海带多因子生长模型建立研究

大型藻类在生长过程中吸收氮磷营养物质并进行光合作用,从而发挥生态修复和固定二氧化碳的重要作用。海带作为兼具经济价值和生态价值的典型大型藻类,其重要性不言而喻。本研究以海带（Saccharina japonica）为研究对象,以VENSIM可视化软件为平台,通过建立多种环境因子与海带生长的函数关系,构建海带多因子生长数学模型。结果表明,所建模型能够较好的模拟海带在不同环境条件下的生长状态。通过Morris函数计算了模型中各参数的灵敏度,分析了光照、温度和氮磷营养盐对海带生长的影响。研究发现：在海带养殖初期,受光照影响最大;在临近收获期,受高温的限制更为明显。除了养殖规模和养殖密度都比较大的海域,氮磷营养盐一般不会对海带生长产生抑制性影响,当营养盐成为限制因素时,氮营养盐的抑制性影响要大于磷。本研究所建模型可以对不同海区海带的生长状况和影响因素进行模拟和分析,从而为海带养殖海域的管理提供参考和借鉴。     

南海北部海洋生态模型的参数分析及遗传算法优化

海洋生态系统动力学模型是研究海洋生态环境的重要手段。随着模型的发展, 生态参数取值不确定性增加, 对模型结果的影响逐渐增大, 因此模型参数优化显得尤为重要。本研究在南海北部应用一维物理-生态耦合模型, 通过对模型生态参数进行敏感性分析, 获取关键生态参数, 利用遗传算法对参数进行优化。结果表明, 模型中的敏感参数主要集中于浮游植物生长和浮游动物生长、摄食和死亡以及碎屑沉降等过程。针对以上参数利用遗传算法优化, 发现仅加入表层卫星数据, 模型表层和垂向模拟误差分别降低27.80%和21.40%; 加入垂向观测数据, 表层和垂向模拟误差分别降低14.90%和32.70%。遗传算法应用于海洋生态模型的关键参数优化研究, 所获取的参数对模型有明显的改善效果, 提高了耦合模型对生态系统的模拟精度, 为参数优化在三维模型中的应用提供了依据。     

胶州湾围隔浮游生态系统氮、磷营养盐迁移-转化模型研究

通过对目前生态动力学模型的总结和综合,以生态系统中氮、磷营养盐循环为主线,建立了适用于海洋围隔浮游生态系统的多变量的营养盐迁移-转化动力学模型.该模型包括浮游植物、浮游动物、溶解无机态营养盐、溶解有机态营养盐和生物碎屑5个模块,涉及溶解无机氮、磷酸盐、溶解有机氮、溶解有机磷、浮游植物、浮游动物和生物碎屑7个状态变量.分别利用1999年秋季和2000年夏季胶州湾围隔生态实验数据进行了模型和验证工作,成功地模拟了富加营养盐条件下围隔浮游生态系统中氮、磷营养盐生物化学迁移-转化过程,并确定了20余个参数的量值.     

基于半参数回归的DDM内插方法

提出了一种基于半参数回归的数字水深模型(DDM)内插方法。将原始水深数据误差和内插函数的逼近误差分别视作数字水深模型的偶然误差和系统误差部分,构建DDM内插的半参数回归模型;基于距离法与L曲线法,分别确定正规化矩阵R与平滑因子α;采用按方位取点的加权平均法,估计内插函数在任意节点处的逼近误差。实验结果表明:所提方法提高了DDM的构建质量;海底地形复杂程度越大,所提方法对DDM构建质量的提高程度越大。     

莱州湾围隔浮游生态系统氮、磷营养盐迁移-转化模型研究

通过对目前生态动力学模型的总结和综合，以生态系统中氮、磷营养盐循环为主线，建立了适用于海洋围隔浮游生态系统的多变量的营养盐迁移-转化动力学模型。该模型包括浮游植物、浮游动物、溶解无机态营养盐、溶解有机态营养盐和生物碎屑5个模块，涉及溶解无机氮、磷酸盐、溶解有机氮、溶解有机磷、浮游植物、浮游动物和生物碎屑7个状态变量。利用2002年8月末莱州湾围隔生态实验数据进行了模型的验证工作，成功地模拟了富加营养盐条件下围隔浮游生态系统中氮、磷营养盐生物化学迁移-转化过程，并通过灵敏度分析探讨了模型主要状态变量对参数改变的灵敏程度。     

