基于RepastS平台的太湖水环境系统承载力研究

运用计算实验方法,以计算机为工具,构造太湖水环境系统承载力模型,通过研究水和人类的各主体行为得出太湖水环境系统的整体特征,并通过人口、TP、TN、CODMn承载度来反映。研究结果表明太湖目前点源污染得到了有效控制,但面源污染和城镇生活用水污染尚需要重点治理。实验显示:通过系统参数的调整,将大大改善太湖现有水环境系统。     

太湖北部流域水化学特征及其控制因素

为了解太湖北部流域主要河网区水质受该流域地质状况、岩石和土壤的化学风化作用以及人类活动的影响等方面,对太湖北部流域河网区主要河道水体中的主要离子进行了采样研究。结果表明：太湖北部流域水体中的TDS平均值为355．74mg·L-1,变化范围为276．08--681．54mg·L-1,其中ca2＋和HCO3-是占绝对优势的离子,分别占阳离子和阴离子总量的46．2％和48．9％;其次是Na＋和SO42-,分别占阳离子和阴离子总量的35．9％和27．5％。进而判断出该流域水化学类型是以碳酸盐岩石和蒸发岩来源为主的HCO3-Ca2＋-Na＋型。再从离子的自然起源和人类活动角度分别对水化学类型的控制因素进行分析,一方面利用吉布斯分布模式投点作图得出结论：其离子自然起源的优势机制是岩石的风化作用,而蒸发一结晶和大气降水的输入作用十分微弱,这与该流域的水文、地理、地质背景相一致;另一方面通过SPSS软件的相关关系分析得出结论：NO3-、SO42-、心、ca2＋和Mg2＋的相关性较强,与cl‘也呈正相关,说明水体中这些主要离子都具有共同的来源,其中NO3-的较高含量（平均值为14．74mg·L-1）反映了该流域受人类影响较大。尤其是NO3-与sO42-的相关性达到0．83,再次说明氮污染对该流域水体的酸化和水质变化有较大影响。     

基于环境DNA宏条形码的太湖流域底栖动物监测与生态健康评价

大型底栖动物是生态环境监测和评估的主要目标生物类群之一。环境DNA宏条形码技术的发展为提高底栖动物多样性监测的通量、精准性、标准化程度提供了新的机遇,但该方法在我国尚未有流域尺度的应用先例,其结果的可靠性和对生态环境健康状况的指示性有待检验。率先将环境DNA宏条形码技术用于太湖流域65个点位的底栖动物监测和流域生态健康评价,并与同步进行的形态学监测结果进行了比较。结果表明:①环境DNA方法能检出更多的底栖动物类群,在科、属、种水平上检出的分类单元数分别是形态学监测结果的106%、132%、155%;②基于环境DNA技术的检测方法能够很好地识别形态学监测结果中的优势物种,检出的科级、属级分类阶元能够覆盖形态学监测结果中90%以上的生物量和个体数,同时包含60%以上的物种数;③两种方法对同一物种的检出频次显著相关(R²>0.7,P<0.0001),总体检出一致率达72.3%;④在底栖动物完整性指数(B-IBI)方面,环境DNA方法与形态学方法的计算结果显著相关(R²=0.235,P<0.0001),94%的点位的B-IBI等级划分误差在1级以内,且两种方法的计算结果在底栖动物完整性的流域空间格局描绘上高度重合。综上所述,环境DNA宏条形码技术在太湖流域底栖动物群落监测和评价中的整体应用结果表明,环境DNA监测方法结果可靠,将其进一步规模化应用有望显著提高我国水生态系统生物监测结果的准确性和生态健康评价的技术水平。     

太湖流域有机毒物污染现状与控制对策

富营养化控制一直以来是太湖水污染防治的重中之重,但太湖流域的有机毒物污染也不容忽视,已对饮用水安全构成潜在的威胁。从分析太湖流域工业污染现状入手,提出了化工、印染为太湖流域有机毒物污染的重要来源,阐述了对太湖流域进行有机毒物污染控制的重要性,总结了太湖流域有机毒物污染控制存在的问题,在此基础上,提出了太湖流域工业污染源有机毒物控制对策建议。     

