变参数赤潮藻类生长模型的非线性动力分析研究

在对一个营养盐和赤潮藻类摄食模型进行非线性分析的基础上,提出了含有变参数的赤潮藻类生长模型。模型中用一个周期阶跃函数来近似模拟了藻类生长率参数,并对此模型做了数值模拟。结果表明,引入变参数后的模型更能体现藻类生长的季节性特点,和实际情况符合更好。     

东海原甲藻赤潮的垂向发展过程:生物-物理耦合数值模拟

近年来,东海原甲藻赤潮在我国东海近岸海域频繁发生。本研究利用生物-物理耦合模型对发生于2005年的东海原甲藻赤潮进行后报模拟,并对控制其起始与发展的因素展开研究。该模型由东海原甲藻种群动力学模型与多层嵌套的水动力模型组合。通过对比模拟结果与室内实验结果,证实种群动力学模型能够很好地重现东海原甲藻在不同光照与磷营养限制条件下的生长过程,同时能够再现藻细胞内部磷含量及藻类对外部营养盐浓度的影响。耦合模型能够较好地再现模拟海域水动力（见Sun et al.,2016）与东海原甲藻赤潮的时空分布。模拟的赤潮发展过程与此前研究中的观测结果一致,且模拟结果表明模型能够捕捉到赤潮初期种群的次表层孕育现象。随后模拟结果被用于诊断决定赤潮垂直分布的决定性因素,结果表明磷酸盐是控制这一现象的关键因素。同时,表层风场在决定赤潮的分布中扮演着重要角色。模拟结果强调了营养盐限制在东海原甲藻次表层孕育及消散过程中的作用,本文所建立的耦合模型需要进一步优化并应用于其它条件下东海原甲藻赤潮的研究中。     

一个单种P-Z赤潮生态模型的非线性分析

对植食性浮游动物摄食模型(仅对一个赤潮藻类)进行非线性分析,得出了该确定性参数方程的稳定性条件和发生 Hopf 分岔的条件,并且用数值模拟证实了理论分析.为更好的吻合实际情况,提出了含有变参数的赤潮藻类生长模型.模型中用一个周期函数来近似模拟了藻类生长率参数,并对此模型做了数值模拟.结果表明,引入变参数后的模型能出现概周期解,更能体现藻类生长的季节性特点,与实际情况符合更好.     

大鹏湾的赤潮生态仿真模型

通过海洋动力学和赤潮生物动力学相结合的方法，建立了一个赤潮发生的仿真模型。模型包括水动力、扩用和生物动力学三部分，综合考虑了潮流、营养物质等环境要素的时空变化对赤潮过程的影响，并以大鹏湾夜光藻赤潮为例进行了数值模拟。模型再现了赤潮发生前海水中营养物质的浓度一次明显的增高，而在赤潮发育盛期营养物质降至低谷的现象并反映了赤潮物质容易在海湾的角落等水交换不畅的地域聚集的情况。     

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     

最优插值法在东海赤潮高发区赤潮生消过程数值模拟中的应用

将最优插值法与赤潮数值模型相结合,针对时空分辨率不统一的卫星遥感数据及海洋常规调查数据,进行了东海赤潮高发区海表温度场及海表营养盐浓度场的数据同化研究,并在此基础上进行了该海区春季赤潮过程的数值模拟研究。数据同化结果显示,最优插值数据同化方法不仅在一定程度上修正了海表温度场模拟结果的误差,尤其体现在对赤潮藻的生长影响较大的温度区段18—20℃等值线的南移,而且较为明显地优化了研究海域海表营养盐浓度场,使模拟结果更加接近观测值。对比赤潮过程数值模拟结果发现,在未加同化情况下,海区赤潮藻并未形成大规模赤潮,并且消散较快;而在加入同化后,研究海域交替出现了硅藻及甲藻的大范围赤潮,赤潮生消过程与现场调查数据分析结果较为一致。耦合了最优插值数据同化方法的赤潮数值模型,由于具有改进海洋环境背景场的优势,因此可以在赤潮预报预警工作中得到较好应用。     

基于模糊神经网络(FNN)的赤潮预警预测研究

为研究各种理化因子与赤潮藻类浓度间的非线性对应规律和有效预测赤潮藻类浓度,构建了基于BP 算法的一个四层模糊神经网络模型。将模糊神经网络(FNN)技术引入赤潮预测研究,并与普通 BP 网络、RBF 网络的结果作比较,结果表明,该模型能够较好地反演出各种理化因子与夜光藻密度的非线性对应变化规律,有更好的预测功能。     

