鱼类摄食量的研究方法

鱼类摄食量的评估通常包括对个体摄食量的评估和对种群摄食量的评估。前者主要有室内直接测定法、基于消化道内含物的方法、生物能量学方法、化学污染物质量平衡法以及根据耗氧量间接计算法等5类方法。后者有生物能量学方法和多元回归模型。     

重金属对鱼类早期发育的生态毒理效应

鱼类早期生活阶段对外界环境极为敏感,即使低浓度的污染物暴露也可能对其胚胎发育、仔鱼生长存活造成损害,导致种群数量和质量的降低。研究污染物对鱼类早期生活阶段的毒理效应和机制是揭示污染物对生物种群和水生生态系统潜在风险的有效途径。重金属对鱼类的影响在精、卵发生时即可显现。例如,抑制卵(精)母细胞成熟和精子活力降低,使受精率降低;影响受精卵吸水膨胀过程,改变胚胎发育速率、引起胚胎畸形、影响胚胎心率、改变孵化时间、降低孵化率;影响初孵仔鱼体长、造成仔鱼畸形、影响卵黄囊吸收和胚后仔鱼发育生长、摄食行为等。重金属对鱼类早期发育阶段的毒性效应主要取决于金属种类、暴露浓度和受试鱼种及其发育阶段。此外,外界环境条件等因素也会对重金属的毒性产生显著影响。本研究综合分析国内外关于重金属污染物对鱼类精卵、胚胎、仔鱼等早期发育过程生态毒理效应的研究进展,并结合相关报道阐述了其毒性机制。     

基于QuEChERs-GC/ECD快速检测贝类中有机氯农药及多氯联苯残留

建立基于QuEChERS前处理方法和气相色谱-电子捕获检测器同时测定贝类样品中17种持久性有机污染物残留的方法。样品经QuEChERS法进行预处理,选用已腈为提取剂,N-丙基乙二胺(PSA):C18(4∶6,m/m)净化,外标法定量。17种持久性有机污染物在1.0~50.0μg/kg范围内质量浓度与峰面积呈现良好的线性关系,相关系数均大于0.9957。17种持久性有机污染物的方法检出限(信噪比为3)和定量限(信噪比为10)分别为0.01~0.25μg/kg和0.25~1.0μg/kg。添加浓度为10.0、15.0、25.0μg/kg时,17种持久性有机污染物的平均回收率为84.1%~119.2%,相对标准偏差为3.9%~12.6%。本方法具有快速简便、定量准确,可应用于贝类样品中17种持久性有机污染物的快速检测。     

海洋鱼类摄食生态与食物网研究进展

首先总结归纳了海洋鱼类摄食生态与食物网研究中的实验方法,主要包括胃含物分析法、碳氮稳定同位素法、特定化合物同位素法等实验方法的发展历史和应用现状；随后介绍了海洋鱼类摄食生态与食物网最新研究进展和取得的成绩,主要包括海洋鱼类摄食生态中食物组成、摄食方式、摄食量和食物用于机体各种生命活动分配方式,以及海洋食物网研究中以传统胃含物分析法为基础、以简化食物网为核心,碳氮稳定同位素技术和生态系统模型的应用发展；最后,着重分析了我国海洋鱼类摄食生态和食物网研究中有待解决的问题,并对该领域今后的发展趋势进行了展望。     

重金属对鱼类的危害作用

近年来环境污染成为世人最关注的问题之一。随着科技的进步和社会的发展，工业的三废、农业的杀虫剂以及城市的废弃物等等，使水环境受各种有机污染物、无机污染物、重金属离子和放射性物质的污染，导致水生生物特别是鱼类的生存受到威胁，鱼类易于得病和死亡。重金属作为一类主要的污染物，其对鱼类的毒害作用，也日益受到人们的关注。本文主要就重金属污染对鱼类免疫、呼吸强度、呼吸运动、生理生化作用以及基因毒性等方面的危害作一综述，以进一步提高环保意识，加大对水体重金属污染防治的技术和政策投入力度。１重金属离子对鱼类免疫的…     

