Aside from the need for effective scientific monitoring, the biggest ongoing challenges remain having politicians, governments, fisheries industry members, and other stakeholders commit to scientifically recommended long-term conservation measures.
Fisheries science is an ecological science that relates the growth and development of fish and fish populations to their environments, but is also an economic science that relates fish productivity to fisheries production, a human activity.
Overfishing investigations began in the 1860s; glimmerings of a new scientific field appeared in the 1870s when governments started hiring scientists for newly created positions as commissioners or directors of fisheries. In the 1880s Western and Japanese governments hired full-time researchers to do fishery investigations, and by the 1890s fisheries biology was a discernible discipline. Because it helps governments to adjudicate the allocation of living aquatic resources it emerged primarily within government-funded research facilities. Governments want fisheries science to assist economic growth, food security, tax generation, and their own political interests.
Early fisheries scientists’ ideal of service made them willing to conduct applied research, but the economic purposes of their research in turn gave them political agency: they championed certain sectors of the fishing industry; helped to centralize government control of the fisheries; and sought specific environmental and economic outcomes. Fisheries science has been dedicated to conserving living resources but has harbored a contradictory, equally important industrial development agenda: locating new concentrations of fish, expanding the range of species being exploited, and improving fishing and fish processing techniques and the quality of fish products.
Fisheries biology investigates the physiology, swimming behavior, predation and nutrition, diseases, pathogens, and parasites of commercial shellfish and fish, and develops measures to enhance commercial populations, including aquaculture (see Hubbard, Wildish, & Stephenson, 2016). Fisheries biology involves ecological, sampling, and fishing surveys and communicating with fishermen. Catch and sampling data are used to assess how fishing affects commercial populations. Using the logistic curve of density-dependent populations enabled fisheries biologists in the 1930s to develop quantitative dynamic population models. After World War II they also hoped to identify catch rates for a maximum sustainable yield (MSY–see below) to maintain fish populations and assist fisheries development for a growing world population. When North Atlantic catch rates declined in the 1960s, fisheries biologists adopted maximum quotas (total allowable catches, or TACs) and individual transferable quotas (ITQs) to restrict catches, and integrated parameters for trophic levels and energy flow into their dynamic models. After some of the world’s most productive fisheries collapsed, and a complete moratorium—still in place in 2016—was imposed in 1992 on the Grand Banks cod fishery, fisheries science underwent a paradigm shift. Precautionary fisheries management and protecting wild ecosystems became new priorities, as did co-management with industry stakeholders and closer involvement with fishers.
Fishery Depletion, Science, and Conservation Debates
Fisheries science emerged in response to concerns that fishing, industrial pollution, and mill-dam construction were depleting fish stocks. We now know that fisheries depletion is of long standing. The Baltic herring fishery never fully recovered after its collapse in the 1200s. By 1400 England had prohibited weirs on rivers and fine meshed nets for salmon fishing. Reaching Newfoundland in 1497, John Cabot had captured enormous cod simply by lowering weighted baskets, but by 1700 Massachusetts’s Cape Cod required open weirs for part of the week to let fish escape, and New England penalized mill-dams that blocked spawning migrations. Efficient 18th-century long lines, purse seines, and gill nets reduced abundance (Longhurst, 2010; Jester, 1971; Bolster, 2012; McKenzie, 2010); in the 19th century depletion was hastened by trawling, urban demand for fresh fish (thanks to railway transport), and reduction plants for fish-meal fertilizer and animal feed. Each generation’s standard of the size, variety, and abundance of fish being caught was diminished compared to its predecessor’s. This “shifting baseline syndrome” prevented clear recognition of overfishing, especially because the situation was complicated by mill-dams that blocked spawning runs, and urban, agricultural, and industrial effluent pollution (Pauly, 1995; Longhurst, 2010; Allardyce, 1972).
Depletion was first clearly seen in the oyster fishery. Oyster reefs disappeared, European fisheries closed, and the New England industry relocated to oyster-rich Chesapeake Bay. Victor Coste in France began investigating oyster culture to rehabilitate depleted oyster beds in 1853. Johns Hopkins biologist William Keith Brooks founded the Chesapeake Zoological Laboratory in 1878 to study oyster cultivation and embryology. While oyster culture was hindered by property rights issues, opposition by oystermen, expense, disease, and pollution (Keiner, 2009), 19th-century fish hatcheries enjoyed near-universal support. These hatched eggs from captured fish, and released larval and juvenile fish into lakes, rivers, and coastal waters.
Spencer Fullerton Baird at the Smithsonian Institution promoted fish culture. He became the first U.S. commissioner of fish and fisheries in 1871 and founded the future U.S. Bureau of Fisheries. Frank Buckland’s expertise with fish hatcheries led to his hire as an English fishery inspector (Jester, 1971). They belonged to a growing cadre of biologists serving as chief inspectors or commissioners of fisheries in government agencies, including ichthyologist Dr. Francis Day in India (1871), Edward E. Prince in Canada (1883), and Lake F. Ayson in New Zealand (1898). These individuals created the professional context for fisheries biology, and most helped to develop its institutional context: coastal laboratories with “water tables” and water-supply systems, like those at Bergen, Norway (1900), St. Andrews, Canada (1898), and Portobello, New Zealand (1904), built for the study of aquatic organisms. Oceanographic expeditions supplied the ecological context, revealing high productivity in estuaries, along coasts, and above continental shelves, and vast “deserts” of low productivity in ocean expanses.
Biologists offered their expertise to adjudicate fishing disputes. In Britain, the weighted nets that bottom trawlers dragged over the seafloor were accused of damaging inshore fisheries, forcing fishermen to travel to distant fishing grounds even before efficient steam trawlers appeared in 1877 (Robinson, 1996). Thomas Henry Huxley chaired two royal commissions, in 1861–1863 and 1883–1885, hearing testimony from around the United Kingdom. Neither found evidence for overfishing. The later commission’s outcome was determined when Scottish biologist W. C. M’Intosh and his assistant Edward E. Prince found that floating groundfish eggs are unharmed by bottom trawls. Huxley famously stated at London’s 1883 International Fisheries Exhibition that “in relation to our present modes of fishing, a number of the most important sea fisheries, such as the cod fishery, the herring fishery, and the mackerel fishery, are inexhaustible.” Huxley elided the weight of testimonial evidence for overfishing, reasoning that the huge number of eggs each female spawned annually more than compensated for the catch (Schwartz, 2013a, 2013b; Hubbard, 2014a, 2006). Walter Garstang argued in 1900 that Fishery Board for Scotland data revealed overfishing in near-shore waters (Smith, 1988), but Huxley’s stance proved highly influential when fisheries scientists professed expertise in interpreting fisheries conservation issues. Their new scientific authority helped governments to centralize control over fisheries and replaced traditional local practices that had regulated access to resources and preserved their basis and profitability (McEvoy, 1986; McKenzie, 2010; Muscolino, 2009).
Fisheries Science 1890–1939: Development
Fisheries science’s distinctive focus required an interdisciplinary array of scientific approaches: life-history studies, studies of fish scales, embryology, anatomy, physiology, statistics, population demographics, experimental fishing, physical and biological oceanography, and marine ecology. Lacking a theory of population fluctuations, scientists first studied how migrations might cause poor catches (Sinclair & Smith, 2002). In 1864, Norway hired Georg O. Sars to investigate declining herring catches. Using sea temperature data sent by Henrik Mohn at the Meteorological Institute, he linked good herring catches with warm water. Sars and Mohn’s Vøringen expeditions (1876–1878) showed that currents carried young cod northward, and colder conditions meant poor catches (Mills, 1989). At Kiel in 1898, Friedrich Heincke revealed that fish biometrics, like the number of rays in fins, varied according to region; fish racial studies could reveal migration patterns and responses to environmental change. Danish biologist C. G. Johannes Petersen pioneered fish tagging, offering rewards for tags returned with data on date and location of recapture. Fish-tagging differentiated fish stocks, gave information on migration patterns, growth rates, and feeding ecology and distribution, and suggested that populations within a species might differ from each other and also fluctuate in abundance—a new possible explanation for good and poor fishing years (Sinclair & Smith, 2002; Smith, 1994). In 1898, German biologist C. Hoffbauer’s finding that concentric rings on carp scales were formed annually was confirmed for marine fish scales by J. Stuart Thompson. A year later Johannes Reibisch found annual growth rings in otoliths (ear bones) and vertebrae of marine fish, useful in species with unclear scale markings (Jackson, 2007). Age data from catch samples are crucial for population assessments, which analyze spawning success, fish fry survival to the age they enter the fishery (recruitment), and population age structure (Hilborn & Walters, 1992).
Northern European oceanographers and biologists lobbied their governments for internationally funded coordinated research, and in 1902 founded the International Council for the Exploration of the Sea (ICES). ICES coordinated fishery statistics and soon shifted to population assessments, the main focus of fisheries biology. ICES carried out trawl surveys, pioneered by Fishery Board for Scotland biologist Thomas Wemyss Fulton, and created three fisheries committees: for fish migrations; for cod and herring; and for important Baltic species (Rozwadowski, 2002; Stephenson, 2002). Coordinated quarterly cruises from Iceland to Spain for intensive area studies and biological sampling revealed seasonal changes and clues for relating stock fluctuations to hydrography (Sinclair & Smith, 2002; Mills, 1989).
