种群模拟在渔业资源评估中的研究现状及展望

随着渔业资源评估理论、数理统计方法和计算机技术的进步, 资源评估模型朝着多样化和复杂化不断发展, 其中种群模拟技术是检测模型适用性和局限性的重要手段。该技术由种群仿真理念发展而来, 通过模拟“真实”种群的方式, 对资源评估结果和管理策略进行有效的评价和预测, 并凭借可结合海洋环境因子、鱼类洄游空间分布以及多鱼种渔业进行资源评估的特性, 已成为开发新资源的重要评估方法之一。为此, 本文对种群模拟的结构和发展过程进行了回顾, 对该技术的核心组成部分操作模型和常见的四类误差(过程误差、观测误差、模型结构误差和管理误差)展开分类讨论。此外, 本文还结合近年来迅速发展的数据缺乏和数据适中模型的特点, 根据实际应用案例对种群模拟的作用和使用前景进行梳理, 并就种群模拟技术发展中存在的主要问题和潜在解决办法提出分析和建议。     

连续形Fox产量模型在模拟和实际渔业评估中的应用

剩余产量模型因为具有形式简单和所需数据少的特点,在渔业资源评估中被广泛应用。文章应用连续形Fox产量模型对3种模拟渔业以及北大西洋剑鱼渔业进行了评估,并对模拟渔业的评估结果进行了比较,以发现连续Fox产量模型比较适宜的渔业条件。蒙特卡罗（Monte Carlo）分析表明,模型在产量和捕捞努力量随时间波动的波动性渔业中评估效果最好,可能是由于该类型渔业过程比较完整,数据中包含的信息比较丰富。比较不同的白色噪音水平,当白色噪音小于10%时评估结果偏差较小,小于3.3%;当白色噪音为50%时,评估结果偏差较大,最大偏差为36.7%。     

Inclusion of discards in stock assessment models

A large portion of the catch in many stocks may comprise discards which need to be accounted for in assessments in order to avoid bias in estimates of fishing mortality, stock biomass and reference points. In age‐structured assessment models, discards are sometimes treated as a separate fleet or are added to the landings before fitting so that information about discard behaviour and sampling error is lost. In this paper, an assessment model is developed to describe the discard process with size as a covariate while retaining age‐structured population dynamics. Discard size selection, high grading and bulk dumping of fish at sea are modelled so that the temporal dynamics of the process can be quantified within the assessment. The model is used to show that discarding practices have changed over time in a range of Northeast Atlantic demersal fish. In some stocks, there is a substantial increase in high grading and evidence for bulk discarding which can be related to regulatory measures. The model offers a means of identifying transient effects in the discard process that should be removed from both short‐term forecasts and equilibrium reference point calculations.     

渔业数据失真对两种非平衡剩余产量模型评估结果的影响比较

为了研究渔业数据失真对两种非平衡剩余产量模型评估结果的影响,以南大西洋长鳍金枪鱼渔业产量和单位捕捞努力量渔获量(CPUE)数据作为基础数据,加入5种不同程度[变异系数(CV)=1%、5%、10%、20%和30%]的随机误差,模拟了(1)无数据失真,(2)仅产量数据失真,(3)仅CPUE数据失真,(4)产量和CPUE数据均失真等4种情况。利用基于ASPIC的非平衡剩余产量模型(ASM)和基于贝叶斯状态空间建模方法的非平衡剩余产量模型(BSM)分别评估了最大可持续产量(MSY)、B_(MSY)、F_(MSY)、B_(2011)/B_(MSY)、F2011/F_(MSY)等5种生物学参考点和管理指标。结果显示,在无数据失真情况下,ASM和BSM评估的MSY分别为2.866×10~4 t和2.836×10~4 t,B_(2011)/B_(MSY)分别为1.366和1.324,F2011/F_(MSY)分别为0.627和0.667,均相差不大,表明该渔业目前状态良好,ASM得到了较大的B_(MSY)(31.48×10~4 t)和较小的F_(MSY)(0.091);数据失真对ASM评估的B_(MSY)和F_(MSY)分别产生了严重的过低估计和过高估计,且CPUE数据失真产生的影响要比产量数据失真大;随着随机误差的增大,BSM评估的生物学参考点和管理指标的绝对百分比偏差有增大趋势;与ASM相比,BSM能够更好地处理渔业数据中存在的随机误差,除了MSY以外,BSM评估的生物学参考点和管理指标绝对百分比偏差均要比ASM的评估结果低,尤其是B_(MSY)和F_(MSY)。因此,在使用存在较大随机误差的渔业数据进行资源评估时,BSM具有一定的优势。     

