MS Work 2011 Daniel Meyer
Master´s Thesis, 60 credits Ecosystems, Governance and Globalization Master´s programme 2008/10, 120 credits
Transitions and Resilience in the Frozen Commons
Linking Aquaculture, Krill Fishery, Governance and Ecosystem change in the Scotia Sea, Southern Ocean
Daniel E. Meyer
TRANSITIONS AND RESILIENCE IN THE FROZEN COMMONS:
LINKING AQUACULTURE, KRILL FISHERY, GOVERNANCE AND ECOSYSTEM CHANGE IN THE SCOTIA SEA, SOUTHERN OCEAN
Daniel E. Meyer
Master’s Thesis in Ecosystems, Resilience and Governance (ERG) 120 credits
Supervision: Henrik Österblom
Stockholm Resilience Centre 2011
ABSTRACT The Antarctic krill (Euphausia superba) is a forage fish species that is increasing in importance for Southern Ocean fisheries and world aquaculture production. However, this species also has a fundamental role in the Scotia Sea food web and is the main conservation target for the region’s natural resource management organization the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). The aim of this thesis is therefore to examine the inter relationship between CCAMLR, krill fishery and the Scotia Sea ecosystem in the Southern Ocean, as well as broader socio economical and ecological settings since 1970s and measure system resilience. The premise here is that the current krill regime in the Scotia Sea must be understood as a complex adaptive system (CAS) of social, ecological and economical attributes that operates over different temporal and spatial scales. Thus, by applying the framework of a social ecological system (SES), together with the adaptive cycle heuristic model, both quantitative and qualitative data is revised and integrated. Two alternate management states are identified within the krill regime; an early krill fishery state (1972 – 1991), and an ecosystem based governance state (1991 2010). Resilience is however fading in the Scotia Sea due to a combination of cross scale attributes, in a range from low krill density (n/m ²), increased competition for marine resources between predators and krill fishery, to elevated demand and global market prices of non food commodities by the aquaculture sector in Asia, thus, moving the Scotia Sea towards an unknown fish regime. Although such future regime is still retained by the region’s slow changing physical variables such as sea ice and seasonality, as well as the adaptive management capacity of CCAMLR, the sudden appearance of an undesirable regime in the Scotia Sea would probably have comprehensive socio ecological consequences if reached.
ACKNOWLEDEMENTS First of all, I would to thank my supervisor, Henrik Österblom, from Baltic Nest Institute and Stockholm Resilience Centre who patiently supported me during the examination year. I want to thank Miriam Huitric and Lisa Deutsch, also from the Stockholm Resilience Centre for their support. Many thanks to Angus Atkinson from the British Antarctic Survey, and Steve Nicol from Australian Antarctic Division, and Chiara Piroddi from the Fisheries Centre at University of British Columbia, Canada. And finally, I wish to express gratitude to my Academia friends Quentin Dilasser, Rolands Sadauskis, and Ulla Gabrielsson for your comments.
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TABLE OF CONTENTS
Abbreviation Figure and tables
INTRODUCTION ...... 8
THEORY ...... 10 Resilience ...... 10 Adaptive cycle ...... 11 Social ecological systems ...... 12 Governance ...... 14 Ecosystem dynamics ...... 16 Research framework ...... 19
CASE STUDY DESCRIPTION ...... 20 The Southern Ocean ...... 20 The Scotia Sea ...... 20 Antarctic krill ...... 22 Krill predators ...... 23 Forage fishery ...... 24 Forage fishery in the Southern Ocean ...... 25 Management of the Southern Ocean ...... 26 CCAMLR ...... 27
METHOD ...... 31 Epistemological background ...... 31 Methodological approach ...... 32 Indicators ...... 33 Applying the adaptive cycle ...... 34 Data sources ...... 35 Critical reflection of method and data used ...... 36
RESULTS ...... 38 Users (U) ...... 38 Resource system (RS) ...... 41 Resource unit (RU) ...... 42 Governance system (GS) ...... 43 Related ecosystems (ECO) ...... 44 Socio economical settings (S) ...... 46
DISCUSSION ...... 49
CONCLUSION ...... 56
REFERENCES ...... 58 Appendices
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ABBREVIATION
ACC Antarctic Circumpolar Current ACZ Antarctic Convergence Zone APEI Antarctic Peninsula Elephant Island APDPE Antarctic Peninsula Drake Passage East APDPW Antarctic Peninsula Drake Passage West APGR Average Annual Percentage Growth Rate AT Antarctic Treaty ATCM Antarctic Treaty Consultative Meeting CAS Complex Adaptive Systems CCAMLR Convention/Commission for the Conservation of Antarctic Marine Living Resources CEMP CCAMLR Ecosystem Monitoring Program CM Conservations Measures ECO Ecological/Environmental Setting EA Ecosystem Approach ES Executive Secretariat FAO Food and Agriculture Organization of the United Nations FIGIS Fisheries Global Information System GS Governance System I Interactions IFFO International Fishmeal and Fish Oil Organisations IUCN International Union for Conservation of Nature IUU Illegal, Unreported and Unregulated LC Least Concern MOR Mid oceanic Ridges NASA National Aeronautics and Space Administration O Outcomes PA Precautionary Approach RS Resource System RU Resource Unit S Socio economical Setting SES Social ecological System SC Scientific Committee SCAF Standing Committee on Administration Finance SCOI Standing Committee on Observation and Inspection SOW South Orkney West SSMU Small scale Management Unit THC Thermohaline Circulation U Users UNCLAS United Nations Convention on the Law of the Sea WG EMM Working Group on Ecosystem Monitoring and Management WG FSA Working Group on Fish Stock Assessment
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FIGURES AND TABLES
Figure 1 . The adaptive cycle and its four phases Figure 2. A framework for analyzing social ecological systems
Figure 3. The Southern Ocean food web
Figure 4. The theoretical research framework Figure 5. The Scotia Sea and the Southern Ocean Figure 6. Antarctic krill density (n/m ²) around the Southern Ocean Figure 7. Antarctic krill density (n/m ²) near (a) the Antarctic Peninsula and South Orkney and (b) South Georgia Figure 8. Total global catches by forage fishery destined for non food and reduction uses, and total catch of the seven most target species commonly destined for non food uses (1970 2009) Figure 9. Comparison of fisheries in the Southern Ocean since 1950s until recent times Figure 10. The CCAMLR Convention Area
Figure 11. Example of how the adaptive cycle is applied on the SES of the Scotia Sea
Figure 13. Share of annual reported catch (tons) of Antarctic krill per country (1970 2010)
Figure 14. Total nominal catch of Antarctic krill per subarea and year in FAO’s fishing area 48
Figure 15. Two different catching technologies used by krill fishery in the Scotia Sea
Figure 16. Changes in lantern fish density (1990 2000s)
Figure 17. Change in mean density (ind. m ²) of Antarctic krill within the Scotia Sea
Figure 18. Development of conservation measures in the Scotia Sea on krill fishery Figure 19. Sea ice cover extension changes in the Southern Ocean and Antarctic
Figure 20. Temporal sea ice cover changes in the Southern Ocean and Antarctic
Figure 21. Comparison between world capture fishery and aquaculture production with emphasis on Asia and China
Figure 22. Global fish meal and fish oil market
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Figure 23. Fish meal production by country (1976 2008) Figure 24. Fish meal use by country (1976 2008) Figure 25. Fish oil production by country (1976 2008) Figure 26. Fish oil use by country (1976 2008) Figure 27. Schematic summarize of results Figure 28. The way of the SES in the adaptive cycle between 1970 – 1990 and the strength of connection between analyzed internal and external variables Figure 29. The way of the SES through the adaptive cycle between 1990 – 2010 and the strength of connection between analyzed internal and external variables
Table 1. Variables affecting a system and the adaptive cycle Table 2. Biomass estimation on Antarctic krill from different studies since 1970 Table 3. Main krill dependent predators in the Scotia Sea Table 4. Governance regimes in the Southern Ocean Table 5. Metaphors of knowledge recognized within normal science and post normal science
Table 6. Categorization of primary and secondary data sources used in this work
Table 7. Development of the Scotia Sea’s rule configuration
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If you would understand anything, observe its beginning and its development Aristotle
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INTRODUCTION Forage fish such as anchovies, herrings, menhaden and krill are important prey for marine mammals, seabirds and several other predators. These small fishes have a crucial role throughout the world’s oceans, as they transfer energy in marine food webs from lower to higher trophic levels (Alder et al 2008). Without forage fish many of the existing marine ecosystems would collapse. However, harvesting effort of forage fish in 2008 accounted for 31.5 million tons (Mtons), 37 % of global marine landings (ibid.). A majority of this was reduced into non food (i.e. fishmeal and fish oil) and used by the worlds fastest growing animal food producing sector; aquaculture (Deutsch et al 2007, Naylor et al 2009, FAO 2010). Thus, the major question nowadays, as forage fisheries and marine ecosystems are becoming fully exploited, is from where aquaculture will provide their future aquafeeds. In recent years there has therefore been a renewed interest in the Antarctic krill ( Euphausia superba ), a shrimp like species and forage fish targeted since early 1970’s in the Southern Ocean. During the 2009/10 fishing season total catches reached > 210 000 tons, up from 90 000 tons in 1997/98 (CCAMLR 2011, FIGIS/FAO 2011). Due to its highly estimated biomass, protein and amino acids richness, the extraction and commercial interest in this species is expected to continue to increase in the Southern Ocean (Naylor et al 2009).
The Convention on the Conservation of Antarctic Marine Living Resources (CCAMLR) is the international agreement responsible to conserve marine life of the Southern Ocean. Set into force in 1982, CCAMLR was to become a pioneer in incorporating the ecosystem and precautionary approaches (EA/PA) into management objectives; wherein scientists and fishing nation delegates, through collection of data, were to set catch limits and monitor fishery, ensuring that it would not impact adversely on species related to, or dependent on the target specie (Gascon & Werner 2006). In a recent examination of 13 regional fisheries management organizations, Mooney Seus & Rosenberg (2007) concluded that CCAMLR today is the most advanced natural resource management organization in terms of developing and implementing EA/PA measures. This is mainly achieved by using precautionary reference points (targets and limits), which changes according to weighting of uncertainties in data on what is known about the ecosystem. Despite of these encouraging remarks, krill fishery has since early 1970s focused nearly all its harvesting efforts in one and relatively small area of the Southern Ocean; namely the Scotia Sea.
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The Scotia Sea has during a long time sustained high density concentrations of Antarctic krill (Atkinson et al 2009), therefore considered to have a fundamental role in the Scotia Sea food web, mainly by supporting populations of larger marine animals (Dziek & Jazdzewski 1978, Reid & Croxall 2000, Gascón & Werner 2006, Murphy et al 2007). Nevertheless, seals and whales, many recovered from centuries of hunting and near extinction have rapidly increased in abundance here. The International Union for Conservation of Nature and Natural Resources (IUCN) (2011) has recently even classified some, such as the humpback whale (Megaptera novaeangliae ) and the Antarctic fur seal ( Arctocephalus gazella ) in the conservation category of least concern (LC) 1. The escalated coexistence between marine predators will hypothetically result in tough rivalry for prey, and establish competition with the krill fishery by the passing of time. In addition, the Scotia Sea ecosystem is also embedded in larger socio economic and environmental settings. The appearance of new krill fishing nations, international market fluctuations in the supply and demand of non food commodities, increasing aquaculture production, changes in sea ice extension or climate change are some examples of external forces that are connected to the Scotia Sea. This scenario creates vast complexities, challenging the operational capacity of CCAMLR. A transdisciplinary examination on the historical socio ecological changes in the Scotia Sea is therefore needed, considering both its capacity of regeneration and resilience for the future.
The aim of this work is therefore two fold; firstly to provide improved understanding on the inter relationship between CCAMLR, krill fishery, the Scotia Sea ecosystem and its larger socio economical and ecological settings over time, and secondly to measure the resilience of the Scotia Sea as an interacting self organizing system in the Southern Ocean. As far as it is known no research attempts have been made to evaluate such a proposition for the Scotia Sea. This will be done by answering the following two research questions: Which were the outcomes from using, or not using, a set of fishing rules for the Scotia Sea ecosystem and krill fishery in a multiple dependent socio economic and ecological environment since early 1970’s? And how did the outcomes of this relationship affect the resilience of the Scotia Sea? To answer these questions a cross scale framework will be applied and used in the context of resilience theory. This will no only support the organization in bringing together what is known, but also help it to meet the new challenges due to ecosystem and global change.
1 Not qualified as threatened, near threatened, or conservation dependent 9
THEORY During most of the 20th century natural resource management asserted scientific decision making as objective and neutral, emphasizing constant stability, prediction, certainty and control (Holling & Maffe 1996). This surpassingly created a belief that it was possible to manage the environment without accounting for natural variations, disturbances, cross scale interactions or the different human stakes involved (Allison 2003). However, during the last decades notions such as complexity, uncertainty, multiple stable states and feedbacks have emerged, creating discussions about the ‘problem of fit’ between natural resource management systems to the dynamic behavior of ecological system (Rittel & Webber 1973, Ludwig 2001, Folke et al 1998, Folke 2006, Galaz et al 2006). One of the cornerstones of this new thinking lies in the lenses of resilience, embedded in complex systems theory, which tries to understand changes and interactions between ecosystems, and integrated systems of people and the natural environment (Walker & Salt 2006, Resilience Alliance 2010).
Resilience
Rather than being solution orientated, resilience theory provides a metaphorical way of characterizing a system and interprets its dynamic behavior over both time and space (Allison 2003). Resilience is here defined as the capacity of a system to absorb disturbance and reorganize while undergoing change so as it still retain the same function, structure, identity, and feedbacks (Walker et al 2004). A system is a set of variables working together through interactions, processes and the mechanisms that govern those (Walker & Salt 2006). A resilient system evades unwelcome surprises, through its greater capacity of making the system work in a (desirable or undesirable) condition, or regime, suggesting both stability and the existence of multiple stable states (ibid.). The state of a system is defined by the values of the variables that constitute that system (Resilience Alliance 2010). Underlying, slow changing variables such as climate, ocean currents, and human culture are largely influential as they can drive the system gradually (Walker & Salt 2006). Nevertheless, the mechanisms by which resilience is reinforced or rapidly lost relates to changes in feedback processes. Feedbacks are unbounded processes taking place when the output in a variable, through a loop, influences the input of the same variable. These delineate the nature of interactions and outcomes among faster variables, such as seasonal variations in weather, population densities, food availability, number of resource users and even disturbances such as floods, fires or economical crises (Bennett et al 2005). An amplifying process (i.e. destabilizing) within the
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system is termed positive feedback loop, while a feedback that dampens the process (i.e., stabilizing) is termed negative feedback loop (ibid.). Influences from a range of different temporal and spatial scales are however constantly affecting these feedbacks, leading to cross scale interactions. Feedbacks therefore change in strength, direction and size over time, thus creating system complexity (Walker & Salt 2006, Cash et al 2006). However, it is through these scales, and their interrelations and spatial heterogeneity that the multi stable behavior of a system renews and reorganizes (Folke 2006), allowing for the detection of thresholds; a transition point to a new state, in which feedbacks change structure and composition, rather temporary in form of a phase shifts, or significantly through regime shifts (Nystrom et al 2008).
Adaptive cycle
To measure resilience, the adaptive cycle is commonly used by scholars (Walker & Salt 2006). The adaptive cycle is a heuristic model (see figure 1) generated from observations of ecosystem dynamics (Folke 2006). It is divided into four different phases; exploitation (r), conservation (K), release (Ω) and reorganization (α) (Ibid.). The four phases exhibit two major periods: From r to K, is the slow, incremental period of growth and accumulation (yellow green in the figure below). The back loop, from Ω to α (red purple in the figure below), is the rapid period of reorganization, which leads to renewal and reorganization (Resilience Alliance 2010). The change from one period to another is usually triggered by some kind of disturbance (Folke 2006).
Figure 1. The adaptive cycle and its four phases. Source: Resilience Alliance (2010)
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Each phase in the adaptive cycle has its own characteristic. In the r phase components are weekly connected and there is a lot of space for actors (e.g. organism, animals, capital, and resource users etc) to grow and seize upon opportunity. In the K phase energy accumulates and connections increase, while the growth rate decreases. The competitive edge shifts from opportunistic to specialized actors, who are efficient in their use of resources. In this phase the system becomes more rigid, and strongly regulated. The Ω phase is characterized by a drastic change or a shock (fire, diseases, political or economic crises etc), which creates a chaotic condition due to a rapid disconnection of energy accumulated in the r and K phases. This phase is characterized by uncertainty. In the α phase options become available and the system starts a process of reorganization where innovations and experiments are common (Walker & Salt 2006). At all, the resilience of the system expands and contracts depending on the potential for change and connectiveness among variables (Allison 2003). For a better understanding of how to measure resilience see table 1 below.
Reorganization (α) Conservation (K)
Potential High High Connectiveness Low High Resilience High Low Exploitation (r) Release (Ω)
Potential Low Low Connectiveness Low High Resilience High Low Table 1. Variables affecting a system and the adaptive cycle. Source: Allison (2003)
Social-ecological systems
A social ecological system (SES) is a system of people and nature. It helps researchers to recognize sets of empirical variables within the context of resilience, underlining the impracticality of separating the social and natural world. It considers systems as heterogeneous self organizing identities, also called complex adaptive systems (CAS), which constantly create feedbacks, interactions and outcomes, and sometimes even new reconfigurations (Berkes & Folke 1998). A SES can be used when tackling so called ”wicked problems”; with no definitive formulation, or no stopping rule, aiding in the process of understanding the nature of problems instead of trying to resolve them (Rittel & Webber 1973). They also generate innovative result for research and create a proactive discourse of how natural resource management should respond to and manage feedbacks between ecosystems and society for sustainability (Ostrom 2007).
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In this work a SES developed by Ostrom (2007) is applied. It is used to define the system boundaries and make the self organization preposition between CCAMLR, krill fishery and the Scotia Sea ecosystem operational. The author suggests scholars to analyze four nested core subsystems that co exist within a focal system: The resource system (RS), the resource units (RU) generated by that system, its users (U) operating within a set of rules crafted by local, distal, or nested governance systems (GS). The next step is then to analyze how these jointly create, and indirectly are affected by, interactions (I) and outcomes (O); here also comprehended as the feedbacks in the system. The approach includes two broader systems; social, economic and political settings (S) as well as related ecosystems (ECO) allowing for cross scale interactions to become part of the study. For an overview of the SES suggested by Ostrom (2007) see figure 2 below.
Figure 2. A framework for analyzing social ecological systems. Source: Ostrom (2007)
This SES will be useful for this work as it provides a common set of relevant variables and guides the diagnosis of self organization between CCAMLR, krill fishery and the Scotia Sea ecosystem, as well as how these interact over different scales . It will also facilitate the study of the selected system over time, through an examination on which variables differ to enable former system survive changes and disturbances while other not, supporting the discussion about how the linkages are affecting the resilience of the SES.
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Governance
The ability of managing resilience is frequently related to governance, suggested as the structures and processes by which societies share power and shape individual and collective actions (Young 1992). The governance approach helps us to understand changing processes and collective decisions when the government does not play the leading, or any role (Hague & Harrop 2002), as in the case of the Southern Ocean. A concept of study within this school is that of international regimes, which has been defined as a set of explicit or implicit principles, norms, rules and decision making procedures, around which various actors’ expectations converge in a given issue area to guide behavior of participants at the international level (Krasner 1982). International regimes are created by governments in order to resolve problems of interstate interaction, thus, making cooperation possible (Joyner 1998). CCAMLR is here seen as an international regime, but that is regionally working through institutions.
Institutions vs. roving bandits
The Southern Ocean is a common and includes common pool resources (CPR); valuable stocks making it hard to exclude potential beneficiaries from using them (Ostrom 1990). Fish harvesting by one user usually reduces the amount of the resource left for other users, a dilemma that according to Hardin (1968) only lead to the tragedy of the commons, or resource collapse. Thus, without some kind of institutions, with a set of rules governing the use, including the character of the common resource, CPR´s are destroyed (Ostrom 1990). Institutions are here defined as a formal or informal structural feature, with some stability over time, which affects individual behavior, and consequently shape human interaction with its environment (Peters 1999). The krill fisheries are actors whose behavior is embedded in institutional frameworks (e.g. they may chose to follow, or not follow, CCAMLR rules on resource extraction in the Southern Ocean). If no institutional structure is available (i.e. open access), there can be no rules, and each resource user hold absolute freedom; wherein no communication, cooperation or trust exists between actors (Ostrom 1990).
Open access inspires the sequential exploitation of resources over spatial scales. It is a mismatch that is usually exemplified in the exploitation of roving bandits and local monitoring organizations. Roving bandits are fishing fleets that move around the globe, targeting valuable marine species deplete local stocks, and then continue to exploit stocks
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located in other regions (Olson 2000, Ostrom 2007). According to Berkes et al (2006), in today’s globalized and technological world, a new market develops rapidly, stimulating roving banditry to move towards institutional unconstrained or less exploited sea water areas. This in turn overwhelms the ability of local institutions to respond successfully, resulting in an increasingly serious ecological and management problem (ibid). Thus, social self organization is here implicitly related to adaptability, defined here as the capacity of institutions and actors to reorganize in response to changing socio economical and environmental conditions (Walker & Salt 2006). If natural resource management eliminates this from its policies and practices they also leave out their capacity to monitor, evaluate, and adapt over time (Ostrom 2005).
Governance rules vs. the supply and demand of the international market
Adaptability is in this work determined through how fishing rules are applied on krill fishery by CCAMLR, and how the fishing industry continuously reconsider and adjust themselves in accordance to what is known about the social economical environment and the resource system. Rules can have diverse meanings, and are many times found in both formal and informal features of society (Ostrom 2005). In this work I look at CCAMLR’s formal rules, which are grounded on ecosystem basis’s and executed on krill fishery in the Scotia Sea. In other words, the policy statement that carries out an additional, assigned sanction if forbidden actions are taken and observed by a monitor (Ostrom 2005, 2008). The krill fishery is not only embedded in the CCAMLR’s rule framework but also in an international market structure. This structure works through the supply and demand of products, goods and capital. One observable attribute is the quantity and price of products available. Hence, in this work I use four basic assumptions from economics to analyze the international flow of krill commodities. Firstly, if the international demand of krill increases and supply remains unchanged, it leads to a higher product price and less quantity sold. However, if demand decreases and supply remains unchanged, it leads to lower product price and more quantity sold. On the other hand, if supply of krill increases and demand remains unchanged, it leads to lower product price and higher quantity sold. And finally, if supply decreases and demand remains unchanged, then it leads to higher price and lower quantity sold (Besanko & Braeutigam 2005). This approach allows us to analyze the behavior of the sectors involved in catching and manufacturing Antarctic krill as well as the behavior of the consumer of these products.