Seminal work by Johan Hjort, appointed to head Norway’s new Fisheries Directorate in 1900, helped to explain sharp changes in cod catches. His team analyzed plankton, hydrography, life histories, statistics, birth rates, migrations, and thousands of samples of fish scales from ICES’s research cruises. Discovering that fish can live more than 20 years, they found that a stock could have many three- and seven-year olds, with other age groups scantily represented. Hjort’s classic Fluctuations in the Great Fisheries of Northern Europe (1914) revealed that herring born in the 1904 “year class” were spectacularly important. First appearing in 1907, they constituted 34% of the 1908 catch, peaked at 77% of the 1910 catch, and in 1913 still formed over 60% of the catch. Hjort saw no link between total fishing effort and catch fluctuations, or adult population and spawning success: the varying success of different year classes proved more important than overfishing for population fluctuations (Schwach, 2014).
Hjort’s work seemed to exonerate fishing for falling catches, because each female produced so many eggs that a good year class would regenerate the stock. Hjort hypothesized that poor year classes were determined by events when larvae first hatched; if they failed to find food, or if currents swept eggs and larvae to regions where they could not hatch, survive, or return to recruit, a poor year class would result (Houde, 2008). His “Critical Period” hypothesis became a scientific holy grail for forecasting populations (Robert, Murphy, Jenkins, & Fortier, 2014).
Hjort introduced his array of techniques to North America during the Canadian Fisheries Expedition of 1914–1915, personally training Archibald G. Huntsman, later director of the Atlantic Biological Station, to assist in his herring investigations. Huntsman became the first North American scientist to determine fish ages using scale growth rings, and he spread this method at the American Fisheries Society meeting in 1919 (Hubbard, 2014b; Jackson, 2007; Carlander, 1987). He was also a moving force behind the creation of the North American Commission for Fisheries Investigations (NACFI), founded in emulation of ICES in 1921. NACFI included Canada, France, Newfoundland, and the United States. During the interwar period these bodies were also joined by two international Pacific fishery commissions, both headed by William F. Thompson, founder of the University of Washington’s School of Fisheries. He was hired in 1924 by British Columbia to investigate declining halibut catches for the new International Pacific Halibut Commission (IPHC) and in 1936 to lead the International Pacific Salmon Fisheries Commission (1936–1985) (Thompson & Freeman, 1930).
ICES, NACFI, and the IPHC demanded improved fishing statistics and standardized catch data, and subdivided the North Atlantic and Northeast Pacific into regulatory areas still used for statistical analysis (Hubbard, 2013; Skud, 1977). They obtained regulations requiring ships’ captains to keep logbooks to record dates, locations, and quantities of catches. Fishery inspectors had to take scale samples and record lengths, weights, and condition of fish being landed. From these data scientists generated the catch-per-unit effort: the total daily catch divided by number and average size of vessels. This served as an index of stock size (Cushing, 1988). Among other studies, NACFI supported a survey of mackerel eggs and larvae, ocean conditions, and plankton abundance from Cape Cod to Chesapeake Bay by U.S. Bureau of Fisheries biologist O. E. Sette in 1931. Sette’s careful analysis found no link between egg and fry mortality and plankton abundance. The significance of his finding that fewer than one mackerel were recruited for every million eggs spawned (Smith, 1994) was missed by fisheries biologists.
Hjort’s other main contribution was to entrench fisheries development in fisheries science. Exploratory fishing revealed commercial concentrations of shrimp off Norway; he developed new fishing gear, promoted his discoveries, and inaugurated a new Norwegian fishery. In Canada, he pushed improved brining and “fast-freezing” methods. Fisheries research thereafter included locating and promoting “under-utilized” species; improving fishing and fish processing technologies; and biochemical and microbial research on fish products to improve canning and processing (Schwach, 2009; Schwach & Hubbard, 2010; Hubbard, 2006).
This focus also characterized Japanese fisheries science. The Bureau of Fisheries, founded in 1885, surveyed marine life, commercial populations, and fishing practices, and collected statistics for spawning and fishing grounds, vessels, gear, production, processing, and sales. The Fisheries Institute, Fisheries Training School, and other institutions turned out experts in aquaculture, fish processing, and science (Matsuda, 2002). Tasaku Kitawara attended the first ICES meeting in Kristiania, and melded oceanography into Japanese fisheries research: “Kitawara’s Law” states that fish accumulate around oceanic fronts (Hart & Reynolds, 2002). Japan’s 29 fisheries experimental stations in 1907 grew to 59 by 1939. Their practical focus included aquaculture, fish processing, economics, and exploratory fishing (Finley, 2007; Matsuda, 2002).
Japan’s research outpaced fisheries science in British colonies and dominions. European scientists headed research programs that reflected European interests. Their surveys led to new and industrialized fisheries, and to importing sport fish—Atlantic salmon and trout—into native streams. The Madras Bureau of Fisheries introduced rainbow trout to southern India’s Nilgiri mountain rivers. John D. Gilchrist started South Africa’s commercial Aqulhas sole trawl fishery, and a sport fishery for trout he stocked in Natal (Van Stittert, 1995; Britz, 2015). Harald K. Dannevig failed to introduce Atlantic plaice to Australia but discovered 10,000 square miles of fishing grounds off its southeast and southern coasts (Harrison, 1991; Murray-Smith, 1981). Lake F. Ayson in New Zealand introduced Atlantic salmon and trout to inland lakes, and Chinook salmon to the South Island; however, at his Portobello research station, scientists’ repeated attempts to introduce turbot, crabs, lobsters, and other Atlantic species floundered (Putnam, 1977; McDowall, 1996). In southern India, James Hornell’s exploratory trawling led to commercial fisheries on the 5,000-square-mile Wadge Bank. ICES-inspired science in the 1920s included surveys, ecology, and fisheries statistics in New Zealand (NZ Fisheries InfoSite, n.d.) and fish processing research in the new Ennore experimental station in India (Government of Tamilnadu, 2016). Colonial authorities in Tanganyika and Uganda hired Michael Graham from the Fisheries Laboratory in Lowestoft, England, to lead a six-month ecological survey of Lake Victoria in 1927 and advise on managing tilapia and other valuable species (Worthington, 1983). Australia’s Council for Scientific and Industrial Research (CSIR) appointed Harold Thompson in 1935 to direct its Fisheries Division. He hired 10 scientists, founded a research station at Cronulla, then battled to do oceanography and population assessments, not just exploratory fishing and development work (Harrison, 1991; Austin, 1981).
Fisheries development work strongly characterized Chinese fisheries science. Japanese-trained fisheries bureaucrats were entrenched early in the Republican era (1912–1949), when Chinese demand for fish outstripped domestic production. Coastal fishing resources were strained and declining, according to experts, because “dull-witted” fishermen used wasteful and inefficient fishing methods. Chinese experts were confident that modern science, by locating new productive fishing grounds and ending the capture of immature fish, would help over-exploited fish stocks replenish themselves. Japanese-trained scientists in the new fishery research institutes improved fishing gear, fish processing, and storage and spread aquaculture. Fisheries experts abolished regional fishing lodges that levied fees, arbitrated fishing disputes, and restricted fishing practices to maintain profitability, policies that had indirectly conserved resources. The technocrats’ state-directed fishing organizations instituted new practices to facilitate “rational” production increases, eliminate waste, and expand the resource base. Their policies, however, worsened ecological degradation and resource conflicts (Muscolino, 2009).
Theory of Fishing and International Commissions: 1918–1980
Fisheries scientists favored industrialized fisheries operations, which, unlike traditional small-scale fisheries, easily invested in scientists’ innovations. Industry leaders in turn lobbied governments for concessions and aid, ensuring close contact with scientists but also attenuating conservation (Hubbard, 2014a, 2012). During the Great Depression, biologists created the “theory of fishing”: mathematical treatments of the biological effects of fishing. Two kinds of overfishing had been identified. Growth overfishing takes too many large fish, leaving a catch of smaller fish of lower total weight and value than if each fish had been allowed to grow. Recruitment overfishing does not leave enough adults to reproductively maintain the stock. No scientist then thought that stocks could be fished to extinction, however (Cushing, 1988).
