Development of a spatial Decision Support System (DSS) for the Spencer Gulf penaeid prawn fishery,South Australia

The Spencer Gulf penaeid prawn fishery in South Australia has undergone a substantial increase in fishing efficiency (and profitability) mainly due to the implementation of adaptive harvest strategies requiring rapid response for change to harvesting plans. This paper describes the management background and the decision-making process leading to the development of a basic Decision Support System (DSS) that uses spatial information techniques and near real-time fishery-independent survey data. The system is implemented through linking an Oracle database to ArcGIS, Genstat and Splus. Two examples show the application of the DSS for optimal harvest timing and assessment of fishery sustainability. Fishery-independent survey data are used to assess stock and model population growth. The first example shows the information flow leading to a dynamic stock model and the estimate of value change as a function of harvest time. The second example shows how the DSS is used to validate and refine existing biological reference limits by evaluating long-term detailed data sets of the prawn population structure and catch dynamics. We conclude that it is important for the economic benefit and sustainability of the fishery to maintain and improve the collection of long-term data sets that are independent of commercial fishery statistics.     

A system dynamics model to support the management of artisanal dredge fisheries in the south coast of Portugal

This paper presents a management model developed to promote the sustainability of artisanal fisheries, considering socioeconomic and environmental dimensions. The management of artisanal fisheries faces many challenges, including the lack of appropriate tools to support policy makers and stakeholders in the decision‐making process. The model presented in this study is based on system dynamics and allows the simulation of the behavior of the artisanal dredge fishery on the south coast of Portugal, including four main species and two fleets. Two scenarios were simulated to assess the impact of regulatory measures on the system sustainability: scenario 1 simulated a permanent reduction of fishing effort, returning an improvement of biologic and economic sustainability; scenario 2 simulated the closure of one species for a period of one year to allow its recovery. It was found that although the revenue of fisheries decreases in that year, the system is able to return to the average levels of revenue three years after the closure. The study aimed to guide decision makers in the selection of the most appropriate measures toward the preservation of marine ecosystems and socioeconomic stability of fishing communities. The developed system dynamics model, combining available data with knowledge of fisheries experts, proved to be a useful scientific tool to identify management policies and organizational structures leading to greater success. This technique can be applied to the study of other fishery systems worldwide.     

A model to predict climate-change impact on fish catch in the world oceans

Water temperature plays a very important role in fish production. The assessment of the impact of water-temperature changes on fish catches in world fishery is essential for the sustainable management of world fishery resources. Fish catch includes different species, but using information analysis, it is shown that total fish catch can be used without significant loss of information about the dynamic properties of the system. A new method for the forecasting of the fish catch of the major fishing areas in the world's oceans under global climate change (temperature) has been developed. This method predicts the tendency (increase or decrease) for fish catch, with quantitative predictor's power, if the temperature is known. This method has been applied to the Indian Ocean to assess the climate-change impact on fish catch. Based on the temperatures predicted using the CLIMate-BiospheRE model for the years 2000-2100, a decrease of fish catch in the Indian Ocean, with the confidence of the predictor's power at /spl ges/ 90%, has been predicted.     

Models for fisheries management

Realization of the massive potential harvests from the oceans, coupled with disastrous collapses of substantial fisheries has seen the development over the last 25 years of a quantitative fisheries management science. As an aid to management, models are used to represent fish populations and the effects of exploitation on them. Basic models currently used for fisheries management are reviewed. The models discussed range from the simple surplus production model through to the analytical model of Beverton and Holt incorporating age structure and finally to Kicker's stock-recruitment model. The models are used to examine the dynamics and stability of fish stock when subjected to different exploitation policies. Some of the problems for management in interfacing real fisheries data with the mathematical models are discussed. The goals of management, including catch, fishing effort and economics (e.g. price, cost and inflation) are quantified to produce an objective function which may be used to determine optimal strategies. The optimal harvesting strategies are examined for each model, with a view to developing a general workable robust harvesting policy, independent of the model used.     