黄海鱼类功能群及其对浮游动物捕食的季节变化

用2006年9月-2007年8月对黄海中南部进行的5次断面调查,通过胃含物分析、聚类分析、功能群划分以及估算摄食量等方法,研究了黄海鱼类群落功能群组成及其对浮游动物摄食的季节变化。结果表明,黄海鱼类群落包括7个功能群,除初春以外,黄海鱼类群落主要以浮游生物食性功能群为主。春夏季的功能群组成简单,秋冬季的功能群组成变得复杂。黄海鱼类群落摄食的浮游动物种类主要有11种,春季摄食的浮游动物量最大,夏秋季逐渐减少,直至冬季摄食的浮游动物量最少,初春摄食的浮游动物量有所回升。不同季节摄食的浮游动物种类,以及摄食量都有较大差异,仅太平洋磷虾在各个月份的食物中均有出现,其余浮游动物饵料种类均是季节性的。     

沿黄地区不同养殖鱼类重金属残留特征

为探讨沿黄地区不同养殖鱼类重金属残留特征,利用ICP-MS和AFS方法测定获得沿黄地区4种养殖鱼类中5种重金属含量,统计重金属残留指标,分析评价残留水平和变化特征。结果表明,沿黄地区养殖鱼类体内Pb、Cr、Cd、Cu、As 5种重金属元素的残留存在较大差异,其平均含量分别为0.27,0.45,0.05,1.29,0.07 mg·kg~(-1),从高到低依次表现为CuCrPbAsCd;不同鱼类重金属残留差异明显,整体上表现为上层鱼类重金属残留低于下层鱼类。与《农产品安全质量无公害水产品安全要求》和《食品中污染物限量》中规定的污染物限量标准相比,沿黄地区养殖鱼类重金属残留水平总体较低。     

渤海渔业生物重金属污染及风险评价

重金属污染是渤海长期面临的环境问题之一，同时对渤海海产品安全和人体健康构成潜在风险。为了解渤海海域鱼类重金属污染状况，在该海域采集的渔业生物中随机选取了10种144条鱼类样本，运用电感耦合等离子体质谱法测定了鱼类肌肉组织中重金属Cu、Zn、Pb、Cd、Cr和As的含量；采用单因子污染指数法、内梅罗综合污染指数法和金属污染指数法评价了单一重金属和综合重金属污染情况；采用每日摄入量和目标危害系数评估了渤海鱼类重金属污染对人体的食用安全风险。研究结果显示，渤海鱼类肌肉中重金属Cu、Zn、Pb、Cd、Cr和As的平均含量分别为(0.702±0.680)、(9.697±5.279)、(0.035±0.059)、(0.029±0.035)、(0.093±0.091)和(0.959±0.813) mg/kg。与我国其他海域相比，渤海鱼类重金属含量处于较高水平。鱼类重金属污染评价结果显示，Cd和无机As (iAs)为渤海鱼类重金属污染的主要元素，细纹狮子鱼(Liparis tanakae)受到重金属综合污染的程度最大。食用风险评估结果表明，摄食渤海鱼类带来的重金属每日摄入量处于较低水平，所有鱼类样本单一重金属和综合重金属目标危害系数值均<1，表明正常摄食渤海鱼类不会对消费者构成健康风险。本研究结果有助于加深理解渤海渔业生物的重金属污染状况，同时为保障渤海水产品的食用安全提供科学依据。     

重金属对鱼类危害作用的研究

随着工业的发展，大量的污染物包括重金属排入河流、湖泊和海洋，使水质恶化，严重影响了水产养殖业的发展。主要就重金属污染对鱼类免疫功能、呼吸强度、呼吸运动、生理生化作用、鱼类胚胎发育和仔鱼毒性的影响以及基因毒性等方面的危害作一综述。     