A Russian and a Canadian scientist separately originated fisheries population dynamics in 1918. Russia lacked industrial fisheries and had no government fisheries department. The government did fund several expeditions, including the Murman Scientific-Fishery Expedition of 1897–1899, led by St. Petersburg University professor Nicolai Knipowich. A purpose-built research vessel, Andrei Pervoswanny, was used for biological and fishing surveys and testing fishing gear to modernize the Barents Sea fisheries. Knipowich persuaded Russia to join the International Council for the Exploration of the Sea (ICES) in 1902, despite official fears that the fees and his hydrographic work would only assist European fisheries (Lajus, 2002; Sörlin, 2013). Knipowich served on the ICES migration committee until 1909, when the Dumas removed funding (Stepanyants, Chernova, Lajus, & Bjorklund, 2002). With connections lost, Födor Ilyich Baranov’s groundbreaking work, published in Russian, gained no international attention. Baranov, a professor at Moscow’s Agricultural Academy, was calculating the optimum mesh size for trapping fish in gill nets and designing hydrodynamically efficient trawl nets that would let undersized fish escape from the cod-end (Fridman, 2009). His paper “On the Question of the Biological Basis of Fisheries” explored the progressive removal of older year classes from a stock by intensive fishing. He showed how to compute the trade-off between decreasing numbers of older fish and increasing sizes of those remaining to maximize the fisheries, and represented this graphically. Meanwhile, Huntsman used pyramid-shaped graphs to depict how fishing changes Atlantic Canadian plaice populations. He argued that the effects of removing larger fish could only be seen by following each year class over several years, and would leave a stock composed of younger, smaller fish with a smaller biomass. Because Huntsman published in a bulletin for fishermen, his paper remained as obscure as Baranov’s (Smith, 2002).
Huntsman did, however, share his insights with W. F. Thompson in Seattle in 1920, while visiting the Pacific Biological Station on Vancouver Island. These helped Thompson explain why, from 1888 to 1914, fishermen had to travel ever-greater distances to catch Pacific halibut (Smith, 1988). Thompson’s celebrated analysis showed declining catch rates despite rising fishing effort, represented fishing effects in tabular form, and provided the basis for new regulations, including the world’s first quota restrictions. The International Pacific Halibut Commission (IPHC) prohibited fishing in the spawning season and year-round in two “nursery areas”—marine protected areas—created for spawning halibut. Thompson’s hope to ensure the “largest permanent yield” (Thompson & Bell, 1934) reflected that era’s belief in “Gospel of Efficiency” conservation for human utility.
“Rational” exploitation involved conserving resources while fully utilizing them (Hubbard, 2016) and underlay “theory of fishing” models based on the logistic curve of density-dependent population regulation. Derived by Pierre Verhulst after reading Malthus’s Essay on Population in 1838, it had been rediscovered by Raymond Pearl at Johns Hopkins in 1920. This S-shaped or sigmoid curve reflects a population’s slowing growth at high densities or when many individuals reach a certain age; their growth slows, and death rates rise. In 1933, Hjort applied the sigmoid curve to Norway’s whaling catches and showed that growth rates were greatest when a whale population was about half the size of an unfished population (Smith, 1994; Holt, 2014). Edward S. Russell, director of the Lowestoft Fisheries Laboratory, used the sigmoid curve in 1931 to develop a mass balance equation that predicted the future fish stock biomass from its current status using catch data. It included factors for the environment’s carrying capacity, a fish stock’s productivity, biomass growth through recruitment and individual fish growth, and losses due to fishing and natural mortality (Russell, 1931; Smith, 1994).
Russell and those he inspired treated the environment as unchanging, due to the sheer difficulty in gathering essential population and fishing data (Longhurst, 2010). His successor, Michael Graham, thought fisheries should be managed for sustaining profits rather than for some high catch level in a competitive free-for-all. His model used North Sea catch data to show how reducing numbers of fishing vessels and time spent fishing would increase each fishing trip’s catch. Less effort and money would be spent to locate fish, so profits would rise, and the fisheries would be more efficiently exploited (Graham, 1935). With fewer fish being caught, those remaining would grow larger in size and value, and fish stocks would also recover, as they had during World War I, when fishing nearly stopped. Graham’s “Great Law of Fishing” stated that “Fisheries that are unlimited become unprofitable” (Graham, 1943, p. 153).
While tracking and calculating missile trajectories with mathematician H. R. Hulme in Special Operations during World War II, Graham challenged Hulme to apply Russell’s equation to preventing overfishing by using specified mesh openings. Hulme jotted his solution—a fundamental integral equation—on the back of an envelope during the Battle of Normandy (Hulme, Beverton, & Holt, 1947; Smith, 1994). In 1946 Graham hired two young scientists, Raymond Beverton and Sidney Holt, to develop predictive models based on Hulme’s solution so it could be used to generate advice on fishery regulations (Beverton & Holt, 1957, 1993).
From North Sea haddock studies, and plaice tagging studies by Dorothy Thursby-Pelham—the first sea-going woman fisheries scientist (Lee, 1992)—Beverton and Holt estimated instantaneous fishing mortality. For growth of fish within the stock, they used physiologist Karl Ludwig von Bertalanffy’s equation that describes individual growth curves. They incorporated recruitment and age distributions, and integrated the numbers lost from each age group as they grew older (due to natural mortality, predation, and fishing) with the weight gain of surviving fishes as they age (Cushing, 1988). Their model integrated the catch-per-unit effort of many small areas in the North Sea to make overall statistics proportional to fish abundance and avoid the problem of fish migrations (Holt, 2004). They also calculated the overall fishery’s yield-per-recruit in terms of fish weight. A flaw in their model was its treatment of recruitment and natural mortality rates as being constant. But it allowed a focus on how fishing mortality affects separate year classes differently across their life spans, theoretically allowing scientists to use mesh size to conserve fish stocks. It was foundational to modern single-species fishery assessments and management, and remains influential even for multi-species fisheries assessments (Pauly, 1998).
Graham organized courses to disseminate Beverton and Holt’s work before their seminal On the Dynamics of Exploited Populations finally appeared in 1957, and made Lowestoft the headquarters for a scientific dynasty that placed the Beverton-Holt model at the heart of modern fisheries biology and management. The United Nations’ Food and Agriculture Organization (FAO), founded at the end of World War II, also promoted their model. Geoffrey Kesteven, an Australian biologist at the CSIR Fisheries Division, joined the FAO as its first commonwealth director of fisheries in 1946 (Harrison, 2008a). He stopped his own efforts to develop fishing equations when Holt joined the FAO in 1953 (Holt, 2008b). Kesteven then arranged for Holt to teach the Beverton-Holt model in Turkey and other less-developed countries, and himself introduced it to Australia upon his return in 1960 (Harrison, 2008b).
By this time two other influential models were being used to manage Pacific fisheries. William E. Ricker’s spawner and recruitment model was based on sockeye salmon studies, and Milner B. Schaefer developed the surplus production model to manage tuna fisheries.
Ricker’s model grew out of his work assisting Pacific Biological Station director R. E. Foerster in a pivotal 1924–1937 study at Cultus Lake that ended Canadian government support for salmon hatcheries by revealing they were ineffective (Hubbard, 2006; Hachey, 1965; Walters & Martell, 2004). By measuring the average weights of young sockeye salmon and recording their population numbers, Ricker and Foerster discovered that the total weight of fry at first increased and then decreased over the year. A larger spawning population meant more adults might eat more eggs and vulnerable young fish of their own species; in addition, more fry also competed for limited food. Later tagging studies on Indiana lake fish helped Ricker assess their effectiveness for estimating catch and survival rates and population size. Influenced by Baranov, whose paper Russell had discovered and translated in 1938, Ricker theorized that recruitment goes down at higher stock densities and developed dome-shaped recruitment curves (Smith, 1994; Ricker, 1990). His Handbook of Computation of Biological Statistics of Fish Populations, published in 1958, when he was editor of the Journal of the Fisheries Research Board of Canada, became a worldwide reference for managing regional fisheries (Beamish, Noakes, Noakes, & Beamish, 2003). His “spawner and recruitment” model, now called the Ricker curve, is the basis for Pacific salmon management. Unlike the Beverton-Holt model, his model predicted recruitment from the number of spawning fish. But it ignored highly variable population fluctuations and sometimes failed: for example, scientists did not anticipate the record run of 30 million fish in 2010—the greatest since 1913 (Larkin, 2010).
A third key model was introduced by Schaefer, who in 1951 became the first director of the Inter-American Tropical Tuna Commission (IATTC) formed by Panama and the United States. His “surplus production model” was developed to maintain tuna and bait-fish fisheries at a maximum sustainable yield. Inspired by Hjort’s suggestion that whale populations grow fastest when a population is cut to about half its maximum size, he applied the sigmoid curve to long-term Pacific halibut and sardine catch and fishing-effort data. Because growth slowed when populations were highest, Schaefer theorized that while removing “surplus” fish would reduce a population, increased growth rates would cause its biomass to approach the maximum (Smith, 1994). Schaefer’s relatively simple model had a lower information demand than the others, and was used to generate production quotas for the U.S. Pacific coastal tuna fishery, but it ignored variable recruitment and expanding fishing fleets (Gulland, 1988; Longhurst, 2010). He also never clarified how to identify the maximum sustainable yield.