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Ecosystem dynamics
An ecosystem is here defined by their combined physical and biological processes; as an environment consisting of all the organisms, animals and microorganisms (biotic factors) living in a particular area and functioning together, as well as all the nonliving, physical (abiotic factors) components of the environment with which the organisms interact (SOSP 2009). Marine ecosystems can be divided into two interacting zones; the pelagic and benthic, where the first is the upper sunlit area, and the second is the bottom area (Vander Zanden & Vadebonceur 2002). It is often assumed that species and organisms found in an ecosystem disperse to the best places that suit their requirements, meaning that they are in equilibrium with their environment. However, the realized niche of a species, or how an organism or population responds to the distribution of resources and competitors, is in this work seen as in a state of flux (Sinclair et al 2010). In other words, the distribution of species and organisms in an ecosystem depends on changes and interactions of different abiotic and biotic factors varying over temporal and spatial scales (Trathan & Croxall 2004). Food web responses in the Scotia Sea are thus considered here as an important factor when looking at this dynamism.
Food webs
A food web is a representation of the feeding relationship between animals and organism, or the “who eats whom” by different species. It establishes the chaotic condition on which ecosystems function (Pimm 1982, Mintenbeck 2008). When certain parts of the food webs are emphasized, they are usually referred to as the food chain, with different trophic levels; primary producers (e.g. phytoplankton) as the first level, herbivores (e.g. zooplankton) as the second, carnivores (e.g. small fishes) as the third, carnivores that eat carnivores (e.g. bigger fishes and predators) as the next, and so on (Mintenbeck 2008). Predation from larger animals is accordingly seen as a top down force, holding that organisms at the top of the food chain are food limited. Hence, with an increase, or decrease, in predators that feeds on animals and organism at lower level, the relative abundances of the remaining trophic levels change, which can lead to trophic cascades. Trophic cascades occur when predators change behavior, or are removed, influencing the abundance of organisms’ more than two trophic levels down (Carpenter et al 1992). On the other hand, influences from lower trophic levels are described as a bottom up force, meaning that energy and nutrient pathways come from below. In other words, without primary producers there cannot be any communities higher up (Smee et al
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2010). However, the influence of both top down control and bottom up forcing should be included when explaining historical dynamics of the ecosystems. For example, Osterblom and colleagues (2007) show that in the Baltic Sea two major ecological transitions have occurred between 1900 and 1980; where a shift from seal to cod domination was caused by a virtual elimination of marine mammals followed by a shift from an oligotrophic to a eutrophic state. For a classical and theoretical representation of the Southern Ocean food web and its feeding relationship, including the pelagic and benthic zones, as suggested by Laws (1985) see figure 3 below:
Figure 3. The Southern Ocean food web. Source: Adapted from Laws (1985)
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Changing predator prey relationships
Changing predator prey relationship is here determined by looking at food availability in the Scotia Sea food web, and on marine predator, Antarctic krill and myctophid fish densities, as well as migration areas. Much of the research conducted on Southern Ocean ecosystems means that the Antarctic krill is a key component in its food web (Dziek and Jazdzewski 1978, Reid & Croxall 2001, Gascón & Werner 2006, Murphy et al 2007). Lower densities of Antarctic krill in the Scotia Sea must therefore impact on communities higher up in the trophic level. Although, it could also mean that the krill based food web could shift among trophic “paths” when krill are abundant or when krill are scarce, making predators look for other prey (Murphy et al 2007). This assertion lies in parallel to the “junk food hypothesis”, suggested as a potential explanation for a dramatic population decline of stellers sea lions (Eumetopias jubatus ) in the Gulf of Alaska, meaning that its not only the quantity of food, but also about the quality of food that affects food web structure (Rosen and Trites 2000, Osterblom et al 2008). One possible prey alternative for predators in the Scotia Sea is to be found in one of the most important group of fishes in the Scotia Sea, the mesopelagic fish (myctophids), identified in 12 genera and 33 species (Kock 1992). Case studies on marine mammals' diets in the Scotia Sea indicate that a major food compliment for Antarctic fur seals when krill is scarce is just the mesopelagic fish (myctophids) (Collins et al 2008). The Scotia Sea food web is however not only embedded in vertical trophic interactions, but also dependent on interactions across horizontal scales. In order to include external influences into the analyze of changing predator prey relationship, another important factor is taken into consideration; migration, or, a seasonal relocation of animals that involves movement of much longer duration than those arising in its normal daily activities (Dingle & Drake 2007). Most fishes, animals and predators in the Scotia Sea shift living location during the year. Migration can be horizontal or vertical, and is triggered by the climate, the season of the year, light and food availability or due mating reasons (ibid.).
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Research framework
After presenting the theoretical foundations of this work, an overall research framework can now be constructed and is summarized next in figure 4.
Figure 4. The theoretical research framework. It follows a casual order and shows how I will achieve the aim and respond my research questions
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CASE STUDY DESCRIPTION
The Southern Ocean
The Southern Ocean is regarded as the fourth largest of the five principal oceanic divisions and comprises about 10% of the world’s oceans (Boyd 2002). While the Antarctic continent set a geological boundary in the south, the Antarctic Convergence Zone (ACZ) a seawater area where colder waters meet warmer southward flowing waters creates a northern oceanographic and biological boundary (Fallon & Stratford 2003). In the depth, a system of deep basins separate three large mid oceanic ridges (MOR’s): the Macquarie Ridge south of New Zealand and Tasmania; the Kerguelen–Gaussberg Ridge, between India and Antarctica; and the Scotia Ridge, extending east from the southern Patagonia (Kock 2000). The absence of land barriers in the latitude band allows the eastward flowing Antarctic Circumpolar Current (ACC) to drift uninterrupted around the Antarctic. The ACC is driven by strong westerly winds, and was formed around 23 – 30 million years ago during the early Miocene epoch 2 (Hassol et al 2009), connecting the Southern Ocean to major oceans world over, renewing them with deep cold waters, as well as having a significant role in the function of the global thermohaline circulation (THC) 3 (Borowski 2003). The biota 4 of the Southern Ocean differs from the rest of the world’s ocean. This is due to the strong influence of the ACC that maintains surface temperatures stabile, but also due to the long and dark winters and the roll of the sea ice extension (Murphy et al 2007). Sea ice, or the ice which forms in salt water, grows extensively during winter in the Antarctica and the Southern Ocean, but melts away during the summer (NSIDC 2011). This yearly environmental change makes it hard for the Southern Ocean to build up long and complex food chains, such as usually found in tropical seawater areas (Murphy et al 2007). However, there are some areas where the environmental parameters diverge.
The Scotia Sea
Confined between the South American continent and the Antarctic Peninsula, the Scotia Sea extends over approximately 750 km north–south, and approximately 2000 km to the east from west encompassing an area of approximately 1.5x10 ⁶ km² (Murphy et al 2007). For a better overview over the Scotia Sea see figure 5 below.
2 A geological epoch extending from about over 23 to 5 million years ago 3 The transport of heat and salinity around the world oceans through a water current belt 4 All the plant and animal life of a particular region 20
Figure 5. The Scotia Sea and the Southern Ocean. On the left, the Antarctic continent and the Antarctic Circumpolar Current (ACC) (in light gray). On the right and in focus; the Scotia Sea. Source: Figures and maps taken and customized from WDCS (2011)
Scotia Sea physical, oceanographic and ecosystem dynamics
The Scotia Sea ecosystem has during a long time been molded by the interactions of tectonic evolution, physical oceanography and a range of ecological processes. Its flow and ecological regime works mutually with the regional underwater bathymetry and seasonality (variations in solar irradiance, upper ocean temperature, light levels and sea ice extension). This is the structural preface of the current environmental state of the Scotia Sea (Murphy et al 2007). As the ACC flows east through the Drake Passage it encounters the Scotia ridge, a strongly topographically constrained underwater shelf which has slowly evolved during the last 40 million years (Barker et al 2001). Great inputs of seawaters are also received from the Weddell Sea, and its counter flowing gyre 5, in the south (Murphy et al 2007). This encounter between the ACC, the Scotia ridge and the Weddell gyre, creates zones of water turbulence in measures not found anywhere else in the Southern Ocean. Hence, in contrast to other regions, the Scotia Sea receives extensive blooms of large diatoms and copepods during the warmer and lighter periods of the year. The upwelling of nutrients, due to constant mixing, together with high levels of iron in the seawater, coming from a range of sources, such as shelf water inputs from the Antarctic Peninsula region and shelf sediments of the Scotia Arc, makes the Scotia Sea chlorophyll rich, thus, promoting phytoplankton growth (ibid.). This condition is favourable for crustaceans in the pelagic zone, such as the Antarctic krill, which can develop quickly in response to abundant levels of phytoplankton (ibid.).
5 The Weddell gyre is a relatively smaller ocean current than the ACC 21
Antarctic krill
The Antarctic krill ( Euphausia superba) is a small shrimp like crustacean. There are 85 known krill species, although, the Antarctic krill is today the best known zooplankton specie in the Southern Ocean (Parker 2011). Its attributes are however very similar to small fishes, as it can live for up to seven years, and grow to around 60 mm in length; taking 3 years to become reproductively mature (SOSP 2009). Spawning females, adults and juvenile population commonly aggregate into large swarms. The females and adults are found mostly in open oceanic water during the summer, while the juveniles stay closer to the shelf areas year round (ibid.). Antarctic krill feeds mainly on phytoplankton, although they can also feed on their own eggs and larvae and break down their own body mass into amino acids in periods of low food availability (Parker 2011). During the winter the krill larvae, juveniles and adults take shelter under the sea ice and feed on ice algae (SOSP 2009). According to research, the Antarctic krill has one of the largest biomasses on the planet (Siegel 2005). However, quantified estimations from scholars have differed since major investigations started in the 1970s. See table 2 below.
Krill biomass (Mt) in the Year of study Southern Ocean 1970 750 1973 800 - 5000 1979 1200 1983 60 - 100 1983 100 -400 1992 40 2000 44.3 2006 208 2007 37 2008 117 - 379 Table 2. Biomass estimation on Antarctic krill from different studies since 1970. Source: Atkinson et al (2008), as well as cited in Parker (2011)
Distribution
The distribution of the Antarctic krill is circumpolar in the Southern Ocean, although, and according to Atkinson and colleagues (2009), the Scotia Sea is the region that supports a larger part of the overall population. The highest krill densities in the Scotia Sea have mainly been confined to the western shelf of the Antarctic Peninsula, the southern seawater areas of South Orkney Island and around the eastern and northern shelf of South Georgia Island (ibid.). For a closer overview over the density distribution of Antarctic krill in the Southern Ocean and in the Scotia Sea see figure 6 and 7 below.
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Figure 6. Antarctic krill density (n/m ²) around the Southern Ocean. Source: Atkinson et al (2009)
Figure 7. Antarctic krill density near (a) the Antarctic Peninsula and South Orkney and (b) South Georgia. The plots are of arithmetic mean (standardised) density (ind. m ²) on a 0.5° latitude by 1° longitude grid. Source: Atkinson et al (2009)
Krill predators
The Antarctic krill is mainly eaten by marine mammals and sea birds in the Scotia Sea, mostly during the breeding season 6. In the north, macaroni penguins ( Eudyptes chrysolophus ), gentoo penguins ( Pygoscelis papua ), the grey headed ( Thalassarche chrysostoma ) and black browed albatrosses ( Thalassarche melanophrys ), as well as antarctic fur seals (Arctocephalus gazelle ) are the major krill depending predators. Further south, chinstrap penguins ( Pygoscelis antarcticus ) and adelie penguins ( Pygoscelis adeliae ) are the major krill depending predators, although, smaller colonies of gentoo penguins and antarctic fur seals also exist together with the crabeater seal (Lobodon carcinophagus ) (Croxall et al. 1987; Trathan et al. 1996, Boyd 2002, Boyd et al 2002, ACAP 2011, Birdlife 2011). Most of the mammals and seabirds aggregate on a group of continental and volcanic islands: South Sandwich, South Orkney, South Georgia and South Shetland, as well as the Antarctic Peninsula, although, even the pack ice is used by some species (Murphy et al 2007).
6 The summer season; when animals reproduce and produce their offspring 23
Other predators and animals that prey on Antarctic krill, such as the dove (antarctic) prion (Pachyptila desolata ), southern (antarctic) fulmar ( Fulmarus glacialoides ) and several fish, squid and whale species such as the mink whale ( Balaenoptera bonaerensis ), humpback whales ( Megaptera novaeangliae ), southern right whale ( Eubalaena australis ), blue whale (Balaenoptera musculus ), the fin whale ( Balaenoptera physalus ) and the sei whale (Balaenoptera borealis ), but these species have a more disperse distribution over the Scotia Sea (Murphy et al 2007, ACAP 2011, IWC 2011). For an overview over the main krill dependent predators in the Scotia Sea see table 3 below.
Krill demand Krill dependent Total individuals (10x⁶tonnes yr-¹) predators in the (n) in the southern Habitat Winter in the Scotia Sea Scotia Sea hemisphere food web Antarctic fur seal > 4.5 million Islands & coasts 1.1 – 3.8 Migratory Crabeater seal > 7 million Islands, coasts & pack ice 4.5 Migratory Macaroni penguin > 18 million Islands & coasts 3.8 – 8.1 Migratory Adelie penguin > 4 million Islands & coasts 0.46 Migratory Chinstrap penguin > 8 million Islands & coasts 3.8 Migratory Gentoo penguin > 520 000 Islands & coasts 3.7 – 7.9 Migratory Antarctic fulmar > 4 million Islands & coasts 0.54 Migratory Dove prion > 50 million Islands & coasts 1.4 Migratory Whales > 850 000 Marine & coastal waters 1.6 – 2.7 Migratory Black-browed albatross > 1 million Islands & coasts N/D Migratory Grey-headed albatross > 250 000 Islands & coasts N/D Migratory Squid N/D Marine & coastal waters N/D Vertical migration Pelagic fishes N/D Marine & coastal waters N/D Vertical migration
Table 3 . Main krill dependent predators in the Scotia Sea. Population size, main habitat, annual krill demand and winter roll. Values valid for present time. Source: Murphy et al (2007) and Birdlife (2011)
Forage fishery
For millenniums the human has used small pelagic fishes in their diets. However, it was not until the 19th and 20th century that these fishes were to become used for non food and reduction (Alder et al 2007). By then, mainly for its fish oil; used in leather tanning and in the production of soap, glycerol and fertilizers (FAO 1986). After 1950 the destination changed and catches were instead used to produce animal feeds for the diets of poultry and pigs (ibid.). Today fish farms are the highest consumers of both fish meal and fish oil. According to estimates, 63 % of the fish meal and 81 % of fish oil production nowadays goes to aquaculture farms in main producing countries through import (Deutsch et al 2007, IFFO 2011).
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During the last decades a range of pelagic fish species has therefore been targeted by fishery, with the Peruvian anchoveta (Engraulis ringens ), caught along the coast of Chile and Peru, as the foremost specie for the industry with almost 7 Mtons of landings in 2009. For a closer overview over the development of the global forage fishery see figure 8 below. For detailed numbers see appendix 1.
Total catches by forage fishery of selected fish species commonly destined for non-food uses (1970-2009)
40 Total forage fish catch per year 30 Peruvian anchoveta Chilean jack mackerel 20 Atlantic herring Mtons 10 Capelin Blue whiting 0 Japanese pilchard 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Figure 8. Total global catches by forage fishery and total catch of the seven most target species commonly destined for non food uses (1970 2009). The choice of these seven species was based on data from over 41 commonly caught forage fish species, including Antarctic krill. Source: FAO/FIGIS (2011)
Forage fishery in the Southern Ocean
Humans have exploited the marine resources of the Southern Ocean for over 250 years, but it is only during the recent decades that fishery has started to target forage fish. Previous to, in the 18th century, Antarctic fur seals where hunted intensively around the continental and islands of the Scotia Sea (Kock 2000). The specie was almost extinct at the end of the 19th century (ibid.). During the upcoming decades commercial efforts felled on the elephant seals, and particularly on several whale species (ibid.). After mid 1950s, fishing effort moved down in trophic levels, towards finfish such as the Patagonian toothfish ( Dissostichus eleginoides ) and Mackerel icefish ( Champsocephalus gunnari ). In recent times, there has also been smaller exploratory fishing for stone crabs and squid (CCAMLR 2011). Nevertheless, today the Antarctic krill is the largest and most important targeted specie in the Southern Ocean (Kock 2000, Croxall & Nicol 2004, CCAMLR 2011, Parker 2011). For an overview of the historical development of the Southern Ocean fishery and krill fishery, in terms of total catch, see figure 9 below. For a detailed data on annual catches, comparing catch on whales, different marine fish species and the Antarctic krill in the Southern Ocean, see appendix 2.
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Annual nominal catches (tons) of Antarctic krill, marine fishes and whales in the Southern Ocean (1950 -2010) 500000
400000
300000 Antarctic krill
Tons 200000 Marine Fishes 100000 Whales
0
1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 Figure 9. Comparison of fisheries in the Southern Ocean since 1950s until recent times. Whales include blue whales, fin whale, humpback whale, killer whale, long finned pilot whale, minke whale, northern bottlenose whale, sei whale, sperm whale and toothed whales nei. Marine species include humped rockcod, mackerel icefish, marbled rockcod, patagonian toothfish and South Georgia icefish. Source: FAO/FIGIS (2011)
Management of the Southern Ocean
The Southern Ocean has over half a century been, and still is, under the supervision of a range of different international regimes. The exact numbers of regimes cannot be stated here as each one’s modus operandi differs over large spatial scales, such as the 1982 global regime of United Nations Convention on the Law of the Sea (UNCLOS). Instead, seven international regimes are here identified to have endowed special attention in their agendas towards the Southern Ocean. For a better overview of the existing regimes operating in the Southern Ocean see table 4 below. In this work the focus is on the management regime of CCAMLR, which has its headquarters located in Hobart, Tasmania, Australia.
Regime In force since Aim
International Convention for the Regulation of Whaling (ICRW) & 1946 Conservation of whale stocks International Whaling Commission (IWC)
Support on issues of science and Scientific Committee on Antarctic Research (SCAR) 1958 conservation
Establish institutional foundations, Antarctic Treaty (AT) 1959 regulations and relationships
Limit the vulnerability of Antarctic Convention for the Conservation of Antarctic Seals (CCAS) 1978 seals The Convention on the Conservation of Antarctic Marine Living Resources Conservation of Antarctic marine living (CCAMLR) & Commission for the Conservation of Antarctic Marine Living 1982 resources Resources (CCAMLR) Protocol on Environmental Protection to the Antarctic Treaty (PEPAT) & Protection of the Antarctic 1998 Committee for Environmental Protection (CEP) environment
Committee for the Conservation of Albatrosses and Petrels (ACAP) 2004 Conserve albatrosses and petrels
Table 4. Governance regimes in the Southern Ocean
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CCAMLR
CCAMLR started to take form during the 1970s when researchers and leading fishing nations aggregated for discussions over management options for the krill fishery. Concerns were particularly raised on the agenda during the 9th Antarctic Treaty Consultative Meeting (ATCM) in London 1977. Negotiations resulted in the signing of the Convention on the Conservation of Antarctic Marine Living Resources (CCAMLR) in Canberra in May 1980, establishing the Convention Area (see figure 11), which came into force on 7th of April 1982 (Kock 2000). Although the CCAMLR is an independent agreement, it is as a rule a mandate of the Antarctic Treaty 7. The difference, however, was that the negotiated boarders of the Convention Area were not established on sovereignty principals, but follows the natural shores of the Antarctic continent and the ACZ. This resulted in a larger management area (32.9 million km² under CCAMLR jurisdiction) than the one recognized in the Antarctic Treaty (AT) (Croxall & Nicol 2004). Set into force in 1982, CCAMLR was a pioneer in incorporating the EA and PA approaches into management objectives. Article II of the Convention text (CCAMLR 1980), sign in 1980, is central to the understanding of CCAMLR’s development towards EA and PA. It states the following operational objectives and principals:
1. The objective of this Convention is the conservation of Antarctic marine living resources.
2. For the purposes of this Convention, the term ‘conservation’ includes rational use.
3. Any harvesting and associated activities in the area to which this Convention applies shall be conducted in accordance with the provisions of this Convention and with the following principles of conservation: (a) prevention of decrease in the size of any harvested population to levels below those which ensure its stable recruitment. For this purpose its size should not be allowed to fall below a level close to that which ensures the greatest net annual increment; (b) maintenance of the ecological relationships between harvested, dependent and related populations of Antarctic marine living resources and the restoration of depleted populations to the levels defined in subparagraph (a) above; and (c) prevention of changes or minimization of the risk of changes in the marine ecosystem which are not potentially reversible over two or three decades, indirect impact of harvesting, the effect of the introduction of alien species, the effects of associated activities on the marine ecosystem and of the effects of environmental changes, with the aim of making possible the sustained conservation of Antarctic marine living resources.
Source: CCAMLR (1980)
7 The Antarctic Treaty was signed in Washington in 1959 to establish Antarctica as a region of peace and cooperation, and to deal with issues relating to claims of sovereignty. Available at < http://www.ats.aq/e/ats.htm> 27
Under CCAMLR, conservation is mainly defined as “ ration use ”, but also, as formulated in Article II (3) (b), to maintain “ the ecological relationships between harvested, dependent and related populations of Antarctic marine living resources, and the restoration of depleted populations ”, as well as formulated in Article II (3) (c), the “ prevention of changes or minimization of the risk of changes in the marine ecosystem ”. This design means that CCAMLR should collect the data it can, and then weighs the extent and effect of the uncertainties and gaps in such data before making a management decision. Not only for certain species, but also to ensure that fishery does not adversely affect other species that are related to, or dependent on, the target species, which include Antarctic krill, Patagonia toothfish, Antarctic toothfish, sub Antarctic lantern fish, mackerel, icefish, sevenstar flying squid, Antarctic rock cod and crabs (Mooney Seus & Rosenberg 2007).
CCAMLR´s Convention Area
The CCAMLR Convention Area is divided into three statistical areas; Atlantic Ocean (Statistical Area 48), Indian Ocean (Statistical Area 58) and Pacific Ocean (Statistical Area 88), internationally agreed and recognized by the Food and Agriculture Organization (FAO). Within each one of the statistical areas there is a number of subareas. According to Kock (2000), the reason for dividing the Convention Area into subareas was to enable the reporting of fisheries data for individual stocks and to make possible the imposition of management measures on a stock by stock basis. For the 2010/2011 fishing season, the total catch limit of krill in the Convention Area was 8.6 Mtons. For subareas 48.1, 48.2, 48.3 and 48.4, the total catch limit increased from 3.47 Mtons to 5.61 Mtons, with a trigger level of 620 000 tons8 (CCAMLR 2011). In 2002 the CCAMLR proposed 15 small scale management units (SSMU) 9 to be applied in subareas 48.1, 48.2 and 48.3. However, catch limits in these have not yet been defined by CCAMLR and still set on subarea level (Hill et al 2009). This work focus on the subareas found within Statistical Areas 48. For a better overview over the convention areas see the figure 10 below.
