Prediction of algal blooming using EFDC model: Case study in the Daoxiang Lake

Algal blooming has become one of the key fields of study on eutrophication of water body recently. The mechanism of algal blooming is still not understood well. However, it is obvious to understand that algal blooming has close relationship with chlorophyll-a. Therefore, if the trends of chlorophyll-a concentration can be simulated accurately, it will be helpful for the prediction of algal bloom events. In this study, a model named Environmental Fluid Dynamics Code (EFDC), which was developed by U.S. Environmental Protection Agency, was described and used to simulate the eutrophication process in the Daoxiang Lake, Beijing. To run the eutrophication model for the Lake, a field sampling was conducted in March-October of 2008 with interval of 10-20 days. Meanwhile, the algal bloom assessment criteria were investigated and the indicator of chlorophyll-a concentration was selected as input for the prediction of algal bloom in the Daoxiang Lake. After model calibration and validation, traditional statistics has been done between modeled results and observed values. The modeled results show that the simulated chlorophyll-a concentration basically agrees with the observed concentration except the later period of station 2# and the average algal bloom prediction accuracy is 63.43%. It was verified that the EFDC model can be used for chlorophyll-a concentration simulation and algal blooming prediction in the Daoxiang Lake.     

Enhancing generic ecological model for short-term prediction of Southern North Sea algal dynamics with remote sensing images

Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration.     

The development of a multi-species algal ecodynamic model for urban surface water systems and its application

An ecodynamic model that can simulate four phytoplankton species has been developed to deal with the unique characteristics of urban river systems which has manmade river profile, flow controlled by gates, severe eutrophication status, and fragile aquatic ecosystem. The ecodynamic model was developed referencing two typical models: the water quality simulation model WASP and ecological model CAEDYM. The model can simulate 11 state variables: dissolved oxygen, carbonaceous biochemical oxygen demand, ammonia nitrogen, nitrate nitrogen, organic nitrogen, inorganic phosphorus, organic phosphorus and four phytoplankton species with zooplankton as a boundary condition. The ecodynamic model was applied to Sihai section of the Beijing urban river system, where serious algal blooms broke out in recent years. The dominant phytoplankton species are Cyanophyta, Chlorophyta, Bacillariophyta, and Cryptophyta. Site-specific data on geometry, meteorology, pollution sources, and existing ecosystem parameters were collected and used for model calibration and verification The model results mimic observed trends of water quality and phytoplankton species succession and can be used for forecasting algal blooms as well as assessment of river management measures.     

一株溶藻细菌对铜绿微囊藻的溶藻机理初探

为确定溶藻细菌S7（Chryseobaterium）对铜绿微囊藻的溶藻方式,分别采用高温灭菌（121~123℃）、离心（10 000 r.min-1）、0.22μm滤膜过滤等方式对S7菌液进行处理,检测其对铜绿微囊藻的去除效果。并通过对溶藻过程中叶绿素a和丙二醛（MDA）含量的测定,藻细胞显微结构的观察和细胞成分的红外光谱分析,初步探讨菌株S7对铜绿微囊藻的作用机理。结果表明,S7是通过释放胞外活性物质间接溶藻,该物质具有很强的热稳定性,不属于蛋白质类物质。该活性物质对铜绿微囊藻的叶绿素a有明显的去除效果,并可导致藻细胞膜脂过氧化产物MDA积累量的显著提高和藻细胞解体。藻细胞红外光谱分析表明,经过溶藻物质作用的藻细胞,其蛋白质结构遭到破坏。通过试验结果,推测出菌株S7的溶藻机理：溶藻物质先损伤铜绿微囊藻的细胞壁和粘质胶被,然后通过改变膜的选择透过性进入藻细胞内部,分解叶绿素a,破坏蛋白质,造成藻体正常生理功能的丧失,最终导致藻细胞破裂。     