The three main models were used by the 39 international fisheries commissions created after World War II to forge agreements between nations, scientifically monitor international fisheries, and give conservation advice (Longhurst, 2010), beginning with the Permanent Overfishing Commission, created during the Overfishing Convention in London in 1946. Many international fisheries commissions were created when the FAO made contact with university biologists from underdeveloped nations in the Indo-Pacific, Caribbean, South Atlantic, South Pacific, and Mediterranean. In 1959 the FAO helped create the North-East Atlantic Fisheries Commission (NEAFC) to replace the Permanent Commission. The most important FAO-linked body for its time, however, was the International Commission for the Northwest Atlantic Fisheries (ICNAF; 1949–1980). Government scientists from the United States, United Kingdom, Canada, Northern Europe, Spain, Portugal, and the Soviet Bloc standardized units and measures to track the catch-per-unit effort (Walford, 1956), a Sisyphean exercise due to expanding sizes and numbers of English, Spanish, Soviet, Soviet Bloc, and Japanese factory trawlers. ICNAF scientists surveyed, sampled, did exploratory fishing, and tested the effectiveness of the only internationally agreed-upon restriction: minimum mesh size. With no routine on-board monitoring, undersize fish and other by-catch, often crushed to death in huge trawl nets, were discarded, and thereby lost to future fisheries and to science. Their quantity could only be guessed at, adding to a host of unmeasurable variables. ICNAF lost its relevance in 1980 when the UN Law of the Sea Convention created 200-mile exclusive economic zones (EEZs). A new non-FAO body, the North Atlantic Fisheries Organization (NAFO), took its place.
The FAO’s immediate goal was assisting war-shattered Europe to rebuild; its long-term agenda was global food stability. It endorsed the Beverton-Holt, Ricker, and Schaefer models because “the results were expressed in relatively simple terms” (Cushing, 1988, p. 122). The maximum sustainable yield (MSY) became a universal goal of fisheries management due largely to U.S. policies. William C. Herrington, a fisheries biologist and adviser to the Undersecretary of State for Fish and Wildlife, pushed for fisheries policies that meshed with America’s geopolitical objective of exhibiting the abundance generated by Western capitalism and democracy (Finley, 2013, 2010). U.S.–built Japanese and American factory trawlers assailed South American coastal waters. Meanwhile, British trawlers invaded Icelandic waters. In response, Peru, Chile, Ecuador, and Iceland demanded that the UN extend coastal exclusive economic zones (EEZs) to 200 miles. To protect existing three-mile EEZs and the freedom of the seas, while defending American coastal fisheries, Herrington offered the “abstention principle” which supported fishing in coastal regions outside three-mile limits unless nations were “scientifically managing” specific resources, as the United States did with Bristol Bay salmon. This would inspire all nations to develop scientific fisheries regimes. Herrington and his predecessor, Wilbert Chapman, initiated the International Technical Conference on the Conservation of the Living Resources of the Sea, held at the FAO headquarters in Rome in 1955, to endorse MSY as a tool for conservation. While MSY was opposed by British, Peruvian, and Icelandic scientists, American and British political diplomacy ensured that it became the research and management basis for all international fisheries commissions (Finley, 2010), including ICES, ICNAF and NEAFC; the Schaefer MSY model was used by Japanese and U.S. scientists in the Pacific (Longhurst, 2010; Matsuda, 2002). EEZs remained unchanged after the 1956 UN Convention on the Law of the Sea (UNCLOS-I).
The focus on population models left biology subservient to mathematics in fisheries laboratories. Biologists were relegated to secondary research, like economic aspects of fisheries management or finding the earliest age at maturity of fish (Larkin, 1988). The “real” or “true” fishing effort became the factor on paper, while values from the fishery, such as the “catch per day’s absence,” “catch per standard drag,” and “catch per angler day” counted only as “nominal” efforts (Radovich, 1975). Mathematical models, for John A. Gulland, embodied the evolution of fish populations under fishing pressure (Longhurst, 2010).
The Fisheries Laboratory at Lowestoft, when Gulland arrived there in 1951, was full of confident mathematicians and biologists fearlessly refining the Beverton-Holt model (Longhurst, 2010). Gulland modified Canadian freshwater biologist F. E. J. Fry’s method for calculating how much a year class (cohort) contributes to the fishery across its lifetime—the heart of the Beverton-Holt model. Fry had added together the number of fish in a cohort caught in each successive year (Smith, 1988). Gulland’s virtual population analysis (VPA) instead reconstructed the total population size for a given year, using catch data to back-calculate the numbers of fish in each cohort. VPA needed accurate estimates for how many 2-, 3-, or even 20-year olds were caught each year—the value for a given year class as it was adjusted over time. VPA was used to calculate how many fish were removed from the population by fishing, the size of the population in a given year, and its projected size for the beginning of the next year (Cushing, 1983). Gulland’s FAO manual, Fish Population Dynamics: A Manual of Basic Methods (1965) was widely translated and extensively used. VPA became standard in ICES’s and ICNAF’s North Atlantic work (Pauly, 1994). Mathematician John G. Pope offered a simpler statistical “cohort analysis,” but his and Gulland’s formulae remained tricky to use. In 1976, biologists in ICES demanded, and got, a 10-day training course at Lowestoft (Rozwadowski, 2002).
Each model had ambiguities. In 1975, Pope and D. J. Garrod showed that Schaefer’s model assumed that fish were randomly dispersed. But dense aggregations of fish in schools are the norm, and are relatively easily located by modern fishing fleets equipped with sonar (Cushing, 1988). Their high catches would then hide the diminishing total biomass, and the MSY would be lower than Schaefer’s methods estimated (MacCall, 1975). MSY itself is difficult to identify: a falling catch-per-unit-effort is one identifier; but in unregulated open access fisheries, this might indicate too many competing fishing vessels. Dockside and sea sample data exacerbate problems. Reading otoliths and fish scales requires skill and patience; one careless reader can contaminate entire data sets and throw off estimates for the population age structure. No model incorporated external factors like El Niño phenomena, climate change, long-term natural cycles, disease, pollution, parasites, predation, or changes in lower trophic organisms. Uncritical acceptance of model predictions led to incorrect conclusions (Longhurst, 2010; Schnute & Richards, 2001; Jennings, Kaiser, & Reynolds, 2001).
Exporting Western Fisheries Science for Globalized Fisheries
The period from 1950 to the early 1980s was a golden age for fisheries science. The U.S. Sea Grant program in 1966 created Sea Grant Colleges as centers of applied research, starting with Texas A&M University and state universities in Oregon, Rhode Island, and Washington (National Sea Grant, 1999). Challenged by a growing world population and mass starvation in poor nations, fisheries scientists enthusiastically participated in the “race to the sea.” A 1966 United Nations resolution on “Resources of the Sea” urged international ocean research for development in an era in which “useless” species (like sharks) were seen as competing for profitable fish; therefore prized species should be harvested at the highest rates that still preserved stocks, and worthless species should be replaced by valued ones. Soviet biologists introduced Pacific red king crab to the Barents Sea, opening a valuable new fishery, but unfortunately doomed the ecosystem that supported bait fish used in traditional Norwegian fishing (Longhurst, 2010). Development assistance funding from the UN Development Programme (UNDP), the World Bank, the IMF, national, and private sources (Alverson, 2002) spread Western models of modernization around the world. For example, United Nations’ Food and Agriculture Organization (FAO) scientist Gunnar Sætersdal, who worked in Chile and Peru, saw how hard it was for poor nations to map and assess their marine resources, and he organized and led the Dr. Fridtjof Nansen Programme of 1975–1993, assisted by the Norwegian Agency for Development Cooperation. With the research vessel Dr. Fridtjof Nansen, he mapped and surveyed Third World fisheries resources globally (Sætersdal, Bianchi, Strømme, & Venema, 1999). Poor nations were not necessarily the main beneficiaries, however, as foreign, subsidized industrial fishing fleets took advantage of new opportunities. By 1980 Soviet, Japanese, Romanian, South Korean, Polish, and European Union factory trawlers (including around 700 from Spain) fished off Sierra Leone, Morocco, and Guinea for global markets, hurting traditional indigenous small-scale fisheries (Longhurst, 2010).
Catches, exports, economic yields, and fish protein in poor nations’ diets all increased. But over-simplistic maximum sustained yield (MSY) management accompanied the widely held belief that fisheries could be industrialized without threatening fish populations (Hersoug, 2004a; Longhurst, 2010). With Marshall Plan funding and FAO assistance, Turkey built fish meal and oil (dolphin oil) reduction plants and canneries, and the Fisheries Research Centre in Istanbul in 1955. Turkish research, however, avoided a focus on fish themselves: in the 1970s “water produce” research institutes and colleges trained fisheries biologists as “water produce engineers” (Knudsen, 2011). In Thailand, German experts helped to create a new industrial trawl fishery, and trained Thai experts to manage it for MSY. Bottom trawling, however, mangled the Gulf of Thailand’s delicate coral reefs as the trawl fleet grew to over 3,300 boats in 1971. German scientists now begged Thai managers to end MSY targets and trawling to save fragile ecosystems, but their pleas were rejected as ecological imperialism (Torma, 2013; Longhurst, 2010).
Increased fishery production rarely involved small-scale fishers. Instead, large-scale enterprises concentrated profits in corporate sectors. During Norway’s 1952–1972 bilateral program with southern India, new gear, larger vessels, and exploratory fishing led to a shrimp export fishery for U.S. markets, enriched new entrepreneurs and helped economic development. The drawbacks, however, included worsened socioeconomic inequality and waste. Shrimp constituted only 10% of the trawl catch; the rest was mostly discarded (Hersoug, 2004b).