8 A precautionary limit is to be agreed on by the Commission, on the basis of advice of the SC if total catch in subareas during any fishing season, exceeded a trigger level of 620 000 tons 9 The 15 proposed SSMU´s are APE: Antarctic Peninsula East; APW: Antarctic Peninsula West; APW: Antarctic Peninsula West; APBSE: Bransfield Strait East; APDPW: Antarctic Peninsula Drake Passage West; APDPE: Antarctic Peninsula Drake Passage East; APEI: Antarctic Peninsula Elephant Island; SOSE: South Orkney South East; SOW: South Orkney West; SONE: South Orkney North East; SGW: South Georgia West; SGE: South Georgia East; APPA: Pelagic Area of FAO Subarea 48.1; SOPA: Pelagic Area of FAO Subarea 48.2; SGPA: Pelagic Area of FAO Subarea 48.3 28
Figure 10. The CCAMLR Convention Area. The map also includes the boundaries of the statistical reporting areas in the Southern Ocean. Source: CCAMLR (2011)
CCAMLR’s bodies
The main body of CCAMLR is the Commission. It has currently 25 members representing a range of different countries 10 . Participation in the Commission is open to any interested fishing nation or regional economic integration organization. The main function of the Commission is to draft and adopt binding conservation measures (CM) through consensus. It cannot regulate fishing activities of non party states (Joyner 1998). CCAMLR members are affiliated to the Scientific Committee (SC), which provides management advice to the Commission. The management advice from the SC is based on assessments and research conducted by different working groups; the Working Group on Ecosystem Monitoring and Management (WG EMM), formed in 1994 by the merged Working Group on Krill (WG Krill), the Working Group on Fish Stock Assessment (WG FSA), formed in 1984 (Kock 2007), and the CCAMLR Ecosystem Monitoring Program (CEMP), formed in 1985, which is a program constituting of constituting of a small number of subgroups with the aim to monitor the performance of a number of dependent predator species 11 in relation to harvested species (Nicol & Foster 2003).
10 Members of the CCAMLR Commission since 1997; Argentina, Australia, Belgium, Brazil, Chile, China, European Union, France, Germany, India, Italy, Japan, Republic of Korea, Namibia, New Zealand, Norway, Poland, Russia, South Africa, Spain, Sweden, Ukraine, UK, USA and Uruguay. Source CCAMLR (2011)
11 Penguins; Adélie penguin, chinstrap penguin, gentoo penguin, macaroni penguin. Seabirds; black-browed albatross, Antarctic petrel, Cape petrel. Seals; Antarctic fur seal, crabeater seal. Source CCAMLR (2011) 29
Fishing rules
Fishery rules are set by CCAMLR through conservations measures (CM). Each year some are introduced, carried on, revised or lapse. The Commission adopts CM’s during the CCAMLR’s annual meeting, on advice and background work from the SC. Even changes are based on recommendations and advice from this body, as stated under the Article IX of the Convention (CCAMLR 1980). CM’s are agreed upon by members, and becomes binding within 180 days. Fishing rules can also be created through resolutions, but these are not binding. Monitoring activities and sanctions towards krill fishery are regulated by article XXIV of the Convention, and executively by the Standing Committee on Observation and Inspection (SCOI) (ibid.). Fines for not following fishing rules are imposed on the fishing vessels and related companies by the involved actors own countries and fishery departments (Joyner 1998).
Annual meetings
Annual meetings have been held since 1980, and occur one time per year during a two week period. The Executive Secretariat (ES), appoint by the Commission, supports the annual meetings and carries out the day to day functions. During the events the different bodies and members of CCAMLR meet in open plenary session 12 . After some days it goes into recess, where the Standing Committee on Administration Finance (SCAF) and the SCOI together with the SC discuss, debate and finalize the reports to be presented to the Commission. During the second week the Commission reconvenes in plenary session to consider and discuss the reports as well as proposing measures and actions (Joyner 1998).
12 International non-governmental organizations and other interest stakeholders usually take part of the open sessions 30
METHOD The conventional wisdom says that a method should be selected so it can guide an investigation, helping it to use, develop or test existing theories, consequently achieving the aim and respond its research questions (Esaiassons et al 2003). Nevertheless, this work is of transdisciplinary character. To embrace this empirical data needed to be synthesized by using different quantitative and qualitative approaches.
Epistemological background
Research on how natural environments should be managed is commonly divided in two paradigms; normal science and post normal science. A paradigm is sets of practices and concepts applied by science during a specific time period, and decides the overall framework of a scientific investigation (Kuhn 1962). Normal science is in other words what scientist does within an accepted framework of methods and knowledge structure (ibid.). Natural resource management has during a long time been under the influence of the paradigm of positivism; a problem solving school of thought that assumes an observer that is separated from its subject (Alisson 2003). This kind of science classifies features, counts them, and constructs statistical models in an attempt to explain what is observed, arguing that a rational scientific method could create objective results (Hay 2002). Positivism has however been under critique for not taking into account different perceptions of involved actors, which consequently should inspire them to act in preoccupation with the consequences (ibid.). A post normal science paradigm has therefore appeared, oriented towards context dependency, learning, interpretation and different understandings of the reality. According to this approach, facts are uncertain, values are in dispute, stakes are high and a decision is urgent (Funtowicz & Ravetz 1990). This way of gathering knowledge, also called constructivism, give emphasis to the social constructions as well as to the subjective individual (Hay 2002). However, neither constructivism has been spared from critique and is said to course towards relativism, making it hardworking and costly when trying to achieve consensus (ibdi.).
At all, the epistemological background of the two conflicting paradigms have been summarized into three knowledge metaphors by Miller et al (2008), which are presented in the table 5 below.
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Table 5. Metaphors of knowledge recognized within normal science and post normal science. Source: Adapted from Miller et al (2008)
While the positivistic school mostly sees knowledge as mechanistic, constructivists often shift their view between the contingent and the narrative knowledge systems. However, transdisciplinary research should try to unify methods, theories and disciplines, and consequently knowledge structures, creating a holistic approach which enhances science based contributions to complex problems (Wiesmann et al 2008). This work tries therefore to distance itself from an epistemological sovereignty by unifying the three different knowledge metaphors presented by Miller (2008). The argument is that there are multiple ways of knowing about the cross scaling challenges confronting CCAMLR in the Scotia Sea and Southern Ocean.
Methodological approach
The methodological approach here is not only a result of epistemological consideration, but also of obtainable research conditions. Travelling to the Southern Ocean or to CCAMLR’s headquarters in Australia would have been the most reliable option. However, fieldwork (marine ecological data sampling or semi structured interviews with members of CCAMLR or fishermen) was not conducted; thought to be costly and time consuming. Instead, to achieve the aim and respond to research questions a literature review, through desk research, was first conducted. Theoretical and conceptual emphasis was given to resilience theory, but even governance, ecology and economy approaches was integrated. The empirical part consisted of gathering qualitatively and quantitatively data over selected variables, which support the qualitative discussion on interactions (I) and outcomes (O) in the SES.
Two research questions where stated in the introduction. These questions were answered by gathering empirical data from four time periods (P1: 1970 1980, P2: 1980 1990, P3: 1990 2000 and P4: 2000 2010) selected as temporal boundaries of this work. To go further back in time would just have obliterated the scope of the existing management regime (CCAMLR) created in 1982, or make data searching to difficult. In order to answer question 2 regarding
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the resilient capacity of the SES over time, it was necessary to first find answers to question 1. Hence, Ostrom’s (2007) framework of cross scale interactions gave initial support, helping me identify a possible SES with four nested attributes; the Scotia Sea ecosystem (RS), Antarctic krill (RU), krill fishery (U) and CCAMLR (GS). The framework also helped me link the SES to external social (S) and ecological (ECO) variables. The framework does not allow for integration of physical core variables, such as ocean currents, some of these are therefore only presented in the case study chapter. The result gathering in this work therefore consisted in finding empirical data over time for RS, RU, U, GS, S and ECO, while the discussion part felt on a qualitatively analysis over the (I) and (O) in the SES.
In order to understand how RS, RU, U, GS, S and ECO jointly have created (I) and (O) a testable hypothesis was presented in the introduction chapter, mainly derived from resilience theory; when a resource overlap between krill fishery and marine predators arise, feedbacks are developed between existing governance forces and the Scotia Sea ecosystem. However, external variables can also have an influence, in form of related ecosystems and global socio economical forces. At all, these feedbacks can either stabilize, or push the SES towards a new phase in the adaptive cycle, triggering new condition, or a socio ecological regime shift in the Scotia Sea.
Indicators
Real world indicators where selected to empirically test above hypothesis and find (I) and (O) in the system. For RS the indicators were selected by looking at the population trend of main krill dependent predators and the fish group of mesopelagics, or lantern fishes. It would have been unrealistic to try to get population trend data for all predators and fish species involved in the Scotia Sea. I therefore limited predators to the most krill dependent seals, seabirds and whales according to data presented in Murphy et al (2007) and the most abundant lantern fish species according to Collins et al (2008). The lantern fish species were introduced as indicators of an “alternative path” in the RS due their highly estimated biomass in the South West Atlantic, including the Scotia Sea. However, I excluded circumpolar smaller birds and squids from RS as the data on these where scarce. For the RU, the indicator was density (n/m ²) over time of Antarctic krill in the Scotia Sea. The spatial distribution of this specie is marked by complexity, and therefore only presented in the case study chapter, while its temporal density value is presented in the results. For U the indicators were the history of use, technology, as well as the krill fishing location and fishing season in the Scotia Sea. For GS
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the indicator was CCAMLR’s adaptive capacity in form of fishing rules. These where quantitatively analyzed for each year, but also qualitatively analyzed by using the following topics and questions adapted from Sandström & Rova (2010): (1) Framework of rules: Are there rules that regulate access to and appropriation of the resource? (2) Fishery response: Are the rules used, accepted, and followed by the resource users? (3) Ecological response: Are the rules considering the resource system to be complex, non linear and characterized by uncertainty? (4) Formulation of rules: Are rules continuously changed in reaction to existing ecological knowledge? Each rule configurations that appeared a result of a combination of rule statements, have a dissimilar level of influence over the krill fishery and the Scotia Sea ecosystem. Affirmative answers to all topics indicate that the management process of CCAMLR is adaptive. The external indicator for ECO was migration areas of selected predators, Antarctic krill and fish species, helping me define related ecosystems. The external indicator of S was aquaculture production and the international market of fish meal and fish oil with focus on consumers and producers. Political settings are presented in the case study chapter and not integrated in the discussion due to the large number of regimes that actuate in the international marine environmental arena. As no long time data exist for each country’s fish meal and fish oil consumption, this was estimated by the following basic formula ((import quantity + production quantity) – exports quantity). The average annual percentage growth rate (APGR) of the aquaculture production and fish meal and fish oil market was calculated by using the following formula:
Where v stands for the value of production, which is divided on the average production, and thereafter on amount of years of production and multiplied for 100 to get annual percentage growth in %.
Applying the adaptive cycle
Research question two is answered by measuring resilience of the SES. This is done by applying the results from question 1 on table 1, found in the theoretical chapter. For each period of (P1 – P4), the connectiveness between the attributes between the SES, S and ECO was analyzed. Connectiveness is in this work seen as a flow in material or ideas between variables. Thus, if no connectiveness existed during a specific time period, 0 was given. If
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connectiveness existed (i.e. some kind of flow of ideas and material) between variables, a + was given, and if connectiveness was high (i.e. intensive flow of ideas and material) between variables, ++ was given. By applying this qualitatively modelling, the potential for change could be deliberated and discussed in each period of time, and consequently it was possible to measure resilience in the SES over time and the position of the SES in the adaptive cycle. For a better overview of how this was done see figure 11 below.
Figure 11. Example of how the adaptive cycle is applied on the SES of the Scotia Sea. 0, + or ++ are placed between the connections in order to measure potential of change and resilience in the SES, and consequently its position in the adaptive cycle
Data sources
Both primary and secondary data was used in this work. Only use primary data (surveys, interviews, statistical inventories etc) was not an option, as I was not able to travel to the Southern Ocean. Fishery data was obtained through FAO/FIGIS (2011) database. Data over total krill catch and fishery rules and their configuration over time were obtained in the CCAMLR’s yearly commission and scientific reports (1980 2010). These reports contain detailed data over catches between nations and how each rule has been created, debated and accepted by member states. International market price for fish meal over time was obtained through the database Indexmundi, which gives detailed market and country statistics for multiple food commodities. FAO, on personal communication, mailed me data over the historical development on global fish oil prices. For population trend of marine mammals and seabirds in the Scotia Sea I consulted a different studies; Laws (1977, 1985), Payne (1979), Boyd (1993), Boveng (1993), Ericson and Hanson (1990), Trathan et al (1998), Croxall et al (1999), Adam (2005), Christensen (2006), Poncet et al (2006) Burns et al (2008) and Trivelpiece et al (2011). I also consulted the specie databases from IUCN Red List (2011) and Birdlife (2011). For Antarctic krill density I used existing estimations from research on arithmetic mean krill densities (n/m ²). This data was based on both subsets of standardized and un standardized data from Atkinson et al (2008), who compiled all available net based
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density data on post larvae from 8137 mainly summer stations 1926 2004. The author then forwarded me the raw data from this study so I could construct a diagram for he density over time in the Scotia Sea. Myctophids density was estimated by using fieldwork data from mesopelagic fish community research in the Scotia Sea. Estimation was made by quantifying number of individuals taken in trawl, and divided with volume of seawater filtered (m ³). After all only three author’s data (Piatkowskil et al 1994, Collins et al 2004 and Flores et al 2008) to construct visualization about density changes which is presented in the result chapter. Due to the scarcity of data for the Scotia Sea region, only population densities for P3 and P4 were estimated. The general trend in the sea ice extent over Antarctica was taken from investigations done by NASA (2011), with basement on investigations undertaken by Zwally et al. (2002) and Cavalieri and Parkinson (2008), Parkinson et al (2002), Stammerjohn et al (2008) and Turner (2009) a. All authors used satellite passive microwave radiometers to estimate changes 13 . Information regarding predator’s migration areas, and their general changes, was summarized by consulting related literature for each region. At all, the data sources can be classified as in the table 6 below:
Data sources Primary data Secondary data Nested attributes Fishery Fishery U, S FAO/FIGIS Fish meal and fish oil Fish meal and fish oil S CCAMLR Krill fishery rules Fishery GS, U Population trends RS, S Other databases Myctophids density Population trends RS, RU
Sea ice extent ECO Author's Fishery U Related ecosytems ECO
Table 6. Categorization of primary and secondary data sources used in this work.
Critical reflection of method and data used
The method applied here is transdisciplinary in its nature and tries to develop the existing understanding about management, fishery and ecosystem change in the Southern Ocean over different temporal and spatial scales. For this I tried to use different knowledge systems and disciplines. New approaches will always fall under critique, especially when the results are
13 A complete description of method used by NASA to calculate sea ice extent can be found at http://neptune.gsfc.nasa.gov/csb/index.php?section=59, for method used by Turner (2009) see analysis of microwave satellite data at http://ruby.fgcu.edu/courses/twimberley/EnviroPhilo/Turner.pdf
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based on a range of different sources. It was therefore an essentiality to be clear when defining and using the theoretical framework and concepts.
Empirical data limitation was an apprehension. For example, the scarcity of applicable data regarding myctophids needs to be taken into consideration when discussing possible changes in the structuring and functioning of the Scotia Sea ecosystem. Moreover, some of the data used comes from an outline of research that surrounds CCAMLR. In other words, many results from field studies on the resource system or on marine predators are based on efforts made by CCAMLR researches. Furthermore, the secondary data used in this work for some of the variables can also have lowered the reliability, but most research is in consensus on the numbers presented in the result chapter.
At last, another constrain is that the data presented in this work does not include illegal, unreported and unregulated (IUU) fishing. IUU fishing has been a common phenomenon in the Southern Ocean and carried out by CCAMLR non member vessels. IUU fishing is thought to account for a significant annual catch, however, not equal to the legitimate harvest by permitted vessels operating under flags of CCAMLR members (Nevill 2009, Osterblom & Sumaila 2011). Accurate catch estimates for this kind of fishing was however not available.
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RESULTS The results will now be presented, firstly through the empirical findings for each attribute U, RS, RU and GS in the SES, followed by the values of the external variables ECO and S, thus, responding to the first research question. The complete assemblage will then be used to discuss the second research questions in the upcoming chapter.
Users (U)
Nations
The krill fishery in the Scotia Sea were during the 1970s and 1980s (P1 P2) dominated by vessels from Soviet Union and Japan. During 1990s and 2000s new fishing countries emerged, such as Russia, Ukraine and Poland taking a relative part of Soviet Unions share during P3. As a consequence, Japan became the dominating krill fishing nation, followed by South Korea, although, European vessels have increased their share recently, mainly as a result of Norway’s entrance. For a better overview of the share of annual reported catch of Antarctic krill per country (1970 2010), see figure 13 below. For detailed numbers, see appendix 3.
Figure 13: Share of annual reported catch (tons) of Antarctic krill per country (1970 2010). Source: FAO/FIGIS (2011)
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History of use
The krill fishery has since its start in early 1970s (P1 P4) extracted a total of > 6.5 Mtons of krill in different localized areas the Scotia Sea. A phase shift occurred rapidly between the years 1981 1983, mainly explained by the discovery of high fluoride levels in krill exoskeletons or by processing and marketing difficulties. Catches recovered, however, until the end of the Soviet Union in 1991 (Parker 2011). Fishing operations has been conducted particularly close to the coasts of the Antarctic Peninsula (subarea 48.1), the South Orkney Islands (subarea 48.2) and South Georgia Islands (subarea 48.3). Other areas have stood for insignificant catch amounts. Figures 14 below gives an overview over total nominal catch per subarea.
Total catch of Antarctic Krill per subarea in FAO's fishing area 48 (1970 -2008) 500000 Peninsular (Subarea 48.1) 400000 South Orkney (Subarea 48.2) 300000 South Georgia (Subarea 48.3) Tons 200000 South Sandwich (Subarea 48.4) 100000 Weddel Sea (Subarea 48.5) 0 Bouvet (Subarea 48.6) Not specified in which subarea 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006
Figure 14. Total nominal catch of Antarctic krill per subarea and year in FAO’s fishing area 48. Source: CCAMLR (2011). Appendix 4 gives detailed numbers.
Until the end of the 1970s (P1) fishing vessels did not report location of krill catch. However, between the years of 1980 1990 (P2) around 45 % of total catch was taken in subarea 48.2, and 38 % was taken in subarea 48.3. In the early 1990´s (P3) total catch dropped drastically, from 3.3 Mtons for P2, to 1.4 Mtons for the years 1990 2000 (P3). The redistribution between different subareas was mostly equal during this decade with subarea 48.1, 48.2 and 48.3 standing for 400 000 – 550 000 tons each (~ 30%). During the first years of P4 krill fishery focused on subarea 48.3 with 45 % of catches for 2000 2004 (see appendix 4). In recent years krill fishery has switched towards subarea 48.2 where 51 % of catches have been taken. According to Kawaguchi and colleagues (2006), of total krill catch taken inside subarea 48.1 until 2004, 88 % has been taken within the SSMU’s of Antarctic Peninsula Drake Passage West (APDPW), Antarctic Peninsula Drake Passage East (APDPE) and the Antarctic Peninsula Elephant Island (APEI). In subarea 48.2, 70 % has been taken in the SSMU of South Orkney West (SOW). In subarea 48.3, 77 % were taken in the SSMU of South Georgia East (SGE). For a better outline over the distribution of catch in each SSMU see appendix 12.
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Fishing season
The krill fishing season in the Scotia Sea has smoothly shortened. Until 1992 (P1 and P2), krill fishing in subarea 48.1 operated between December May. From 1993 and onwards (P3 and P4), fishing season shifted to only encompass March May. Until 1991 (P1 and P2), the main fishing period in subarea 48.2 was December May. Thereafter (P3 and P4), most catch has been taken only in March–May. From the 1980’s (P2 – P4) to present days, the main fishing period in subarea 48.3 has been June–August, but some catches has also been reported from the March–May period (Kawaguchi and colleagues 2006).
Technology
Echo sounders are used to locate krill aggregations in fishing grounds, and the main gear used by vessels is still the mid water otter trawl, a cone shaped trawling system using fine mesh nets which is towed in mid water (Gascon & Verner 2006, FAO 2011). According to Nicol et al (2011), the conventional trawling gears for krill has been refined by the years, and the average catch rates has therefore rose, from approximately 100 tonnes/day to 400 tonnes/day. Even integrated pumps are being used (see figure 15), sucking the krill directly from the cod end of the trawl to processing facilities onboard, allowing the trawl to stay underwater and making it possible to process the catch efficiently before the krill begins to break down and lose nutritional value (Parker 2011). Furthermore, more of the krill vessels are nowadays using advanced processing systems onboard to ensure fast and effective catch selection and high quality (ASOC 2011).
Figure 15. Two different catching technologies used by krill fishery in the Scotia Sea. At left, the traditional mid water otter trawl, and at right, the same system but with the new pump system integrated. Source: FAO (2011) and Parker (2011)
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Resource system (RS)
Predator abundance
Since 1970 significant ecological changes has occurred in the Scotia Sea’s pelagic ecosystem and food web. The abundance of the Antarctic fur seal population has risen remarkably, mainly at South George Island (in subarea 48.3), which today accounts for 90 95 % of total population of over > 4.5 million individuals. The annual rate of increase in this area was as high as 16.8 % (Payne 1977) in the 1960s and early 1970s, dropping to 9.8 % between 1976/1977 (P1). In 1975 (P1), the fur seal population in South Georgia was estimated to 369 thousand individuals, and in 1990 (P3) > 1.5 million (Boyd 1993). The rapid increase continued during 1990s and early 2000s (P3 P4), but has slowed down during the last years of P4, as new beaches are not being colonized at the same rate as before 14 . The population trend of the crabeater seal also points towards an increase since 1970s (P1). However, the trend for the Scotia Sea is subjected uncertainties, given its pack ice allocation, and thus, the non randomly distribution of the specie (Boveng 1993, Burns et al 2007). The most consensus related estimates found of its population trend is circumpolar, and range from 2 million in 1958 to a present population of around 7 15 million individuals (Laws 1977, Ericson & Hanson 1990, Adam 2005). Another group of marine mammals that are growing, or are stable, in abundance in the Southern Ocean are the whales, many of which migrate towards the Scotia Sea during summer. The estimated rate of increase of Southern Hemisphere sei whales, right whales, fin whales and blue whales population varies between 0,5% 7% since 1970s (Christiansen 2006, IWC 2011).
Most of the sea birds in the Scotia Sea have since 1970s however been in declined. Macaroni penguin’s colonies around Bird Island, South Georgia decreased by 20 % per annum from 1978 to 1981 (P1 P2) (Trathan et al 1998), and between 1986 and 1998 (P2 P3) the overall population in South Georgia decreased by 65 % (ibid.). The population is in South Georgia is estimated to be only half of the 5.5 million breeding pairs estimated in 1979. North of the Antarctic Peninsula, the Adélie and Chinstrap penguin populations also have declined, more than 50 % during the last 30 years (P2 – P4), mainly at South Shetland Island (in subarea 48.1) (Trivelpiece et al 2011). Even the Gentoo penguin populations is declining, with populations at Bird Island, South Georgia (33% of the total population) decreasing by 67 %
14 Steinland on personal communication 2010 41
over the last 25 years (P2 P4) (Croxall et al 1999). On the Antarctic Peninsula (25% of the total population) the population is however increasing at most sites, doubling in the last 20 years (P3 – P4) (Birdlife 2011). Populations of Black browed albatrosses and Grey headed albatross at South Georgia (where 6 % and 19 % of total population breed during summer) have also decreased, with the first species population declining with 17.5 %, ( 1.1% per annum), between 1988 – 2006 (P2 P4), and Grey headed albatross declining with 18.7% overall, or 1.1% per annum for the same period (Poncet et al. 2006).
