茅洲河流域水环境治理工程的生态效应研究

评价水环境治理工程对流域水生态环境的影响,可为茅洲河流域进一步的生态修复工作提出建议。对水环境治理初期(2016年5月)和治理期间(2018年8月)茅洲河流域水生态状况进行调查,选取44个采样点,覆盖茅洲河流域的干流以及主要支流,以获取的样本和水质理化数据,对比分析水质、底栖动物群落、浮游藻类及大型水生植物群落变化。结果显示,治理期间茅洲河流域水体化学需氧量(COD)、氨氮(NH_3-N)和总磷(TP)平均浓度分别降低了41.2%、50.6%和66.7%,溶解氧(DO)平均浓度升高了130.8%;底栖动物群落物种多样性增加了53.6%,耐污种类的密度和优势度降低,并在部分样点新增敏感性较高的蜉蝣目、鞘翅目、毛翅目和半翅目水生昆虫类群。大型水生植物种类和分布范围明显增加,流域内分布有挺水植物24种、沉水植物4种、漂浮植物2种、浮叶植物1种。Palmer藻类污染指数指示为重污染的样点减少了56.3%,中污染样点增加了16.3%,轻污染的样点增加了40.0%。BMWP指数评价结果也有好转,最高得分为49。研究表明,治理后的茅洲河流域水污染程度降低,生态环境状况总体有所好转,但流域生态健康状况仍然较差,需进一步开展系统的流域生态修复工作。     

大型底栖动物快速生物评价指数在城市河流生态评估中的应用

为提供更加全面和有效的生态评估方法用以指导城市河流修复和保护,2017年3-4月选择深圳典型城市化区域河流,设置21个监测样点,开展大型底栖动物快速生物评价指数的适用性研究。分别选择生物多样性指数、群落结构指数、敏感性指数和耐污性指数,在评估不同指数适用性的基础上,筛选和构建用于城市河流健康评价的大型底栖动物快速生物评价综合指数。龙岗河大型底栖动物共采集到28科43种,寡毛类是龙岗河的主要优势类群。基于底栖动物群落结构特征对6个大型底栖动物快速生物评估指数进行了比较和分析,其中3种指数较适用于龙岗河城市河流健康评估。在考虑各参数离散度和相关性的前提下,可选择物种数、寡毛类相对丰度和科级耐污生物指数(Family Biotic Index, FBI)构建综合指数用于深圳市河流快速生物评价。健康评价的结果表明龙岗河2个样点为"理想状态",6个样点属于"亚健康"等级,其余13个样点处于"不健康"和"病态"。我国城市河流的有机污染总体较重,以大型底栖动物耐污类群或者敏感类群构建的快速生物评价指数能够较为灵敏地指示河流生态修复成效。     

抚河流域底栖动物群落结构及基于完整性指数的健康评价

为了解抚河流域底栖动物群落结构特征及其健康状况,分别于2017年丰水期(7月)和枯水期(12月)对抚河流域范围内40个样点的大型底栖动物群落进行调查,在此基础上构建丰水期和枯水期底栖动物生物完整性评价指数(B-IBI),对抚河流域水生态系统进行健康综合评价。结果表明,两个水文期共采集到底栖动物28科、54种,其中昆虫纲21种,占总数的38.89%;腹足纲13种,占24.07%;瓣鳃纲10种,占18.52%;甲壳纲、蛭纲、寡毛纲共10种,占18.52%。底栖动物群落结构季节差异不显著,密度组成以腹足纲、甲壳纲和瓣鳃纲为主,米虾属、铜锈环棱螺和河蚬为抚河流域优势种。B-IBI显示,抚河流域健康状况总体尚好,67.65%的样点处于良好以上状态,10.29%的样点处于一般状态,22.06%的样点处于较差或极差状态。健康程度较差或极差的样点主要集中在抚河干流中下游以及支流宝塘水、崇仁河和东乡水,应加强该类水域的综合治理与生态修复。     