Norwegian experts’ stays were also too brief for the intended transfer of science. The International Indian Ocean Expedition (IIOE) of 1959–1965, was also intended to help South Asian scientists to found marine science institutions in India, Thailand, and Indonesia (Hamblin, 2005; Qasim, 1998). Because Western science was designed for developed, centralized, and industrialized fisheries harvesting a few major species (Hubbard, 2014a), it was often off-target. In developing nations, small-scale local fisheries, dispersed among far-flung small coastal communities, harvest many stocks and species at the same time. Poorly funded research institutions mirrored the Western focus on rational exploitation of a few species, development, and predictive models for MSY management by a centralized bureaucracy. Many over-fished tropical fisheries remained mismanaged or not managed at all (Degnbol, 2004).
India’s Central Marine Fisheries Research Institute (CMFRI) founded in 1947, was an exception. Through collecting data on catches and craft, gear, landing centers, and fishing villages, by 1961 CMFRI had developed a stratified, multistage random-sampling model designed to estimate catch and effort for managing India’s dispersed coastal fisheries, later spread through training workshops (Modayil, 2004, 2005). Another exception was the International Center for Living Aquatic Resources Management (ICLARM), opened in Manilla in 1977 to address concerns about the poor management of developing nation’s fisheries that supplied employment and one-third or more of dietary protein for large coastal populations. With Rockefeller Foundation, USAID, and Australian Development Assistance Bureau funding, ICLARM worked on three fronts: resource management, aquaculture research, and developing small-scale fisheries. ICLARM—renamed WorldFish in 2015—encouraged donors and development banks to shift away from industrialized fisheries. A “laboratory without walls,” it had a few offices and a library, support staff, and six to nine scientists, with project staff operating in the field. ICLARM’s scientists built a research database and worked side-by-side with researchers in the universities and laboratories of developing countries seeking assistance. Through person-to-person contact, ICLARM scientists transmitted new or proven methods, while learning about their client colleagues’ cultural, technological, economic, fiscal, or political limitations and opportunities (Smith & Jackson, 1987).
Shifts in the Political Context of Fisheries Science: 1960s and 1970s
While fisheries biologists remained confident in their numerical models, governments began questioning their role in the face of changing economic and political circumstances. The huge sardine fishery that sustained California’s canning, fertilizer, and animal feed reduction industries closed down in 1952. Annual catches in the Grand Banks region escalated through the 1960s, and then declined after 1972, despite fishing effort doubling in this period. Scandinavian annual herring catches fell from 2 million to under 50,000 tons from 1965 to 1975 (Dickey-Collas et al., 2010). Peru, Chile, Ecuador, and Iceland kept up demands for 200-mile exclusive economic zones (EEZs), since the UN Convention on the Law of the Sea (UNCLOS-II) in 1960 had changed nothing. Then, in 1972, an El Niño exacerbated the overfishing of Peruvian anchovy; the annual catch dropped from 15 million to 1.5 million metric tons. This catastrophe and a cod war between Iceland and Britain helped fuel UNCLOS-III (1973–1982) which extended EEZs to 200 miles (Saunders, 1995; Hubbard, 2012).
Not until 1982 could Peru impose a fishing moratorium, enabling anchovy stocks, sea life, sea birds, and later the Peruvian anchovy industry to recover (Laws, 2000). Fisheries research was now the purview of nations, not international commissions. By this time, however, civil service reforms in Canada, France, Britain, and the United States had replaced highly qualified administrators with management experts whose interests did not include resource conservancy (Gough, 2006; Hayes, 1973). Also, after Canadian economist H. Scott Gordon’s seminal “The Economic Theory of a Common Property Resource: The Fishery” (1953), economists were hired as new government experts. They promoted efficiency, profitability, market studies, subsidized and industrialized fisheries, and wealth redistribution. Economists treated fish stocks as being inexhaustible and MSY as passé (Hubbard, 2014a; Wright, 2001). Gordon’s ideas inspired measures to restrict access to fisheries and create a form of property rights through setting total allowable catches (TACs), and licensing individual quotas or individual transferrable quotas (ITQs) within this limit. International Commission for the Northwest Atlantic Fisheries (ICNAF) officials pioneered setting TACs in 1969 with quotas for national fishing fleets. The use of restrictive ITQ measures has both assisted and hindered conservation and wealth creation (Gezelius, 2008; Harrison, 2008b; for positive outcomes see Mace, Sullivan, & Cryer, 2014; for problems with ITQs see Sumaila, 2010).
In the 1970s fisheries scientists were ordered to include economic and sociocultural parameters in fishing equations so as to pinpoint the nebulous optimum sustainable yield (OSY) or maximum economic yield (MEY). The MEY required using the ideal technologies and setting the precise catch amount that would help fishing communities, the industry, and the nation (Hubbard, 2014a). The U.S. National Marine Fisheries Service (NMFS) in the new National Oceanic and Atmospheric Administration (NOAA) hired economists and anthropologists to prod vexed biologists into managing people and fish populations for an OSY defined as the catch level giving the greatest benefit overall to U.S. food production, recreational fisheries, and marine ecosystems (Abbot-Jamieson & Clay, 2010). Canadian Peter Larkin, in his classic “Epitaph for Maximum Sustained Yield,” observed cynically that while government and UNCLOS-III policymakers had replaced MSY with OSY, they gave no operational basis to assist fisheries biologists (Larkin, 1977). Fearing political fallout, governments also failed to lower catch limits for MEY (Garrod, 1988). In 1972, ICNAF officials set an economically optimum TAC for Georges Bank herring two to three times higher than the scientists recommended (Stephenson, 1997).
Hazy goals meant conservation remained a low priority despite falling fish catch rates. Nevertheless, NAFO, the Canadian Department of Fisheries and Oceans (DFO), and UNCLOS-III in the 1980s adopted new management protocols. Followed Gulland and Borema’s (1971) proposal, they used virtual population analysis to manage fisheries around a new target of F0.1 as an alternative to MSY (or Fmax) (Gulland & Borema, 1971). This uses a reference point on the yield-per-recruit curve with a slope of only 10%—or F0.1—of the maximal growth rate, and sets the maximum catch level an order of magnitude below MSY (Brodziak & Overholtz, 1995). However, by convention, the natural mortality rate used, regardless of species, was 20%, or 0.2. If this educated guess was wrong, the entire F0.1 calculation was wrong. Moreover, F0.1 could not work under expectations that renewable resources not be under-utilized, and here and around the world, the politicians and bureaucrats overseeing national science programs refused to make effective conservation measures a priority. To do so would have involved severely restricting the catch limits, which would risk alienating voters. In non-democratic nations, the politicians simply did not care about conservation issues, and in developing nations or second tier nations like Canada, fisheries conservation came a distant second or even third place to economic dividends from trade agreements that allowed international fishing in national waters.
Mariculture and aquaculture research surged in the early 1970s as the future of wild-capture fisheries came into question. Central Marine Fisheries Research Institute (CMFRI) in India began researching seaweed, shrimp, pearl oysters, and clam cultivation when the natural pearl fishery collapsed (Central Marine Fisheries Research Institute, 2016). At Tahiti’s Pacific Oceanological Center, Japanese-born biologist I Chiu Liao set up a research program in 1969 that advanced shrimp-hatching methods, trained experts, and led to shrimp farms worldwide (Wyban, 2014; Nash, 2011). Norway began sponsoring aquaculture research when an international Atlantic salmon fishing frenzy in feeding grounds off Greenland annihilated wild populations. Dag Møller and Harald Skjaervold advanced techniques that made sea-farmed salmon Norway’s fourth biggest export; drove the emergence of Atlantic salmon farms worldwide; and facilitated, with the help of the International Center for Living Aquatic Resources Management (ICLARM), Atlantic, chum, and chinook salmon farming in Chilé’s remote southern coastal region (Nash, 2011; Cook, 2016; Liu, Olaussen, & Skonhoft, 2011).
Meanwhile, a full-blown environmental movement emerged in the 1970s. Learning that the tuna fishery caused incidental deaths of around 350,000 dolphins per year, the public boycotted canned tuna. The tuna industry developed new fishing maneuvers and modified technologies, reducing dolphin mortalities to negligible levels. Fisheries biologists also began gear modification research to reduce by-catch in shrimp trawls and juvenile mortality in other fisheries. Research to improve fishing gear selectivity and reduce incidental harm replaced designing ever-more efficient fishing technologies (Kennelly & Broadhurst, 2002).
1970s and 1980s: Multispecies Models and Ecology in Fisheries Biology
New scientific technologies in the 1960s included waterproof movie and still cameras. Towed underwater using in-house technology, these provided the first glimpses of commercial species’ undersea terrains (Foulkes, 2016). John Caddy later created the first dynamic spatial population models based on underwater Georges Bank scallop observations using a rented Perry submersible (Caddy, 2016). Hand-cranked calculators were replaced by IBM punch cards processed by offsite mainframe computers; by 1970 some laboratories owned mainframes. Later, with time-share computer terminals, scientists tried to develop multi-species models.