Myctophid density
The average density (n/m2) of the fish group of lantern fishes has declined in some parts of the the Scotia Sea since 1990s, especially along South Georgia northern western point, where the density was between 0.006058 0.008654 during P3. During P4 the density had lowered to 0.004728 0.0737988 (see comparisons in figure 16 below). For a detailed view see appendix 5.
Figure 16. Changes in lantern fish density (1990s 2000s). Based on calculation made by quantifying number of individuals taken in trawl, and divided with volume of seawater filtered (m ³).
Resource unit (RU)
The Antarctic krill densities (n/m2) trend in Scotia Sea have since mid 1970’s declined (P1 P4) from 146,95 in 1976 to 2,16 in 2003. An up going trend was visible during the 1990s (P3) and early 2000s (P4), but dropped back in 1998 and 2001 respectively. The general negative trend is presented in the figure 17 below. Detailed numbers are found in the appendix 6.
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1000
100 Antarctic krill density in the Scotia Sea
Ind/m2 10 Linear (Antarctic krill density in the Scotia Sea)
1 1970 1975 1980 1985 1990 1995 2000 2005
Figure 17. Change in mean density (ind. m–2) of Antarctic krill (1976 – 2003) within the Scotia Sea. Based on standardized densities. A trend line (black) has also been added. Source: Data gather with basement on the authors article Atkinson et al (2009)
Governance system (GS)
Fishing rules and rule configuration
Since 1982 (P2 P4), 430 conservation measures (CM’s) have been adopted by CCAMLR. Although, at present time only 77 CM’s are in force in the whole Southern Ocean (CCAMLR 2011). Of these, 23 CM´s are at present focusing on krill fishery in the Scotia Sea. For a quantitatively overview over the development of fishing rules in the Scotia Sea see figure 18 below.
Development of conservation measureas applied on the krill fishery per year in the Scotia Sea (1970 - 2009) 25 Adopted 20 15 Carried N° 10 Revised 5 0 Lapsed In force 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006
Figure 18. Development of conservation measures in the Scotia Sea on krill fishery. The graph show CM´s adopted (blue dark), carried (red), revised (green), lapsed (purple) and in force (blue light) per year in the Scotia Sea since 1970. Source: Based on CCAMLR´s annual reports (1980 2010)
CCAMLR rule configuration has since its formation changed with P3 and P4 standing for the most significant alterations. During P1 no CM’s on krill fishery was created or applied as CCMALR only came into force in 1982 and very few CM’s were created and set into force to regulate krill fishery in the Scotia Sea during P2. Only a weak rule framework could therefore
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be identified for P2. During P3 a well established framework of rule was developed, which took into consideration both complexity and uncertainty in the ecosystem. However, fishery response was low. P4 was marked by the reviewing of CM’s, with the total catch limit RU in subareas 48.1, 48.2, 48.3 and 48.4 changing many times, lowering in 2007 to 3.47 Mtons (CM51 01). But again, for 2010/2011 season, rose to 5.61 Mtons through a revision. Fishery response was during P4 higher, possible due the revision of the schemes to promote compliance by member as well as non Contracting Party vessels. For a better overview of the development of fishing rules applied by CCAMLR see table 7 below, for a detailed overview over all fishing rules applied and their modifications see appendix 7.
Rule Fishery Formulation of Framework of rules Ecological change configuration response rules P1 (1970s) Not existing Not existing Not existing Not existing P2 (1980s) CM1, CM7 Not existing Not existing Not existing CM7, CM18, CM32, CM40, CM46, CM50, CM18, CM32, CM50, P3 (1990s) CM61, CM62, CM64, CM68, CM82, CM85, Not existing CM62, CM68, CM82, Not existing CM95, CM118, CM119 CM85, CM95, CM173 10.02 (CM119), 23.02 (CM61), 23.03 (CM40), 26.01, 33.01 (CM95), 23.06, 26.01, 51.01 23.06, 31.01 (CM7), 31.02, 33.01 (CM95), 51.01(CM32), 91.01 (CM32), 91.01 (CM18), 51.01 (CM32), 51.04, 51.07, 91.01 (CM18), Existing P4 (2000s) (CM18), 91.02 (CM82), 91.02 (CM82), n/d 91.02 (CM82), 51.07, 91.01 (CM18), 91.02 n/d (CM62), 91.03 (CM62), 91.03 (CM82), n/d (CM62), 91.03, Table 7. Development of the Scotia Sea’s rule configuration. Source: Based on CCAMLR´s (2011) annual reports (1980 2010)
Related ecosystems (ECO)
Sea ice
According to NSIDC (2011), and despite variation per regions, the general extension trend of the whole Antarctic sea ice has smoothly increased since end of 1970s (see figure 19), a trend which according to Turner et al (2009) includes the larger part of the Weddell Sea, south of Scotia Sea. Drastic drops in sea ice extension were identified for the following years; 1979 80, 1981 82, 1982 83, 1986 87, 1998 99, 2001 02 and 2005 06. The sea ice extension period is however according to Stammerjohn et al (2008) changing, mainly in the Antarctic Peninsula region, south west of Scotia Sea, moving towards earlier retreats and later advances (see figure 20). Temporally changes for the sea ice in the Weddell Sea are mixed, with the northwestern portion of the sea having experienced a shortening of the sea ice season but a substantial area in the south central portion of the sea having experienced a lengthening of the ice season until 1999 (Parkinson et al 2002). Other ecosystems related to the Scotia Sea are presented in appendix 12.
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Figure 19. Sea ice cover extension changes in the Southern Ocean and Antarctic. On the left, trend in the Antarctic sea ice extents (1978 2009). Data based on monthly deviations and 12 month running means. Source: NASA (2011)
Figure 20. Temporal sea ice cover changes. (A) Monthly sea ice extent (km²) and (B) monthly anomalies normalized by the standard deviation. In (A) the mean summer sea ice extent minimum (16,084 km2) occurs in March, while the mean winter maximum (172,455 km2) occurs in August. Source: Stammerjohn et al (2008)
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Socio-economical settings (S)
Aquaculture
The global aquaculture production has since 1970s not stop growing. Its average annual percentage growth production rate between 1970 and 2008 (P1 P4) was + 4,7 % reaching approximately 53 Mtons in 200815 , which means a share of 59 % towards the global fish capture production (FAO/FIGIS 2011). Asian countries are the world leaders, and since mid 1980s China is the foremost producer, today standing for over 60 % of the total production. For a better overview over the development of global aquaculture production since 1970, in relation to the global fish capture production, see figure 21 below or appendix 8.
World capture fisheries and aquaculture production (mtons), with empasis on regions and China (1970-2008) 100 Global fish capture production 80 Global aquaculture production 60 40 Mtons Aquaculture production in China 20 0 Aquaculture production in Asian 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 countries excluding China
Figure 21. Comparison between world capture fishery and aquaculture production with emphasis on Asia and China. Data on aquaculture production does not include aquatic plants. Source. FAO/FIGIS (2011)
Fish meal and fish oil
The global production of both fish meal and fish oil has remained relatively stable since 1970s (P1 P4). The average annual percentage growth between 1976 and 2008 for fish meal was + 0,84 % per annum, reaching 6.1 Mtons in 2008. Fish oil production however has only risen with + 0,27 % per annum, reaching around 1 Mtons for the same year. Despite falling back in recent years, the average global consumption rates of both commodities has since 1995 increased with + 5,2 % and + 3,9 %, with global consumption situated at 3.6 Mtons for fish meal and 778 thousand tones for fish oil in 2007 (Tacon and Metian 2008). Moreover, since 2000 the international market price for fish meal and fish oil has risen significantly. For a better overview over the development over the international fish meal and fish oil market and the price development for both commodities see figure 22 below, or appendix 9.
15 Its current growth is even higher; of 8.5% per year. Source (Tacon and Metian 2008, FAO 2010)
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Global fish meal/oil production International market price for fish meal and use (1976 -2008) and fish oil (1981-2010)
8 2000 1800 6 1600 1400 4 Fish 1200 meal 1000 Mtons 2 800 0 US$/ tonne 600 Fish 1976 1984 1992 2000 2008 400 oil 200 Fish meal production Fish oil production 0
Fish meal use Fish oil use 1981 1985 1989 1993 1997 2001 2005 2009
Figure 22. Global fish meal and fish oil market. Comparison between production, use and prices of the two commodities. Source: FAO/FIGIS (2011), Indexmundi (2011) and data on fish oil price index obtain by Helga Josupeit working on FAO thorough email)
The main producing countries of fish meal during the 1970s and 1980s (P1 P2) were Japan, Peru, Chile and Soviet Union. Both Peru and Chile has taken over by the pass of time (P3 P4). In 1998 production dropped significantly, mainly for Peru. Other fish meal production drops for Peru occurred in 1972, 1983, 2003 and 2006; all correlates mostly with Peruvian anchoveta stock reductions due El Nino events and heavy fishing efforts (Clark 1976, Aranda 2009). Since 1997, China has started to produce its own fish meal with an average annual percentage growth rate of + 8,5 %. China is in other words today’s leading producing country, with almost 1.5 Mtons in 2008. For a better overview over the production rates of fish meal from leading countries see figure 23 below or appendix 10.
Fish meal production by country (1976-2008)
3000000 China 2500000 Peru 2000000 Chile 1500000 Thailand
Tons 1000000 Denmark Japan 500000 Soviet Union 0 Norway 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Figure 23. Fish meal production by country (1976 2008). Source: FAO/FIGIS (2011)
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The main consuming countries of fish meal were during the 1970s and 1980s (P1 P2) Japan, Soviet Union and United Kingdom. However, these countries started to fell back at the end of 1980s, and during the 1990s and 2000s (P3 P4) China has taken over. Its average annual percentage growth since 1988 has been + 4,9 %, today standing for an usage of over 2.8 Mtons. China’s consumption rate has made three main drops (1998, 2003 and 2006) during the last two decades, correlating with fish meal production stops in Peru. For a better overview over the development of main consuming countries of fish meal see figure 24 below or appendix 11.
Fish meal use by country (1976-2008) 3000000 China 2500000 Japan 2000000 Norway Vietnam 1500000
Tons United Kingdom 1000000 Denmark 500000 Soviet Union 0 Thailand
1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Figure 24. Fish meal use by country (1976 2008). Source: FAO/FIGIS 2011
The main producing countries of fish oil during the 1970s and 1980s (P1 P2) were Norway, Peru, Chile and Soviet Union. During the 1990s (P3) Denmark raised to the third largest fish oil producer after Peru and Chile. Norway’s production has however declined with an average of 3,5% since 1976. Notable again is that the production of fish oil of Chile and Peru fall during El Niño years (1982, 1998 and 2002). For a better overview over the development of the main producing countries of fish oil see figure 25 below, or appendix 12
Fish oil production by country (1976-2008)
800000 Peru 600000 Chile China 400000
Tons Denmark 200000 Soviet Union 0 Norway 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Figure 25. Fish oil production by country (1976 2008). Source: FAO/FIGIS (2011)
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The main consuming countries of fish oil were during the 1970s and 1980s (P1 P2) almost all European countries, with United Kingdom, Germany and Norway as leaders, smoothly followed by Chile. Since 1985, average annual using rates for both United Kingdom and Germany has felled down drastically by 6,6 % and 4 %, while Norway and Chile has risen remarkably. Both these countries are today the main consumers of fish oil. During recent years Denmark has raised, and China has become the third largest user. For a better overview over the development of main consuming countries of fish oil see figure 26 below, or appendix 11.
Fish oil use by country (1976-2008) 300000 Norway 250000 Denmark 200000 Chile 150000
Tons China 100000 50000 United Kingdom 0 Germany 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Figure 26. Fish oil use by country (1976 2008). Source: FAO/FIGIS (2011)
After all we can now summarize the result, wherein it now can be showed that the relationship between analyzed variables has changed within the SES since 1970s, wherein many attributes has increased in significance, while the Antarctic krill is losing significance in the system. The can be contemplated in the following schematic figure 27:
Figure 27. Schematic summarize of results. Significance level of analyzed variables in the SES of the Scotia Sea.
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DISCUSSION The result from the first question in this work shows that the outcomes from not using a set of fishing rules were moving the SES towards collapse, while the introduction of fishing rules in the Scotia Sea ecosystem and krill fishery during P3 steadily have increased the SES adaptive capacity. However, other attributes and external factors have also risen in significance, increasing the connectiveness and complexity of the SES. Despite a more interconnected planet than ever before, recent research on the Southern Ocean has barely accounted for different socio ecological variables over temporal and spatial scales. How these relationships have developed and moved the krill regime towards change will now be discussed next, consequently, responding to the second research question regarding the resilience capacity of the SES.
The krill fishery state (1972 1991)
During P1 most of the variables were loosely connected or not connected at all in the SES. The potential for change was low and resilience high, positioning the SES into an r phase in the adaptive cycle. Despite the existence of other governance systems (GS) in the Southern Ocean, such as the IWC and CCAS, there were still no institutions or a framework of rules present to regulate the newly formed krill fishery (U) in the Scotia Sea ecosystem (RS). Moreover, with a shortfall of marine mammals preying on Antarctic krill (RU) there was still a lot of space for actors to seize on opportunity. In other words, few interactions existed between the loosely connected attribute U, RS and the RU in the SES. This open access situation created a desirable krill fishery state, emerging from an undesirable mammal fishery state. The connection between the SES with related ecosystems (ECO) and external socio economical settings (S) should however not be excluded during P1.
Despite the mean duration of winter sea ice (ECO) cover around the Antarctic has become shorter around the Antarctic, sea ice extension (km²) in its overall has been expanding; a phenomenon also observable in the Weddell and Scotia Sea (see figure 19 and 20) (Stammerjohn et al 2008, Turner et al 2009, NASA 2011). Sea ice should be seen as a supporting force for RU, enhancing the resilience of the newly formed SES during P1, mainly in maintaining high density levels, as krill can shelter and prey under the sea ice on ice algae (Murphy et al 2007), stabilizing the krill regime and the krill fishery state 16 . However,
16 For a better overview compare figure 19 and 20 with figure 6 and 7 50
although this newly formed state was comprised by high krill catches, few U’s where operating in the RS during P1. The main krill harvesters were Soviet Union and Japan; by that time highly dependent on forage fish for fish meal production and consumption. Their operations in the SES were mainly triggered by their own industrial food sectors; towards human consumption, livestock and animal production (IFFA 2011). Global aquaculture production was still not a significant force, despite its average annual percentage growth production rate of + 4,7 %. Another triggering force was the Peruvian anchoveta fishery in the Humboldt Current system (ECO) along Chile and Peru, which collapsed in 1972, as a result of overfishing and El Niño events (Clark 1976, Aranda 2009). This collapse must have shortened the global supply of non food commodities. Thus, stimulated by the following external factors; the collapse of the Peruvian anchoveta fishery, the low abundance of mammals and growing governance structures on mammal fishing, made the two largest forage fish and fish meal dependent nations, Japan and Soviet Union, to move their efforts and vessels towards the institutional constrained and krill rich Southern Ocean, leading to the phenomenon known as roving bandits, as stated by Olson (2000). The connection between both external components, S, ECO and the SES of the Scotia Sea was therefore to a degree influential when establishing the krill fishing state.
According to CPR research such as Hardin (1968) and Ostrom (1990, 2007), the scenario in the Scotia Sea during P1 was assembled for an overharvesting of Antarctic krill and a collapse of the whole RS. In other words, there were no implicitly installed institutional structures or a framework of rules to constrain resource use of Antarctic krill. However, during P2 connections started to appear between attributes in order to not destabilize the SES. The potential for change was therefore enhanced. With the set into force of the governance system (GS) of CCAMLR in 1982, sub institutions and fishing rules appeared to ensure that the exploitation of marine resources was not to harm the RU and RS, supporting the claim that it lays in actors interest to resolve a common problem by creating the international regime of CCAMLR (Krasner 1982, Joyner 1998). Connection between the GS and U were however still non existing, with only one fishing rule CM1 created for the extraction of marine resources in the seawaters around South Georgia (subarea 48.3), prohibiting any fishing activity other than for scientific research purposes. Moreover, Soviet Union and Japan were still catching high amount of Antarctic krill, possible explained by the stronger connection that existed between S and the SES by that time. The Peruvian anchoveta fishery, which has produced a relatively small amount of forage fish to the global market since its collapse in P1
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was still encouraging main consumers and producers of fish meal, Soviet Union and Japan, to continue their extraction of Antarctic krill in the SES. Main fish oil consumers were still not acting in the SES. Overall, the interactions created in P2 between the internal attributes in the SES and the external variables decreased the resilience of the SES. Although, it was still in a desirable krill fishery state with high resilience, which means that the SES was by this time concluding the r phase from P1 and entering a K phase in the adaptive cycle. The position of the SES in the adaptive cycle for P1 and P2 is presented in the figure 28 below.
Figure 28. The way of the SES in the adaptive cycle between 1970 – 1990 and the strength of connection between analyzed internal and external variables.
The ecosystem based governance state (1991 2010)
In the third analyzed period P3 interactions intensified within the SES, as connections between GS and the RU, RS, U became strengthened. The connection between U and RU, RS is however weakened due to external disturbances. The establishment of a more receptive rule configuration in 1991, through the first rule CM32 on catch limits for Antarctic krill, and following the SC yearly report, total catch limit for Antarctic krill became 1.5 million tons for any fishing season in statistical area 48 (CCAMLR 2011). A precautionary limit was to be agreed on by the Commission, on the basis of SC advice if total catch in subareas 48.1, 48.2 and 48.3, during any fishing season, exceeded a trigger level of 620 000 tons (ibid.), regulating the access to RU and considering the RS to be complex and characterized by uncertainty. This now makes the SES more adaptable, taking into consideration ecological changes. The SES is in other words restructuring from a krill fishery state towards a regional ecosystem based governance state, jumping over the K and Ω phase, and moving the SES instead directly towards α phase where it is reorganize and later would move into a an r phase. This phase shift, from a desirable krill fishery state into a desirable ecosystem based governance state, shows signals of self organization and a strengthened capacity of CCAMLR 52
to monitor, evaluate, and adapt over time (Ostrom 2005). The external socio economical settings of interaction with the SES should not be excluded from this outcome. During the first two years of the 1990s (P3) Soviet Union catches was already reaching > 575 000 tons (CCAMLR 2011). But as its political and economical system collapses in 1991, Soviet Union withdraws from krill fishery in the Scotia Sea. This explain the weakening connection between U and RU, RS, making total krill catches in the whole SES to drop drastically from over 300 000 – 400 000 tons per annum during P1 and P2, to 80 000 – 130 000 tons per annum during P3 (ibid). Japan now becomes the strongest U, but due to its reduced production and consumption of fishmeal this nation weakens the connection between the SES and the former S connection from P1 and P2. At the same time, China is increasing its use of fish meal for aquaculture production (FAO/FIGIS 2011), but is not acting as a U in the SES, at least not formally. Neither the drastic drop of global fish meal nor fish oil production in 1998 (see figure 8), due to this years El Niño event, seems to have affected the SES as it did during P1 and P2. This drastic change in U’s catch however opened up the door for a range of new smaller nations, such as the as Ukraine and Poland which together with Japan would become the main U’s of krill in the SES by the end of P3. Main fish oil producing nations were still not operating significantly in the Scotia Sea.
The spatial and temporal redistribution of catch also changes between different subareas. Catch is now mostly equal with subarea 48.1, 48.2 and 48.3 standing for 400 000 – 550 000 tons each during the whole P3. The fishing season is even postponed to the month March – August (Kawaguchi and colleagues 2006). In the RS krill demand by marine predators grows due to higher marine mammal abundance around South Georgia (subarea 48.3). Even so, the krill density during P3 smoothly increases, despite the increases in the abundance of marine mammals, which however outcompete most of the seabird species, which are still decreasing in abundance.
P4 is characterized by an end of the r phase from P3 and an entrance of the SES’s ecosystem governance regime into a K phase with lower resilience, despite CCAMLR’s adaptable and ecosystem based efforts to manage the resilience of the SES, by constantly revising the existing krill fishing rules and changing catch limits during P4 to new situations and environmental conditions. This outcome was mainly triggered by the strengthening of a range of connection and the intensification of interactions between the attribute from P3.
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The abundance, and krill demand from marine mammals, has increased in the RS, especially in subarea 48.3, together with the lowering in seabird abundance and the lowering in the densities of alternative prey lantern fish. The competitive release between species has in other word been loosening up, and competition for prey in the Scotia Sea is increasing (Trivelpiece et al 2011). The RU density continued its decline during P4, now situating itself at 2,16 n/m ² in 2003 (see figure 17). Despite further increases in sea ice extension cover (ECO), the temporal extensions of sea ice has been lowering (see figure 19 and 20) (Parkinsson et al 2002, NASA 2011). How this affects the lowering of Antarctic krill density can not be determined here as many more physical variables must be analyzed. However, the probability of the RU to reach a critical level in the Scotia Sea, approximating a population threshold for this forage fish is high in P4. If the decreasing density levels of the RU can be compensated by the circumpolar distribution of the species is still an open issue. Nevertheless, this intensification of the RS with the rest of attributes seems to make the RS and its predators to move from krill competitiveness towards diet switch in order to compensate lost prey (krill). The lowering of myctophid density shown in figure 16 is an indicator of this phenomenon, but needs to be investigated further due the scarcity of data. However, it can be said that both top down and bottom up forces are now playing a role in structuring the Scotia Sea ecosystem, moving a krill centred food web towards a fish centred wood web.
Moreover, as the RS is intensifying its connection with RU, intensification also occurs between U and RS, S. The low consistency in krill fishing locations, a process extending from P3, is now on regularly bases by krill fishery. During the first years of P4 krill fishery mainly focused on subarea 48.3 whit 45 % of catches for 2000 2004. However, during the recent years krill fishery switched towards subarea 48.2 with 51 % of total catches (FAO/FIGIS 2011). Furthermore, with the appearance of two additional krill fishing nations, Norway and South Korea, and changing and improved technology, daily and total catches has been increasing in the SES at the end of P4. Thus, in 2010, the focus becomes subarea 48.1 with over 154 000 tons of krill catch, making CCAMLR for the first time to close a subarea as its the trigger level is reached (CCAMLR 2011). This operational intensification of U’s could also be explained by the reinforcement of the connections between the SES and S during P4. As fish meal and oil prices (S) are increasing since P3, forage fish depending actors, using both fish meal and fish oil, are now seeking for new fishing areas and easy catch. The position of the SES in the adaptive cycle for P3 and P4 is presented in the figure 29 below.