毒性污染物抵达世界最深海洋

<正>我国科学家研究表明,多氯联苯类、多溴联苯醚类、二噁英等毒性有机污染物已抵达世界最深海洋。持久性有机污染物是指通过大气、水等环境介质长距离迁移并长期存在于环境之中、对生物健康和环境具有严重危害的天然或人工合成的有机污染物质,包括多氯联苯类、多溴联苯醚类、双对氯苯基三氯乙烷和二噁英等,它们能在海洋环境中长时间滞留而不分解,且分布十分广泛。由于持久性有机污染物本身具有毒性,并能在食物链中逐级富集和传     

Influence of fish feed composition on oxygen utilization during decomposition of aquaculture effluents

The decomposition of the organic matter, in the form of excess feed and excreted faeces, introduced to the environment by aquaculture can endanger living organisms by lowering oxygen levels. To increase the accuracy of the oxygen utilization assessment, we developed linear (L‐MOD) and non‐linear models (NL‐MOD) for the dynamics of decomposition and accumulation of the organic matter, oxygen utilization and ammonium production. The models are based on mass‐balance stoichiometric reactions for conversion of organic matter into bacterial biomass under aerobic conditions. Organic matter is represented by a general chemical formula sensitive to protein, carbohydrate and lipid content. The mass of organic matter is expressed in chemical oxygen demand (COD) units, providing more convenient tracking of oxygen utilization. Degradable part of the organic matter is distinguished from a non‐degradable part. The model results are compared with the data sets from simulated aquaculture pond experiment.     

Environmentally driven forecasts of northern rock sole (Lepidopsetta polyxystra) recruitment in the eastern Bering Sea

Northern rock sole recruitment in the eastern Bering Sea has been hypothesized to (a) depend on wind‐driven surface currents linking spawning and nursery areas, (b) be density‐dependent, and (c) be negatively impacted by cold bottom temperatures over a large nursery area during the first summer of life. A suite of models was developed to test these hypotheses. Data included 32 years of recruitment and spawning biomass estimates derived from a stock assessment model and wind and temperature indices customized to the environmental exposure of age‐0 northern rock sole in the eastern Bering Sea. The predictive ability of the models was evaluated, and the models were used to forecast recruitment to age‐4 for recent year classes which are poorly retained by the standard multi‐species bottom trawl survey gear. Models which included wind and temperature indices performed better than a naïve forecast based on the running mean. The best‐performing model was a categorical model with wind and temperature thresholds, which explained 49% of the variation in recruitment. Ricker models performed more poorly than models without a spawning biomass term, providing no evidence that recruitment is related to stock size. The models forecast higher recruitment for the most recent year classes (2015–2018) than for prior year classes with observed poor recruitment (2006–2013). These environment‐based recruitment forecasts may improve recruitment estimates for the most recent year classes and facilitate study of the effects of future climate change on northern rock sole population dynamics.     

Population‐level consequences for wild fish exposed to sublethal concentrations of chemicals – a critical review

Concentrated chemical spills have been shown to impact adversely on fish populations and even cause localized population extinctions. Evaluating population‐level impacts of sublethal exposure concentrations is, however, complex and confounded by other environmental pressures. Applying effect measures derived from laboratory‐based chemical exposures to impacts in wild fish populations is constrained by uncertainty on how biochemical response measures (biomarkers) translate into health outcomes, lack of available data for chronic exposures and the many uncertainties in available fish population models. Furthermore, wild fish show phenotypic plasticity and local adaptations can occur that adds geographic and temporal variance on responses. Such population‐level factors are rarely considered in the chemical risk assessment process and can probably be derived only from studies on wild fish. Molecular technologies, including microsatellite and SNP genotyping, and RNASeq for gene expression studies, are advancing our understanding of mechanisms of eco‐toxicological response, tolerance, adaptation and selection in wild populations. We examine critically the application of such approaches with examples including using microsatellites that has identified roach (Rutilus rutilus) populations living in rivers contaminated with sewage effluents that are self‐sustaining, and studies of stickleback (Gasterosteus aculeatus) and killifish (Fundulus heteroclitus) that have identified genomic regions under selection putatively related to pollution tolerance. Integrating data on biological effects between laboratory‐based studies and wild populations, and building understanding on adaptive responses to sublethal exposure are some of the priority research areas for more effective evaluation of population risks and resilience to contaminant exposure.     