Multi-species models were first developed by International Council for the Exploration of the Sea (ICES) scientists stymied by the “gaddoid outburst,” a doubling in North Sea cod yields in the 1960s and 1970s. Danish scientists Knud P. Anderson and Erik Ursin found no linkage with plankton blooms, and to demonstrate that changing predation and species interactions caused it, introduced a multi-species model with predation factors in 1977. It was too complex to ever be used (Cushing, 1983; Pauly & Christenson, 2002; Rozwadowski, 2002). The gaddoid outburst led to ICES’s “Year of the Stomach” in 1981. Survey cruises collected over 100,000 stomachs from five commercial species. Predator-prey relations and food webs in the North Sea were revealed from stomach contents, analyzed via a computer program developed by Pope for a multi-species VPA (virtual population analysis) model incorporating changing predation mortality rates. Lowestoft physicist John Sheppard’s improved and widely used multi-species VPA model in 1988 included predatory mortalities and stock and recruitment relationships for eight species in five mixed fisheries. These models showed that predation mortalities for young fish were much higher than previously estimated, and confronted fisheries biologists with many new questions (Rozwadowski, 2002; Cushing, 1988).
Tropical fisheries biology was likewise challenged by complexity. High biodiversity means many species are captured simultaneously. Fisheries biologists used biomass-based versions of Schaefer’s surplus production model, or variations on single-species models that bundled related species or species with similar ecological profiles. But traditional reductionist models left out ecological factors that often have stronger effects on short-lived tropical fish populations than does fishing. Moreover, the catch and effort data required is difficult and expensive to gather. With no seasonality, most tropical species’ scales have no annual growth rings, but management models need population age structure. Verification was time-consuming, delicate, and costly, often involving counting daily growth rings in otoliths, bones, and scales using electron microscopy. Fisheries biologists nevertheless were able to devise methods to correlate lengths to age in tropical fish (Degnbol, 2004). In 1979 French fisheries biologist Daniel Pauly joined the International Center for Living Aquatic Resources Management (ICLARM) with a doctorate from the University of Kiel and offered a new length-based multi-species population model for tropical fisheries. Aided by two computer programmers, Pauly then developed ELEFAN (Electronic Length-Frequency Analysis) in 1980. ELEFAN uses length-frequency data to estimate fish growth and mortality. Pauly and Dang Palomares gave a course on ELEFAN at Senegal’s University Cheikh Anta Diop. Disseminated later via USB sticks, ELEFAN saw widespread use in tropical fisheries (Palomares & Pauly, 2013). Other aids come from the United Nations’ Food and Agriculture Organization (FAO)’s FiSAT software program for DOS, and FiSAT II, developed with ICLARM for Microsoft Windows, which use length measurement data in Beverton-Holt fishing equations (Degnbol, 2004).
Fisheries oceanography remains a weak area for fisheries science. While ICES had been founded to relate ocean dynamics to fish populations, most oceanographers preferred deep water research over iterative plankton surveys. World War II drew them into strategic physical oceanography; thereafter, biological oceanography studies remained underfunded and unable to assist Lowestoft biologist John Cushing’s quest to confirm his 1969 “match/mismatch” hypothesis that probed the timing of spawning and phytoplankton blooms caused by nutrients mixing vertically in the water column. If they coincided, a plankton bloom would sustain larval fishes and give a good year class; climate anomalies, however, could shift the timing or range or overall productivity, and larval fish would starve. Biological oceanographers by the 1980s had a fair understanding of how climate, ocean currents, and temperature anomalies affect phytoplankton biomass. However, insufficient funding has left them unable to relate these to zooplankton fluctuations and fish populations (Longhurst, 2010; Rozwadowski, 2002). The insights that might be generated are exemplified by Canadian scientists Derrick Iles and Michael Sinclair’s discovery that herring larvae aggregate in stable “retention” areas due to the ocean’s physical structure and larval herring behavior. In 1990–1992, ICES’s Cod and Climate Change (CCC) program was created and coordinated with the new and ongoing U.S. Global Oceans Ecosystem Dynamics (GLOBEC) program to address these problems (Rozwadowski, 2002).
Population ecology also offers insights into how environmental effects govern species’ life histories and affect population fluctuations and evolution. Charles Elton’s Bureau of Animal Population at Oxford University, founded in 1932, pioneered much of the work that influenced fisheries ecologist Hiroya Kawanabe, a Kyoto University professor of ecology who visited in 1963, and Canadian fisheries biologist Peter Larkin, Elton’s doctoral student. Elton insisted that complexities and local variations in populations had to be incorporated into applied population ecology. He commended the Japanese focus on individuality shown in Kawanabe’s research, and decried Western scientists’ over-generalizations (Yuma & Harada, 1998).
Using a snorkel and mask, Kawanabe had spent years floating above and observing ayu. The ayu, a short-lived (annual) algae-eating amphidromous freshwater fish, supports Japan’s most important commercial freshwater fishery. Kawanabe’s studies of their social structure and ecology helped determine optimum stocking densities in rivers. Their territorial behavior altered dramatically with changing population density, during dam construction, and in streams versus lake habitats. During international fisheries and ecological investigations of Lake Tanganyika led by Kawanabe in 1979, 1981, and 1983, he also discovered that a third species will alter the behaviors of two interacting species (Yuma & Harada, 1998). Japanese fish ecology gained influence in the 1970s, once articles in English started appearing in international journals (Fausch & Nakano, 1998). In the 1990s Western scientists awoke to the important impacts individual fish behaviors can have on commercial species’ populations.
Larkin, after researching Blenheim Palace estate’s mole population (Crowcroft, 1991), in 1948 became British Columbia’s first chief fisheries biologist and a professor at the University of British Columbia (UBC). He also directed the Pacific Biological Station from 1963 to 1966. In 1952 he created the British Columbia Fisheries Research Section at UBC to connect fisheries managers and academics; the Institute of Fisheries he also founded in the UBC Department of Zoology in 1955 (Northcote, 1996) was reincarnated as the influential Fisheries Centre, formed in 1991. Larkin’s ecological insights were missing from most of his colleagues’ work. For example, his 1971 “Epitaph for the Concept of Maximum Sustainable Yield” predicted that intensive fishing placed evolutionary pressure on fish populations, because fewer fish survived to full reproductive maturity. Fisheries biologists only fully recognized this after the cod crisis of 1992. By this time many population ecologists, like Carl Walters and Ray Hilborn, had been lured into fisheries science by the jobs and research funding that arose from the new 200-mile exclusive economic zone (EEZ) (Hilborn, 2016). Their recognition of ecological complexity led them to develop stochastic dynamic models. These incorporate the uncertainty of highly random events that might affect the resource, predators, and prey species (Hilborn & Walters, 1992). Unlike deterministic and mechanistic mid-century models, stochastic models in the late 1980s gave multiple outcomes and could be used to assess the risks of various management options (Degnbol, 2004).
Beverton and Holt themselves had proposed that fisheries population data were ideal for investigating life-history patterns in population ecology. They discovered certain ratios between life span, rates of growth, natural mortality, and age of recruitment were both dimensionless and invariant, and that these invariants could be substituted for hard-to-estimate natural mortality and growth rates. These also give insights into physiological trade-offs between growth, survival, and reproduction in populations. Beverton’s studies of walleye in lakes from northern Canada to California showed that lifetime egg production was almost constant, despite the walleye being slow growing and reaching the age of 20 in the north, and fast-growing but living to only the age of 3 in the south. Temperature must affect recruitment, growth, and death rates. Theoretical ecologist E. L. Charnov in 1993 confirmed Beverton’s suggestion that evolutionary trade-offs caused the invariants’ constancy across species with differing life histories. Growth rates trade off with body size: fast-growing species are small at maturity, and slow-growing species like cod, lobsters, and lizards become large and often have no maximum size related to age, showing indeterminate or asymptotic growth. Beverton-Holt invariants have helped fisheries biologists to predict a population’s yield-per-recruit, recovery from recruitment overfishing, or resilience to low population size. Ransom Myers applied them to spawner-recruit data as a less data-intensive method for estimating intrinsic rates of population increase for many species. Pauly in 1980 based a method for estimating natural mortality on Beverton-Holt invariants that has become almost standard (Jennings & Dulvy, 2007). Where fishing data are lacking, knowledge of a species’ life history in relation to the environment can now be used to predict how its population will be affected by fishing and whether overfished stocks are in danger of commercial extinction (Reynolds, Dulvy, Goodwin, & Hutchings, 2005).
After 1990: The Threat of Extinction
Up to the early 1990s, fisheries biologists tended to dismiss the possibility of stock or species extinction. Yet in the Black Sea, dolphins and monk seals had disappeared, and only 6 of 20 formerly commercially viable fisheries were left, due to uncontrolled subsidized fishing fleets, pollution, and eutrophication (Oral, 2013). A few scientists promoted precautionary management principles to prevent irreversible change in ill-understood ecosystems (Garrod, 1988), but extinction risks were only widely acknowledged for slow-growing species like endangered right whales. Commercial extinction occurred for blue whales by 1955, humpbacks and fin whales by 1965, and sperm and sei whales by 1980, each after about 30 years of industrial-scale fishing (Longhurst, 2010). In 1986, a decades-long campaign by Sidney Holt and others finally convinced the International Whaling Commission to set catch limits for all species to zero—a ban still resisted by Japanese and Norwegian fisheries managers.