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Figure 29. The way of the SES through the adaptive cycle between 1990 – 2010 and the strength of connection between analyzed internal and external variables
Implications of findings
The foremost implication of this work is the existence of both stability and multi stable states in the Scotia Sea, and that the resilience of the SES is at present decreasing. This suggests that the SES is now closing in towards a threshold, with the risk of moving over into a new regime where the Scotia Sea will behave in a different but still unidentified way. Previous regime shifts were not identified or discussed. However, the transition towards both states (krill fishery state and ecosystem based governance state) in the SES was a result of different interactions, mainly provoked by internal and external disturbances of the nested attributes, as suggested by Folke (2006) for changes between phases in the adaptive cycle. Accordingly, this work is suggesting that research should not regard the Scotia Sea as a closed krill regime; independently diminished by a few variables, either in local fishery, or in regional physical or ecological forces, but as being part of complex and global system of people and nature dominated by flows of commodities, capital, as well as oceanographic and climatic patterns.
After all, CCAMLR should prepare for upcoming changes and create governance mechanisms and fishing rules in the Scotia Sea that facilitate a smooth transition of the SES from a K phase, enhancing the desirable services provided by the Scotia Sea ecosystem to both marine predators and fishery and buffering against external disturbance. This work therefore presents the following recommendations: (1) Take into consideration changing predator prey relationships in the Scotia Sea food web, and mitigate increased competition between predators and krill fishery for Antarctic krill. This could involve creating and developing fishing rules and trigger levels on a small scale basis, emphasizing the management units (SSMU’s); (2) take into consideration the role of alternative prey in the Scotia Sea food web as the krill density is now reaching critical levels in the Scotia Sea. The possibility of a
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transition from a krill dominated ecosystem towards an unknown fish dominated ecosystem is in other words probable; (3) take into consideration the appearance of new and more efficient krill fishing nations in the Scotia Sea, attracted by the global aquacultures’ increased production and demand of aquafeeds, lower catch of other forage fish species world over, and higher non food commodities prices; (4) take into consideration the sea ice cover capacity to continue expanding in size and provide shelter to Antarctic Krill species, thus, enhancing resilience despite decreasing temporal expansion, and the implication of this for the current SES krill regime; (5) continue the development and revision of the compliance rules to increase trust for member and non member states and reduce IUU fishing in the region, and finally; (6) develop a holistic database for transdisciplinary work which will help analyze future interaction of cross scaling political, socio economical, physical and ecological forces, thus, getting ready for an aquaculture world with increased anthropogenic pressure on the Sothern Ocean.
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CONCLUSION The aim of this work was to examine the inter relationship between CCAMLR, krill fishing and changes in Scotia Sea ecosystem and external socio economical and environmental forces, to improve our understanding on how their cross scale relationships have affected the resilience of this SES over time. The results mainly prove the existence of stability and the existence of multi stable states in the Scotia Sea; an early krill fishery state characterized by open access, which shifted towards an ecosystem based governance state in 1991 characterized by a more adaptive rule configuration and higher fishery responses. However, despite relatively low catches of krill nowadays, in comparison with the allowable catch, and with CCAMLR’s strengthened capacity to implement an adaptive and operational ecosystem management approach, the resilience of the SES is now fading due to a combination of internal and external factors; lower Antarctic krill density, increasing abundance of marine mammals, mounting competition for marine resources between predators and krill fishery, the implementation of new and more efficient fishing technologies, and mounting international production, demand and prices of non food commodities from an expanding aquaculture sector in Asia. These nested attributes are together moving the Scotia Sea towards an unknown fish regime. The transition from a krill regime to an unknown fish regime could be provoked by a drastic change in one of the physical variables such as ocean currents, sea ice extension and seasonality, or by continues increasing krill demand from both predator and krill fishery for the target species. The exact role of all related ecosystems and physical, climatically and oceanographic forces in maintaining the resilience of the SES could not with exactitude be measured in this work. Such questions must therefore be considered open for further research. In order to maintain the desirable krill regime in the SES this work suggests CCAMLR to take further consideration of the inter related role of krill dependent predators and feedbacks from a changing food web structure. This could involve creating and developing fishing rules and trigger levels on a small scale basis, emphasizing the management units (SSMU’s). Future scenarios will also have to take into consideration the mutual interaction of political, socio economical, physical and ecological forces such as the role of climate change. Hence, a holistic and transdisciplinary analysis of what determines the resilience of a future krill, fish or other food web structure is fundamental when maintaining a desirable state and considering how the SES of the Scotia Sea will change over time.
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APPENDIX 1 – GLOBAL ANNUAL NOMINAL CATCHES (Tons) OF FORAGE FISH SPECIES DESTINED FOR NON-FOOD USES (1970-2009)
Fish commonly caught for 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 non-food and reduction Chilean jack mackerel 108700 159100 110300 164500 322723 299904 397358 848071 1026180 1306337 Peruvian anchovy 13059900 11243700 4815300 1704800 3972670 3318656 4297095 810775 1416049 1413390 Blue whiting 38811 80855 43203 42620 39452 62032 120302 246672 549429 1101612 Japanese anchovy 419500 417600 473900 430900 460973 420615 342866 385775 335639 296428 Atlantic herring 2320434 2151383 1909320 1979461 1564947 1526723 1177633 990206 939474 887533 Chub mackerel 2016143 1835475 1876550 1935762 2152898 2089184 1938137 2679088 3412547 2872083 Capelin 1514724 1584219 1946235 2054060 1907869 2248185 3358826 4008746 3158301 2933573 European pilchar 610438 716777 696090 949501 991013 1070685 1315679 1113414 809060 789342 Californian pilchard 35500 50700 53600 64700 84142 121908 142080 107345 155929 186044 European sprat 236685 303798 331362 514583 650621 990299 911625 641884 726517 674353 Gulf menhaden 548600 729900 502200 487100 587717 542794 561525 447461 820352 807107 South American pilchard 11400 21400 16600 186200 280867 227799 501948 1491709 1990772 3345997 Atlantic mackerel 668523 758112 783725 1021010 982447 1092759 1072519 684779 704081 757744 Norway pout 308400 400000 527100 503200 877910 694439 644067 498296 437363 428734 Southern African anchovy 358300 367000 372200 558200 595778 400949 299481 376913 564291 587693 Horse mackarel 173895 155384 203918 263968 229778 221294 288205 146414 95737 111351 Pacific herring 581800 515400 620700 660700 519998 538263 430895 412136 188011 192110 Pacific saury 162900 263800 281600 490700 218085 316562 187545 343237 459922 364038 Atlantic menhaden 284900 266200 378006 369200 319852 275278 363666 367251 356739 374278
Argentine hake 108100 116400 139300 183700 172600 125646 225745 359149 416777 462039
European hake 143140 93572 121822 136593 138118 138788 127345 106042 77423 92722
Southern hake 0 0 0 0 0 0 0 0 0 45065
Senegalese hake 11229 10450 32432 99171 99510 38171 101934 58589 32977 35922
Silver hake 222030 235668 233400 434937 225283 232092 177548 112667 85826 72704
South Pacific hake 105500 93100 107600 224700 164001 135659 153041 173362 382439 125060
North Pacific hake 171300 183100 119600 163600 207462 230354 238219 126242 101222 141622
Shallow-water Cape hake 0 0 0 0 0 0 0 0 0 0
Rainbow sardine 33700 36000 41300 44400 46621 54770 51206 66838 40930 31274
Japanese pilchard 16900 57500 58200 300600 351878 529602 1076846 1470811 1933926 2155865
Southern African pilchard 627400 415600 551100 494600 617770 667517 637689 179997 111853 66212
European pilchard 610438 716777 696090 949501 991013 1070685 1315679 1113414 809060 789342
Round sardinella 96851 104887 108538 120827 109618 189059 161877 188851 198821 220116
Goldstripe sardinella 26800 27300 25500 40400 50613 63216 55566 65054 75627 79168
Brazilian sardinella 135400 161000 170700 228000 177089 136104 105276 145576 144685 149542
Japanese sardinella 0 0 0 0 0 0 2869 6227 9607 4212
Bali sardinella 17900 18200 17800 12900 16314 41779 41400 62507 49617 45625
Indian oil sardine 235000 217700 136000 85500 151336 262100 284889 264497 326091 320542
Elongate ilisha 12500 15500 16000 4400 1318 2263 7177 2882 14311 16891
Pacific sandlance 227100 271900 194900 194000 299696 274850 224312 137218 102908 110834
Golden threadfin bream 4900 5700 10200 13600 18011 12305 4299 8037 6460 6044 Antarctic Krill 0 0 0 59 19339 41352 885 75359 78940 266534
69
Fish commonly caught for non-food and 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 reduction Chilean jack mackerel 1280639 1740315 2204641 1678875 2324010 2148841 1960897 2681782 3245699 3654628 Peruvian anchovy 822818 1550313 1826402 126410 93654 986796 4945315 2100508 3613107 5407527 Blue whiting 1108535 907165 556084 543749 613873 669290 817987 711554 671636 666493 Japanese anchovy 320261 344819 359709 339460 379193 349336 412272 308238 303604 316203 Atlantic herring 923179 951801 971171 1143386 1201373 1452831 1532217 1593895 1724399 1649629 Chub mackerel 2667477 1919834 1 865875 1675537 2220408 1742730 2011056 1569696 1825740 1686926 Capelin 2592471 2805095 1843533 2553381 2595117 2216484 1407809 1107606 1145354 903508 European pilchar 967405 1000023 865359 960742 913590 926110 980587 1184213 1366307 1539138 Californian pilchard 328096 344433 432588 381373 278331 372344 470534 477076 446127 509248 European sprat 652553 600122 558068 372296 296212 220525 265761 312669 322345 314060 Gulf menhaden 702073 552567 854336 923585 982888 883514 828503 907103 638733 583350 South American pilchard 3253365 2973133 3475535 4066403 5734667 6509301 4960771 4949842 5382681 4440783 Atlantic mackerel 651122 625796 610499 569534 658095 597844 608520 700768 710931 631595 Norway pout 552572 349583 522763 548550 519863 344693 284519 339344 276807 351914 Southern African anchovy 508750 492970 389571 424011 285962 323239 315110 969401 682457 373095 Horse mackarel 125515 157082 187612 160769 157241 194992 202134 247168 343175 367766 Pacific herring 202584 216691 224613 261504 248076 293178 324734 348517 304651 213152 Pacific saury 238150 202863 240700 251861 242344 273760 251055 227347 346997 330592 Atlantic menhaden 430399 402440 400341 420353 328507 359151 256230 323184 360463 356868
Argentine hake 354708 326521 360338 347688 254851 376496 381245 428779 434343 398682
European hake 107991 101041 96582 109792 128825 134810 122151 125465 124822 107903
Southern hake 37095 39774 45943 32200 31742 33361 39323 58342 72668 64298
Senegalese hake 30000 13912 20114 26161 14013 8420 23456 16469 15580 19419
Silver hake 62439 63748 78780 53477 95924 98902 102292 77920 90725 105905
South Pacific hake 191438 102779 52891 31260 45328 47064 74278 64286 149831 156176
North Pacific hake 57086 142212 115280 124138 146470 118605 222806 372682 255108 315655
Shallow-water Cape hake 0 0 0 0 5 16 19 19 5 2
Rainbow sardine 40974 37843 32102 31923 47354 40184 40215 42896 49235 44450
Japanese pilchard 2595315 3613379 3966090 4464825 5156086 4722862 5191036 5321064 5428922 5142930
Southern African pilchard 58120 91726 58074 79654 78284 85792 86536 106921 101146 102567
European pilchard 967405 1000023 865359 960742 913590 926110 980587 1184213 1366307 1539138
Round sardinella 244302 205781 245611 278702 230010 343266 384457 448191 454822 485120
Goldstripe sardinella 92646 108714 98980 104617 109393 108543 120646 118299 134076 141888
Brazilian sardinella 146276 111967 98873 139377 137236 123962 126197 91316 65139 78116
Japanese sardinella 5102 4244 5625 10606 10829 8994 14033 10300 10693 7280
Bali sardinella 52354 44172 56987 90900 79365 54058 51387 61531 94644 99387
Indian oil sardine 295078 386736 311744 268456 306995 290229 292499 265704 251173 300210
Elongate ilisha 18169 16665 17604 15338 19711 18593 24659 15470 16300 18289
Pacific sandlance 201227 163548 127887 123262 170236 124656 143387 124672 83560 77850
Golden threadfin bream 6592 6306 4817 4957 5298 5844 6737 6405 9760 8131 Antarctic Krill 356978 288868 373586 138351 104680 180807 425871 346505 364173 394394
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Fish commonly caught for 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 non-food and reduction Chilean jack mackerel 3828452 3953748 3379343 3376871 4261941 4955186 4378843 3597117 2025758 1423447 Peruvian anchovy 3771577 4017106 6157269 8482463 12520611 8644576 8863714 7685098 1729064 8723265 Blue whiting 577493 448104 475254 550424 493973 544310 632471 712279 1185003 1321195 Japanese anchovy 536271 613664 662540 1001372 820626 972008 1254487 1575399 1937750 1674762 Atlantic herring 1541590 1404217 1546449 1641860 1930045 2352857 2328688 2533912 2421462 2411408 Chub mackerel 1330358 1182964 963326 1475721 1544017 1578164 2182476 2401727 1892371 1921299 Capelin 1006030 1259142 2115140 1742686 884404 748800 1527422 1603338 982312 904045 European pilchar 1521993 1464150 1156750 1076230 1133637 1208655 996314 1001734 954628 912683 Californian pilchard 313602 325330 279293 272630 300714 363464 450596 498653 381898 405402 European sprat 244876 273108 288784 380675 579681 601998 671616 700239 696228 684189 Gulf menhaden 519583 550730 432848 551822 767448 472039 491612 597565 497461 694242 South American pilchard 4253718 4189889 3057073 1966530 1746544 1503131 1493936 722807 937269 442790 Atlantic mackerel 657866 681641 784816 840833 855596 794329 559251 555608 666964 618014 Norway pout 295634 303371 452926 324318 291005 389800 275667 211394 97478 112613 Southern African anchovy 200605 167657 386133 298680 180675 218331 41792 62640 110296 180954 Horse mackarel 405480 366090 426076 515361 434438 559867 474625 455109 350298 320186 Pacific herring 199488 215522 227434 211269 184651 211676 257870 436701 506149 468928 Pacific saury 435869 402017 384444 402930 335604 350287 276111 388643 180973 187898 Atlantic menhaden 428198 397525 340546 347806 286502 365736 304665 322239 276230 208000
Argentine hake 419750 518902 475759 526822 526132 636385 688650 652104 528660 375995
European hake 98775 107721 115913 114660 113129 119906 92332 76958 66159 70553
Southern hake 61199 47784 49865 32005 28797 39463 36970 39073 43201 47560
Senegalese hake 15228 14854 14246 13872 14435 14779 16485 16430 18318 23219
Silver hake 90843 82794 45305 45957 24380 35480 43164 33565 31892 27609
South Pacific hake 224602 140168 93054 152962 203812 256585 323470 265573 162516 140910
North Pacific hake 263797 130468 153548 203375 369421 236436 295219 325048 318475 308739
Shallow-water Cape hake 17 109 219 92 24 26 832 777 906 2060
Rainbow sardine 38108 35632 36279 25949 40094 39904 41347 38045 42960 48265
Japanese pilchard 4732154 3774247 2488533 1796132 1313739 733427 430837 408476 282017 495962
Southern African pilchard 149279 120865 134220 166775 209901 158002 106381 144681 196581 175969
European pilchard 1521993 1464150 1156750 1076230 1133637 1208655 996314 1001734 954628 912683
Round sardinella 484866 540197 495707 401767 359886 412811 562366 469882 517362 420242
Goldstripe sardinella 134972 136626 139352 152560 166452 161096 157104 156914 174691 162710
Brazilian sardinella 32106 64323 64846 50015 84648 60212 97093 117642 82283 25518
Japanese sardinella 4205 4463 3597 24383 23974 18345 10663 5593 1973 6674
Bali sardinella 113515 145055 137022 122039 128202 98905 88590 138636 153965 89286
Indian oil sardine 338135 253215 270668 262302 197717 197601 223355 298979 257073 222278
Elongate ilisha 24667 31685 30296 28966 32839 47101 51969 72004 75088 95986
Pacific sandlance 75545 90107 124273 106568 109344 108124 115766 108666 90688 82918
Golden threadfin bream 12511 7685 8933 9841 4142 3664 4261 4401 3681 3990 Antarctic Krill 344364 355460 302911 83086 83063 117448 91150 75653 90098 101959
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Fish commonly caught for non-food and 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 reduction Chilean jack mackerel 1542812 2528924 1750078 1790007 1873900 1747955 1992783 1953710 1430129 1252552 Peruvian anchovy 11276357 7213077 9702614 6203751 10679338 10244166 7007157 7611858 7419295 6910467 Blue whiting 1472105 1821887 1572594 2385036 2428955 2070286 2038723 1684853 1283536 640953 Japanese anchovy 1563262 1651361 1678869 1892856 1629486 1481442 1509170 1390596 1265763 1071200 Atlantic herring 2381011 1952605 1873503 1958928 2020491 2315431 2224747 2368656 2479202 2509260 Chub mackerel 1422804 1800045 1439305 1817748 1956679 1991021 1974021 1714734 1900387 162410 Capelin 1484818 1667702 1980885 1143971 663533 751905 268859 422700 254450 364097 European pilchar 947685 1139051 1097324 1050093 1060087 1070234 1034417 981506 1043560 1217346 Californian pilchard 546079 685497 722071 633554 565280 339130 355527 559520 742028 758070 European sprat 658412 648677 621808 637848 689435 792053 592879 575209 562175 667187 Gulf menhaden 591434 528506 582497 522195 464148 369906 408875 456576 420719 454758 South American pilchard 338131 135712 27338 20037 6898 4507 1268 1035 400 205 Atlantic mackerel 685545 703375 761340 689593 706080 560038 547912 566096 610994 706394 Norway pout 204845 90837 107879 37833 22513 354 54348 4809 39223 57261 Southern African anchovy 267986 289323 254643 260525 192305 283446 135463 252997 266105 174493 Horse mackarel 230135 249938 211736 208794 205423 218871 210797 204344 184324 242209 Pacific herring 455029 399309 313032 298510 294602 324259 342742 267947 283580 305596 Pacific saury 306069 376173 335473 446066 355790 478226 394861 524947 622119 476883 Atlantic menhaden 207122 261401 211574 203263 215163 194243 183868 215506 187742 182210
Argentine hake 246744 306771 412068 380283 480588 422715 406876 346832 315516 331359
European hake 71241 57914 66503 72909 81168 88989 86426 75373 81553 93927
Southern hake 52478 48737 42566 52264 56968 47887 47776 47352 40103 42774
Senegalese hake 24688 23584 7486 6393 5528 2294 3585 5161 4524 13489
Silver hake 25756 33000 24293 20223 22384 18903 17935 18418 18723 18415
South Pacific hake 193504 246265 162291 123008 112248 78036 77436 77534 83256 94306
North Pacific hake 229094 233919 187665 210371 341207 364069 356651 274275 312056 172003
Shallow-water Cape hake 658 1863 3225 1457 1799 1600 1800 5876 2565 2146
Rainbow sardine 36754 37303 27175 29687 31360 38314 35111 35158 30639 29724
Japanese pilchard 283889 315759 208805 191355 203490 185164 235092 248332 192039 195724
Southern African pilchard 161448 200100 264886 312249 402435 274043 219642 176782 114057 108049
European pilchard 947685 1139051 1097324 1050093 1060087 1070234 1034417 981506 1043560 1217346
Round sardinella 371240 525681 479543 514791 486733 434762 375241 334160 379446 315749
Goldstripe sardinella 172219 185912 182026 153771 145428 177302 170522 169823 174356 175800
Brazilian sardinella 17053 39847 22057 25266 53421 42657 54201 55940 74631 83286
Japanese sardinella 4603 766 796 885 755 1756 953 795 4893 5983
Bali sardinella 88744 103710 132170 136436 103362 96994 163129 176665 139350 139010
Indian oil sardine 418091 457490 361607 373972 382186 360981 377693 385082 428529 422560
Elongate ilisha 92519 86500 80425 81558 80704 84490 92183 88800 94192 98657
Pacific sandlance 66129 92967 72901 283621 259261 266443 266026 188429 197529 181510
Golden threadfin bream 4824 3536 2995 4274 3523 3684 2670 2626 1754 1886 Antarctic Krill 114429 104182 125987 117728 118167 129026 106635 104586 156521 123949
Source: FAO/FIGIS (2011)
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APPENDIX 2 – ANNUAL NOMINAL CATCHES (Tons) OF ANTARCTIC KRILL, SELECTED MARINE FISHES AND WHALES PER YEAR (1950 – 2009) IN THE SOUTHERN OCEAN
Annual nominal catches (t) 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960
Antarctic krill 0 0 0 0 0 0 0 0 0 0 0 Marine fishes 0 0 0 0 0 0 0 0 0 0 0 Whales 32396 33945 35320 30653 34869 37780 38538 36214 40007 41570 41354
1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971
Antarctic krill 0 0 0 0 0 0 0 0 0 0 0 Marine fishes 0 0 0 0 0 1100 12900 5400 89100 399709 220531 Whales 43677 39981 30206 30995 32569 24696 20245 15089 11496 11999 12199
1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982
Antarctic krill 0 59 19339 41352 1552 75267 83358 263116 357047 289726 373656 Marine fishes 192937 28772 51730 35768 59107 185449 320008 113718 119766 116526 137934 Whales 14570 15627 18372 16043 10907 11791 7783 7819 8074 6240 7154
1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993
Antarctic krill 144710 97399 259135 378739 400835 388953 352271 276099 331318 257663 60783 Marine fishes 255035 100114 51922 74943 117394 114917 67180 98573 78200 11664 6773 Whales 6447 6055 4968 4969 4969 273 241 330 327 288 330
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Antarctic krill 84645 134419 91150 75653 90026 101957 114426 104182 125987 117728 118224 Marine fishes 7359 11980 9350 12777 13695 14223 22581 16342 20364 24816 20644 Whales 330 330 440 440 438 389 439 440 440 441 445
2005 2006 2007 2008 2009 2010 Antarctic krill 129057 106595 104621 156521 125824 211180
Marine fishes 20387 21263 22340 20420 20176 n/d
Whales 441 856 510 551 679 n/d
Whales include blue whales, fin whale, humpback whale, killer whale, long finned pilot whale, minke whale, northern bottlenose whale, sei whale, sperm whale and toothed whales nei. Marine fishes include marbled rockcod (Notothenia rossii), mackerel icefish (Champsocephalus gunnari), grey rockcod (Nothotenia squamifrons), patagonian rockcod (Patagonotothen Notothenia) guntheri), sub Antarctic lanternfish (recorded as Electrona carlsbergi), the Patagonian toothfish (Dissostichus eleginoides and D. mawsonii), the spiny icefish (Chaenodraco wilsoni). Source: FAO/FIGIS (2011)
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APPENDIX 3 – ANNUAL NOMINAL CATCHES (Tons) BY COUNTRY AND DECADE IN THE SOUTHERN OCEAN (1970-2009)
Total krill catch (tons) by country and decade in the Southern Ocean (1970-2009)
1970s Tons 1980s Tons
Japan 83631 Japan 520162
Poland 8578 Poland 17815
Un. Sov. Soc. Rep. 535395 Un. Sov. Soc. Rep. 3080411
Chile 368 Chile 24118
German Dem. Republic 110 German Dem. Republic 446
Korea, Republic of 511 Korea, Republic of 10876