基于模糊神经网络(FNN)的赤潮预警预测研究

为研究各种理化因子与赤潮藻类浓度间的非线性对应规律和有效预测赤潮藻类浓度,构建了基于BP算法的一个四层模糊神经网络模型。将模糊神经网络(FNN)技术引入赤潮预测研究,并与普通BP网络、RBF网络的结果作比较,结果表明,该模型能够较好地反演出各种理化因子与夜光藻密度的非线性对应变化规律,有更好的预测功能。     

赤潮预报的人工神经网络方法

基于渤海湾赤潮观测数据(2003年5月~9月),对藻类浓度与环境因子进行了相关性分析,选择出影响藻类浓度的主要环境因子,然后对主要环境因子作主成分分析,在主成分分析的基础上,建立了一个用于赤潮预报的人工神经网络模型。     

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。     

Analysis of temporal and spatial variability of phytoplankton by physical-biological models

I reviewed my research on analysis of temporal and spatial variability of phytoplankton by physical-biological models. This paper was prepared for a lecture of the member awarded the Okada Prize for 1991 from the Oceanographical Society of Japan.Temporal change of phytoplankton in a local upwelling was studied by simulated upwelling experiments conducted with natural phytoplankton communities under natural surface light conditions. Results of the culture experiments was explained by a simple model. This model allows to predict the chlorophyll and nutrient concentration changes in a given upwelled water mass.Above model was verified by a local upwelling observed off Izu, Japan, on May, 1982. Phytoplankton growth and nutrient decrease in surface water of the local upwelling were observed within two days followed by decrease of phytoplankton concentration under depleted nutrient environment. The phytoplankton growth and nutrient decrease could explained by the model with phytoplankton removal rate of about half of the growth rate. Centric diatom was the dominant phytoplankton group and pennate diatom showed less abundance in the upwelled water. Pennate diatom showed fast growth rate when nutrient was abundant and fast decreasing rate after nutrient depleted. On the other hand, flagellate and monads showed relatively slow change of biomass under the change of nutrient concentrations. Furthermore, resting spore formation of centric diatom,Leptocylindrus danicus, was observed in a response to nutrient depletion.Temporal and spatial variability of phytoplankton in the southeastern U.S. continental shelf ecosystem was studied by physical-biological models. First, differences of the biological responses to frontal eddy upwelling during spring and to intrusion during summer was considered by Lagrangian particle tracing experiments with optimally-interpolated flow fields. In spring, particles showed residence time of a few days; however, particles in summer intrusion stayed on the shelf nearly 30 days. It was concluded that difference of particle residence time of upwelled water make the difference of plankton communities. Similar flow fields and particle tracing experiments were used to trace the features in chlorophyll distributions during spring of 1980 derived by Coastal Zone Color Scanner (CZCS). Phytoplankton patchness were created and deformed by frontal eddy events. Eularian physical-biological model was constructed to understand the CZCS-chlorophyll distributions. Statistical comparisons with series of numerical experiments indicate that horizontal advection is an important process for the chlorophyll distributions and that upwelling and associated phytoplankton growth are responsible for the across-shelf gradients and maintenance of concentrations. Furthermore, the CZCS data were assimilated to the model to improve the phytoplankton concentrations, and phytoplankton carbon flux across shelf was estimated. Processes causing the time changes of chlorophyll concentrations were estimated with the model and satellite data further indicated that the both physical and biological forcing is important for the time chages. Several other studies conducted presently were mentioned.     

Modelling the influence of environmental factors on the physiological status of the Pacific oyster Crassostrea gigas in an estuarine embayment; The Baie des Veys (France)

It is well known that temporal changes in bivalve body mass are strongly correlated with temporal variations in water temperature and food supply. In order to study the influence of the year-to-year variability of environmental factors on oyster growth, we coupled a biogeochemical sub-model, which simulates trophic resources of oysters (i.e. phytoplankton biomass via chlorophyll a), and an ecophysiological sub-model, which simulates growth and reproduction (i.e. gametogenesis and spawning), using mechanistic bases. The biogeochemical sub-model successfully simulated phytoplankton dynamics using river nutrient inputs and meteorological factors as forcing functions. Adequate simulation of oyster growth dynamics requires a relevant food quantifier compatible with outputs of the biogeochemical sub-model (i.e. chlorophyll a concentration). We decided to use the phytoplankton carbon concentration as quantifier for food, as it is a better estimator of the energy really available to oysters. The transformation of chlorophyll a concentration into carbon concentration using a variable chlorophyll a to carbon ratio enabled us to improve the simulation of oyster growth especially during the starvation period (i.e. autumn and winter). Once validated, the coupled model was a suitable tool to study the influence of the year-to-year variability of phytoplankton dynamics and water temperature on the gonado-somatic growth of the Pacific oyster. Four years with highly contrasted meteorological conditions (river inputs, water temperature and light) 2000, 2001, 2002 and 2003, were simulated. The years were split into two groups, wet years (2000 and 2001) and dry years (2002 and 2003). Significant variability of the response of oysters to environmental conditions was highlighted between the four scenarios. In the wet years, an increase in loadings of river nutrients and suspended particulate matter led to a shift in the initiation and the magnitude of the phytoplanktonic spring bloom, and consequently to a shift in oyster growth patterns. In contrast, in the dry years, an increase in water temperature—especially during summer—resulted in early spawning. Thus, the gonado-somatic growth pattern of oysters was shown to be sensitive to variations in river loadings and water temperature. In this context, the physiological status of oysters is discussed using a relevant indicator of energy needs.     