环境因素对胶州湾栽培龙须菜的影响及生长预测模型构建

龙须菜(Gracilariopsis lemaneiformis)是重要的养殖海藻,研究海区栽培状态下龙须菜生长与生态因子变化的响应规律具有重要科学意义,并可以为龙须菜栽培实践和管理提供科学依据。通过对海区实时监测,关注了龙须菜良种(981和鲁龙1号)的生长速率和海区营养盐、水温、光照等因素变化。其中温度、光照、海水溶解碳、氨态氮、磷和pH有显著的变化(p0.05),其余因素变化比较平稳。相关性分析表明,光周期与龙须菜生长具有极显著的相关性(p0.01),硝态氮与龙须菜生长有显著相关性(p0.05)。通过逐步回归的方法构建回归方程:Y_(SGR)=5.794X_(光周期)-76.932(R~2=0.511),来表述龙须菜生长速率与环境因素的关系。     

渤海浮游植物生物量季节变化的模拟研究

在近海生态系统中,浮游植物生物量的季节变化仍然缺乏全面的机制解释。为研究渤海生态系统中浮游植物生物量季节变化的影响机制,建立了1个包括营养盐(无机氮)、浮游植物、浮游动物、底碎屑4种生物变量的箱式模型,模拟了渤海1983年浮游植物生物量的季节变化,再现了浮游植物生物量一年内的双峰分布。通过对模型参数敏感性的定量和定性分析,讨论了模型对不同生物参数的敏感性,发现模型对浮游植物最大生长率、浮游植物最大死亡率、浮游植物吸收营养盐的半饱和系数最敏感。通过一系列数值试验,进一步讨论了理化因子对渤海浮游植物生物量季节变化的影响,发现理化因子的改变不仅影响浮游植物生物量的大小,也决定了其季节变化的特征。     

基于ARMA模型船摇预报的船用稳定平台PID控制算法研究

传统船用稳定平台的PID控制器在闭环调节过程中存在固有的时滞,这会导致稳定平台的稳定精度无法进一步提高,针对此问题提出采用ARMA模型对船的姿态进行预测,经过处理后得到下一时刻稳定平台将要产生的误差,并将此误差作为输入施加到PID控制器中,以实现事先调节,最终达到提高稳定平台的稳定精度的目的。在ARMA模型中,采用最小二乘法对模型的参数进行实时估计,并提出使用预测值的均方误差最小的原则确定模型阶数和单次预测所使用样本数。试验结果表明,ARMA模型的预测结果具有较高的准确度,相对于传统PID控制器而言改进后的PID控制器一定程度上提高了船用稳定平台的稳定精度。     

渤海赤潮藻类生态动力学模型的非线性动力学研究

基于渤海典型赤潮藻类——中肋骨条藻 ,考虑浮游动物的捕食、光照及营养物质的作用 ,建立了渤海湾的浮游动物—藻类—营养物质三者的动力学模型。运用现代非线性动力学理论着重分析了模型的稳定性及分岔行为。研究了多个参数对藻类生长的影响 ,发现某些参数对藻类的生长影响不大 ,而某些参数则会致使藻类模型出现分岔乃至混沌行为 ,并给出了这些参数的阀值 ,这与赤潮的形成 (爆发性增殖 )密切相关 ;并根据渤海湾的赤潮数据进行了有效的数值模拟 ,所得结果对于研究赤潮的形成机理有一定的参考价值     

赤潮藻类营养盐限制方程的非线性动力学研究

以赤潮代表性藻类－硅藻为研究对象，利用生物生长的生化机理，并考虑在海洋富营养化条件下氮和磷的浓度变化对藻类生长的影响及底物消耗和反馈机制，建立了新的藻类生长非线性动力学模型。首次利用现代非线性动力学的方法，研究了其解析解的分岔行为。指出了磷是影响藻类生长的限制营养盐因子，并对模型进行了仿真。文章对赤潮发生的预警和预测有一定的参考价值。     