Spain 379
1990s Tons 2000s Tons
Argentina 6524 Argentina 172
Japan 650155 Japan 410926
Poland 127597 Poland 94179
Un. Sov. Soc. Rep. 575429 Chile 2
Chile 21341 Korea, Republic of 217971
Korea, Republic of 8648 Russian Federation 997
India 6 Ukraine 121793
Latvia 71 United Kingdom 18
Panama 637 Uruguay 6477
Russian Federation 105466 Norway 112261
Ukraine 143922 United States of America 34665
United Kingdom 942
Uruguay 3444
South Africa 3
Source: CCAMLR (2011)
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APPENDIX 4 – ANNUAL NOMINAL CATCHES (Tons) OF ANTARCTIC KRILL PER YEAR AND SUBAREA IN FAO's FISHING AREA 48 (1970 -2008)
Year 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979
Peninsular (Subarea 48.1) 0 0 0 0 0 276 92 0 0 49439
South Orkney (Subarea 48.2) 0 0 0 0 0 0 0 0 0 173765
South Georgia (Subarea 48.3) 0 0 0 0 0 0 6966 2 18 133774
South Sandwich (Subarea 48.4) 0 0 19 0 0 0 0 101 130 0
Weddel Sea (Subarea 48.5) 0 0 0 0 0 0 0 0 0 0
Bouvet (Subarea 48.6) 0 0 40 200 0 0 0 0 0 0
Not specified in which subarea 0 0 0 19139 41352 609 68301 78837 266386 0
Year 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989
Peninsular (Subarea 48.1) 92859 69023 531 32128 11592 42113 70515 78918 105554 42477
South Orkney (Subarea 48.2) 60540 257695 125605 64112 123830 241673 19779 94659 82406 220518
South Georgia (Subarea 48.3) 135252 46868 11480 8440 45385 142084 256206 190492 206354 81369
South Sandwich (Subarea 48.4) 0 0 0 0 0 0 0 0 0 0
Weddel Sea (Subarea 48.5) 0 0 0 0 0 1 0 0 0 0
Bouvet (Subarea 48.6) 217 0 735 0 0 0 5 104 0 0
Not specified in which subarea 0 0 0 0 0 0 0 0 0 0
Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Peninsular (Subarea 48.1) 64641 78385 37716 45085 35025 61964 48843 56575 38897 71977
South Orkney (Subarea 48.2) 167257 123186 12670 19259 48833 2734 99 6673 62077 16891
South Georgia (Subarea 48.3) 123562 101310 30040 18648 33590 26452 26711 26776 985 25557
South Sandwich (Subarea 48.4) 0 0 50 0 0 0 0 0 0 0
Weddel Sea (Subarea 48.5) 0 30 0 0 0 0 0 0 0 0
Bouvet (Subarea 48.6) 0 0 33 0 0 0 0 0 0 0
Not specified in which subarea 0 0 2577 71 0 0 0 74 0 4
Year 2000 2001 2002 2003 2004 2005 2006 2007 2008
Peninsular (Subarea 48.1) 46778 10646 35377 13882 7095 88876 18419 2884 32206
South Orkney (Subarea 48.2) 4981 72059 15426 46456 73494 3103 65591 93384 91742
South Georgia (Subarea 48.3) 52423 43282 66925 57829 48437 14613 20576 60253 1
South Sandwich (Subarea 48.4) 0 0 0 0 0 0 0 0 0
Weddel Sea (Subarea 48.5) 0 0 0 0 0 0 0 0 0
Bouvet (Subarea 48.6) 0 0 0 0 0 0 0 0 0
Not specified in which subarea 0 0 0 0 0 43 0 0 0
Source: CCAMLR (2011)
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APPENDIX 5 – CHANGES IN MEAN DENSITY (N/mˉ²) OF DIFFERENT LANTERN FISH SPECIES IN THE SCOTIA SEA (1991 – 2004)
Year Region Specie Lat Long Density
2004 Scotia Sea Electrona carlsbergi 53 56 S 40 57 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 22 S 38 29 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 22 S 38 28 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 42 S 39 34 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 29 S 39 27 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 31 S 38 14 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 32 S 38 17 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 33 S 37 50 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 38 S 38 18 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 25 S 41 34 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 28 S 40 38 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 29 S 40 10 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 32 S 38 14 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 19 S 37 57 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 42 S 40 38 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 47 S 39 5 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 35 S 42 42 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 47 S 40 13 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 47 S 39 4 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 26 S 42 1 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 26 S 42 4 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 29 S 41 25 W 0,049489881
2004 Scotia Sea Electrona carlsbergi 53 30 S 41 34 W 0,049489881
2004 Scotia Sea Electrona antarctica 53 56 S 40 57 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 22 S 38 29 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 22 S 38 28 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 42 S 39 34 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 29 S 39 27 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 31 S 38 14 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 32 S 38 17 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 33 S 37 50 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 38 S 38 18 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 25 S 41 34 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 28 S 40 38 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 29 S 40 10 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 32 S 38 14 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 19 S 37 57 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 42 S 40 38 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 47 S 39 5 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 35 S 42 42 W 0,02430788
76
2004 Scotia Sea Electrona antarctica 53 47 S 40 13 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 47 S 39 4 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 26 S 42 1 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 26 S 42 4 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 29 S 41 25 W 0,02430788
2004 Scotia Sea Electrona antarctica 53 30 S 41 34 W 0,02430788
2004 Scotia Sea Electrona subaspera 53 42 S 40 38 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 47 S 39 5 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 35 S 42 42 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 47 S 40 13 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 47 S 39 4 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 26 S 42 1 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 26 S 42 4 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 29 S 41 25 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 30 S 41 34 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 56 S 40 57 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 38 S 38 18 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 25 S 41 34 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 28 S 40 38 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 29 S 40 10 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 32 S 38 14 W 1,94507E-05
2004 Scotia Sea Electrona subaspera 53 19 S 37 57 W 1,94507E-05
2004 Scotia Sea Electrona spp. 53 56 S 40 57 W 0,004727775
2004 Scotia Sea Electrona spp. 53 42 S 39 34 W 0,004727775
2004 Scotia Sea Gymnoscopelus bolini 53 56 S 40 57 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 22 S 38 29 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 22 S 38 28 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 42 S 39 34 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 29 S 39 27 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 31 S 38 14 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 32 S 38 17 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 33 S 37 50 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 38 S 38 18 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 25 S 41 34 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 28 S 40 38 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 29 S 40 10 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 32 S 38 14 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 19 S 37 57 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 42 S 40 38 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 47 S 39 5 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 35 S 42 42 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 47 S 39 4 W 0,00059771
2004 Scotia Sea Gymnoscopelus bolini 53 26 S 42 4 W 0,00059771
2004 Scotia Sea Gymnoscopelus fraseri 53 56 S 40 57 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 22 S 38 29 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 22 S 38 28 W 0,024941329
77
2004 Scotia Sea Gymnoscopelus fraseri 53 42 S 39 34 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 29 S 39 27 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 31 S 38 14 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 32 S 38 17 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 33 S 37 50 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 38 S 38 18 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 25 S 41 34 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 28 S 40 38 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 29 S 40 10 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 32 S 38 14 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 19 S 37 57 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 42 S 40 38 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 47 S 39 5 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 35 S 42 42 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 47 S 40 13 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 47 S 39 4 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 26 S 42 1 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 26 S 42 4 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 29 S 41 25 W 0,024941329
2004 Scotia Sea Gymnoscopelus fraseri 53 30 S 41 34 W 0,024941329
2004 Scotia Sea Gymnoscopelus microlampas 53 42 S 40 38 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 47 S 39 5 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 35 S 42 42 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 47 S 39 4 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 38 S 38 18 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 25 S 41 34 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 28 S 40 38 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 29 S 40 10 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 32 S 38 14 W 0,000606923
2004 Scotia Sea Gymnoscopelus microlampas 53 19 S 37 57 W 0,000606923
2004 Scotia Sea Gymnoscopelus nicholsi 53 56 S 40 57 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 22 S 38 29 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 22 S 38 28 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 42 S 39 34 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 29 S 39 27 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 31 S 38 14 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 32 S 38 17 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 33 S 37 50 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 38 S 38 18 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 25 S 41 34 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 28 S 40 38 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 29 S 40 10 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 32 S 38 14 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 19 S 37 57 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 42 S 40 38 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 47 S 39 5 W 0,032404089
78
2004 Scotia Sea Gymnoscopelus nicholsi 53 35 S 42 42 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 47 S 40 13 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 47 S 39 4 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 26 S 42 1 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 26 S 42 4 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 29 S 41 25 W 0,032404089
2004 Scotia Sea Gymnoscopelus nicholsi 53 30 S 41 34 W 0,032404089
2004 Scotia Sea Gymnoscopelus braueri 53 56 S 40 57 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 22 S 38 29 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 22 S 38 28 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 42 S 39 34 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 29 S 39 27 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 31 S 38 14 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 32 S 38 17 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 33 S 37 50 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 38 S 38 18 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 25 S 41 34 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 28 S 40 38 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 29 S 40 10 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 32 S 38 14 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 19 S 37 57 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 42 S 40 38 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 47 S 39 5 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 35 S 42 42 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 47 S 40 13 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 47 S 39 4 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 26 S 42 1 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 26 S 42 4 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 29 S 41 25 W 0,038017524
2004 Scotia Sea Gymnoscopelus braueri 53 30 S 41 34 W 0,038017524
2004 Scotia Sea Gymnoscopelus spp 53 42 S 40 38 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 47 S 39 5 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 35 S 42 42 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 47 S 40 13 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 26 S 42 1 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 29 S 41 25 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 30 S 41 34 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 38 S 38 18 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 25 S 41 34 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 28 S 40 38 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 29 S 40 10 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 32 S 38 14 W 0,000551062
2004 Scotia Sea Gymnoscopelus spp 53 19 S 37 57 W 0,000551062
2004 Scotia Sea Krefftichthys anderssoni 53 56 S 40 57 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 22 S 38 29 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 22 S 38 28 W 0,018279526
79
2004 Scotia Sea Krefftichthys anderssoni 53 42 S 39 34 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 29 S 39 27 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 31 S 38 14 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 32 S 38 17 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 33 S 37 50 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 38 S 38 18 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 25 S 41 34 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 28 S 40 38 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 29 S 40 10 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 32 S 38 14 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 19 S 37 57 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 42 S 40 38 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 47 S 39 5 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 35 S 42 42 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 47 S 40 13 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 47 S 39 4 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 26 S 42 1 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 26 S 42 4 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 29 S 41 25 W 0,018279526
2004 Scotia Sea Krefftichthys anderssoni 53 30 S 41 34 W 0,018279526
2004 Scotia Sea Lampanyctus achirus 53 56 S 40 57 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 22 S 38 29 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 22 S 38 28 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 42 S 39 34 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 29 S 39 27 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 31 S 38 14 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 32 S 38 17 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 33 S 37 50 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 38 S 38 18 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 25 S 41 34 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 28 S 40 38 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 29 S 40 10 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 32 S 38 14 W 0,084161657
2004 Scotia Sea Lampanyctus achirus 53 19 S 37 57 W 0,084161657
2004 Scotia Sea Protomyctophum gemmatum 53 56 S 40 57 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 22 S 38 29 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 22 S 38 28 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 42 S 39 34 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 29 S 39 27 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 31 S 38 14 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 32 S 38 17 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 38 S 38 18 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 25 S 41 34 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 28 S 40 38 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 29 S 40 10 W 0,005755421
2004 Scotia Sea Protomyctophum gemmatum 53 32 S 38 14 W 0,005755421
80
2004 Scotia Sea Protomyctophum gemmatum 53 19 S 37 57 W 0,005755421
2004 Scotia Sea Protomyctophum tenisoni 53 42 S 40 38 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 47 S 39 5 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 35 S 42 42 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 47 S 40 13 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 26 S 42 1 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 29 S 41 25 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 30 S 41 34 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 38 S 38 18 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 25 S 41 34 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 28 S 40 38 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 29 S 40 10 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 32 S 38 14 W 0,000110212
2004 Scotia Sea Protomyctophum tenisoni 53 19 S 37 57 W 0,000110212
2004 Scotia Sea Protomyctophum bolini 53 56 S 40 57 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 22 S 38 29 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 22 S 38 28 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 42 S 39 34 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 29 S 39 27 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 31 S 38 14 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 32 S 38 17 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 33 S 37 50 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 38 S 38 18 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 25 S 41 34 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 28 S 40 38 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 29 S 40 10 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 32 S 38 14 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 19 S 37 57 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 42 S 40 38 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 47 S 39 5 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 35 S 42 42 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 47 S 40 13 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 47 S 39 4 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 26 S 42 1 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 26 S 42 4 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 29 S 41 25 W 0,041323396
2004 Scotia Sea Protomyctophum bolini 53 30 S 41 34 W 0,041323396
2004 Scotia Sea Protomyctophum parallelum 53 56 S 40 57 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 22 S 38 29 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 22 S 38 28 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 42 S 39 34 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 29 S 39 27 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 31 S 38 14 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 32 S 38 17 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 33 S 37 50 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 38 S 38 18 W 0,004430087
81
2004 Scotia Sea Protomyctophum parallelum 53 25 S 41 34 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 28 S 40 38 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 29 S 40 10 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 32 S 38 14 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 19 S 37 57 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 42 S 40 38 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 47 S 39 5 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 35 S 42 42 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 47 S 39 4 W 0,004430087
2004 Scotia Sea Protomyctophum parallelum 53 26 S 42 4 W 0,004430087
2004 Scotia Sea Protomyctophum choriodon 53 56 S 40 57 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 22 S 38 29 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 22 S 38 28 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 42 S 39 34 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 29 S 39 27 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 31 S 38 14 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 32 S 38 17 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 33 S 37 50 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 38 S 38 18 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 25 S 41 34 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 28 S 40 38 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 29 S 40 10 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 32 S 38 14 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 19 S 37 57 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 42 S 40 38 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 47 S 39 5 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 35 S 42 42 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 47 S 40 13 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 47 S 39 4 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 26 S 42 1 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 26 S 42 4 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 29 S 41 25 W 0,02304387
2004 Scotia Sea Protomyctophum choriodon 53 30 S 41 34 W 0,02304387
2004 Scotia Sea Protomyctophum spp 53 56 S 40 57 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 22 S 38 29 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 22 S 38 28 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 42 S 39 34 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 29 S 39 27 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 31 S 38 14 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 32 S 38 17 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 33 S 37 50 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 38 S 38 18 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 25 S 41 34 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 28 S 40 38 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 29 S 40 10 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 32 S 38 14 W 9,72315E-05
82