渔业资源评估模型的研究现状与展望

制定合理的渔业管理计划, 实现渔业资源的可持续利用, 需对渔业资源进行科学的评估, 而渔业资源评估模型则是进行渔业资源评估的重要工具。随着计算机计算能力的提高及在多学科交叉的推动下, 近30多年来渔业资源评估模型得到了快速发展。随着渔业资源评估模型日益复杂、多样化, 模型的选择、使用难度也相应地增加了, 而模型的不恰当运用则可能导致渔业资源管理的失误。本文对渔业资源评估模型的基本结构、主要类型及参数估计所使用的统计模型等方面进行了全面回顾, 介绍了目前使用的主要渔业资源评估模型, 展示了渔业资源评估模型的发展历程及所取得的进展。同时, 文章对渔业资源评估模型中存在的问题进行了探讨, 并对其未来的发展进行了展望。

     

渔业资源增殖放流效果评估方法的研究

依据渔业资源评估原理,结合渔业资源增殖放流的特点,提出一套计算群体生物统计量进而评估渔业资源增殖放流效果的方法。选用渔业资源评估模型,估算未建立生长方程的增殖放流种类的生长参数及其自然死亡系数,以及增殖放流种类的合理放流数量。提出确认渔获物中来自放流种苗数量的方法。推导了计算捕捞死亡系数和按时间序列计算放流群体残存量、回捕量、回捕率和回捕效益等的公式。     

A multispecies stock assessment of a pelagic coastal fishery of the south-west Gulf of Mexico

Abstract. Multispecies stock assessment based upon Schaefer's theory was applied to a coastal pelagic fishery (Spanish mackerel, Scomberomorus maculatus (Mitchill); king mackerel, S. cavalla (Cuvier) and the blue runner, Caranx fusus (Geoffroy-St Hilaire)), from the west central Gulf of Mexico. Linear and non-linear systems of equations were estimated by using a multiple stepwise regression technique. The values of interaction parameters show a clear competition between mackerels, and technological interdependences between the blue runner and mackerels, The maximum yield estimation was from 4000 to 5000 tonnes, obtained with 23 and 34 beach seines respectively, depending on the applied model. Two stages were observed from the statistical records; in the first the Spanish mackerel is the most important species while in the second the abundance of this species declines and the others remain at the same level. Significant interactions were found from the first data group.     

象山港海洋牧场建设与生物资源的增殖养护技术

通过生物资源生境营造、适宜性增殖物种筛选与应用、牧化物种增殖与采捕、效果评估和管理等技术的研究与运用,建立有效恢复生物资源、实现天然水域渔业生物资源产出功能最大化的象山港海洋牧场示范区。至今已建成由15个圆角六边形和1 000个台面框架型诱导礁组合而成的7个鱼礁群,面积25 hm~2,形成空方规模53 810 m~3;移植海带、坛紫菜和龙须菜等大型海藻,建成以浮式平面藻床为主的人工藻场80 hm~2。底播毛蚶、栉江珧等贝类2 000万粒;年放流大黄鱼、黑鲷、黄姑鱼、褐鲳鲉等鱼类苗种160万尾;中国明对虾、日本对虾等虾类1亿尾。调查结果显示,牧场示范区富营养化程度有所降低,初级与次级生产力明显提升,其中海藻年生物量约为18 000 kg/hm~2;海洋牧场的渔业资源养护效果良好,人工鱼礁投放19个月后,鱼礁区游泳动物群落的物种丰富度、总生物量和总丰度分别为对照区的1.32倍、2.04倍和1.49倍。     

CPUE standardisation and the construction of indices of stock abundance in a spatially varying fishery using general linear models

Construction of annual indices of stock abundance based on catch and effort data remains central to many fisheries’ assessments. While the use of more advanced statistical methods has helped catch rates to be standardised against many explanatory variables, the changing spatial characteristics of most fisheries data sets provide additional challenges for constructing reliable indices of stock abundance. After reviewing the use of general linear models to construct indices of annual stock abundance, potential biases which can arise due to the unequal and changing nature of the spatial distribution of fishing effort are examined and illustrated through the analysis of simulated data. Finally, some options are suggested for modelling catch rates in unfished strata and for accounting for the uncertainties in the stock and fishery dynamics which arise in the interpretation of spatially varying catch rate data.     