海马齿对不同盐度水质的碳汇作用以及不同形态氮利用的研究

为探讨海马齿(Sesuvium portulacastrum)对水域环境修复作用,本文研究了水培海马齿对不同盐度水质的碳汇作用以及不同形态氮的利用情况。实验设计0、10、20、30、35盐度梯度,海马齿水培时间82 d,然后测定植株干重、营养元素含量以及积累速率,最后在抑菌与不抑菌条件下研究海马齿根际与铵态氮(NH₄⁺-N)、硝态氮(NO₃^--N)、无机磷(PO₄^3-)以及色氨酸(Trp)吸收转化关系。研究结果表明,盐度10条件下海马齿植株干重、有机元素含量以及积累速率最高,有机碳、有机氮与有机磷积累速率分别为(5.572±1.611)、(0.313±0.058)、(0.057±0.013)mg/(d·ind.),而高盐环境35盐度条件下对海马齿生长造成一定胁迫。盐度0～35范围,海马齿均未出现死亡现象。不同盐度抑菌培养条件下,色氨酸与无机氮共存时均能被能被海马齿利用,色氨酸利用量远高于硝态氮、铵态氮;不抑菌条件下铵态氮则表现出增加的结果。海马齿作用在盐度...     

海洋盐生植物海马齿(Sesuvium portulacastrum)对环境盐度胁迫的耐受性及营养价值综合评价

通过水培实验,系统研究了广泛分布于全球热带和亚热带海岸的多年生匍匐性肉质草本盐生植物海马齿(Sesuvium portulacastrum)在不同盐度培养条件下的生长,探讨其盐环境适应性和适宜栽培盐度,并测定海马齿的营养成分,对其营养价值进行评价。结果表明,海马齿在35和30盐度下的生长受到明显抑制,茎间变短,叶子肉质化程度加重。在0—20盐度条件下能快速生长,是栽培的适宜盐度。海马齿具有高蛋白低脂肪的营养特点,含有丰富的水分,肉质多汁,平均营养价值估算法得出的ANV分数为2.95—2.96,营养综合评分为2,第四类营养等级,总体营养价值高于红萝卜、马铃薯、莴苣笋、大白菜等多种常见蔬菜,属于营养价值稍高的植物。每100g海马齿食用部分,其能量为74.9—93.3k J,水分为93g,灰分为2.6g,碳水化合物为1.4g,蛋白质为3.0g,粗纤维为0.95g;含有亚麻酸和亚油酸两种必需脂肪酸;含有丰富的矿质元素,其含量大小为NaKCaMgPIMnFeZnCuSe,可为人体提供常量及微量元素的补充;维生素E含量最高,β-胡萝卜素次之;含有16种必需氨基酸,种类齐全。谷氨酸含量最高,蛋氨酸含量最低,含有丰富的鲜味氨基酸,其含量占总氨基酸的23.02%。海马齿含有配比合理的丰富必需氨基酸,占总氨基酸的比例为39.39%。其必需氨基酸RAA值为0.19—0.25,RC为0.84—1.09,SRC为90.69,是极具潜力的可开发为高营养绿色保健的野生海洋蔬菜品种。     

越冬前后海马齿脂肪酸和挥发性有机物组成和变化特征

海马齿是一种热带和亚热带盐生植物, 既是传统野生菜蔬, 也在海岸带生态修复中发挥重要作用。北移种植海马齿进行生态修复时, 越冬低温的影响是成功与否的首要关注问题, 其机制尚待解明。脂肪酸在生物耐受低温中发挥作用, 挥发性有机物与脂肪酸代谢关系密切。本研究利用海湾环境中生态修复浮床上的海马齿样品, 重点解析北移种植环境下, 海马齿植株不同部位受越冬影响前后的脂肪酸和挥发性有机物的组成、差异及变化特征。结果显示, 海马齿的花、叶、茎和根样本中, 共检出14种脂肪酸, 根中的脂肪酸种类数相对最多; 多不饱和脂肪酸在花和叶中的含量(平均分别为56.46%和60.23%)总体大于茎和根(平均分别为41.56%和44.45%)。茎、叶中共检出86种挥发性有机物, 蘑菇醇为优势种类。越冬后脂肪酸和挥发性有机物种类数量显著降低, 多不饱和脂肪酸比例在冻伤植株中显著升高; 就植株脂质营养指数而言, 耐受越冬低温的植株其脂质营养品质提高。越冬造成海马齿两类化合物发生显著变化, 其中C18脂肪酸代谢响应有重要贡献, C18: 3(n-3)和蘑菇醇分别是脂肪酸与挥发性物质中最为重要的两个代谢产物, 可能与抗冻应激有密切关系。本研究为推广海马齿种植以构建可持续近海生态修复体系提供了参考。     