渤海春季营养盐限制的现场实验

1999年4－5月，在现场条件下对天然水体中浮游植物以外加营养盐受控培养的方式，研究和探讨春季渤海中部、莱州湾和渤海海峡3个海区的浮游植物生长的营养盐限制问题。结果表明，在莱州湾附近浮游植物生长受到显著的磷限制；尽管水体中硅酸盐浓度较历史水平大大降低，并且实验进行时硅藻为优势种，但是硅酸盐尚不成为限制因子；渤海中部不存在营养盐的限制问题，营养盐浓度和结构相对适宜；渤海海峡也不存在营养盐的限制问题，但是溶解无机氮的相对含量略低。     

Sewage diversion effects on the water column of a subtropical estuary

A study of the phytoplankton community and water column chemistry in Kaneohe Bay, Oahu, Hawaii, before and after the diversion of secondary treated sewage from the bay has shown that changes in total nutrient concentrations in the water column cannot be accurately predicted without taking into account water column-benthos interactions. During the first year after sewage diversion, the decomposition of about 400 tonnes of benthic organisms, primarily filter feeders, resulted in water column dissolved organic nitrogen and phosphorus concentrations roughly an order of magnitude higher than those expected in the absence of such interactions. The biomass of phytoplankton appears to have been N limited both before and after sewage diversion, with internal nutrient recycling accounting for 70–99% of phtyoplankton nutrient uptake. Both the biomass and growth rate of the phytoplankton declined as a result of the sewage diversion, with post-diversion growth rates evidently well below nutrient-saturated values. Since the principal stresses on the bay's coral reef community as a result of the sewage discharges appear to have resulted from the elevated concentrations of plankton in the water, various measures of seston concentration appear to be the most ecologically significant indicators of nutrient enrichment in this system.     

Variability of nutrients and phytoplankton primary production in a shallow macrotidal coastal ecosystem (Arcachon Bay,France)

Seasonal and spatial variations of phytoplankton primary production were studied using a high frequency sampling strategy in the external (ENW) and internal (INW) part of Arcachon Bay, during 2002 and 2003. In order to better assess the availability of nutrients and their relationship with phytoplankton primary production, nutrient variability was studied in relation to environmental conditions and phytoplankton production. During winter, when primary production rates were the lowest, nutrient concentrations were maximal but did not show excessive levels compared to highly urbanised areas. Seasonal and spatial variations of nutrient concentrations (especially DIN-nitrate + nitrite + ammonium- and Si) were largely influenced by Leyre River loads coupled with high tidal exchange with the Atlantic Ocean creating a nutrient gradient between the INW and ENW. By February, diatom growth leads to an early severe nutrient depletion in the entire bay. Examination of nutrient ratios showed that the potential limiting nutrient during spring was P in 2003, and Si in 2002. During summer 2003, N and Si concentrations reached their lowest values, and nutrient ratios revealed a N-deficient environment, more pronounced in the INW. The high Si:N ratios during this period might be explained by (1) important N-uptake by all autotroph communities and (2) benthic-pelagic coupling with high Si regeneration. This study shows that nutrient levels in Arcachon Bay seem to play an important role in the control of phytoplankton primary production rates during the productive period and explain their spatial, seasonal and inter-annual variability. Our estimates of annual integrated phytoplankton primary production (103 g C m⁻² y⁻¹) place this bay within the low to moderate phytoplankton primary production systems.     

Phytoplankton distribution in the Agulhas system from a coupled physical–biological model

