Fish demand and supply projections

It has been predicted that the global demand for fish for human consumption will increase by more than 50% over the next 15 years. The FAO has projected that the increase in supply will originate primarily from marine fisheries, aquaculture and to a lesser extent from inland fisheries, but with a commensurate price increase. However, there are constraints to increased production in both marine and inland fisheries, such as overfishing, overexploitation limited potential increase and environmental degradation due to industrialization. The author sees aquaculture as having the greatest potential for future expansion. Aquaculture practices vary depending on culture, environment, society amd sources of fish. Inputs are generally low-cost, ecologically efficient and the majority of aquaculture ventures are small-scale and family operated. In the future, advances in technology, genetic improvement of cultured species, improvement in nutrition, disease management, reproduction control and environmental management are expected along with opportunities for complimentary activities with agriculture, industrial and wastewater linkages. The main constraints to aquaculture are from reduced access to suitable land and good quality water due to pollution and habitat degradation. Aquaculture itself carries minimal potential for aquatic pollution. State participation in fisheries production has not proven to be the best way to promote the fisheries sector. The role of governments is increasingly seen as creating an environment for economic sectors to make an optimum contribution, through support in areas such as infrastructure, research, training and extension and a legal framework. The author feels that a holistic approach integrating the natural and social sciences is called for when fisheries policy is being examined.

Building social and ecological resilience to climate change in Roviana, Solomon Islands: PASAP country activity for Solomon Islands: Brief review: climate change trends and projections for Solomon Islands

As part of the Australian Government’s International Climate Change Adaptation Initiative (ICCAI), the Pacific Adaptation Strategy Assistance Program (PASAP) aims to enhance the capacity of partner countries to assess key vulnerabilities and risks, formulate adaptation strategies and plans, mainstream adaptation into decision-making, and inform robust longterm national planning and decision-making in partner countries. The Department of Climate Change and Energy Efficiency contracted University of Queensland (UQ) and University of California, Santa Barbara (UCSB) to lead the project: “Building social and ecological resilience to climate change in Roviana, Solomon Islands” (2010-2012). Under this project The WorldFish Center was subcontracted to undertake outputs 5 and 6 of Objective three: (5) Review of climate change evidence and projections for the study area and (6) Vulnerability and adaptation assessment for the study area. This report addresses the first of these and comprises a desktop review of climate change evidence and projections for the study area.

Strategies and options for increasing and sustaining fisheries and aquaculture production to benefit poorer households in Asia

The last three decades have witnessed dramatic changes in the structure of supply and demand for fish, especially in Asia. This WorldFish research study sponsored by the Asian Development Bank focussed on nine developing countries – Bangladesh, China, India, Indonesia, Malaysia, the Philippines, Sri Lanka, Thailand, and Vietnam, all active players in the transformation of global fish supply and demand. The study, broken into five components and reported here, considered: 1) the profile of key aquaculture technologies and fishing practices; 2) analysis of policies, institutions and support services; 3) socioeconomic profile of major stakeholders in the fisheries sector; 4) projections of fish demand and supply in the nine Asian countries; and 5) formulation of national action plans based on the findings and recommendations of the study.

Diagnosis and the management constituency of small-scale fisheries

Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages)

A statistical investigation of fish prices in Nigeria

The main objective of this study is to describe and characterize the behaviour of fish prices in Nigeria. Drawing upon aspects of the data from a nationwide fish survey in 1980/81 and on various secondary data, the study analyses the pattern of fish price movement and makes projections of fish prices in Nigeria till 2002 A.D. It is concluded that unless efforts are directed at stemming inflation in fish prices, prices paid by fish consumers in Nigeria will be more than doubled within the next two decades

Strategies for the establishment of profitable fish farms in Nigeria

Cost projections for the establishment of a fish farm in Nigeria was conducted. It is shown that fish farming should be a lucrative venture. However, many private fish farms are not making the desired profits because of a variety of problems. Besides managerial incompetence, availability of fingerlings for stocking in the ponds is shown to be a serious handicap to the success of investments in a fish farm. It is suggested that where the funds are available, each farm should be equipped with facilities for raising its needs of fingerlings. Since useful capital would be involved and knowledgeable experts to run the hatcheries are few, it is recommended that fish farms within a state or adjacent states should combine to establish viable cooperative hatcheries