Applying Dynamic Energy Budget (DEB) theory to simulate growth and bio-energetics of blue mussels under low seston conditions

A Dynamic Energy Budget (DEB) model for simulation of growth and bioenergetics of blue mussels (Mytilus edulis) has been tested in three low seston sites in southern Norway. The observations comprise four datasets from laboratory experiments (physiological and biometrical mussel data) and three datasets from in situ growth experiments (biometrical mussel data). Additional in situ data from commercial farms in southern Norway were used for estimation of biometrical relationships in the mussels. Three DEB parameters (shape coefficient, half saturation coefficient, and somatic maintenance rate coefficient) were estimated from experimental data, and the estimated parameters were complemented with parameter values from literature to establish a basic parameter set. Model simulations based on the basic parameter set and site specific environmental forcing matched fairly well with observations, but the model was not successful in simulating growth at the extreme low seston regimes in the laboratory experiments in which the long period of negative growth caused negative reproductive mass. Sensitivity analysis indicated that the model was moderately sensitive to changes in the parameter and initial conditions. The results show the robust properties of the DEB model as it manages to simulate mussel growth in several independent datasets from a common basic parameter set. However, the results also demonstrate limitations of Chl a as a food proxy for blue mussels and limitations of the DEB model to simulate long term starvation. Future work should aim at establishing better food proxies and improving the model formulations of the processes involved in food ingestion and assimilation. The current DEB model should also be elaborated to allow shrinking in the structural tissue in order to produce more realistic growth simulations during long periods of starvation.     

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide(a.k.a algal bloom) model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.     

CNOP-P-based parameter sensitivity for double-gyre variation in ROMS with simulated annealing algorithm

Reducing the error of sensitive parameters by studying the parameters sensitivity can reduce the uncertainty of the model,while simulating double-gyre variation in Regional Ocean Modeling System(ROMS).Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)is an effective method of studying the parameters sensitivity,which represents a type of parameter error with maximum nonlinear development at the prediction time.Intelligent algorithms have been widely applied to solving Conditional Nonlinear Optimal Perturbation(CNOP).In the paper,we proposed an improved simulated annealing(SA)algorithm to solve CNOP-P to get the optimal parameters error,studied the sensitivity of the single parameter and the combination of multiple parameters and verified the effect of reducing the error of sensitive parameters on reducing the uncertainty of model simulation.Specifically,we firstly found the non-period oscillation of kinetic energy time series of double gyre variation,then extracted two transition periods,which are respectively from high energy to low energy and from low energy to high energy.For every transition period,three parameters,respectively wind amplitude(WD),viscosity coefficient(VC)and linear bottom drag coefficient(RDRG),were studied by CNOP-P solved with SA algorithm.Finally,for sensitive parameters,their effect on model simulation is verified.Experiments results showed that the sensitivity order is WD>VC>>RDRG,the effect of the combination of multiple sensitive parameters is greater than that of single parameter superposition and the reduction of error of sensitive parameters can effectively reduce model prediction error which confirmed the importance of sensitive parameters analysis.     