The greater Agulhas Current system has several components with high mesoscale turbulence. The phytoplankton distribution in the southwest Indian Ocean reflects this activity. We have used a regional eddy-permitting, coupled physical–biological model to study the physical–biological interactions and to address the main processes responsible for phytoplankton distribution in three different biogeochemical provinces: the southwest Subtropical Indian Gyre (SWSIG), the subtropical convergence zone (SCZ) and the subantarctic waters (SAW) south of South Africa. The biological model with four compartments (Nitrate–Phytoplankton–Zooplankton–Detritus) adequately reproduces the observed field of chlorophyll a. The phase of the strong modelled seasonality in the SWSIG is opposite to that of the SCZ that forms the southern boundary of the subtropical gyre. Phytoplankton concentrations are governed by the source-minus-sink terms, which are one order of magnitude greater than the dynamical diffusion and advection terms.North of 35°S, in the SWSIG, phytoplankton growth is limited by nutrients supply throughout the year. However, deeper stratification, enhanced cross-frontal transport and higher detritus remineralization explain the simulated higher concentrations of phytoplankton found in winter in the SWSIG. The region between 35° and 40°S constitutes a transition zone between the SCZ and the oligotrophic subtropical province. Horizontal advection is the main process bringing nutrients for phytoplankton growth. The front at 34°S represents a dynamical barrier to an extension further to the north of this advection of nutrients.Within the SCZ, primary production is high during spring and summer. This high productivity depletes the nutrient standing stock built up during winter time. In winter, nutrients supply in the convergence zone is indeed large, but the deep mixing removes phytoplankton from the euphotic zone and inhibits photosynthesis, yielding lower surface chlorophyll a concentrations.Waters south of the Subantarctic Front have a summer biomass close to that of frontal waters and higher than for subtropical waters. However, these simulated concentrations are slightly higher than the observed ones suggesting that limitation by iron and/or silica may play a role.     

珠江河口氮和磷循环及溶解氧的数值模拟 Ⅰ.模式建立

为了研究珠江河口营养物质循环和溶解氧,建立了一个生态型水质模式.在该水质模式中营养物质以溶解无机态、碎屑有机物质、底栖物质、浮游植物和浮游动物等5种形态出现,而每种形态均分氮和磷两种形式.水质模式采用三维形式,并与斜压水动力和泥沙模式联立运行.     

Nutrient limitation of phytoplankton growth in the freshwater tidal zone of a turbid,Mediterranean estuary

Identification of the limiting nutrient(s) is a requirement for the rational management of eutrophication. Here, we present the first experimental analysis of nutrient limitation of phytoplankton growth and its seasonal variation in the Guadiana estuary (SE Portugal-SW Spain). Ten microcosm experiments were performed during 2005 and 2008, using water samples collected in the freshwater tidal zone of the Guadiana estuary. Nitrate, phosphate and silicate were added in a single pulse, alone and in combinations. Experimental treatments were incubated for 4 days under controlled laboratory conditions. Phytoplankton response to nutrient enrichment was evaluated through changes in biomass (Chla), and abundance of specific phytoplankton groups.     

Modeling iron limitation of primary production in the coastal Gulf of Alaska

A lower trophic level NPZD ecosystem model with explicit iron limitation on nutrient uptake is coupled to a three-dimensional coastal ocean circulation model to investigate the regional ecosystem dynamics of the northwestern coastal Gulf of Alaska (CGOA). Iron limitation is included in the NPZD model by adding governing equations for two micro-nutrient compartments: dissolved iron and phytoplankton-associated iron. The model has separate budgets for nitrate (the limiting macro-nutrient in the standard NPZD model) and for iron, with iron limitation on nitrate uptake being imposed as a function of the local phytoplankton realized Fe:C ratio. While the ecosystem model represents a simple approximation of the complex lower trophic level ecosystem of the northwestern CGOA, simulated chlorophyll concentrations reproduce the main characteristics of the spring bloom, high shelf primary production, and “high-nutrient, low-chlorophyll” (HNLC) environment offshore. Over the 1998–2004 period, model-data correlations based on spatially averaged, monthly mean chlorophyll concentrations are on average 0.7, with values as high as 0.9 and as low as 0.5 for individual years. The model also provides insight on the importance of micro- and macro-nutrient limitation on the shelf and offshore, with the shelfbreak region acting as a transition zone where both nitrate and iron availability significantly impact phytoplankton growth. Overall, the relative simplicity of the ecosystem model provides a useful platform to perform long-term simulations to investigate the seasonal and interannual CGOA ecosystem variability, as well as to conduct sensitivity studies to evaluate the robustness of simulated fields to ecosystem model parameterization and forcing. The ability of the model to differentiate between nitrate-limited, and iron-limited growth conditions, and to identify their spatial and temporal occurrences, is also a first step towards understanding the role of environmental gradients in shaping the complex CGOA phytoplankton community structure.     

Modelling nitrogen and phosphorus cycles and dissolved oxygen in the Zhujiang Estuary Ⅰ. Model development

wrmcrloxHuman activities related to the population growth and developrnent of industry and rnwhci-pality have led to the incrouing hadings of various POllutants into estudries during the past fewdecades. These increasing edlutant lOadings have caused declined estuallne hedth which can bemereured by a vdriety of indices. In order to obtain solutions to environrnent problerns, re-sources manageTnnt apencies are supporting a holistic approach to envirorirnental management.An effcient strategy t…