A minimal model of the variability of marine ecosystems

In marine ecology, population abundance time series often reveal patterns, such as decadal pseudo-cycles, on scales that make them difficult to mathematically characterize by means of conventional models based on functional responses. We propose here a simple non-deterministic model based on three strong ecological constraints, without any use of functional responses or external factors: (i) mass balance constraints between flows and biomass, (ii) a satiation constraint relating inflows and biomass and (iii) an inertia principle restricting the variation of populations of a given species according to its lifespan. This model reproduces in a robust manner observed patterns of variability and can be used to question the relevance of other modelling approaches of ecosystem dynamics with regard to determinism, constraints and stochasticity. Referring to a non-deterministic model without any functional relationships and environmental or anthropogenic forcing can help in avoiding misleading advice based on the belief that we can explain the causes of observed patterns, which may simply result from basic structural constraints within which the ecosystem functions.     

Understanding what controls the spawning distribution of North Sea whiting (Merlangius merlangus) using a multi‐model approach

The processes that control the spatial distribution of North Sea whiting (Merlangius merlangus) spawning adults are investigated using a statistical multi‐model approach. Models of external and internal controls on the population, such as environmental conditions, spatial constraints, present or past spatial distribution, and demographic state of the population, are evaluated, compared and ranked to select those that are the best able to predict the observed distribution of spawning adults. Model selection is greatly influenced by the selection method, either based on data fitting or prediction, as well as by the threshold value used to stop the selection. Model selection based on prediction tends to select simpler models than selection based on data fitting. The hypotheses underlying the selected models are inferred to play a significant role in controlling North Sea whiting spatial distribution. The multi‐model inference approach developed in this study enables comparison of several theoretical concepts and hypotheses and the results provide important clues on the processes involved in the control of the spatial distribution of whiting. We conclude that whiting has a high spatial fidelity to spawning site which can be linked to either geographical attachment or year‐to‐year persistence of the spatial distribution of the population. Environmental factors – temperature and salinity – appear to influence the geographical extent of spawning whiting distribution, whereas local abundance levels are primarily controlled by internal factors, i.e., population size and spatial segregation between ages.     

Use of ecological niche modelling to predict distributions of freshwater fish species in Kansas

Abstract – An essential innovation in aquatic biodiversity research would be a robust approach to accurately predict species’ potential distributions. In this paper, I conduct an analysis to test the efficacy of ecological niche modelling for predicting fish species’ potential distributions using an artificial‐intelligence algorithm, the Genetic Algorithm for Rule‐Set Prediction (GARP). Models of species’ ecological niches are developed using GARP, and projected onto geography to predict species distributions. To test the validity of this approach, I used freshwater fish distribution data for twelve fish species occurring in Kansas. These taxa were chosen to represent phylogenetic, distribution, and habit diversity. I subset these data by omitting half of the counties from model building, and test models using the omitted counties. Models were tested using Receiver Operating Characteristic (ROC) analyses. Of the species tested, all were statistically significant with the models showing excellent predictive ability. Omission errors across taxa ranged from 0 to 17%. This inferential capacity opens doors to many synthetic analyses based on primary point‐occurrence data.     