2004 Scotia Sea Protomyctophum spp 53 19 S 37 57 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 42 S 40 38 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 47 S 39 5 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 35 S 42 42 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 47 S 40 13 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 47 S 39 4 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 26 S 42 1 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 26 S 42 4 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 29 S 41 25 W 9,72315E-05
2004 Scotia Sea Protomyctophum spp 53 30 S 41 34 W 9,72315E-05
2004 Scotia Sea Nemichthys curvirostris 53 56 S 40 57 W 0,012517828
1991 Western Scotia Sea Nansenia antarctica 57 03.8' 08.7' S 55 08.6' 25.9' W 0,024230769
1991 South Georgia Nansenia antarctica 53 22.5' 39.1 S 38 31.9' 55.7' W 0,011538462
1991 Western Scotia Sea Bathylagus antarcticus 57 03.8' 08.7' S 55 08.6' 25.9' W 0,428076923
1991 South Georgia Bathylagus antarcticus 53 22.5' 39.1 S 38 31.9' 55.7' W 0,118461538
1991 Western Scotia Sea Cyclothone spp 53 03.8' 08.7' S 38 08.6' 25.9' W 0,073846154
1991 South Georgia Cyclothone spp 53 22.5' 39.1 S 38 31.9' 55.7' W 0,08125
1991 Western Scotia Sea Borostomias antarcticus 57 03.8' 08.7' S 55 08.6' 25.9' W 0,011538462
1991 South Georgia Borostomias antarcticus 53 22.5' 39.1 S 38 31.9' 55.7' W 0,015865385
1991 Western Scotia Sea Stomias Igracilis 57 03.8' 08.7' S 55 08.6' 25.9' W 0,008653846
1991 South Georgia Stomias Igracilis 53 22.5' 39.1 S 38 31.9' 55.7' W 0,000961538
1991 Western Scotia Sea Benthalbella elongata 53 03.8' 08.7' S 38 08.6' 25.9' W 0,008653846
1991 South Georgia Benthalbella elongata 53 22.5' 39.1 S 38 31.9' 55.7' W 0,012692308
1991 Western Scotia Sea Notolepis coatsi 57 03.8' 08.7' S 55 08.6' 25.9' W 0,01625
1991 South Georgia Notolepis coatsi 53 22.5' 39.1 S 38 31.9' 55.7' W 0,019230769
1991 Western Scotia Sea Electrona antarctica 57 03.8' 08.7' S 55 08.6' 25.9' W 0,203076923
1991 South Georgia Electrona antarctica 53 22.5' 39.1 S 38 31.9' 55.7' W 0,349038462
1991 Western Scotia Sea Electrona carlsbergi 53 03.8' 08.7' S 38 08.6' 25.9' W 0,101538462
1991 South Georgia Electrona carlsbergi 53 22.5' 39.1 S 38 31.9' 55.7' W 0,006057692
1991 Western Scotia Sea Gymnoscopelus bolini 57 03.8' 08.7' S 55 08.6' 25.9' W 0,006153846
1991 South Georgia Gymnoscopelus bolini 53 22.5' 39.1 S 38 31.9' 55.7' W 0,004326923
1991 Western Scotia Sea Gymnoscopelus brauen 57 03.8' 08.7' S 55 08.6' 25.9' W 0,272307692
1991 South Georgia Gymnoscopelus brauen 53 22.5' 39.1 S 38 31.9' 55.7' W 0,394519231
1991 Western Scotia Sea Gymnoscopelus fraseri 53 03.8' 08.7' S 38 08.6' 25.9' W 0,001346154
1991 South Georgia Gymnoscopelus fraseri 53 22.5' 39.1 S 38 31.9' 55.7' W 0,014423077
1991 Western Scotia Sea Gymnoscopelus nicholsi 57 03.8' 08.7' S 55 08.6' 25.9' W 0,001730769
1991 South Georgia Gymnoscopelus nicholsi 53 22.5' 39.1 S 38 31.9' 55.7' W 0,007307692
1991 Western Scotia Sea Krefftichthys anderssoni 53 03.8' 08.7' S 38 08.6' 25.9' W 0,298269231
1991 South Georgia Krefftichthys anderssoni 53 22.5' 39.1 S 38 31.9' 55.7' W 0,458653846
1991 Western Scotia Sea Lampanyctus achirus 57 03.8' 08.7' S 55 08.6' 25.9' W 0,029615385
1991 South Georgia Lampanyctus achirus 53 22.5' 39.1 S 38 31.9' 55.7' W 0,04125
1991 Western Scotia Sea Protomyctophum andnashevi 53 03.8' 08.7' S 38 08.6' 25.9' W 0
1991 South Georgia Protomyctophum andnashevi 53 22.5' 39.1 S 38 31.9' 55.7' W 0,000192308
1991 Western Scotia Sea Protomyctophurn bolini 57 03.8' 08.7' S 55 08.6' 25.9' W 0,178269231
1991 South Georgia Protomyctophurn bolini 53 22.5' 39.1 S 38 31.9' 55.7' W 0,176346154
1991 Western Scotia Sea Protomyctophum choriodon 53 03.8' 08.7' S 38 08.6' 25.9' W 0
83
1991 South Georgia Protomyctophum choriodon 53 22.5' 39.1 S 38 31.9' 55.7' W 0,016923077
1991 Western Scotia Sea Protomyctophum gemmatum 57 03.8' 08.7' S 55 08.6' 25.9' W 0,006730769
1991 South Georgia Protomyctophum gemmatum 53 22.5' 39.1 S 38 31.9' 55.7' W 0
1991 Western Scotia Sea Melanonus gracihs 53 03.8' 08.7' S 38 08.6' 25.9' W 0
1991 South Georgia Melanonus gracihs 53 22.5' 39.1 S 38 31.9' 55.7' W 0,000961538
1991 Western Scotia Sea Nemichthys scolopaceus 57 03.8' 08.7' S 55 08.6' 25.9' W 0,000961538
1991 South Georgia Nemichthys scolopaceus 53 22.5' 39.1 S 38 31.9' 55.7' W 0,002307692
1991 Western Scotia Sea Cyanomacrurus piriei 53 03.8' 08.7' S 38 08.6' 25.9' W 0,006923077
1991 South Georgia Cyanomacrurus piriei 53 22.5' 39.1 S 38 31.9' 55.7' W 0,018846154
1991 Western Scotia Sea Poromitra crassiceps 57 03.8' 08.7' S 55 08.6' 25.9' W 0,02125
1991 South Georgia Poromitra crassiceps 53 22.5' 39.1 S 38 31.9' 55.7' W 0,022884615
1991 Western Scotia Sea Paradiplospinus gracilis 53 03.8' 08.7' S 38 08.6' 25.9' W 0
1991 South Georgia Paradiplospinus gracilis 53 22.5' 39.1 S 38 31.9' 55.7' W 0,008461538 44–50 1996 NW Weddell Sea Electrona antarctica 62–64 S 0.004 W 44–50 1996 NW Weddell Sea Electrona antarctica 62–64 S 0.265 W
Source: Piatkowskil et al (1994), Collins et al (2004) and Flores et al (2008)
84
APPENDIX 6 – CHANGES IN MEAN DENSITY (IND. Mˉ²) OF ANTARCTIC KRILL (1976-2003) IN THE SCOTIA SEA
Year Krill density (no. krill/m2) in the Scotia Sea
1976 146,9499999 1977 N/D 1978 17,62700002 1979 N/D 1980 N/D 1981 29,29304023 1982 78,97 1983 N/D 1984 27,04124668 1985 21,54999998 1986 N/D 1987 19,20000001 1988 34,37654548 1989 11,11062501 1990 6,594000003 1991 N/D 1992 5,039999995 1993 12,80545641 1994 3,434447492 1995 7,745047953 1996 16,4571978 1997 29,96688133 1998 24,52072456 1999 2,216189873 2000 6,470000005 2001 16,94 2002 6,280000004 2003 2,159999999
Source: Atkinson et al (2009)
85
APPENDIX 7 – DEVELOPMENT OF CONSERVATION MEASURES ON KRILL FISHERT IN THE SCOTIA SEA (1980-2010)
Development of conservation measures on the krill fishery in the Scotia Sea (P2)
Conservation Measure N° 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 Still in Still force Closure of waters adjacent to South Georgia 1 n/a n/a n/a n/a A → → → → L L Regulation of fishing around South Georgia 7 n/a n/a n/a n/a n/a n/a A → → → x (statistical subarea 48.3) Catch Reporting System in Statistical Subarea 17 n/a n/a n/a n/a n/a n/a n/a n/a n/a A L 48.3 in the 1989/90 Season Table. The development of conservation measures (CM’s) on Antarctic krill fishery in the Scotia Sea (1980 1990). ´A` means adopted; ´R` means revised, ´L` means lapsed; ´→` means in force and carried to the next year; and ´n/a` means not adopted yet. The last cell marked with ´X` means that the CM is still in force Development of conservation measures on the krill fishery in the Scotia Sea (P3)
Conservation Measure N° force Still in Still 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 Regulation of fishing around South Georgia 7 → → → → → → → → → → x (Subarea 48.3) Catch reporting system in statistical subarea 17 L ------L 48.3 for the 1989/90 season Procedure for according protection to CEMP 18 A → → → R → → → → → x site Catch and Effort System in Statistical Subarea 25 A L ------L 48.3 Net Monitor Cables 30 n/a A → → → → → → → L L Precautionary catch limitations on Euphausia 32 n/a A → → → → → → → → x superba in Subarea 48.3 Monthly catch and effort reporting 40 n/a A → → → → → → → → x Allocation of precautionary catch limit on Euphausia superba in Statistical Area 48 to 46 n/a n/a A → → L - - - - L Statistical Subareas Scientific research exemption provisions 47 n/a n/a A L ------L Limitation of the by-catch in Subarea 48.3 for 50 n/a n/a A L ------L the 1992/93 season Ten-day catch and effort reporting 61 n/a n/a A → → → → → → → x Protection of the Seals Islands CEMP site 62 n/a n/a A → → → → → → → L Regulation of the use and disposal of plastic 63 n/a n/a n/a A → → → → → → L packaging bands Application of measures to research 64 n/a n/a n/a A → → → → → → x Limitation of the by-catch in subarea 48.3 for 68 n/a n/a n/a A L - - - - - L the 1993/94 Season Protection of the Cape Shirreff CEMP site 82 n/a n/a n/a n/a A → → → → → L Limitation of the by-catch in subarea 48.3 for 85 n/a n/a n/a n/a A L - - - - L the 1994/95 season Limitation of the by-catch in subarea 48.3 95 n/a n/a n/a n/a n/a A → → → → x Scheme to promote compliance by non- 118 n/a n/a n/a n/a n/a n/a n/a A R → x Contracting Party vessels Licensing and inspection obligations of 119 n/a n/a n/a n/a n/a n/a n/a A R → x Contracting Parties Marking of fishing vessels and gear 146 n/a n/a n/a n/a n/a n/a n/a n/a A → x Automated satellite-linked vessel monitoring 148 n/a n/a n/a n/a n/a n/a n/a n/a A → x systems (VMS) Minimization of the incidental mortality of seabirds and marine mammals in the course of 173 n/a n/a n/a n/a n/a n/a n/a n/a n/a A x trawl fishing in the Convention Area
86
Development of conservation measures on the krill fishery in the Scotia Sea (P4)
Conservation Measure Old Old N° New New N° 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 Still in Still force
Marking of fishing vessels and gear 10.01 146 → → → → → → → → → → x
Licensing and inspection obligations of 10.02 119 → R → → R → R R R → x Contracting Parties
Automated satellite-linked vessel monitoring 10.04 148 → R R → R R R R R → x systems (VMS)
Scheme to promote compliance by 10.06 - n/a n/a A → R R R → R → x Contracting Party vessels
Scheme to promote compliance by non- 10.07 CM118 → R R R → R R → R R x Contracting Party vessels
Scheme to promote compliance by 10.08 - n/a n/a n/a n/a n/a n/a A → → R x Contracting Part nationals
Notifications of intent to participate in a 21.03 - n/a n/a n/a n/a n/a n/a A R R R x fishery for Euphausia superb
Ten-day catch and effort reporting 23.02 61 → → → → → → → → → → x
Monthly catch and effort reporting 23.03 40 → → → → → → → → → → x
Data reporting for krill fisheries 23.06 - n/a n/a A → R R → R → R x Application of measures to research 24.01 64 R → R R → R → → R R x
Regulation of the use and disposal of plastic 25.01 63 → → → → → → L - - - L packaging bands
Minimization of the incidental mortality of seabirds and marine mammals in the course 25.03 173 → → → R → → → → → R x of trawling
General environmental protection during 26.01 - n/a n/a n/a n/a n/a n/a A → R R x fishing
Regulation of fishing around South Georgia 31.01 7 → → → → → → → → → → x (Subarea 48.3)
General measure for the closure of all 31.02 - n/a n/a n/a n/a n/a n/a n/a A → → x fisheries
Fishing seasons 32.01 217 n/a A → → → → → → → → x
Limitation of the by-catch in Subarea 48.3 33.01 95 → → → → → → → → → → x
Precautionary catch limitations on Euphausia 51.01 32 R → R → → → R R R → x superba in Subareas 48.1, 48.2, 48.3 and 48.4
General measure for exploratory fisheries for 51.04 - n/a n/a n/a n/a n/a n/a n/a n/a A R x Euphausia superba
General measure for scientific observation in 51.06 - n/a n/a n/a n/a n/a n/a n/a n/a n/a A x fisheries for Euphausia superba
Distribution of the trigger limit in the fishery for Euphausia superba in Subareas 48.1, 48.2, 51.07 - n/a n/a n/a n/a n/a n/a n/a n/a n/a A x 48.3, 48.4 Procedure for according protection to CEMP 91.01 18 R → → → R → → → → → x site
Protection of the Cape Sherriff CEMP site 91.02 82 R → → → R → → → → L L
Protection of the Seals Islands CEMP site N/D 62 R → → → R → → L - - L
Protection of the South Orkney Islands 91.03 - n/a n/a n/a n/a n/a n/a n/a n/a n/a A x southern shelf
87
APPENDIX 8 – GLOBAL AQUACULTURE PRODUCTION IN COMPARISION WITH WORLD CAPTURE FISHERY AND AQUACULTURE PRODUCTION IN ASIA AND CHINA
Mtons 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980
Global fish capture production 62,8 62,8 58,6 59,2 62,4 61,9 65,3 63,9 66,0 66,5 67,2
Global aquaculture production 2,6 2,7 3,0 3,1 3,3 3,6 3,7 4,1 4,2 4,3 4,7
Aquaculture production in China 0,8 0,9 0,9 0,9 1,0 1,0 1,0 1,2 1,2 1,2 1,3 Aquaculture production in Asian countries 1,0 1,1 1,2 1,3 1,4 1,5 1,7 1,8 1,9 2,0 2,2 excluding China
Mtons 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
Global fish capture production 69,4 71,1 71,1 76,7 78,3 83,8 84,4 87,8 88,3 84,7 83,7
Global aquaculture production 5,2 5,7 6,2 6,9 8,0 9,2 10,6 11,7 12,3 13,1 13,7
Aquaculture production in China 1,5 1,7 2,0 2,4 3,2 4,0 4,9 5,6 6,0 6,5 6,9 Aquaculture production in Asian countries 2,4 2,5 2,7 2,8 3,1 3,3 3,7 4,0 4,1 4,3 4,6 excluding China
Mtons 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Global fish capture production 85,2 86,6 92,1 92,4 93,8 93,1 85,7 91,5 93,6 90,8 91,0
Global aquaculture production 15,4 17,8 20,8 24,4 26,6 27,3 28,4 30,7 32,4 34,6 36,8
Aquaculture production in China 8,3 10,4 13,0 15,9 17,7 18,0 18,7 20,1 21,5 22,7 24,1 Aquaculture production in Asian countries 4,9 5,2 5,4 5,8 6,0 6,1 6,2 6,8 6,9 7,6 8,2 excluding China
Mtons 2003 2004 2005 2006 2007 2008 Global fish capture production 88,3 92,5 92,2 89,9 90,1 89,6 Global aquaculture production 38,9 41,9 44,3 47,3 49,9 53,0 Aquaculture production in China 25,1 26,6 28,1 29,9 31,4 32,7 Aquaculture production in Asian countries 9,1 10,3 11,1 12,0 12,8 14,3 excluding China
Source: FAO/FIGIS (2011)
88
APPENDIX 9 – GLOBAL FISH MEAL/OIL MARKET
Fish meal use Fish oil use Fish meal production Fish oil production Fish meal price (US$) Fish oil price (US$) (Mtons) (Mtons) (Mtons) (Mtons) 1970 N/D N/D N/D N/D N/D N/D
1971 N/D N/D N/D N/D N/D N/D
1972 N/D N/D N/D N/D N/D N/D
1973 N/D N/D N/D N/D N/D N/D
1974 N/D N/D N/D N/D N/D N/D
1975 N/D N/D N/D N/D N/D N/D
1976 N/D N/D 4,707511 0,972237 N/D N/D
1977 N/D N/D 4,329839 1,008513 N/D N/D
1978 N/D N/D 4,647403 1,119745 N/D N/D
1979 N/D N/D 4,852039 1,170479 N/D N/D
1980 N/D N/D 4,726992 1,216325 N/D N/D
1981 N/D N/D 4,827013 1,16313 944,36 N/D
1982 N/D N/D 5,120558 1,294866 673,11 N/D
1983 N/D N/D 5,016643 1,13475 870,02 N/D
1984 N/D N/D 5,836035 1,513379 685,16 320
1985 N/D N/D 6,024313 1,480905 510,36 276
1986 N/D N/D 6,497619 1,673755 595,95 150
1987 N/D N/D 6,268598 1,45419 635,54 196
1988 N/D N/D 6,626697 1,558825 673,44 445
1989 N/D N/D 6,673484 1,635145 642,39 196
1990 N/D N/D 6,156286 1,411752 715,45 244
1991 N/D N/D 6,308449 1,376175 501,56 271
1992 N/D N/D 6,137021 1,068785 533,75 367
1993 N/D N/D 6,394604 1,215971 375,25 371
1994 N/D N/D 7,342816 1,503944 401,81 283
1995 1,882 0,474 6,746042 1,38162 539,09 448
1996 2,093 0,535 6,820498 1,381548 577,42 395
1997 2,326 0,575 6,414797 1,16938 627,37 532
1998 2,535 0,589 5,322931 0,856211 706,68 771
1999 2,708 0,622 6,477574 1,392834 393,63 288
2000 2,922 0,631 6,887004 1,325083 471,25 253
2001 3,126 0,718 6,20565 1,098454 525,21 461
2002 3,324 0,695 6,185033 0,851766 652,11 574
2003 3,845 0,768 5,490422 0,946669 668,62 580
2004 4,06 0,809 6,514311 1,063017 666,62 695
2005 4,3 0,843 6,263376 0,920699 656,46 705
2006 3,724 0,835 5,403625 0,955665 959,07 820
2007 3,641 0,778 5,647309 1,067391 1212,95 905
2008 N/D N/D 6,177295 1,060472 1265,05 1815
2009 N/D N/D N/D N/D 1222,51 800
2010 N/D N/D N/D N/D 1705,03 846
2011 N/D N/D N/D N/D 1590,95 1380
89
Largest producers (tons) of fish meal (1976-2008)
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
China 0 0 0 0 0 0 0 50000 53000 54500 51200 56800 Peru 886372 496954 669658 687953 458125 478277 665499 251738 568363 717104 973114 821417 Chile 251745 255107 374991 512597 571857 688318 795768 827743 1022727 1111623 1282357 1081138 Thailand 119880 141600 218165 186437 194200 201701 211814 204811 222558 220358 213005 228660
Denmark 328212 306968 272536 329085 351278 330099 317428 335539 342208 302584 300248 283747
Japan 744030 759396 803140 810258 781990 804742 888001 1040182 1145464 1059089 1103015 1042486
Iceland 110531 162667 202165 207860 172088 148436 51062 68077 171695 174765 178495 159297
Norway 464000 464800 331524 327940 297700 299500 284301 346858 286589 238266 194135 183100
Russian 0 0 0 0 0 0 0 0 0 0 0 0 Federation Un. Sov. Soc. 645430 591610 503359 510659 555130 554400 600180 605200 673530 657280 746450 766340 Rep. World 4 707 511 4 329 839 4 647 403 4 852 039 4 726 992 4 827 013 5 120 558 5 016 643 5 836 035 6 024 313 6 497 619 6 268 598
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
China 58700 90000 110000 100000 100000 142000 184803 260995 359481 533761 692555 601910
Peru 1126242 1169193 1204210 1311634 1441787 1788816 2417217 1789228 1924953 1597134 832093 1769532
Chile 1112229 1381161 1073207 1229758 1269588 1191785 1551670 1554321 1401138 1227391 646718 1004868
Thailand 237156 268524 287408 282808 351111 358199 381361 371085 381903 386083 410360 398530
Denmark 362736 340751 271679 363445 358514 341583 402192 446686 397872 395255 404952 375906
Japan 991121 954475 884759 753559 581602 543641 478312 373688 363453 363444 392884 465513
Iceland 192065 143641 150081 82685 173560 194838 177634 176067 231080 223825 226403 242068
Norway 183560 199690 167030 209431 259255 295213 201455 236667 242996 253402 299396 240808 Russian 0 0 0 0 261700 226930 179180 191600 206800 194260 163422 154640 Federation Un. Sov. Soc. 769030 751599 694864 631964 0 0 0 0 0 0 0 0 Rep. World 6 626 697 6 673 484 6 156 286 6 308 449 6 137 021 6 394 604 7 342 816 6 746 042 6 820 498 6 414 797 5 322 931 6 477 574
2000 2001 2002 2003 2004 2005 2006 2007 2008
China 721815 723198 502000 585088 658359 720190 677568 1054184 1479961
Peru 2241529 1635427 1839209 1224484 1971449 1930727 1342391 1399047 1414728
Chile 880744 779621 845140 706531 1015957 866121 710142 703081 642872
Thailand 387016 451899 474789 598530 541200 473270 461266 428000 468000
Denmark 280945 407690 385251 258128 302484 320228 286563 175427 236625
Japan 452008 298567 290258 295167 230625 221939 219615 202059 204182
Iceland 253249 258600 301458 225159 254894 196796 124528 127854 148215
Norway 264100 216000 241000 212100 215100 154300 169500 171500 130500 Russian 127460 98876 64672 73552 57212 58337 66502 69373 75259 Federation Un. Sov. Soc. 0 0 0 0 0 0 0 0 0 Rep. World 6 887 004 6 205 650 6 185 033 5 490 422 6 514 311 6 263 376 5 403 625 5 647 309 6 177 295
90
Largest importers of fish meal (1976-2008)
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
China 0 0 0 0 0 0 0 0 108226 191262 201447 220680
Japan 59543 181143 84923 101645 141008 84068 44275 95071 61618 80256 161488 187298
Norway 12 76 12 20 126 5 38 94 142 2543 5081 46
Vietnam 0 0 . 0 0 0 0 0 0 0 0 0 0
Denmark 7691 10698 6351 6987 6630 8450 7345 7976 16932 16805 20639 9776
United Kingdom 253634 213589 191520 255129 214559 173208 213088 162254 173349 236237 236121 248548
Spain 3819 9223 6130 11285 1482 3168 2426 8134 11962 14181 9064 17516
Russian Federation 0 0 0 0 0 0 0 0 0 0 0 0
Chile 0 0 0 0 0 0 0 0 0 0 0 0
Korea, Republic of 0 3296 6116 17548 100 2255 1632 9966 4270 4394 7102 17968
Thailand 200 7 639 11 466 62 5 0 17 5 148 93
World 1 962 096 2 036 027 1 947 495 2 299 930 2 179 739 1 996 310 2 424 101 2 236 713 2 490 522 3 066 599 3 192 821 3 154 847
Tons 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
China 456835 472310 223904 634291 639546 434198 668792 693321 884479 988455 420035 634298
Japan 231506 171445 232045 288377 337054 305114 383461 593889 412245 437298 329627 346329
Norway 14023 38012 21592 40512 51905 43218 60753 121288 105462 128447 99753 144688
Viet Nam 0 0 0 0 0 1600 3300 5625 5216 6652 898 10961
Denmark 7846 12247 25873 11185 44378 70437 56345 80792 107239 86685 94878 139768
United Kingdom 265505 265070 273973 258100 242073 251820 248370 236770 241282 284662 238302 220896
Spain 31774 18611 19729 28071 29163 52037 77966 60569 62161 93081 61 045 90105
Russian Federation 0 0 0 0 6251 443 37489 60499 22999 50598 211 117185
Chile 0 0 0 0 2 160 8 31 285 529 755 226
Korea, Republic of 24059 28788 35399 40673 27828 30934 38860 44234 46112 42494 24 804 29411
Thailand 2969 15651 26247 53119 66911 142103 206375 194875 185995 80844 34687 114123
World 3 307 919 3 557 039 3 326 876 3 332 234 3 430 741 3 922 655 4 913 737 4 566 347 4 203 340 4 356 947 2 857 160 3 545 966
Tons 2000 2001 2002 2003 2004 2005 2006 2007 2008
China 1189252 904130 960524 802842 1127883 1582747 983211 969832 1351354 Japan 338140 462309 480015 384359 402217 376412 412429 350594 309607 Norway 185032 143204 128268 149762 161717 202318 210738 222932 242336 Viet Nam 1040 31255 24688 54226 58059 94142 112542 113293 125764 Denmark 131057 125846 135297 164966 131326 133687 126694 117819 108957 United Kingdom 240840 234692 191992 183442 142492 138154 139406 87670 93268 Spain 119990 107365 86776 92578 101225 80730 60495 68051 82975
Russian Federation 75414 130109 101031 112879 84456 102065 57219 59706 72315
Chile 40 5550 8813 10195 49034 12538 53292 38917 48119
Korea, Republic of 47154 55238 38951 39219 44741 48060 48277 43302 36951
Thailand 126582 121441 41290 19574 20468 21383 23282 13321 12968
World 4 445 495 4 187 362 3 794 551 3 495 289 3 783 656 4 304 483 3 704 468 3 314 253 3 668 44
91
Largest fish oil producers (tons) (1976-2008)
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Peru 108811 109420 131637 129810 79347 76994 187416 16581 143160 121052 251843 109086
Chile 34969 57780 75706 108922 111000 127270 144979 56984 184034 184092 224931 172159
China 0 0 0 0 0 0 0 0 0 0 6141 11187
Denmark 97126 96761 79089 83915 124269 115667 100840 91350 84906 86770 90638 89390
USA 92797 60411 134395 121541 141754 83599 157631 181137 169103 129310 152773 135397
Japan 165617 208230 243532 253420 263057 279106 313124 349897 417240 403631 482883 458601
Iceland 34727 75544 98988 94448 89960 84929 14640 26704 90146 119020 105835 82154
Norway 242915 226354 173506 199766 187027 172800 178199 217200 189774 152158 98994 78438 Un. Sov. Soc. 35810 34940 31349 32269 42359 49281 66457 73318 92712 85010 94820 111300 Rep. World 972237 1008513 1119745 1170479 1216325 1163130 1294866 1134750 1513379 1480905 1673755 1454190
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Peru 203273 318304 191726 181886 161376 250135 486296 373928 422548 330042 122956 514818
Chile 187981 260078 188270 241211 152990 191177 289510 326102 291802 205971 106693 201376
China 13798 14000 10695 10000 10000 10000 9024 10142 10673 8417 7034 35701
Denmark 92099 78493 84167 130143 137101 104524 143612 184051 141949 131087 136143 129267
USA 101938 102276 136588 123956 83791 137944 132397 109744 112673 128540 101220 129811
Japan 485802 448835 418063 315480 146044 106719 70502 47320 13312 10851 57901 68517
Iceland 94442 53745 75401 34668 85216 116450 85481 85218 138789 131573 89934 87734
Norway 91710 77260 51795 90670 118060 130132 118057 86162 92322 87995 101808 99866 Un. Sov. Soc. 112450 118820 127112 120403 0 0 0 0 0 0 0 0 Rep. World 1558825 1635145 1411752 1376175 1068785 1215971 1503944 1381620 1381548 1169380 856211 1392834
2000 2001 2002 2003 2004 2005 2006 2007 2008
Peru 587312 302875 188949 206154 349821 290422 279802 309824 293025
Chile 180199 141050 128453 130222 195263 168923 180214 180096 193339
China 15790 18434 23454 18873 23102 30000 50000 72500 92345
Denmark 102301 123648 102576 117784 100027 82303 107102 119858 88990
USA 87249 126743 95648 88769 81376 71523 64749 69040 86194
Japan 59790 63000 64200 66956 68210 62741 69107 60082 62700
Iceland 78533 101109 66297 129888 66255 48899 37955 61467 53837
Norway 85717 69057 64509 55596 39455 33428 42340 46917 39608 Un. Sov. Soc. 0 0 . 0 0 0 0 0 0 0 Rep. World 1325083 1098454 851766 946669 1063017 920699 955665 1067391 1060472
92
Largest fish oil importers (1976-2008)
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Norway 11372 9561 17758 28732 38203 15022 16937 5732 27151 51871 79216 48904
Denmark 2861 2390 3071 3240 2184 1121 1662 836 2695 2791 2333 22171
Chile 6 2 7 30 8 7 120 0 0 0 0 - 0
China 0 0 0 . 0 . 0 . 0 0 . 0 . 0 . 0 . 0 . 968 United 211998 185435 217228 214783 238646 221613 248787 197267 230668 264919 169685 204029 Kingdom Germany 132654 141552 137130 177627 172254 176569 189623 160709 242583 278104 192753 148075