Investigating changes in global tropical cyclone storm frequency and intensity

Understanding fluctuations in tropical cyclone activity along United States shores and abroad becomes increasingly important as coastal managers and planners seek to save lives, mitigate damage, and plan for resilience in the face of changing storminess and sea-level rise. Tropical cyclone activity has long been of concern to coastal areas as they bring strong winds, heavy rains, and high seas. Given projections of a warming climate, current estimates suggest that not only will tropical cyclones increase in frequency, but also in intensity (maximum sustained winds and minimum central pressures). An understanding of what has happened historically is an important step in identifying potential future changes in tropical cyclone frequency and intensity. The ability to detect such changes depends on a consistent and reliable global tropical cyclone dataset. Until recently no central repository for historical tropical cyclone data existed. To fill this need, the International Best Track Archive for Climate Stewardship (IBTrACS) dataset was developed to collect all known global historical tropical cyclone data into a single source for dissemination. With this dataset, a global examination of changes in tropical cyclone frequency and intensity can be performed. Caveats apply to any historical tropical cyclone analysis however, as the data contributed to the IBTrACS archive from various tropical cyclone warning centers is still replete with biases that may stem from operational changes, inhomogeneous monitoring programs, and time discontinuities. A detailed discussion of the difficulties in detecting trends using tropical cyclone data can be found in Landsea et al. 2006. The following sections use the IBTrACS dataset to show the global spatial variability of tropical cyclone frequency and intensity. Analyses will show where the strongest storms typically occur, the regions with the highest number of tropical cyclones per decade, and the locations of highest average maximum wind speeds. (PDF contains 3 pages)

The predicting power of models for eutrophication

Restoration of water-bodies from eutrophication has proved to be extremely difficult. Mathematical models have been used extensively to provide guidance for management decisions. The aim of this paper is to elucidate important problems of using models for predicting environmental changes. First, the necessity for a proper uncertainty assessment of the model, upon calibration, has not been widely recognized. Predictions must not be a single time trajectory; they should be a band, expressing system uncertainty and natural variability. Availability of this information may alter the decision to be taken. Second, even with well-calibrated models, there is no guarantee they will give correct projections in situations where the model is used to predict the effects of measures designed to bring the system into an entirely different ”operating point”, as is typically the case in eutrophication abatement. The concept of educated speculation is introduced to partially overcome this difficulty. Lake Veluwe is used as a case to illustrate the point. Third, as questions become more detailed, such as ”what about expected algal composition”, there is a greater probability of running into fundamental problems that are associated with predicting the behaviour of complex non-linear systems. Some of these systems show extreme initial condition sensitivity and even, perhaps, chaotic behaviour, and are therefore fundamentally unpredictable.

A-SCALA: an age-structured statistical catch-at-length analysis for assessing tuna stocks in the eastern tropical Pacific Ocean