Integrating the standardization of catch-per-unit-of-effort into stock assessment models: testing a population dynamics model and using multiple data types

Standardization of catch-per-unit-of-effort (CPUE) data can be integrated into stock assessment methods. We apply this method to the stock of trevally (Pseudocaranx dentex) off the west coast of New Zealand to address: (1) whether the stock assessment model explains all of the annual variation in the CPUE data, and (2) the impact on the assessment results of how the catch-at-age data are weighted. If not all of annual variation in CPUE is explained by the stock assessment model, the assessment may be statistically inadequate. The inadequacy may be in the representation of the population dynamics, in the relationship between CPUE and abundance, or due to additional variation in CPUE left unexplained by the independent variables. Catch-at-age data often have too much influence on the estimated abundance trajectory, so the sample size used in the catch-at-age likelihood function is often reduced when applying age-structured stock assessment methods. The integrated approach automatically places more weight on the CPUE data compared to the catch-at-age data, and may therefore provide an alternative to arbitrarily downweighting catch-at-age data.     

Stock assessment on fishery-dependent data: Effect of data quality and parametrisation for a red snapper fishery

Data availability, and unreported and unregulated fishing are significant obstacles to evaluating stock status, especially in tropical areas. Limitations in data quantity and quality can lead to model misspecification and erroneous data treatments, potentially causing important changes in model outputs and subsequent management implications. Red snapper Lutjanus purpureus (Poey) in French Guiana provides an example of a stock with a long-time series of fishery-dependent data subject to large uncertainty. A flexible catch-at-age model (Stock Synthesis) was applied to the available data and compared to an historically applied assessment approach. Inter-model variability based on different model specifications and data treatments were compared to identify better the status of the resource. Results showed that a major source of uncertainty in the model was the inclusion of a catch-per-unit-effort abundance index with questionable ability to track abundance. The Stock Synthesis model provided a more flexible and viable method than the virtual population analysis approach. Despite large uncertainty, models depicted a similar trend with a notable stock depletion in the late 1990s but with two distinct biomass trends in more recent years depending on the treatment. To reduce uncertainty and preserve this important economic resource, new data collection programmes and management policies are needed.     

Geostatistics in fisheries survey design and stock assessment: models, variances and applications

Over the past 10 years, fisheries scientists gradually adopted geostatistical tools when analysing fish stock survey data for estimating population abundance. First, the relation between model‐based variance estimates and covariance structure enabled estimation of survey precision for non‐random survey designs. The possibility of using spatial covariance for optimising sampling strategy has been a second motive for using geostatistics. Kriging also offers the advantage of weighting data values, which is useful when sample points are clustered. This paper discusses, with fisheries applications, the different geostatistical models that characterise spatial variation, and their variance formulae for many different survey designs. Some anticipated developments of geostatistics related to multivariate structures, temporal variability and adaptive sampling are discussed.     

Considerations of stock structure of yellowfin tuna (Thunnus albacares) in the Indian Ocean based on fishery data

Yellowfin stock structure in the Indian Ocean was studied by using industrial tuna longline fishery data. Three types of test variables were used to detect stock structure, i.e., CPUE, age-specific CPUE, and coefficient of variation for size. Time-series data of test variables were compiled for six sub-areas that were arranged by dividing the whole region systematically along longitude lines every 20 degrees. Then time-series data were smoothed by moving averages, and regressed by simple models. Patterns of time-series trends were graphically and statistically compared to classify homogeneous sub-area groups. Two assumptions were (a) that homogeneous stocks exist longitudinally and overlap in adjacent waters, and (b) that test variables within homogeneous sub-area groups are equally affected, and hence patterns of the time-series trends are similar. After graphical screening for significant sub-area groups, analysis of covariance was applied to test homogeneity of regression parameters representing patterns of the time-series trends. By classifying homogeneous sub-area groups, stock structures were determined at the P <0.05 and P <0.50 levels. The P<0.50 level was recognized as a useful criterion for ‘weak’ test variables since masked or vague structures at the P <0.05 level were likely cleared at this level in many cases. Results of this study and past stock structure studies were reviewed and compared. It was concluded that there are two major and two minor stocks of yellowfin tuna. The two major stocks (the western and the eastern) are located at 40^o-90^oE and 70^o-130^oE respectively. The minor stocks are the far western and the far eastern stocks (the latter possibly being a part of the Pacific stock), which are located westward of 40^oE and eastward of 110^oE respectively. Neighboring stocks are intermingled in adjacent waters.     