中西太平洋金枪鱼围网渔场专题图服务

中西太平洋渔场是世界金枪鱼捕捞产量最高的渔场之一,由于金枪鱼属于中上层高度洄游鱼类,渔场变动较大,借助遥感产品辅助渔场中心判断是一种有效的手段。上海开创远洋渔业有限公司金枪鱼围网主要集中在中西太平洋,生产过程中利用海表温度、叶绿素、海面流场等海况产品辅助捕捞决策。文章基于地理信息和遥感技术,开发了后台数据自动处理软件,完成数据获取、解码、投影转换、专题图制图等流程,完成渔场专题图自动制图,并通过微信、FTP和网站提供服务,可以很好的为渔业分析与管理。     

Distribution of hotspots of chub mackerel based on remote-sensing data in coastal waters of China

Sustainable use of fishery resources requires the effective monitoring and managing of fish stocks and fish habitats. Chub mackerel (Scomber japonicus), distributed in the East China Sea and Yellow Sea, are mainly caught by purse seine fishing fleets from China, Japan, and South Korea. This study used fishery data from Chinese large lighting–purse seine fleets and environmental data including sea surface height (SSH), sea surface temperature (SST) from remote sensing, and temperature gradient derived from SST (GSST) during 1998–2010 to develop habitat suitability index (HSI) models. The HSI models were then used to identify hotspots for chub mackerel for each month. HSI models were developed separately for each of the three distribution areas defined for chub mackerel. According to the frequency distribution of the fishing effort with respect to three environmental variables, suitability index (SI) values were calculated and SI models for each environmental variable were established. The three SI models were combined into two different empirical HSI models: the arithmetic mean model (AMM) and the geometric mean model (GMM). The results showed that the AMM was more suitable than the GMM to estimate the HSI for chub mackerel. The monthly latitudinal variation trend of hotspots was consistent with that of the gravity centres of fishing effort in almost all months. Hotspot maps based on the predicted HSI values were validated by fishery data in 2011. This result indicates that the HSI model based on the AMM can reliably predict hotspots for chub mackerel in the coastal waters of China.     

一种新的面向渔情预测的智能数据处理模型研究*

结合印度洋大眼金枪鱼渔业应用背景,提出一种新的面向渔情预测的智能数据处理模型。首先利用支持向量机（SVM）对样本数据进行训练,并运用模糊分类器对支持向量进行规则提取;然后对条件和结论分别进行可拓变换和传导变换,获得渔场动态知识。实验结果表明,获得的动态知识具有更强的解释性,对丰富渔情预测方法、解释渔场形成机制具有重要意义。     

Quantifying light-fishing for Dosidicus gigas in the eastern Pacific using satellite remote sensing

The distribution and abundance of the fleet targeting Jumbo flying squid (Dosidicus gigas) in the Eastern Pacific is examined during the 1999 fishery season. The commercial fishery consists of a multinational jigging fleet, which fish at night using powerful lights to attract squid. The emission of light from these vessels can be observed using satellite-derived imagery obtained by the United States Defence Meteorological Satellite Program-Operational Linescan System (DMSP-OLS). In order to quantify fishing effort using lights, data on the distribution and abundance of vessels were obtained via satellite tracking using the ARGOS system. The distribution of the fishery as derived from light signatures was found to closely resemble that derived from ship location data. By using ARGOS data to calibrate DMSP-OLS images, we are able to estimate fishing effort in terms of the ‘area illuminated’ by the fishing fleet. Light signatures derived from DMSP-OLS were successfully used to quantify fishing effort, estimating the number of vessels fishing to within ±2 in 85 out of 103 satellite images (83%). High seas fishing was also quantified, with light signatures corresponding to a single fishing vessel observed in 11 out of 103 satellite passes during the fishery season (July-December 1999). This study examines how much light (in terms of area) is emitted by a single squid fishing vessel, and may prove to be a valuable tool in assessing and policing fisheries using satellite remote sensing.     

渔情海况WebGIS信息服务系统构建

渔情海况是渔业生产和管理过程中的重要辅助信息。以ArcGIS Server为开发平台,后台选用ENVI/IDL提供遥感数据处理服务,ArcObject组件提供地理信息服务,两者一体化集成实现完整的空间信息后台服务,系统能够提供叶绿素、海温、海流、温盐跃层等的信息发布、查询、分析等功能,可以满足渔业生产与科研的需要。     

Strengthening the resilience of small-scale fisheries: A modeling approach to explore the use of in-shore pelagic resources in Melanesia