English: We describe an age-structured statistical catch-at-length analysis (A-SCALA) based on the MULTIFAN-CL model of Fournier et al. (1998). The analysis is applied independently to both the yellowfin and the bigeye tuna populations of the eastern Pacific Ocean (EPO). We model the populations from 1975 to 1999, based on quarterly time steps. Only a single stock for each species is assumed for each analysis, but multiple fisheries that are spatially separate are modeled to allow for spatial differences in catchability and selectivity. The analysis allows for error in the effort-fishing mortality relationship, temporal trends in catchability, temporal variation in recruitment, relationships between the environment and recruitment and between the environment and catchability, and differences in selectivity and catchability among fisheries. The model is fit to total catch data and proportional catch-at-length data conditioned on effort. The A-SCALA method is a statistical approach, and therefore recognizes that the data collected from the fishery do not perfectly represent the population. Also, there is uncertainty in our knowledge about the dynamics of the system and uncertainty about how the observed data relate to the real population. The use of likelihood functions allow us to model the uncertainty in the data collected from the population, and the inclusion of estimable process error allows us to model the uncertainties in the dynamics of the system. The statistical approach allows for the calculation of confidence intervals and the testing of hypotheses. We use a Bayesian version of the maximum likelihood framework that includes distributional constraints on temporal variation in recruitment, the effort-fishing mortality relationship, and catchability. Curvature penalties for selectivity parameters and penalties on extreme fishing mortality rates are also included in the objective function. The mode of the joint posterior distribution is used as an estimate of the model parameters. Confidence intervals are calculated using the normal approximation method. It should be noted that the estimation method includes constraints and priors and therefore the confidence intervals are different from traditionally calculated confidence intervals. Management reference points are calculated, and forward projections are carried out to provide advice for making management decisions for the yellowfin and bigeye populations. Spanish: Describimos un análisis estadístico de captura a talla estructurado por edad, A-SCALA (del inglés age-structured statistical catch-at-length analysis), basado en el modelo MULTIFAN- CL de Fournier et al. (1998). Se aplica el análisis independientemente a las poblaciones de atunes aleta amarilla y patudo del Océano Pacífico oriental (OPO). Modelamos las poblaciones de 1975 a 1999, en pasos trimestrales. Se supone solamente una sola población para cada especie para cada análisis, pero se modelan pesquerías múltiples espacialmente separadas para tomar en cuenta diferencias espaciales en la capturabilidad y selectividad. El análisis toma en cuenta error en la relación esfuerzo-mortalidad por pesca, tendencias temporales en la capturabilidad, variación temporal en el reclutamiento, relaciones entre el medio ambiente y el reclutamiento y entre el medio ambiente y la capturabilidad, y diferencias en selectividad y capturabilidad entre pesquerías. Se ajusta el modelo a datos de captura total y a datos de captura a talla proporcional condicionados sobre esfuerzo. El método A-SCALA es un enfoque estadístico, y reconoce por lo tanto que los datos obtenidos de la pesca no representan la población perfectamente. Además, hay incertidumbre en nuestros conocimientos de la dinámica del sistema e incertidumbre sobre la relación entre los datos observados y la población real. El uso de funciones de verosimilitud nos permite modelar la incertidumbre en los datos obtenidos de la población, y la inclusión de un error de proceso estimable nos permite modelar las incertidumbres en la dinámica del sistema. El enfoque estadístico permite calcular intervalos de confianza y comprobar hipótesis. Usamos una versión bayesiana del marco de verosimilitud máxima que incluye constreñimientos distribucionales sobre la variación temporal en el reclutamiento, la relación esfuerzo-mortalidad por pesca, y la capturabilidad. Se incluyen también en la función objetivo penalidades por curvatura para los parámetros de selectividad y penalidades por tasas extremas de mortalidad por pesca. Se usa la moda de la distribución posterior conjunta como estimación de los parámetros del modelo. Se calculan los intervalos de confianza usando el método de aproximación normal. Cabe destacar que el método de estimación incluye constreñimientos y distribuciones previas y por lo tanto los intervalos de confianza son diferentes de los intervalos de confianza calculados de forma tradicional. Se calculan puntos de referencia para el ordenamiento, y se realizan proyecciones a futuro para asesorar la toma de decisiones para el ordenamiento de las poblaciones de aleta amarilla y patudo.

Multiple stable reference points in oyster populations: implications for reference point-based management

In the second of two companion articles, a 54-year time series for the oyster population in the New Jersey waters of Delaware Bay is analyzed to examine how the presence of multiple stable states affects reference-point–based management. Multiple stable states are described by four types of reference points. Type I is the carrying capacity for the stable state: each has associated with it a type-II reference point wherein surplus production reaches a local maximum. Type-II reference points are separated by an intermediate surplus production low (type III). Two stable states establish a type-IV reference point, a point-of-no-return that impedes recovery to the higher stable state. The type-II to type-III differential in surplus production is a measure of the difficulty of rebuilding the population and the sensitivity of the population to collapse at high abundance. Surplus production projections show that the abundances defining the four types of reference points are relatively stable over a wide range of uncertainties in recruitment and mortality rates. The surplus production values associated with type-II and type-III reference points are much more uncertain. Thus, biomass goals are more easily established than fishing mortality rates for oyster population

A production modeling approach to the assessment of the horseshoe crab (Limulus polyphemus) population in Delaware Bay

Horseshoe crab (Limulus polyphemus) is harvested commercially, used by the biomedical industry, and provides food for migrating shorebirds, particularly in Delaware Bay. Recently, decreasing crab population trends in this region have raised concerns that the stock may be insufficient to fulfill the needs of these diverse user groups. To assess the Delaware Bay horseshoe crab population, we used surplus production models (programmed in ASPIC), which incorporated data from fishery-independent surveys, fishery-dependent catch-per-unit-of-effort data, and regional harvest. Results showed a depleted population (B2003/=0.03−0.71) BMSY and high relative fishing mortality /FMSY=0.9−9.5). Future harvest (F2002strategies for a 15-year period were evaluated by using population projections with ASPICP software. Under 2003 harvest levels (1356 t), population recovery to BMSY would take at least four years, and four of the seven models predicted that the population would not reach BMSY within the 15year period. Production models for horseshoe crab assessment provided management benchmarks for a species with limited data and no prior stock assessment