Maximum likelihood and Bayesian approaches to stock assessment when data are questionable

This study examines the use of age-structured maximum likelihood and Bayesian approaches for stock assessment of the Namibian monkfish, Lophius vomerinus, resource with questionable data, in which time series are short, abundance indices are variable, and research data conflict with commercial data. Bayesian approaches with both noninformative and informative priors are investigated to determine if they enhance estimation stability. Three data scenarios are assessed: commercial and research survey data, research survey data only, and commercial data only. Both statistical approaches show that resource abundance has decreased with exploitable biomass estimated at approximately 44% of pristine levels. The maximum likelihood and the Bayesian approach with noninformative priors result in similar estimates. As the abundance data contained little information pertaining to possible density dependence within the stock–recruit relationship, only a Bayesian approach with informative priors reduces uncertainty in the steepness parameter h. Estimated management quantities are sensitive both to the set of data sources and whether prior information was informative or not. The strengths of the Bayesian approach include the integration of prior information with uncertain data, the exploration of data conflicts, and the ability to show the uncertainty in estimates of management parameters. Its weakness is that estimation stability is dependent on the choice of priors, which alters some posterior distributions of management quantities.     

Bioeconomic assessment of size separators in Pacific saury fishery

In the middle of the 1990s, Pacific saury fishery vessels began to install “size separators” to selectively land large-size class fish with a higher price. Contrary to expectations, this resulted in removal of the separators in 2006 because fishers believed the separators had contributed to price collapses in the 2000s. The intent of this paper is to investigate the effects of separators on both the fishery economy and stock of Pacific saury by simulating population and economic models under a single framework. For this purpose, we developed (1) an age-structured population dynamics model with stochasticity, and (2) an economic model spanning both price and inventory dynamics with stochasticity, in which each set of model parameters were estimated on the basis of time series data. In a 10-year simulation, the harvest quota was set constant from 20,000 to 400,000 t at intervals of 20,000 t, and the effects of separators were incorporated by controlling the catchability of 0-year-old fish. We found that separators increase the expected yield and reduce the deficit risk for harvests of 140,000 t and smaller. However, separators have the opposite effects for harvests of 160,000 t and larger.     

Estimating uncertainty in fish stock assessment and forecasting

A variety of tools are available to quantify uncertainty in age‐structured fish stock assessments and in management forecasts. These tools are based on particular choices for the underlying population dynamics model, the aspects of the assessment considered uncertain, and the approach for assessing uncertainty (Bayes, frequentist or likelihood). The current state of the art is advancing rapidly as a consequence of the availability of increased computational power, but there remains little consistency in the choices made for assessments and forecasts. This can be explained by several factors including the specifics of the species under consideration, the purpose for which the analysis is conducted and the institutional framework within which the methods are developed and used, including the availability and customary usage of software tools. Little testing of either the methods or their assumptions has yet been done. Thus, it is not possible to argue either that the methods perform well or perform poorly or that any particular conditioning choices are more appropriate in general terms than others. Despite much recent progress, fisheries science has yet to identify a means for identifying appropriate conditioning choices such that the probability distributions which are calculated for management purposes do adequately represent the probabilities of eventual real outcomes. Therefore, we conclude that increased focus should be placed on testing and carefully examining the choices made when conducting these analyses, and that more attention must be given to examining the sensitivity to alternative assumptions and model structures. Provision of advice concerning uncertainty in stock assessments should include consideration of such sensitivities, and should use model‐averaging methods, decision tables or management procedure simulations in cases where advice is strongly sensitive to model assumptions.     