Small-scale fisheries play a critical role in both poverty alleviation and food security. A large proportion of the world fish stocks are, however, getting fully or over-exploited. In this article we address these issues in the context of the small-scale fisheries of the Solomon Islands. The paper explores the extent to which in-shore Fish Aggregating Devices (FADs) can help increasing the resilience of the small scale fishery system and reconciling social, economic and ecological priorities. Based on the concept of ‘time of crisis’ developed recently in the viability literature, we propose to calculate a resilience index through a dynamic stochastic model calibrated by ethnological observations. The resilience index calculation reveals two major findings: (i) the resilience of the small scale fishery system is currently nonexistent and (ii) the introduction of FADs can improve it. The effects of the FADs' implementation are then discussed in the light of a socio-economic perspective. Such results bring new insights into the question of the future of the small scale fishery sector, especially in relation to the local economy evolution from a barter dominance to a cash oriented economy. At the same time, the current subsistence fisheries seems more resilient in general due to a distributive effects which ease the ‘race for fish behaviors’. Finally, our analysis reveals that while the FADs implementation stands as a short and mid-term answer, demographic drivers are important and other alternatives will need to be considered if the overall viability of the system is to be maintained in the longer-term.     

基于角色的用户权限管理和功能模块的动态加载

介绍了基于角色的用户权限管理模型以及功能模块的动态加载技术,论述了基于角色的用户权限管理模型以及功能模块的动态加载技术在应用系统中的重要性,并以大洋渔业渔获信息管理系统为例,给出了基于角色的用户权限管理以及功能模块动态加载的设计思路和具体实现。在大洋渔业渔获信息管理系统中,通过使用基于角色的用户权限管理模型和功能模块动态加载技术,简化了用户管理难度,为系统提供了安全性和灵活性。     

面向海洋渔业决策支持的信息综合协调研究

时空信息与社会行业非空间信息的综合是资源环境研究和管理的发展方向之一。该文就研究成果阐述基于信息综合的海洋渔政支持系统及其构造,系统有机综合了地理信息系统(GIS)、全球定位系统(GPS)、管理信息系统(MIS)等技术,对时空信息和社会行业信息进行有机的综合,实现对海洋渔政事务的自动协调处理,进而对渔业多源信息进行综合协调,为海上渔业指挥和调控提供决策支持,从而保障渔业生产安全和资源的可持续利用。     

Time-series modeling of fishery landings using ARIMA models and Fuzzy Expected Intervals software

Forecasting, using historic time-series data, has become an important tool for fisheries management. ARIMA modeling, Modeling for Optimal Forecasting techniques and Decision Support Systems based on fuzzy mathematics may be used to predict the general trend of a given fish landings time-series with increased reliability and accuracy. The present paper applies these three modeling methods to forecast anchovy fish catches landed in a given port (Thessaloniki, Greece) during 1979–2000 and hake and bonito total fish catches during 1982–2000. The paper attempts to assess the model's accuracy by comparing model results to the actual monthly fish catches of the year 2000. According to the measures of forecasting accuracy established, the best forecasting performance for anchovy was shown by the DSS model (MAPE = 28.06%, RMSE = 76.56, U-statistic = 0.67 and R² = 0.69). The optimal forecasting technique of genetic modeling improved significantly the forecasting values obtained by the selected ARIMA model. Similarly, the DSS model showed a noteworthy forecasting efficiency for the prediction of hake landings, during the year 2000 (MAPE = 2.88%, RMSE = 13.75, U-statistic = 0.19 and R² = 0.98), as compared to the other two modeling techniques. Optimal forecasting produced by combined modeling scored better than application of the simple ARIMA model. Overall, DSS results showed that the Fuzzy Expected Intervals methodology could be used as a very reliable tool for short-term predictions of fishery landings.     

基于渔船监测系统的近海捕捞水产品溯源

通过对渔船监测系统的船位、航向、航速等信息挖掘,可以进行水产品溯源,保障海洋水产品的食品安全。基于渔船监测系统数据,结合渔场、沿海区划等信息,构建近海捕捞水产品溯源模型,研究渔船溯源、渔区和渔场溯源、渔获溯源,为水产品安全保障提供参考依据。     

Using an Atlantis model of the southern Benguela to explore the response of ecosystem indicators for fisheries management

Atlantis is a whole-of-system modelling framework developed for Management Strategy Evaluation. This paper describes an Atlantis model that was built to simulate the southern Benguela ecosystem and its major associated fisheries to assist fisheries management in the region. We divided the region into spatial zones based on hydrodynamics, current fishing management, and important ecosystem processes. We divided the biological components of the system into functional groups based on trophic interaction, life history traits and fisheries management objectives. We evaluated the model against historical data and known ecosystem interactions (such as competition and predation), and found that it simulates important ecological processes well at multiple trophic levels. We tested the model under fishing pressure scenarios and evaluated the performance of common ecosystem-level indicators. The response of the modelled system (as shown by indicators) was in line with expected behaviour of the indicators, reinforcing our confidence in the usefulness of the model.     