A three-component model of phytoplankton size class for the Atlantic Ocean

A three-component model was developed which calculates the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) to the overall chlorophyll-a concentration in the Atlantic Ocean. The model is an extension of the Sathyendranath et al. (2001) approach, based on the assumption that small cells dominate at low chlorophyll-a concentrations and large cells at high chlorophyll-a concentrations. Diagnostic pigments were used to infer cell size using an established technique adapted to account for small picoeukaroytes in ultra-oligotrophic environments. Atlantic Meridional Transect (AMT) pigment data taken between 1997 and 2004 were split into two datasets; 1935 measurements were used to parameterise the model, and a further 241 surface measurements, spatially and temporally matched to chlorophyll-a derived from SeaWiFS satellite data, were set aside to validate the model. Comparison with an independent global pigment dataset (256 measurements) also supports the broader-scale application of the model. The effect of optical depth on the model parameters was also investigated and explicitly incorporated into the model. It is envisaged that future applications would include validating multi-plankton biogeochemical models and improving primary-production estimates by accounting for community composition.     

Modelling the temperature and the phytoplankton distributions at the Aveiro near coastal zone,Portugal

The main objective of this paper is to implement a coupled three-dimensional physical and ecological model for the Aveiro coast, and to apply it to study the temperature and the phytoplankton biomass spatial distributions along the coastal ecosystem. The Aveiro coast is located at Portugal within the upwelling system of the Atlantic Iberian coast, characterized by nutrients availability and phytoplankton biomass accumulation, from April to October. In order to implement the ecological model, its validation was assessed by comparing simulations to data relative to the horizontal and vertical distributions of the temperature, nutrients and phytoplankton biomass, obtained during the CICLOS I survey off the Portuguese coast [Moita, M.T., 2001. Estrutura, Variabilidade e Dinâmica do Fitoplâncton na Costa de Portugal Continental. PhD Thesis. Faculdade de Ciências da Universidade de Lisboa, 272 pp.]. A sensitivity analysis of the model has been performed in order to assess the influence of the main ecological model variables. The simulation results show that the model is capable of predicting realistic the temperature, the nutrients and the chlorophyll-a distributions for the study area. The scenarios evidence the setup of a thermal stratification pattern resulting from the upwelling of deep and rich in nutrients water to the surface layer and a chlorophyll-a maxima extending offshore, along the picnocline and the nutricline. The results confirm the crucial role played by the physical processes in the phytoplankton bloom along the Aveiro coast. They also evidence the close link between the surface phytoplankton distribution and the surface temperature distribution.     

Analysis of spatial and temporal patterns in a large reservoir using water quality and hydrodynamic modeling

Effective management of reservoir water resources demands a good command of ecological processes in the waterbody. In this work the three-dimensional finite element hydrodynamic model RMA10 was coupled to an eutrophication model. The models were used together with a methodology for loads estimation to foster the understanding of such processes in the largest reservoir in Western Europe—the Alqueva. Nutrient enrichment and eutrophication are water quality concerns in this man-made impoundment. A total phosphorus and nitrogen loads quantification methodology was developed to estimate the inputs in the reservoir, using point and non-point source data.Field data (including water temperature, wind, water elevation, chlorophyll-a, nutrient concentration and dissolved oxygen) and estimated loads were used as forcing for simulations.The analysis of the modeling results shows that spatial and temporal distributions for water temperature, chlorophyll-a, dissolved oxygen and nutrients are consistent with measured in situ data.Modeling results allowed the identification of likely key impact factors on the water quality of the Alqueva reservoir. It is shown that the particular geomorphological and hydrological characteristics of the reservoir together with local climate features are responsible for the existence of distinct ecological regions within the reservoir.     

Restoration of the Marine Ecological Environment Along the Charting Coast: Primary Productivity and Biomass Study