Integrating recreational fisheries data into stock assessment: implications for model performance and subsequent harvest strategies

Understanding the impacts of recreational fishing on commercially fished stocks is becoming increasingly relevant for fisheries managers. However, data from recreational fisheries are not commonly included in stock assessments of commercially fished stocks. Simulation models of two assessment methods employed in Australia's Commonwealth fisheries were used to explore how recreational fishery data can be included, and the likely consequences for management. In a data‐poor management strategy for blue eye trevalla, Hyperoglyphe antarctica (Carmichael), temporal trends in recreational catch most affected management outcomes. In a data‐rich age‐structured stock assessment for striped marlin, Kajikia audax (Philippi), estimates of stock status were biased when recreational catches were large or when the recreational fishery targeted different size classes than the commercial fishery and these data were not integrated into the assessment. Including data from recreational fishing can change perceptions of stock status and impact recommendations for harvest strategies and management action. An understanding of recreational fishery dynamics should be prioritised for some species.     

赤水河鱼类资源量的初步估算

为了解赤水河的鱼类资源现状,于2010年5～6月和9～10月在赤水河赤水镇、赤水市和合江县的3个江段进行了渔获物调查工作。通过统计各江段的渔业捕捞情况,计算年捕捞量。采用体长股分析的方法,对云南光唇鱼(Acrossocheilus yunanensis)、大鳍鳠(Mystus macropterus)和张氏歺鱼又(Hemiculter tchangi)的资源量进行了估算,并以此推算各江段鱼类的总资源量。结果显示,赤水镇江段的鱼类年总资源量为10.76t,其中云南光唇鱼为1.23t;赤水市江段的年总资源量为51.05t,其中大鳍鳠为8.50t;合江县江段的年总资源量为71.37t,其中张氏歺又鱼为4.39t。估算结果可以为赤水河鱼类资源保护措施的制定提供数据参考。     

渤海渔业生物生殖群体结构及其分布特征

根据2004年春季渤海底拖网调查资料,从渔获物的种类组成、渔业资源结构、优势种以及重要鱼类的体长、体重和性腺成熟度等方面分析了渤海渔业生物生殖群体结构,并利用聚类分析法对生殖群体的区域集群进行了研究.结果表明,春季渤海的生殖群体种类仅为51种,资源量指数为1.54kg/网·h,与20世纪80、90年代相比,优势种更替明显,生殖群体结构的小型化、低龄化更加突出;生殖群体区域集群分布明显,渤海中部和渤海湾的种类组成最相近,相似指数达到67.67%.     

Optimal catch capacity and fishing effort in deterministic and stochastic fishery models

This paper is a survey of fisheries economics, aimed mainly at fisheries biologists. The paper begins by reviewing the static theory, which established two major results. (i) Free access leads to over-exploitation, and (ii) the optimal rate of exploitation is less than the maximum sustainable yield rate. The latter could be regarded as an antithesis to the biological doctrine that fish stocks should be managed to give maximum sustainable yield (MSY).Dynamic theory, which is considered next, showed that the optimal rate of exploitation could be either less or greater than the MSY rate. In particular, a higher discount rate was shown to imply a higher rate of exploitation. This, however, ignores the role of capital invested in the harvesting sector. Once it is recognized that a higher discount rate implies a higher required rate of return on capital, the impact of the discount rate on the optimal rate of exploitation becomes ambiguous. The paper examines the impact of the discount rate with and without stock-dependent harvesting costs. This leads on to the question of how the risk of extinction under free access depends on the sensitivity of unit harvesting costs, or catch per unit of effort, to the size of the exploited stock.Finally, stochastic fishery models are briefly considered. The main purpose of this part of the paper is to demonstrate that deterministic fishery models may give poor guidance for managing the stochastic fisheries of the real world, even if risk neutrality and constant prices are assumed. To demonstrate this as clearly as possible, the unit cost of harvesting is assumed to be constant, implying that the optimal rate of exploitation is constant in a deterministic model. First we consider the simple case of time-invariant stochastic catch quotas (no population dynamics), and demonstrate how optimal catch capacity depends on the cost of investing in the necessary equipment. Then we consider population dynamics, where expected future catch quotas depend on how much is being taken presently. Optimal catch capacity depends on the cost of investment in this case as well, but the derivation of optimal harvesting and investment policies becomes more complicated.