Management system for distributed and hierarchical robot groups

This paper introduces a management system for robot groups with distributed and hierarchical architecture. In order to manage cooperation tasks of a great many robots, we put management systems on each work sub-area. A management system on a certain sub-area divides a task given by the upper sub-area into sub-tasks and gives the lower sub-areas those sub-tasks. With this architecture, we obtain distributed and hierarchical management system for the whole working area. We produced a simulation system and showed an example of task division and execution. We also produced a demonstration system.     

Prioritization of satellite-derived potential fishery grounds: an analytical hierarchical approach-based model using spatial and non-spatial data

Forecast of potential fishing grounds can save considerable amounts of fuel and time involved in marine fishing operations, making the operation more profitable. This study investigates the prospects of using a decision support system for forecasting potential fishery zones and prioritizing them according to profitability using multi-criteria analysis. Ocean Colour Monitor-derived chlorophyll concentration and National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer-derived sea surface temperature maps were integrated to demarcate the potential fishery zones (PFZs). QuickSCAT (NASA) scatterometer wind data obtained from the global 25 km × 25 km gridded dataset were used for updating the locations of PFZ features. An analytical hierarchy process-based prioritization model, which considers different parameters favouring a targeted species, distance to the zone and historical catch per unit effort as the major decision-making parameters, was used to rank the zones based on feasibility. A software package was developed incorporating the above-mentioned functionalities for automatic data processing and PFZ map generation.     

Tracking a benchmark index – using a spreadsheet‐based decision support system as the driver

This paper presents a two‐phase quantitative approach for enhanced index investing based on the mean‐variance model and the goal programming method. In the first stage, we use the mean‐variance theory to select better performing stocks for an investment pool. Then, in the second stage, we use a goal programming method to weight the selected stocks by balancing both the tracking error and the rate of return. In addition to the theoretical formulation, we construct a spreadsheet‐based decision support system (DSS) based on the transaction data to help resolve the index tracking problem. The paper contributes to the literature in two ways. For academics, we present original discussions on combining an interdisciplinary mean‐variance model and a goal programming method. Unlike the conventional approach used for enhanced index investing that requires a fund manager to actively buy and sell stocks to improve returns, our approach is based on historical data and deduces subjective judgments. Meanwhile, for practitioners, we present an original discussion on using a DSS to support index investing. The results of an empirical survey of the Taiwan stock market are also presented.     

Applying machine learning to model management in decision support systems

Model management systems have become increasingly important in handling complicated decision problems in decision support systems (DSS). Aiming at overcoming the weaknesses of currently used model management systems, we present a new framework of model management system which is capable of performing model manipulation more effectively. The new approach incorporates machine learning to acquire model manipulation knowledge, stored in the form of schemata, and to refine these acquired schemata. In addition, we also address two issues that have so far been overlooked in the DSS literature: (1) to refine existing model representations as more experiences are accumulated and (2) to create model selection heuristics adaptive to the DSS environment.     

A new approach to water quality modelling and environmental decision support systems

The concepts and technology of environmental decision support systems (EDSS) have developed considerably over recent decades, although core concepts such as flexibility and adaptability within a changing decision environment remain paramount. Much recent EDSS theory has focussed on model integration and re-use in decision support system (DSS) tools and for design and construction of ‘DSS generators’. Many current specific DSS have architectures, tools, models and operational characteristics that are either fixed or difficult to change in the face of changing management needs. This paper reports on development and deployment of an EDSS that encompasses a new approach to DSS tools, generators and specific DSS applications. The system, named E2, is built upon a conceptualisation of terrestrial and aquatic environmental systems that has resulted in a robust and flexible system architecture. The architecture provides a set of base classes to represent fundamental concepts, and which can be instantiated and combined to form DSS generators of varying complexity. A DSS generator is described within which system users are able to select and link models, data, analysis tools and reporting tools to create specific DSS for particular problems, and for which new models and tools can be created and, through software reflection (introspection), discovered to provide expanded capability where required. This system offers a new approach within which environmental systems can be described in the form of specific DSS at a scale and level of complexity suited to the problems and needs of decision makers.