运用生物能量学模型预测草鱼生长、饲料需求和污染排放

为预测不同生长阶段草鱼生长性能、饲料需求量和污染排放量,提高草鱼投喂管理水平,本研究运用特定增长率(SGR)、日增长率(DGC)、日均增重(ADG)和热积温系数(TGC)等生长模型计算草鱼在不同生长阶段的生长速率,并通过计算定期采样中实际观测值和预测值最小残差平方和法选出最优生长模型。饲料需求模型通过估算鱼类消化能需求量决定,根据能量收支原理,通过计算鱼体储积能(RE)、基础代谢能(He E)、摄食热增能(Hi E)以及尿液和鳃的代谢能(UE+ZE),来估算草鱼的消化能,再根据所用饲料的消化能含量来确定草鱼对饲料的需求量。草鱼污染物排放主要采用营养物质平衡法计算。在模型验证时,以粗蛋白分别为33%、28%、23%的饲料投喂不同生长阶段的草鱼,将草鱼体质量和饲料系数(FCR)的模型预测值与实际观测值进行比较。结果显示,与其他生长模型(SGR、ADG、DGC)相比,调整后的TGC模型能更精确预测草鱼的生长情况;草鱼体质量和FCR预测值与观测值之间显著相关;每生产1 t鱼(体质量为0.5~2 500 g),其消化能需求量约为1.55×107 k J,消耗1 t饲料或生产1 t鱼所排放的总固态污染物分别为440和623 kg。研究表明,该复合性营养模型可以有效地估计实际养殖中草鱼生长、饲料需求量和污染物排放量,有望为草鱼差异化上市、节省饲料成本、减少饲料浪费以及养殖场的污染评价提供有效的预判工具。     

Metabolic profiling of mussel larvae: effect of handling and culture conditions

Gas chromatography mass spectroscopy was applied to characterize the metabolic profiles of hatchery-reared mussel (Perna canaliculus) larvae before and after a prolonged handling and water exchange process, and to investigate the effect of culture conditions. A decrease in succinate and an increase in alanine were observed after the water exchange, which indicated alterations in energy production and osmotic balance. However, these variations were subtle and it is unlikely that the water exchange practice had any lasting negative effects on larval physiology and performance. Multivariate pattern recognition tools (hierarchical clustering, principal component analysis and projection to latent squares discriminant analysis) were used to assess metabolite variations in larvae reared in low-density static and high-density flow through systems and to construct a culture condition classification model. Twelve metabolites contributed most towards the model, which indicated differences in energy, protein and lipid metabolism. The clear group separations were not represented by observable variations in morphological traits. This suggests that growth performance is metabolically buffered through an adaptive physiological mechanism to provide similar developmental characteristics under these conditions.     

Estimation of genetic parameters from pedigreed populations: lessons from analysis of alevin weight in Coho salmon (Oncorhynchus kisutch)

The purpose of the study was to assess the impact of various model structures on REML estimates of variance components using data on alevin weight from two replicate populations from the Genetic Improvement Program for Coho salmon (Chile). Data consisted of 130 d alevin weight from a dams-nested-within-sires mating design over two consecutive generations. Relationship information included direct and collateral relatives but parental individuals lacked records. The construction of a range of animal models considered random effects of direct additive genetic, maternal additive genetic and full-sib family effects as well as the covariance of direct and maternal genetic effects. Fixed effects of year (generation) and spawn date of dams within year were considered and also evaluated. The relative effectiveness of various models in describing the data set were assessed using likelihood ratio tests. The results demonstrated the importance of the correct interpretation of effects in the data set, particularly those effects that can influence the resemblance between relatives. The data structure, as well as the animal model applied, markedly influenced the magnitude of variance component estimates. Models based on year as the only fixed effect did not describe the data nearly as effectively as models containing both year and spawn data of dams within year. Simple models based on animal as the only random effect gave upward biased estimates of additive genetic variance. The most appropriate model for the data set was one based on both year and spawn date as fixed effects, and animal and full-sib family as random effects. The results from models combining maternal genetic and full-sib family effects to exploit the full covariance structure of the data showed that there was confounding between these variance component estimates. The most consistent interpretation of this result was that common environmental effects and non-additive genetic effects were more important sources of variability than maternal genetic effects. The study also demonstrated high variability in parameter estimates for replicate populations.