Since 1986, when green oysters occurred due to the copper and organic pollution in the Charting coastal area, the government banned all maricultural activity. It has been claimed that growing algae in a polluted environment may clean the water of pollutants and restore the marine ecosystem. to test this hypothesis, in the Charting coastal area a three-year programme (from August 1992 to July 1995) was carried out. the survey programme included environmental components such as salinity, temperature, pH, dissolved oxygen, biological oxygen demand (BOD), particulate organic carbon (POC), heavy metals and ecological indicators such as nutrients, chlorophyll-a, primary productivity. in the first year study, the environmental background data collected was used to select the suitable season and locations for growing large algae transferred from the laboratory to the field study area. Since September 1993, various species of large algae have been cultured. Although some of the growing algae were damaged by a typhoon in August 1994, the impact of the growing algae on the environmental conditions in the area has been monitored throughout. Elsewhere, we have reported that in the algae growing area higher dissolved oxygen with lower values of BOD and POC were found, and the concentrations of heavy metals in both water and sediments decreased. the purpose of this paper is to evaluate the possible impact of growing large algae on the ecological conditions in Charting coastal waters through the period from August 1983 to May 1995. As a result of the positive results obtained, large amounts of algae have again been cultured in the same area during the period from April 29 to May 25, 1995. We expect that inorganic and organic pollutants will be reduced by the algal growth, oyster mariculture will be restored and finally, the fishery resources potential will be increased.     

Restoration of the Marine Ecological Environment Along the Charting Coast: Primary Productivity and Biomass Study

Since 1986, when green oysters occurred due to the copper and organic pollution in the Charting coastal area, the government banned all maricultural activity. It has been claimed that growing algae in a polluted environment may clean the water of pollutants and restore the marine ecosystem. to test this hypothesis, in the Charting coastal area a three-year programme (from August 1992 to July 1995) was carried out. the survey programme included environmental components such as salinity, temperature, pH, dissolved oxygen, biological oxygen demand (BOD), particulate organic carbon (POC), heavy metals and ecological indicators such as nutrients, chlorophyll-a, primary productivity. in the first year study, the environmental background data collected was used to select the suitable season and locations for growing large algae transferred from the laboratory to the field study area. Since September 1993, various species of large algae have been cultured. Although some of the growing algae were damaged by a typhoon in August 1994, the impact of the growing algae on the environmental conditions in the area has been monitored throughout. Elsewhere, we have reported that in the algae growing area higher dissolved oxygen with lower values of BOD and POC were found, and the concentrations of heavy metals in both water and sediments decreased. the purpose of this paper is to evaluate the possible impact of growing large algae on the ecological conditions in Charting coastal waters through the period from August 1983 to May 1995. As a result of the positive results obtained, large amounts of algae have again been cultured in the same area during the period from April 29 to May 25, 1995. We expect that inorganic and organic pollutants will be reduced by the algal growth, oyster mariculture will be restored and finally, the fishery resources potential will be increased.     

A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

The spread of invasive species is a long studied subject that garners much interest in the ecological research community. Historically the phenomenon has been approached using a purely deterministic mathematical framework (usually involving differential equations of some form). These methods, while scientifically meaningful, are generally highly simplified and fail to account for uncertainty in the data and process, of which our knowledge could not possibly exist without error. We propose a hierarchical Bayesian model for population spread that accommodates data sources with errors, dependence structures between population dynamics parameters, and takes into account prior scientific understanding via non-linear relationships between model parameters and space-time response variables. We model the process (i.e., the bird population in this case) as a Poisson response with spatially varying diffusion coefficients as well as a logistic population growth term using a common reaction-diffusion equation that realistically mimics the ecological process. We focus the application on the ongoing invasion of the Eurasian Collared-Dove.     

Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches

In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method; (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique; (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm.     

Zur physiologie der aminbildung bei der marinen rotalge Polysiphonia urceolata

The ceramiaceaen Polysiphonia urceolata rapidly degrades ¹⁴C(U)-L-leucine, added to sea water at a final concentration of 2.5x10^-5 M/l, to isoamylamine. Under experimental conditions, 22% of the total radioactivity is found in the amine within 160 min. The amino acid decarboxylase responsible for this reaction has been characterized by Hartmann (1972a). No other mechanisms of leucine degradation could be detected, and the rate of ¹⁴C-incorporation into algal proteins is considerably lower than that of decarboxylation. The rate of decarboxylation is optimal at a leucine concentration of about 5x10^-5 M/l. The amine formed is found in almost equal amounts in algal extract and environment. No further degradation of isoamylamine could be detected. The amine is a metabolic end product in P. urceolata. When ¹⁴C-isoamylamine is used as a tracer, relatively high amounts of amine are found in the algal extracts. It is supposed that the amine does not accumulate within the algal cells, but rather is bound to the acid polysaccharides of the cell walls by means of ionic exchange. The results strongly suggest that decarboxylation is the main route by which P. ureolata metabolizes amino acids from the environment which are substrates of the decarboxylase. The endogenous amino acid pool does not seem to be available to the enzyme as a substrate source. A possible ecological significance of amino acid decarboxylations is discussed.     