World 609919 568092 652499 762098 751585 731454 795218 723174 942899 1081068 813609 820523
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Norway 102584 109570 75307 74873 72126 112994 138812 174551 175739 201675 157126 219570
Denmark 23388 20909 21471 16529 19317 34741 23244 14615 14092 40765 25522 22764
Chile 0 0 0 0 6515 5078 1416 1572 15463 11356 12038 60302
China 1114 1030 752 1399 2045 3501 2805 6870 10724 1761 5133 2737 United 163831 177875 161818 140192 121331 131066 138393 128463 79576 71254 49458 46823 Kingdom Germany 137436 194094 108190 111566 68205 72025 89800 87609 66432 42000 11774 12335
World 798800 907025 802382 730901 599002 683049 903999 1E+06 871617 812302 485994 742798
2000 2001 2002 2003 2004 2005 2006 2007 2008
Norway 234822 246064 183531 199956 199526 214464 188803 231301 200465
Denmark 29644 30772 27266 47829 65508 94557 128197 158388 103812
Chile 94625 66613 32315 91739 87626 62586 75232 91596 80896
China 25826 3862 3918 9542 16740 15472 30258 30805 38798 United 45964 60448 35896 48124 56492 31175 19507 22681 27046 Kingdom Germany 14312 13239 13757 10316 8127 6711 6520 6724 7900
World 865768 823787 600538 695693 755776 781653 776617 906493 842532
Source: Tacon et al (2008) and FAO/FIGIS (2011)
93
APPENDIX 10 – PRODUCTION, IMPORT AND USING RATE (tons) OF LEADING FISH MEAL CONSUMING COUNTRIES (1976-2008)
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 0 0 0 0 0 0 0 0 108226 191262 201447
Production 0 0 0 0 0 0 0 50000 53000 54500 51200
China Prod+Imp. 0 0 0 0 0 0 0 50000 161226 245762 252647
Export 0 0 0 0 0 0 0 0 0 0 0
Total Use 0 0 0 0 0 0 0 50000 161226 245762 252647
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 59543 181143 84923 101645 141008 84068 44275 95071 61618 80256 161488
Production 744030 759396 803140 810258 781990 804742 888001 1040182 1145464 1059089 1103015
Japan Prod+Imp. 803573 940539 888063 911903 922998 888810 932276 1135253 1207082 1139345 1264503
Export 48975 37466 64269 57695 43254 73653 135658 79649 135333 157438 167192
Total Use 754598 903073 823794 854208 879744 815157 796618 1055604 1071749 981907 1097311
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 12 76 12 20 126 5 38 94 142 2543 5081
Production 464000 464800 331524 327940 297700 299500 284301 346858 286589 238266 194135
Norway Prod+Imp. 464012 464876 331536 327960 297826 299505 284339 346952 286731 240809 199216
Export 415523 461557 283741 326642 274674 266311 228443 283720 248436 173699 92300
Total Use 48489 3319 47795 1318 23152 33194 55896 63232 38295 67110 106916
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 0 0 . 0 0 0 0 0 0 0 0 0
Production 0 . 0 . 0 . 0 . 0 . 5997 4285 4823 5344 4877 5358
Vietnam Prod+Imp. 0 0 0 0 0 5997 4285 4823 5344 4877 5358
Export 0 . 0 . 0 . 0 . 0 . 0 0 . 0 . 0 . 73 56 Total Use 0 0 0 0 0 5997 4285 4823 5344 4804 5302
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 253634 213589 191520 255129 214559 173208 213088 162254 173349 236237 236121
Production 81000 78000 66000 58600 68300 59735 56437 54200 55000 53000 46970 United Prod+Imp. 334634 291589 257520 313729 282859 232943 269525 216454 228349 289237 283091 Kingdom Export 7608 10374 8799 6454 8155 3328 1953 3357 2234 3076 6041
Total Use 327026 281215 248721 307275 274704 229615 267572 213097 226115 286161 277050
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 7691 10698 6351 6987 6630 8450 7345 7976 16932 16805 20639
Production 328212 306968 272536 329085 351278 330099 317428 335539 342208 302584 300248 Denmark Prod+Imp. 335903 317666 278887 336072 357908 338549 324773 343515 359140 319389 320887 Export 284562 263824 246598 258452 294682 267396 253815 269112 261770 217794 224661
Total Use 51341 53842 32289 77620 63226 71153 70958 74403 97370 101595 96226
94
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 7000 14727 0 - 0 - 0 - 0 - 0 - 0 - 60000 82902 88778
Production 645430 591610 503359 510659 555130 554400 600180 605200 673530 657280 746450 Un. Sov. Prod+Imp. 652430 606337 503359 510659 555130 554400 600180 605200 733530 740182 835228 Soc. Rep. Export 18000 13615 21465 20283 22469 11877 8900 11386 7614 10445 11794
Total Use 634430 592722 481894 490376 532661 542523 591280 593814 725916 729737 823434
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 0 3296 6116 17548 100 2255 1632 9966 4270 4394 7102
Production 13395 13560 21822 17715 9616 15221 24860 33035 28228 61913 83640 Korea, Prod+Imp. 13395 13560 21822 17715 9616 15221 24860 33035 28228 61913 83640 Republic of Export 10440 5055 1692 679 2414 784 791 2687 3327 2010 2842
Total Use 2955 8505 20130 17036 7202 14437 24069 30348 24901 59903 80798
Tons 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Import 200 7 639 11 466 62 5 0 17 5 148
Production 119880 141600 218165 186437 194200 201701 211814 204811 222558 220358 213005
Thailand Prod+Imp. 120080 141607 218804 186448 194666 201763 211819 204811 222575 220363 213153
Export 49083 78841 109828 138724 126528 134110 103854 128007 129313 128464 141833
Total Use 70997 62766 108976 47724 68138 67653 107965 76804 93262 91899 71320
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 220680 456835 472310 223904 634291 639546 434198 668792 693321 884479 988455
Production 56800 58700 90000 110000 100000 100000 142000 184803 260995 359481 533761
China Prod+Imp. 277480 515535 562310 333904 734291 739546 576198 853595 954316 1243960 1522216
Export 432 801 1046 2233 2327 1077 491 378 5519 1494 2401
Total Use 277048 514734 561264 331671 731964 738469 575707 853217 948797 1242466 1519815
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 187298 231506 171445 232045 288377 337054 305114 383461 593889 412245 437298
Production 1042486 991121 954475 884759 753559 581602 543641 478312 373688 363453 363444
Japan Prod+Imp. 1229784 1222627 1125920 1116804 1041936 918656 848755 861773 967577 775698 800742 Export 216593 212645 22859 147471 113444 44441 40614 20696 18605 16221 8165 Total Use 1013191 1009982 1103061 969333 928492 874215 808141 841077 948972 759477 792577
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 46 14023 38012 21592 40512 51905 43218 60753 121288 105462 128447
Production 183100 183560 199690 167030 209431 259255 295213 201455 236667 242996 253402
Norway Prod+Imp. 183146 197583 237702 188622 249943 311160 338431 262208 357955 348458 381849
Export 87997 68916 45120 45345 110520 139687 139218 71380 65649 86696 63614
Total Use 95149 128667 192582 143277 139423 171473 199213 190828 292306 261762 318235
95
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 0 0 0 0 0 0 1600 3300 5625 5216 6652
Production 6577 10134 2430 1856 16570 25470 25500 26000 24840 24902 25000
Vietnam Prod+Imp. 6577 10134 2430 1856 16570 25470 27100 29300 30465 30118 31652 Export 220 42 60 330 134 357 0 . 0 . 1160 1098 4700 Total Use 6357 10092 2370 1526 16436 25113 27100 29300 29305 29020 26952
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 248548 265505 265070 273973 258100 242073 251820 248370 236770 241282 284662
Production 51000 50000 49000 50600 50200 47700 52386 47661 49562 54565 51005 United Prod+Imp. 299548 315505 314070 324573 308300 289773 304206 296031 286332 295847 335667 Kingdom Export 6848 3901 5128 4630 3569 5686 8876 18631 24632 17337 20572
Total Use 292700 311604 308942 319943 304731 284087 295330 277400 261700 278510 315095
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 9776 7846 12247 25873 11185 44378 70437 56345 80792 107239 86685
Production 283747 362736 340751 271679 363445 358514 341583 402192 446686 397872 395255
Denmark Prod+Imp. 293523 370582 352998 297552 374630 402892 412020 458537 527478 505111 481940
Export 200443 252373 232508 169859 246990 268791 267718 285360 347914 331607 286382
Total Use 93080 118209 120490 127693 127640 134101 144302 173177 179564 173504 195558
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 10000 51500 17850 31 655 0 0 0 0 0 0
Production 766340 769030 751599 694864 631964 0 0 0 0 0 0 Un. Sov. Prod+Imp. 776340 820530 769449 694895 632619 0 0 0 0 0 0 Soc. Rep. Export 12161 11368 11348 8041 4191 0 0 0 0 0 0
Total Use 764179 809162 758101 686854 628428 0 0 0 0 0 0
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 17968 24059 28788 35399 40673 27828 30934 38860 44234 46112 42494
Production 76836 72195 36058 87375 59568 61560 50423 47225 57391 46191 38183 Korea, Prod+Imp. 76836 72195 36058 87375 59568 61560 50423 47225 57391 46191 38183 Republic of Export 5002 4883 3402 4996 22606 11401 14475 16033 21979 24211 23505
Total Use 71834 67312 32656 82379 36962 50159 35948 31192 35412 21980 14678
Tons 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Import 93 2969 15651 26247 53119 66911 142103 206375 194875 185995 80844
Production 228660 237156 268524 287408 282808 351111 358199 381361 371085 381903 386083 Thailand Prod+Imp. 228753 240125 284175 313655 335927 418022 500302 587736 565960 567898 466927 Export 154620 72314 38085 15417 11035 3990 4936 3039 2153 1504 1823
Total Use 74133 167811 246090 298238 324892 414032 495366 584697 563807 566394 465104
96
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 420035 634298 1189252 904130 960524 802842 1127883 1582747 983211 969832 1351354
Production 692555 601910 721815 723198 502000 585088 658359 720190 677568 1054184 1479961
China Prod+Imp. 1112590 1236208 1911067 1627328 1462524 1387930 1786242 2302937 1660779 2024016 2831315
Export 2288 1898 2712 4121 8326 8560 7037 5927 17973 12298 5407
Total Use 1110302 1234310 1908355 1623207 1454198 1379370 1779205 2297010 1642806 2011718 2825908
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 329627 346329 338140 462309 480015 384359 402217 376412 412429 350594 309607
Production 392884 465513 452008 298567 290258 295167 230625 221939 219615 202059 204182
Japan Prod+Imp. 722511 811842 790148 760876 770273 679526 632842 598351 632044 552653 513789
Export 9647 10848 14881 14377 17735 18485 18634 16552 13590 13562 6268
Total Use 712864 800994 775267 746499 752538 661041 614208 581799 618454 539091 507521
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 99753 144688 185032 143204 128268 149762 161717 202318 210738 222932 242336
Production 299396 240808 264100 216000 241000 212100 215100 154300 169500 171500 130500
Norway Prod+Imp. 399149 385496 449132 359204 369268 361862 376817 356618 380238 394432 372836
Export 153982 153157 87530 85260 123009 73431 67497 52529 42077 41769 26258
Total Use 245167 232339 361602 273944 246259 288431 309320 304089 338161 352663 346578
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Import 898 10961 1040 31255 24688 54226 58059 94142 112542 113293 125764
Production 25400 25500 25400 27900 31200 32200 33000 36400 46700 51300 46500
Vietnam Prod+Imp. 26298 36461 26440 59155 55888 86426 91059 130542 159242 164593 172264
Export 6500 4000 7200 5692 11430 6361 58059 8724 28344 19935 16510
Total Use 19798 32461 19240 53463 44458 80065 33000 121818 130898 144658 155754
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Import 238302 220896 240840 234692 191992 183442 142492 138154 139406 87670 93268
Production 51858 53432 50000 47000 47700 51700 51000 53000 53300 56200 55700 United Prod+Imp. 290160 274328 290840 281692 239692 235142 193492 191154 192706 143870 148968 Kingdom Export 19474 17920 15984 13761 10304 6222 4409 8556 8941 4302 12275
Total Use 270686 256408 274856 267931 229388 228920 189083 182598 183765 139568 136693
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Import 94878 139768 131057 125846 135297 164966 131326 133687 126694 117819 108957
Production 404952 375906 280945 407690 385251 258128 302484 320228 286563 175427 236625
Denmark Prod+Imp. 499830 515674 412002 533536 520548 423094 433810 453915 413257 293246 345582
Export 302795 319756 301966 305836 301191 202631 245854 243366 232298 144717 200827
Total Use 197035 195918 110036 227700 219357 220463 187956 210549 180959 148529 144755
97
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 0 0 0 0 0 0 0 0 0 0 0
Production 0 0 0 0 0 0 0 0 0 0 0 Un. Sov. Soc. Rep. Prod+Imp. 0 0 0 0 0 0 0 0 0 0 0 Export 0 0 0 0 0 0 0 0 0 0 0
Total Use 0 0 0 0 0 0 0 0 0 0 0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 24 804 29411 47154 55238 38951 39219 44741 48060 48277 43302 36951
Production 48059 43200 34453 33279 10142 11722 8566 10040 5795 3860 7140
Korea, Prod+Imp. 48059 43200 34453 33279 10142 11722 8566 10040 5795 3860 7140 Republic of Export 24636 29464 30369 29003 24768 35702 24102 30980 31726 35348 30307
Total Use 23423 13736 4084 4276 -14626 -23980 -15536 -20940 -25931 -31488 -23167
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Import 34687 114123 126582 121441 41290 19574 20468 21383 23282 13321 12968
Production 410360 398530 387016 451899 474789 598530 541200 473270 461266 428000 468000
Thailand Prod+Imp. 445047 512653 513598 573340 516079 618104 561668 494653 484548 441321 480968
Export 25959 5359 9886 7064 19922 11423 20141 31334 76739 93871 21700
Total Use 419088 507294 503712 566276 496157 606681 541527 463319 407809 347450 459268
Source: FAO/FIGIS (2011)
98
APPENDIX 11 – PRODUCTION, IMPORT AND USING RATE OF LEADING FISH OIL CONSUMING COUNTRIES (1976-2008)
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 11372 9561 17758 28732 38203 15022 16937 5732 27151 51871 79216 48904
Production 242915 226354 173506 199766 187027 172800 178199 217200 189774 152158 98994 78438
Norway Prod+Imp. 254287 235915 191264 228498 225230 187822 195136 222932 216925 204029 178210 127342
Export 151385 142561 83523 93975 93197 118564 111504 137276 85953 122959 44822 77721
Total Use 102902 93354 107741 134523 132033 69258 83632 85656 130972 81070 133388 49621
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 2861 2390 3071 3240 2184 1121 1662 836 2695 2791 2333 22171
Production 97126 96761 79089 83915 124269 115667 100840 91350 84906 86770 90638 89390
Denmark Prod+Imp. 99987 99151 82160 87155 126453 116788 102502 92186 87601 89561 92971 111561
Export 85677 74487 66090 65116 104864 88862 69825 68258 64155 61061 62441 39645
Total Use 14310 24664 16070 22039 21589 27926 32677 23928 23446 28500 30530 71916
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 6 2 7 30 8 7 120 0 0 0 0 - 0
Production 34969 57780 75706 108922 111000 127270 144979 56984 184034 184092 224931 172159
Chile Prod+Imp. 34975 57782 75713 108952 111008 127277 145099 56984 184034 184092 224931 172159 Export 20234 26017 55897 51787 87880 71604 89232 18575 94748 135026 114022 91592 Total Use 14741 31765 19816 57165 23128 55673 55867 38409 89286 49066 110909 80567
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 0 0 0 0 0 0 0 0 0 0 0 968
Production 0 0 0 0 0 0 0 0 0 0 6141 11187 China Prod+Imp. 0 0 0 0 0 0 0 0 0 0 6141 12155 Export 0 0 0 0 0 0 0 0 0 0 0 5 Total Use 0 0 0 0 0 0 0 0 0 0 6141 12150
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 211998 185435 217228 214783 238646 221613 248787 197267 230668 264919 169685 204029
Production 16000 16000 15000 10000 14000 12065 10407 7455 9000 8900 6500 6900 United Kingdom Prod+Imp. 227998 201435 232228 224783 252646 233678 259194 204722 239668 273819 176185 210929 Export 6736 6287 5826 2725 1662 1203 4249 1819 1130 4082 5297 4845
Total Use 221262 195148 226402 222058 250984 232475 254945 202903 238538 269737 170888 206084
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Import 132654 141552 137130 177627 172254 176569 189623 160709 242583 278104 192753 148075 Production 11034 10901 10593 9697 9739 11194 10479 10173 10327 9945 8314 8124
Germany Prod+Imp. 143688 152453 147723 187324 181993 187763 200102 170882 252910 288049 201067 156199 Export 6965 4918 7113 4036 4214 4738 5060 11824 11551 19274 13543 9003
Total Use 136723 147535 140610 183288 177779 183025 195042 159058 241359 268775 187524 147196
99
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 102584 109570 75307 74873 72126 112994 138812 174551 175739 201675 157126 219570
Production 91710 77 260 51 795 90670 118060 130132 118057 86162 92322 87995 101808 99866
Norway Prod+Imp. 194294 109570 75307 165543 190186 243126 256869 260713 268061 289670 258934 319436
Export 49500 42997 45817 62696 57261 65406 68448 90126 73367 58632 44746 57304
Total Use 144794 66573 29490 102847 132925 177720 188421 170587 194694 231038 214188 262132
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 23388 20909 21471 16529 19317 34741 23244 14615 14092 40765 25522 22764
Production 92099 78493 84167 130143 137101 104524 143612 184051 141949 131087 136143 129267
Denmark Prod+Imp. 115487 99402 105638 146672 156418 139265 166856 198666 156041 171852 161665 152031
Export 48117 27558 39372 78417 94283 74847 97150 140588 107951 104097 75807 94296
Total Use 67370 71844 66266 68255 62135 64418 69706 58078 48090 67755 85858 57735
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 0 0 0 0 6515 5078 1416 1572 15463 11356 12038 60302
Production 187981 260078 188270 241211 152990 191177 289510 326102 291802 205971 106693 201376
Chile Prod+Imp. 187981 260078 188270 241211 159505 196255 290926 327674 307265 217327 118731 261678
Export 75469 141858 83919 108738 51832 71171 165719 150582 127189 32355 4466 64546
Total Use 112512 118220 104351 132473 107673 125084 125207 177092 180076 184972 114265 197132
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 1114 1030 752 1399 2045 3501 2805 6870 10724 1761 5133 2737
Production 13798 14000 10695 10000 10000 10000 9024 10142 10673 8417 7034 35701
China Prod+Imp. 14912 15030 11447 11399 12045 13501 11829 17012 21397 10178 12167 38438
Export 2 0 44 13 203 257 98 128 170 209 2271 913
Total Use 14910 15030 11403 11386 11842 13244 11731 16884 21227 9969 9896 37525
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 163831 177875 161818 140192 121331 131066 138393 128463 79576 71254 49458 46823
Production 7700 7100 9124 7743 10245 10752 11314 11499 12044 8824 9619 11600 United Kingdom Prod+Imp. 171531 184975 170942 147935 131576 141818 149707 139962 91620 80078 59077 58423 Export 1764 1514 7370 2870 11790 11200 12322 15114 6235 6105 4043 2554
Total Use 169767 183461 163572 145065 119786 130618 137385 124848 85385 73973 55034 55869
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Import 137436 194094 108190 111566 68205 72025 89800 87609 66432 42000 11774 12335
Production 6982 7438 8185 10050 9921 9763 8599 7369 6113 5031 6113 6045
Germany Prod+Imp. 144418 201532 116375 121616 78126 81788 98399 94978 72545 47031 17887 18380
Export 14107 22322 16836 12157 8739 3559 3984 16453 4516 3236 6021 3059
Total Use 130311 179210 99539 109459 69387 78229 94415 78525 68029 43795 11866 15321
100
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 234822 246064 183531 199956 199526 214464 188803 231301 200465
Production 85717 69057 64509 55596 39455 33428 42340 46917 39608
Norway Prod+Imp. 320539 315121 248040 255552 238981 247892 231143 278218 240073
Export 62761 43452 38361 40235 28711 25090 39796 57075 64481
Total Use 257778 271669 209679 215317 210270 222802 191347 221143 175592
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 29644 30772 27266 47829 65508 94557 128197 158388 103812
Production 102301 123648 102576 117784 100027 82303 107102 119858 88990
Denmark Prod+Imp. 131945 154420 129842 165613 165535 176860 235299 278246 192802
Export 113716 98077 81809 102481 112726 104550 119845 127584 120279
Total Use 18229 56343 48033 63132 52809 72310 115454 150662 72523
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 94625 66613 32315 91739 87626 62586 75232 91596 80896
Production 180199 141050 128453 130222 195263 168923 180214 180096 193339
Chile Prod+Imp. 274824 207663 160768 221961 282889 231509 255446 271692 274235
Export 16146 6302 23624 18591 28149 42193 61843 71490 80492
Total Use 258678 201361 137144 203370 254740 189316 193603 200202 193743
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 25826 3862 3918 9542 16740 15472 30258 30805 38798
Production 15790 18434 23454 18873 23102 30000 50000 72500 92345
China Prod+Imp. 41616 22296 27372 28415 39842 45472 80258 103305 131143
Export 411 431 341 208 306 984 3521 4034 5335
Total Use 41205 21865 27031 28207 39536 44488 76737 99271 125808
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 45964 60448 35896 48124 56492 31175 19507 22681 27046
Production 10400 10100 10600 11100 11600 12100 12200 12500 12900 United Kingdom Prod+Imp. 56364 70548 46496 59224 68092 43275 31707 35181 39946
Export 1787 1696 2007 1208 3250 2236 3189 3180 2955
Total Use 54577 68852 44489 58016 64842 41039 28518 32001 36991
2000 2001 2002 2003 2004 2005 2006 2007 2008
Import 14312 13239 13757 10316 8127 6711 6520 6724 7900
Production 5355 6156 5521 5894 6526 5800 9790 11041 12182
Germany Prod+Imp. 19667 19395 19278 16210 14653 12511 16310 17765 20082
Export 1750 6152 6820 7465 9299 4755 7762 8767 9684
Total Use 17917 13243 12458 8745 5354 7756 8548 8998 10398
Source: FAO/FIGIS (2011)
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APPENDIX 12 - MAIN LOCATION OF KRILL CATCH IN THE SCOTIA SEA (1972-2004)
Location of total krill catch (1972 2004) in the Scotia Sea. The red areas in the figure x show the main location of SSMU’S where the krill fishery has been operated since 1972. Source: Based on data from CCAMLR reports and Kawaguchi and colleagues (2006)
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APPENDIX 13 - RELATED ECOSYSTEMS TO THE SCOTIA SEA; FUNCTION AND MAJOR CHANGES (1970-2010)
Related Function to the Scotia Major changes since Productivity Possible causes References ecosystems Sea 1970s Schnack-Schiel Benthic Nutrient and iron upflow, and Isla ecosystem of migration of zooplankton High N/D N/D (2005),Murphy the Scotia Sea species and pelagic fishes et al (2007) Murphy et al Bellingshausen Inflow of water with , specie Sea ice extension period Air tempertatur (2007), and Amundsen High interactions shorter increse Stammerjohn Seas et al (2008) Coastal development, Migration area for pinguins, Antropogenical pressures, Pauly et al Patagonian industrial activities, seals and other seabirds as High nonindigenous marine (1998), Ciancio shelf (and sea) turism, pollution and well as whales during winter species et al (2008) increased fishing and demand El Niño -South ern Regime and phase shifts of Oscillation (ENSO), Chilenian shelf sardine and peruvian Migration area for pinguins, High (& coastal (and sea) & achovies fisheries, Alheit and seals and other seabirds as periodically development, Humboldt antropogenical Niquen (2004) well as whales during winter low) industrial activities, current system pressures,nonindigenous turism andincreased marine species fishing and demand
Regime shifts (e.g. collapse Coastal South African van der Migration area for pinguins, High (& of sardines and horse development, shelf & Lingen et al seals and other seabirds as periodically mackerel fishery), industrial activities, Benguela (2006), Barnes well as whales during winter low) increasing antropogenical turism and increased current system (2007) pressures fish demand
Coastal Increased antropogenic Vasconcellos & Brazilian development, Migration area for whales pressures, and increased Gasalla (2001), shelves (and Middle industrial activities, during winter nonindigenous marine Freire & Pauly sea) turism and increased species (2010) fishing and demand
Related ecosystems to the Scotia Sea, the functional relationship and identified changes in these since 1970s. Based on different sources
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