The 1992 closure of Canada’s Grand Banks fishing grounds, historically the world’s most productive fishery, changed everything. Fisheries biologists and fish stocks were finally “swept up in the conservation movement” as conservationists concerned about extinction risks battled fisheries scientists concerned with stock recovery and feeding human populations (Reynolds, Dulvy, Goodwin, & Hutchings, 2005). Debates included the extent and uses of proposed marine protected areas, that is, ocean regions closed to some or all kinds of fishing, which are problematic given that many species are highly mobile or migratory, and their larvae are carried by currents, so no reserve of any economically reasonable size will protect all species, and fishing vessels will target their rich perimeters if they do succeed in increasing biomass, undoing many desired benefits (Sumaila, Guenette, Alder, Pollard, & Chuenpagdee, 1999). But the 1994 United Nations’ Food and Agriculture Organization (FAO) “Review of the State of World Marine Fishery Resources” reinforced the need for a new mindset: in 1990 the global catch fell by 3% from a peak of 93 million metric tons. Experts now acknowledged overfishing caused local extinctions and disrupted natural fish populations and ecology. Support was almost universal when Canada went after Spanish and Portuguese trawlers fishing the Grand Banks that drifted within Canada’s 200-mile exclusive economic zone (EEZ) at night, while using illegal net-liners with small mesh holes. Canada’s demands for new international instruments to conserve depleted stocks led to the UN’s new protocol for the Conservation and Management of Straddling Fish Stocks and Highly Migratory Fish Stocks, opened for signature in December 1995. This agreement legally binds countries to sustainably manage and conserve fish stocks on the high seas using a precautionary approach. In addition, the FAO’s 1995 “Code of Conduct for Responsible Fisheries” called for a precautionary approach with substantially lower target reference points than maximum sustained yield (MSY).
The cod crisis was environmental and scientific. Senior scientists in the Department of Fisheries and Oceans (DFO) had been confident that the cod stocks were rebuilding and being fished sustainably. Their population assessments, however, were compromised by DFO biologists’ extrapolation of assessment results from limited routine stock surveys and over-reliance on reported commercial catch-rates. Commercial catch data were distorted by discards of undersized fish, under-reported catches, and the industrialized fisheries’ ability to target remaining fish concentrations using sonar, thus minimizing effort. Scientists consistently over-estimated the size of cod stocks and set total allowable catches (TACs) that were too high. The DFO also shut down challenges to its official conclusions by its own scientists (Longhurst, 2010; Hubbard, 2006, “Epilogue,” pp. 225–262). In the early 1990s, shifting boundaries between the icy Labrador Current and the warm Gulf Stream in the Grand Banks’ shallow waters caused anomalous temperature spikes, hindering cod reproduction and exacerbating ongoing depletion. DFO scientists, lulled by mechanistic models based on a steady-state fishery ecosystem, were “stupified” by the cod crisis and non-recovery of cod populations (Longhurst, 2010).
Fisheries scientists now acknowledged and discussed the need for a Kuhnian paradigm shift. They critically examined their own assumptions, especially the role of MSY management; recognized that other species in the ecosystem need protection, including allocating commercial species for other species’ needs; criticized over-reliance on reductionist population models; increased scientific focus on how fishing affects target populations in natural ecosystems; called for life history and ecology investigations to improve population models and assist precautionary principles; and attempted to adopt or at least define ecosystem management.
Experimental models helped to gauge how multi-species communities respond to fishing. Some argued that models were gross abstractions, conveying their properties to fish populations (Schnute & Richards, 2001). However, critical insights after 1992 came from the analysis of data from historical databases. National fisheries agencies, ICES, NPFC, ICLARM, NAFO, IATTC, ICNAF, and other commissions had amassed huge data archives for catches, catch compositions, fishing technology, and fishing effort. The FAO added annual global fishing vessel data. John Gulland, who joined the FAO in 1964, guided its publication of The Fish Resources of the Oceans in 1970, which gave the first estimates of global fishery production, including tropical resources. At the International Center for Living Aquatic Resources Management (ICLARM) Pauly also created and standardized a new central repository of published data. In 1988 he recruited German graduate student Rainer Froese to develop FishBase, a software database. Froese took charge of the project in 1990, and with ICLARM and FAO support, expanded it from tropical fish to include all fin-fish (Froese, 2000), headquartering it at Kiel’s Helmholtz Centre for Ocean Research when he joined as a senior scientist. Updated data from international institutions and scientists were released annually via CDs; since1996 the FishBase website has offered daily updates (Froese & Pauly, 2016). These free online data files enable ongoing scientific assessments of global fisheries.
Ransom A. (Ram) Myers, with his MSc in mathematics and a PhD in biology from Dalhousie University, Nova Scotia, began the meta-analysis of these data series. Working at the DFO’s Northwest Atlantic Fisheries Centre in St. John’s, Newfoundland, he observed the cod crisis firsthand. Myers used historical data and led a handful of DFO scientists in publishing evidence that rebutted DFO attempts to attribute the collapse only to predation and abnormal temperatures. Unlike his colleagues, however, he aired his scientific disagreement publicly (Hubbard, 2006; Harris, 1998). After DFO attempts to silence him, he joined Dalhousie University in 1997, holding the Killam Chair in Ocean Sciences until his untimely death in 2007. To show that low population densities from overfishing caused the collapse, Myers revisited the issue of juvenile fish survival rates. He, Nicholas Barrowman, Jeffrey Hutchings, and others painstakingly trolled through international fisheries agency reports. They normalized 364 time-series of data to form comparable units within and between stocks for a wide variety of commercial species (Myers, 1997). They found that in large species at low population sizes, only three to five young survive to become adult fish out of the millions of eggs each female sheds that become fertilized. Myers ended the possibility that scientists imbued with the “millions-of-eggs” fallacy could continue giving fishery managers over-optimistic advice (Pauly, 2007).
Myers confirmed that industrial fisheries worldwide had serially annihilated stocks of tuna, marlin, swordfish, and other large pelagic fish, and large demersal fish such as cod and plaice. He pioneered fisheries conservation biology, which identifies species nearing commercial or total extinction through over-exploitation and develops ideas to rebuild populations while also rehabilitating and restoring their ecosystems, not primarily for the fishing industry but to aid organizations and governmental and international bodies mandated to preserve marine biodiversity and ecosystems for humanity, nations, and nature (Pauly, 2007). Myers also began the “Future of Marine Populations” (FMAP) project for the Census of Marine Life (COML). Funded by the Alfred P. Sloan Foundation from 2000 to 2010, and headed by Dr. Ron O’Dor at Dalhousie University, it drew more than 2,700 scientists from 80 nations to inventory all marine life from pole to pole. COML used new technologies such as satellite transmitting tags to assess fish migrations and movements. FMAP offered models and simulations for predicting marine populations and ecosystems, and an online stock-recruitment database of over 600 populations of more than 100 fin-fish species, Canadian Atlantic leatherback turtles, and the PEW Global Shark Assessment, for use by scientists worldwide.
When northwestern cod populations failed to recover after 1992, biologists began to ask if depensation was a factor. University of Chicago ecologist Warder C. Allee introduced the theory of depensation in the 1930s from studies on tank-raised goldfish populations. Goldfish grew faster when tanks held more individuals. He speculated that low-density populations might lack some factor like cooperation and this might cause depensation. Few studies of fisheries depensation were done prior to 1995, when Myers tried to detect it in fishery data sets for 128 fish stocks, using a modified Beverton-Holt spawner-recruitment function. Depensation was found in only a few cases, including some Pacific salmon stocks and an already-identified case in Icelandic spring and summer spawning herring from the 1970s (Holt, 2008a; Myers, Barrowman, Hutchings, & Rosenberg, 1995). Other fishery biologists were skeptical. Using Bayesian analysis and more complete spawner-recruitment data sets, in 1997 Martin Liermann and Ray Hilborn compared many population groups within selected heavily fished species. Bayesian analysis, developed by Thomas Bayes in 1763, incorporates probability distributions of chosen parameters but was too complex for much use before powerful personal computers became available (Cowles, Kass, & O’Hagen, 2016). Evidence for depensation in a Gulf of Maine cod population indicated that fisheries managers must consider it as a possibility (Liermann & Hilborn, 1997).
Since 1995 many different depensation mechanisms have been identified. A 2000 study for the Caribbean Marine Research Center showed that the queen conch, a prized Caribbean food, will not mate when densities fall below 48 adults per hectare, with an ideal mating density of 200 adults per hectare. A 2004 study of northern cod found that up to three other males release milt in the vicinity of a mating pair. Such spawning aggregations will rarely occur in a depleted population, and females will delay spawning if no males are near, reducing the viability of their ripened ova. Depensation also affects non-reproductive behaviors. Young sockeye salmon and small species like capelin or anchovy form daytime shoals to assist individual survival rates: large masses of small fish confuse predators. At low populations, individual fish that disperse to feed at night cannot easily find each other and form shoals as day breaks. Smaller schools offer less protection against large predators. Models show that at higher densities, prey-prey encounters are likelier than prey-predator encounters (Longhurst, 2010).