Dynamics of the nitrogen cycle in a lake and its stability

Recent eutrophication of lakes or sea water has caused serious damage to the ecological balance in aquatic systems and to the quality of water for human use. The purpose of this study is to construct a dynamic model of the nitrogen cycle in a lake and to study the dynamic behavior of the various nitrogen forms such as organic, inorganic and plankton in connection with the mechanism of algal blooms in lakes. The dynamics of the system are represented by a system of non-linear differential equations which include the predator-prey relation between plankton types, and are discussed with the stability analysis of the critical points of differential equations. The effects of seasonal changes of environmental parameters are studied with computer simulations.     

大鹏湾中叶绿素-a的多年调查结果及其与环境因子的灰关联分析

依据1998-2009年145个航次的调查资料,简要描述和分析大鹏湾海水中叶绿素-a含量的空间分布和时间变化,并对其与各环境因子之间的灰关联进行分析。结果表明大鹏湾海水中的叶绿素-a含量夏、秋季较高,而冬、春季较低,且表层高于底层,平均为4．6μg-L^-1;由于受到香港和深圳陆源排放的影响,终年吐露港和沙头附近海域的叶绿素-a含量明显高于其他区域。lla（1999-2009）调查期间,香港海区叶绿素-a含量各航次均值的年际变化略呈下降趋势,表明大鹏湾海水的生态环境质量有所改善。灰关联分析结果表明各因子对叶绿素-a含量影响大小的排序为：亚硝酸盐≥硝酸盐≥5d生化需氧量≥磷酸盐≥酸碱度≥氨≥可溶性总氮≥盐度兰可溶性总磷≥溶解氧≥可溶性硅兰温度。     

内蒙古乌梁素海水质时空分布特征

将地质统计学理论与地理信息系统相结合对乌梁素海富营养化指标、有机污染指标和盐化污染指标进行了kriging空间插值,结果表明：从时间角度分析,冬季总氮浓度、总磷浓度、化学需氧量质量浓度明显高于其他季节;叶绿素a质量浓度浓度冬季最低;时空电导率平均值在4.0 ms.cm-1左右波动。从空间角度分析,总氮浓度、总磷浓度、叶绿素a质量浓度呈现出由北向南递减的趋势;夏秋季化学需氧量空间分布与春冬季节相反;冬季电导率空间分布与其他季节明显不同。从浓度大小分析,乌梁素海复合污染已十分严重。     

Model-based analysis of the influence of ecological processes on forest point pattern formation—A case study

Many different spatio-temporal individual-based models (IBM) for forests have been developed for studying the development of trees in space and time. Such models typically depend on various numerical parameters that represent the ecological processes of growth (G), inter-plant competition (C) and birth-and-death (B&D; also called regeneration and mortality). Until now little work has been done to systematically trace the influence of these processes and their model parameters on the spatial structure of forest ecosystems.This paper attempts to fill this gap by addressing an important aspect of forest structure, spatial variability, characterised by the mark variogram as a summary characteristic. The model used was inspired by components of various well-established IBMs including a shot-noise competition field. Time series data from monospecies forests in three different countries of the northern hemisphere provided ecological reference scenarios. Though a case study, the paper's methodology is rather general and can be applied to any model and forest ecosystem.Methods of sensitivity analysis revealed that only a small number of model parameters is crucial for forming spatial variability. Particularly important is the range of competition between trees; with increasing range the variability increases. Growth processes have considerable importance particularly with short observation periods and in young forests, whereas mortality processes become more influential in the long-term. Naturally, these statements depend upon the initial structure and on the length of the observation period.     