A Linked Physical and Biological Framework to Assess Biogeochemical Dynamics in a Shallow Estuarine Ecosystem

The littoral zone of Chesapeake Bay contains a mosaic of shallow vegetated and nonvegetated habitats with biotic components that are sensitive to changes in biological and physical driving factors. Static and dynamic modelling frameworks provide an integrative way to study complex hydrodynamic and biogeochemical processes in linked estuarine habitats. In this study we describe a spatial simulation model developed and calibrated relative to a specific littoral zone, estuarine ecosystem. The model consisted of four distinct habitats that contained phytoplankton, sediment microalgae, Zostera marina (eelgrass), and Spartina alterniflora. There was tidal exchange of phytoplankton, particulate and dissolved organic carbon and dissolved inorganic nitrogen between the littoral zone ecosystem and the offshore channel. Physical exchange and biogeochemical transformations within the habitats determined water column concentrations in each habitat. Predicted subtidal water column concentrations and Z. marina and S. alterniflora biomass were within the variability of validation data and the predicted annual rates of net primary production were similar to measured rates. Phytoplankton accounted for 17%, sediment microalgae 46%, the Z. marina community 24% and S. alterniflora 13% of the annual littoral zone primary production. The linked habitat model provided insights into producer, habitat and ecosystem carbon and nitrogen properties that might not have been evident with stand-alone models. Although it was an intra-ecosystem sink for particulate carbon, the seagrass habitat was a DOC source and responsible for over 30% of the littoral zone carbon and nitrogen primary production. The model predicted that the Goodwin Islands littoral zone was a sink of channel derived POC, but a source of DOC to the surrounding estuary. The framework created in this study of estuarine ecosystem dynamics is applicable to many different aquatic systems over a range of spatial and temporal scales.     

Parameters of JONSWAP spectral model for surface gravity waves—II. Predictability from real data

Monte Carlo simulation of wave spectra was carried out to provide an assessment of JONSWAP spectral model and parameters. The simulation method is found to be satisfactory because (a) it excludes the spectral variability due to geophysical factors from the sampling errors in the spectral estimates and the statistical uncertainty in determining the model parameters; and (b) the simulated spectra can represent ideal spectral estimates where the sampling errors have been minimized by increasing the degrees of freedom of the spectra. The latter (b) allows both the magnitude of sampling errors to be evaluated and errors due to statistical uncertainty to be isolated. Thus, the stimulation study provides a useful error analysis to assess the JONSWAP spectral model and parameters. For instance, it is found from the results that the sampling errors could be as high as 20% while errors due to uncertainty in determining the model parameter could be as high as 17%. However, the overall errors may be reduced to the minimum of approx. 15% if the simulated spectra have 80 degrees of freedom and constant values of σ_a and σ_b i.e. σ_a = 0.07 and σ_b = 0.09. This implies that the maximum accuracy of 85% may be achieved in JONSWAP spectral model even though the α parameter has been underestimated by about 1.5%. The overestimated values of γ might come from the underestimated α and the biased φ_m estimator caused by the statistical uncertainty in the presence of a sharp spectral peak. Although the scale parameters (α and φ_m) exhibit smaller errors and variability than the shape parameters (ψ, σ_a and σ_b), they are more sensitive to the degrees of freedom of the spectra and their estimators are not better than the estimators of shape parameters. The simulation experiments have also shown that simulated spectra at 20–40 degrees of freedom contain a substantial amount of sampling errors. Therefore, the measured wave spectra at the same degrees of freedom (20–40) are not suitable and should not be used for evaluating the accuracy of any wave spectral model.     

重金属锌对海洋微藻藻源氨基酸产出的影响

锌是海洋微藻生长必需的金属元素,低浓度时可促进微藻的生长,而在高浓度时则表现为抑制其生长。受人类活动的影响,海洋中锌有富集增加的趋势,从而会对海洋微藻的生长产生影响。本论文探究了锌离子以及纳米氧化锌对硅藻中肋骨条藻(Skeletonemacostatum)和新月菱形藻(Nitzschia closterium)生长的影响,特别是对藻源氨基酸产生的影响,结果发现:纳米金属颗粒会通过释放离子的形式抑制海洋浮游植物的生长,中肋骨条藻比新月菱形藻对锌的响应更敏感。锌离子和纳米氧化锌可通过抑制浮游植物的生长来减少氨基酸的释放量和改变藻源氨基酸的种类,从而可能会对海洋氮循环过程产生影响。