PICES Press, Vol. 20, No. 2, Summer 2012

•The 2012 Inter-sessional Science Board Meeting: A Note from Science Board Chairman (pp. 1-4) ◾PICES Interns (p. 4) ◾2012 Inter-sessional Workshop on a Roadmap for FUTURE (pp. 5-8) ◾Second Symposium on “Effects of Climate Change on the World’s Oceans” (pp. 9-13) ◾2012 Yeosu Workshop on “Framework for Ocean Observing” (pp. 14-15) ◾2012 Yeosu Workshop on “Climate Change Projections” (pp. 16-17) ◾2012 Yeosu Workshop on “Coastal Blue Carbon” (pp. 18-20) ◾Polar Comparisons: Summary of 2012 Yeosu Workshop (pp. 21-23) ◾2012 Yeosu Workshop on “Climate Change and Range Shifts in the Oceans" (pp. 24-27) ◾2012 Yeosu Workshop on “Beyond Dispersion” (pp. 28-30) ◾2012 Yeosu Workshop on “Public Perception of Climate Change” (pp. 31, 50) ◾PICES Working Group 20: Accomplishments and Legacy (pp. 32-33) ◾The State of the Western North Pacific in the Second Half of 2011 (pp. 34-35) ◾Another Cold Winter in the Gulf of Alaska (pp. 36-37) ◾The Bering Sea: Current Status and Recent Events (pp. 38-40) ◾PICES/ICES 2012 Conference for Early Career Marine Scientists (pp. 41-43) ◾Completion of the PICES Seafood Safety Project – Indonesia (pp. 44-46) ◾Oceanography Improves Salmon Forecasts (p. 47) ◾2012 GEOHAB Open Science Meeting (p. 48-50) ◾Shin-ichi Ito awarded 2011 Uda Prize (p. 50)

Annual report 2006 - North Pacific Marine Science Organization (PICES). Fifteenth meeting, Yokohama, Japan, October 13-22, 2006

◾ Report of Opening Session (p. 1) ◾ Report of Governing Council (p. 15) ◾ Report of the Finance and Administration Committee (p. 47) ◾ Reports of Science Board and Committees: Science Board Inter-sessional Meeting (p. 63); Science Board (p. 73); Biological Oceanography Committee (p. 87); Fishery Science Committee (p. 95); Marine Environmental Quality Committee (p. 105); MONITOR Technical Committee (p. 115); Physical Oceanography and Climate Committee (p. 125); Technical Committee on Data Exchange (p. 133) ◾ Reports of Sections, Working and Study Groups: Section on Carbon and Climate (p. 139); Section on Ecology of Harmful Algal Blooms in the North Pacific (p. 143); Working Group 18 on Mariculture in the 21st Century - The Intersection Between Ecology, Socio-economics and Production (p. 147); Working Group 19 on Ecosystem-Based Management Science and its Application to the North Pacific (p. 151); Working Group 20 on Evaluations of Climate Change Projections (p. 157); Working Group 21 on Non-indigenous Aquatic Species (p. 159); Study Group to Develop a Strategy for GOOS (p. 165) ◾ Reports of the Climate Change and Carrying Capacity Scientific Program: Implementation Panel on the CCCC Program (p. 169); CFAME Task Team (p. 175); MODEL Task Team (p. 181) ◾ Reports of Advisory Panels: Advisory Panel for a CREAMS/PICES Program in East Asian Marginal Seas (p. 187); Advisory Panel on Continuous Plankton Recorder Survey in the North Pacific (p. 193); Advisory Panel on Iron Fertilization Experiment in the Subarctic Pacific Ocean (p. 197); Advisory Panel on Marine Birds and Mammals (p. 201); Advisory Panel on Micronekton Sampling Inter-calibration Experiment (p. 205) ◾ Summary of Scientific Sessions and Workshops (p. 209) ◾ Membership List (p. 259) ◾ List of Participants (p. 277) ◾ List of PICES Acronyms (p. 301) ◾ List of Acronyms (p. 303)