Phytoplankton patchiness and their role in the modelled productivity of a large, seasonally stratified lake

Phytoplankton concentration in Lake Kinneret (Israel) has varied up to 10-fold in space and time, with horizontal patches ranging from a couple of kilometres to a basin scale. Previous studies have used a 1D model to reproduce the temporal evolution of physical and biogeochemical variables in this lake. The question that arises then is how appropriate is a 1D approach to represent the dynamic of a spatially heterogeneous system, where there are non-linear dependencies between variables. Field data, a N-P-Z model coupled to both a 1D and a 3D hydrodynamic model, a 1D diffusion-reaction equation and scaling analysis are used to understand the role of spatial variability, expressed as phytoplankton patchiness, in the modelling of primary production. The analysis and results are used to investigate the effect of horizontal variability in the forcing and in the free mechanisms that affect the growth of patterns. The study shows that the use of averaged properties in a 1D approach may produce misleading results in the presence of localised patches, in terms of both concentration and composition of phytoplankton. The reason lies in the fact that the calibration process of ecological parameters in the 1D model appears to be site and process specific. That is, it depends on the pattern's characteristics and the underlying physical processes causing them. And this is a critical point for the success of numerical simulations under spatial variability. In this study, it is also shown that a length scale based on diffusion and growth rate of phytoplankton could be used as a criterion to assess the appropriateness of the 1D assumption.     

Estimating the critical phosphorus loading of shallow lakes with the ecosystem model PCLake: Sensitivity, calibration and uncertainty

There is a vast body of knowledge that eutrophication of lakes may cause algal blooms. Among lakes, shallow lakes are peculiar systems in that they typically can be in one of two contrasting (equilibrium) states that are self-stabilizing: a ‘clear’ state with submerged macrophytes or a ‘turbid’ state dominated by phytoplankton. Eutrophication may cause a switch from the clear to the turbid state, if the P loading exceeds a critical value. The ecological processes governing this switch are covered by the ecosystem model PCLake, a dynamic model of nutrient cycling and the biota in shallow lakes. Here we present an extensive analysis of the model, using a three-step procedure. (1) A sensitivity analysis revealed the key parameters for the model output. (2) These parameters were calibrated on the combined data on total phosphorus, chlorophyll-a, macrophytes cover and Secchi depth in over 40 lakes. This was done by a Bayesian procedure, giving a weight to each parameter setting based on its likelihood. (3) These weights were used for an uncertainty analysis, applied to the switchpoints (critical phosphorus loading levels) calculated by the model. The model was most sensitive to changes in water depth, P and N loading, retention time and lake size as external input factors, and to zooplankton growth rate, settling rates and maximum growth rates of phytoplankton and macrophytes as process parameters. The results for the ‘best run’ showed an acceptable agreement between model and data and classified nearly all lakes to which the model was applied correctly as either ‘clear’ (macrophyte-dominated) or ‘turbid’ (phytoplankton-dominated). The critical loading levels for a standard lake showed about a factor two uncertainty due to the variation in the posterior parameter distribution. This study calculates in one coherent analysis uncertainties in critical phosphorus loading, a parameter that is of great importance to water quality managers.     

污水再生处理工艺中卡马西平的去除过程模拟及其生态风险评价

卡马西平在污水和水环境中广泛存在,且对水生生态系统安全构成风险,因此成为目前研究较多的药品之一。以北京清河再生水厂为例,研究"超滤—臭氧氧化—氯消毒"处理工艺中卡马西平的去除特性,并针对臭氧氧化和氯消毒工艺建立模拟卡马西平去除过程的机理模型。同时,利用美国环境保护署ECOTOX数据库,获取卡马西平对北京市水生生物物种的毒性数据,并基于毒性数据建立物种敏感度分布(species sensitivity distribution,SSD)模型,评价再生水厂出水补给地表水体时卡马西平产生的生态风险。臭氧氧化和氯消毒模型对卡马西平、总有机碳、氨氮等指标的模拟误差总体低于20%,模型的灵敏参数均可以被较好地识别,且其不确定性显著下降。对比7种SSD模型发现,对数正态分布和对数Logistic分布模型较好地拟合了北京市6个物种的卡马西平毒性数据,二者预测得到的总体生态风险期望值分别为7.4%和8.5%。