外源输入对底泥疏浚新生表层磷恢复及迁移的影响

外源输入对底泥疏浚新生表层磷恢复及迁移转化的影响尚不清楚,阐明该问题对于底泥疏浚实施后流域尺度上的外源控制及管理具有重要的意义.本研究以太湖梅梁湾沉积物为研究对象,采用野外原位模拟疏浚的方法研究在有无外源颗粒物输入条件下,疏浚前后新生泥水界面磷的迁移转化过程,并探讨疏浚对内源磷释放的控制效果.结果表明,疏浚后阻止外源颗粒物输入对沉积物总磷(TP)和总氮(TN)的控制产生着积极的影响;疏浚显著降低了表层沉积物潜在可移动磷的含量,有外源颗粒物输入组潜在可移动态磷(Mobile-P)含量显著高于无外源组,变化的Mobile-P以铁结合态磷(Fe-P)为主,有机磷(Org-P)次之,弱结合态磷(Lb-P)含量较低不足总磷的1‰;实验210d后,有外源颗粒物输入疏浚组间隙水PO_4~(3-)-P浓度低于未疏浚组,无外源疏浚组显著低于未疏浚组(P 0. 05);无外源疏浚组间隙水PO_4~(3-)-P浓度保持着较低的水平,其余组间隙水中PO_4~(3-)-P浓度呈现先增加后减小的趋势,间隙水PO_4~(3-)-P浓度与其对应分层沉积物中Fe-P含量显著正相关;冬春季间沉积物的源-汇功能发生了转变,沉积物对上覆水由汇转变成为源;疏浚措施降低了底泥内源磷释放速率,可有效控制其内源磷释放,阻止外源颗粒物输入对疏浚控制内源磷负荷起到了较好的促进作用.     

Ecological risk assessment of pesticide residues in Taihu Lake wetland, China

As a major ecosystem type, wetland provides invaluable ecological services. Environmental pollution, especially pesticides pollution should be paid more attention to keep wetlands healthy. Based on the risk quotient method, coupled with a probabilistic risk assessment model, this paper proposed a methodology suitable for ecological risk assessment of pesticide residues for wetland ecosystems. As an important industrializing and ecologically vulnerable area in China, the Taihu Lake wetland was chosen for the case study. The risks of eight pesticides in Taihu Lake wetland were assessed, as single substances and in mixtures. The assessment indicates that risks of the representative species are not significant. In general, the herbicide is found to be more toxic for algae, whereas insecticides pose more risks to zooplankton, insect and fish. For each pesticide in the wetland, the ecological risk it poses is acceptable. But the combined ecological risk posed by mixture can harm more than 10% of species of the wetland ecosystem, mainly dominated by dichlorvos, dimethoate and malathion contributions. These results imply that pesticide residues have been posing pressures on the ecosystem of the Taihu Lake wetland. It is recommended that proper countermeasures should be implemented to reduce the risks.     

太湖和巢湖夏季蓝藻水华期间产毒微囊藻和非产毒微囊藻种群丰度的空间分布

应用荧光定量PCR技术对蓝藻水华暴发期间太湖和巢湖水体中产毒微囊藻和总微囊藻种群丰度的空间分布进行了研究.分别以微囊藻毒素合成基因基因家族成员mcyD和小核糖体16S rDNA序列构建定量PCR标准曲线,研究产毒微囊藻和总微囊藻种群丰度.结果表明:太湖和巢湖微囊藻种群由产毒微囊藻和非产毒微囊藻组成;蓝藻水华暴发期间,微囊藻种群组成及其丰度分布具有明显的空间差异性:太湖产毒微囊藻种群丰度为9.89×104～4.51×106 copies mL-1,产毒微囊藻占总微囊藻种群的比例为20.5%～38.1%;巢湖产毒微囊藻种群丰度为4.12×104～5.44×106 copies mL-1,其占总微囊藻种群的比例为8.4%～96.6%.总的来说,富营养化严重的湖区总微囊藻和产毒微囊藻种群丰度较高,产毒微囊藻占总微囊藻种群的比例也较高.图7表3参29     