Many population models failed because they treated individual and species interactions like “random encounters of chemical species in reaction vats” though even field biologists with limited experience know organisms are never randomly distributed in nature (Walters & Martell, 2004; Pauly & Christensen, 2002). Fisheries biologists awakened to their need for life-history information. Their ability to predict depensation and collapse from the intrinsic aspects of life histories means that they can help set priorities for conservation action.
The increased focus on life histories also revealed that issues of precision, accuracy, and standardization persist in assessing the age structure of fish stocks. Thirty years of work by the ICES Study Group on Baltic Cod showed systematic differences between age readers; moreover their scale and otolith readings consistently under-estimated fishes’ true ages; fishery biologists were thus shocked by the revelation of the extreme age of fecund female redfish (Longhurst, 2010). Pacific rockfish or redfish (Sebastes spp.) can live 200 years or more; unlike in mammals, females become increasingly fecund with greater age. The eggs of BOFFFs (Big Old Fat Fecund Females) are also more viable than those shed in smaller quantities by younger females (Longhurst, 2002).
Population ecology showed that neither theory nor empirical evidence supports Huxley’s idea that highly fecund ocean fishes are inexhaustible and can thus withstand heavy fishing (Reynolds et al., 2005). It is true that smaller, fast-growing species with high intrinsic population growth, like plankton-feeding herring and sprat, show “low compensation”: little relationship exists between population size and juvenile mortality. High intrinsic reproduction rates reflect their ability to use the abundant energy at the food-web base, so they rapidly recover when fishing is ended. However, large-bodied, slow-growing species, like cod, are highly vulnerable to population loss. High fecundity levels ensure the survival of populations across long periods of unfavorable hydrographic and environmental conditions. Cod recruitment is density dependent: when the population is depleted, fewer eggs, larvae, and juveniles survive (Goodwin, Gran, Perry, Dulvy, & Reynolds, 2006; Jennings & Dulvy, 2007). For cod, the mean adult age before industrial fishing was 25, and the older females were more fecund and spawned better quality eggs. The cod crisis of 1992 occurred because heavy fishing meant that cod rarely survived beyond the age of 6. This caused the evolution of smaller, fast-maturing cod with lower fecundity, but this life history profile does not accord with naturally evolved characteristics that ensure population survival in northern waters.
Fisheries Biology for Food Security, Ecosystems-Based Management, and Co-Management
Global food security concerns emerged from the continuing non-recovery of northern cod and from global industrial overfishing. At the University of British Columbia (UBC), Larkin’s former Institute of Fisheries was revived in 1991 as the Fisheries Centre (as of 2015 the Institute for the Oceans and Fisheries) under the direction of Tony Pitcher. Scientists at The Fisheries Centre, perhaps the world’s most influential fisheries science institution, used historical data-series to evaluate global fisheries. Pitcher, Carl Walters, Daniel Pauly, Villy Christensen, Rashid Sumaila, Dirk Zeller, Sylvie Guénette, and others in the “Sea Around Us Project” (SAUP) analyzed world data sets going back to the 1950s, finding that illegal, unreported, and unregulated fisheries, and discards of unwanted and underweight fish equaled about half the total landings reported to the United Nations’ Food and Agriculture Organization (FAO) since 1970. Christensen and Pauly also developed the Ecopath ecosystem modeling software started at the National Oceanic and Atmospheric Administration (NOAA) by Jeffrey Polovina. Their analysis of changes in North Atlantic fish abundance at all trophic levels since 1950, using ecological groups instead of age-structured populations, showed that biomass declined linearly even as catches peaked around 1970. Most experts had no doubt that industrial fishing led this change (Longhurst, 2010). Moreover, after overfishing choice top predator species like tuna, the industry has gone after fish at progressively lower trophic levels, thus “fishing down the food web” (Pauly, Christensen, Dalsgaard, Froese, & Torres, 1998) and reducing food resources and species diversity. Remaining predators become more vulnerable to population fluctuations of prey species, and destabilized systems become harder to predict (Pauly et al., 2002; Pauly, 2010).
SAUP scientists also conducted detective work on international catch reportage. When China liberalized economically in the 1980s, fishing fleets rapidly expanded with minimal regulations or enforcement for conservation. The FAO in 1996 was concerned that China’s increasing wild harvest contrasted with stable or falling catches around the world. In a 2001 article in Nature, Reg Watson and Pauly critiqued Chinese fishing statistics (Watson & Pauly, 2001; Pauly, 2010). A 2009 history of Chinese fisheries confirmed their suspicions that management objectives still promoted increasing fishery production and profits for economic development. Bureaucratic infighting, political posturing, budgetary struggles, and the need to appear to boost production and revenues shaped scientists’ research (Muscolino, 2009). The outcry following Watson and Pauly’s paper led China to acknowledge its errors. Then it carried on as usual. China allegedly caught 13.8 million tons in 2012, over twice the catch of the next most important fishing nation, Indonesia, and a higher total catch than in 2002 (FAO, 2014).
The cod crisis provoked the emergence of a new paradigm that replaced the maximum sustainable yield as a target for fisheries managers, while keeping maximum sustainable yield estimates as important tools for fisheries scientists. The new paradigm is ecosystems-based fishery management. It was first mooted in NOAA-NMFS’s 1987 “Ecosystems Monitoring and Fisheries Management” plan, but only began to gain traction in 1995 (Longhurst, 2010). The concept implies holistic and field-observation studies of all ecosystem parameters followed by conceptual models of these ecosystems. Ironically, its use in fisheries management, if such has yet occurred, actually depends upon model simulations to test specific ecosystem ideas and management models. Any computer program integrates its maker’s biases, offering, according to John Caddy, co-creator of YAREA, the first spatial marine fisheries management model, “Pre-digested solutions to your modelling needs” (Caddy, 2016, 2008).
As with all other developments since 1992, ecosystem-based fisheries management has only strengthened fisheries scientists’ reliance on metrics; their new ecosystem models are so complex that their work environment is dominated by computers. Defining and implementing ecosystems-based management has also proved problematic; despite many studies of its principles, there are few concrete results (Longhurst, 2010). One exception is Rapfish (Rapid Appraisal for Fisheries; rapfish.org), developed by John Caddy at FAO in collaboration with Pitcher at the Fisheries Centre (Pitcher, 1999). It offers a simple, “traffic light” approach to determine whether a fishery could be ranked on a scale from “good” to “bad,” using numerical values for a range of chosen indicators including social needs, the ecosystem, and economic outcomes. Adding them gives a total that indicates if certain measures are needed. Rapfish is an easily used, fast, cost-effective tool to appraise whether a fishery is sustainably managed; best and worst-case examples act as reference points (Longhurst, 2010).
Ecosystems-based management in itself will not solve fisheries problems. The 20th century’s open-access industrialized fisheries and replacement of traditional local governance by top-down government management resulted in depleted fish stocks, disrupted ecosystems, and reduced compliance with regulations. Poor management decisions de-legitimized fisheries managers and scientists. Government decision-makers, the fishing industry, and scientists all exploit uncertainties in scientific estimates. During the cod crisis, politicians prioritized fishing sector votes over serious resource conservation, and exploited scientific uncertainty to set high fishing quotas. Decisions ultimately rested with the fisheries minister, who shed responsibility by invoking scientific failure. Finally, scientists themselves called for further research funding. Government scientists, moreover, have allowed themselves to be pressured into defending and setting higher total allowable catches (TACs) than are scientifically justified (Cochrane, 2000). Beyond these problems, most coastal nations, both developed and developing, neither effectively manage nor police their coastal fisheries, lacking finances or sufficient political will to do so, and the international community is complicit in turning a blind eye. For example, according to Longhurst, “piracy of fishing vessels is not uncommon off Nigeria, the catches of the captured vessels being sold to freezer ships waiting offshore, to be landed and sold in a complaisant port” (personal communication). In this context, the collection of international fisheries statistics as a measure of the status of the world’s wild stocks remains highly problematic. Modern fisheries science has not yet been successfully adapted to the social contexts of local institutions and practices. Different interest groups, including aboriginal peoples, have been excluded from resource conservation policies. Greater inclusiveness is required to give resource science legitimacy among stakeholders (Degnbol, 2004). Applied science needs to serve a society’s requirements, so fisheries scientists face the challenge of learning about the human “ecosystem” in which the fishery is operating, including its changing economic incentives and political pressures, and integrate considerations of ecology, sustainability, maximum sustainable and maximum economic yields from the fishery, the traditional ecological knowledge of fishers and their management perspective, and the social traditions and employment and lifestyle needs of fishing communities (Longhurst, 2010). Scientists have become more deeply engaged with fishers, fisheries associations, sociologists, anthropologists, and representatives of indigenous communities to champion engagement of all legitimate interest groups, including conservationists, to ensure that the best available information is used and shared, and that formal and iterative management decisions are developed through co-management that involves all legitimate stakeholders (Lane & Stephenson, 1998). These approaches will not solve all fundamental conflicts between stakeholders going forward, as different fisheries require sometimes conflicting management goals (Cochrane, 2000), but they do provide principles for moving forward.
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