应用遥感技术监测和评价太湖水质状况

利用遥感信息和有限的实地监测数据建立了太湖水质参数预测模型 ,该方法可以用于太湖水质污染的预测、分析和评价 ,能够较好地反映水质的空间分布特征 ,尤其适合于大范围水域的快速监测 .研究结果表明 ,利用单波段、多波段因子组合以及主成分分析等手段可以使遥感信息得到更充分的利用 ,从而使预测结果更加精确 .预测结果显示 ,太湖流域已经呈现了严重的富营养化趋势 ,且空间分布不均衡 .东太湖以及靠近无锡和苏州的湖体附近相对污染更为严重 .     

Multivariate Analysis of Interactions Between Phytoplankton Biomass and Environmental Variables in Taihu Lake, China

Phytoplankton variation in large shallow eutrophic lakes is characterized by high spatial and temporal heterogenity. Understanding the pattern of phytoplankton variation and the relationships between it and environmental variables can contribute to eutrophic lakes management. In this study Taihu Lake, one of the largest eutrophic fresh water lake in China, was taken as study area. The water body of Taihu Lake was divided into five regions viz. Wuli bay (WB), Meilian Bay (MB), West Taihu Lake (WTL), Main Body of Taihu Lake (MBTL) and East Taihu Lake (ETL). Concentrations of chlorophyll-a and the related environmental variables were determined in each region in the period 2000–2003. Factor analysis and multivariate analysis were applied to evaluate the interactions between phytoplankton variation and environmental variables. Results showed that the highest average concentrations of TN, TP and Chl-a were observed in WB, followed in a descending order by MB and WTL, and the lowest concentrations of TN, TP and Chl-a were observed in MBTL and ETL. Chl-a and TP concentrations in most regions (except ETL) declined during the study period. It suggested that to some extent the lake was recovering from eutrophication. However, persistent ascending of TN and NH₄–N in all five regions indicated the deteriorating of water quality in the study period. Results of multivariate showed that the relationships between phytoplankton biomass and environmental variables varied among regions. TP illustrated itself a controlling role on phytoplankton in WB, MB, WTL and MBTL according to the significant positive relations to phytoplankton biomass in these regions. Nitrogen could be identified as a limiting factor to phytoplankton biomass in ETL in view of the positive correlations between TN and phytoplankton and between NH₄–N and phytoplankton. Spatial variation of interactions between phytoplankton and environmental parameters suggested proper eutrophication control measures were needed to restore ecological system in each region of Taihu Lake.     

Eutrophication conditions and ecological status in typical bays of Lake Taihu in China

Sampling was conducted at three site groups, group E (in East Taihu Bay), G (in Gonghu Bay) and M (in Meiliang Bay) in Lake Taihu. TN and TP concentrations among site groups was in the increasing order of E < G < M. TP level at G sites is at the critical threshold for loss of submersed macrophytes. Mean values of DO and Transparence showed different trend, i.e., E > G > M. The mean phytoplankton fresh-weight biomass at M sites was 5.81 mg/l, higher than that at E sites (4.96 mg/l) and G sites (5.18 mg/l). Mean zooplankton fresh-weight biomass was in the decreasing order of M (6.4 mg/l) > G (4.9 mg/l) > E (2.7 mg/l). However, Rotifera density was in the sequence of E > G > M. Both zooplankton biomass and phytoplankton biomass increased with the rise of TN and TP concentrations. Relationships between zooplankton biomass and phytoplankton biomass showed that zooplankton played a limited role in the control of algae in eutrophic lakes. Nutrient availability is much more important than zooplankton grazing pressure in controlling phytoplankton growth in lakes. For most sites in Lake Taihu, reduction of nutrient loading, as well as macrophyte conservation, zappears to be especially important in maintaining high water quality and regulating lake biological structure, but for M sites, it’s urgent to control nutrient inputs rather than to restore macrophyte community.