赤水河流域秋季底栖硅藻群落结构特征及水质评价

为研究赤水河流域底栖硅藻群落特征及水质状况,2019年9月测定了赤水河流域36个代表性样点的水体理化指标,调查了底栖硅藻群落组成,并应用硅藻指数评价了赤水河流域的水质状况。结果表明：秋季赤水河流域上游的电导率和总磷、总氮浓度均高于下游;调查采集到底栖硅藻29属138种,其中扁圆卵形藻多孔变种(Cocconeis placentula var. euglypta)、变异直链藻（Melosira varians）、极细微曲壳藻（Achnanthes minutissima）和谷皮菱形藻（Nitzschia palea）等为秋季赤水河流域优势种;下游底栖硅藻群落稳定性高于中上游;CCA结果显示可溶活性磷（SRP）和总氮（TN）是影响赤水河流域底栖硅藻群落的主要环境因子。TDI和CEE硅藻指数评价结果表明,赤水河流域水质等级整体为“中等”,55.6%的样点水质等级为“中等”以上,8.3%的样点水质等级为“极差”。     

高黎贡山南段河流生态系统健康评价

研究高黎贡山南段河流生态系统健康状况，以更好地开展生物多样性与生态系统保护工作。2018年11月，调查了高黎贡山南段6条河流22个样点的物理生境、水质和大型底栖无脊椎动物，采用河流水文指标、形态指标、河岸带指标、水质指标和大型底栖无脊椎动物指标对河流生态系统健康状况进行单因子评价，并基于多项指标构建评价体系进行综合评价。结果显示：研究区域内共采集到大型底栖无脊椎动物95个分类单元、33 725头，稀有种（单个物种数量少于338头）81种、占比85.26%，EPT指数高于5的样点19个、占比86.36%，生物多样性处于较高水平；水质状况整体较好，68.18%的样点水质为Ⅱ类水标准，其余样点水质均为Ⅲ类水标准；栖息地环境质量良好，QHEI平均得分为180.36分；综合评价结果表明研究区域内达到健康等级的样点占比为90.9%，河流生态系统整体处于健康状态，老窝河2个样点处于亚健康状态。人类活动已对少数河段的健康状况造成了影响，主要是农牧业活动、河岸河床硬化、筑坝、取水等。建议对相关河段定期开展河流健康评价，根据评价结果调整河流及河岸带的生产和开发活动，减少非必要的渠道化，针对易受干扰河段建立缓冲区，保护河流水生生物多样性。     

济南流域大型底栖动物群落生物完整性评价

为了对济南市流域大型底栖动物群落生物完整性的探究,于2014年春季、夏季和秋季在济南市全流域31个采样站位进行3次大型底栖动物群落样品采集和水体环境因子的野外采样调查。通过分类、鉴定、数据整理与分析,计算得到3次大型底栖动物生完整性评价指数(B-IBI),分析济南市大型底栖动物群落结构和生物完整性指数在时间和空间上的差异,进而对济南市水生态健康状况进行评价。结果显示,济南南部山区位于并渡口-卧虎山水库这条支流大型底栖动物物群落结构比较完整,生物多样性较高,生态环境状况比较健康;济南市主城区人为干扰程度较大,大型底栖动物群落结构破坏严重,生态环境状况较差。     

黄河源典型卵石河床底栖动物的小尺度分布

研究卵石河床上底栖动物的小尺度分布对保护河流生态完整具有重要意义。为了解底栖动物在单个卵石上的分布特征,于2012年7月和2013年6月在黄河源区兰木错曲卵石河床选取6个样点进行底栖动物采样调查,同时对样点环境参数进行监测,对河流水质、底栖动物组成、物种丰富度和卵石表面积进行分析,以揭示底栖动物种数、个体数与卵石表面积的关系,探究大卵石层和卵石夹沙层中的底栖动物群落特征。结果表明,研究河段基本处于自然状态,水质为II类。调查期间共采集底栖动物2门、4纲、9目、16科、28属,在物种组成上,以水生昆虫为主。单个卵石上底栖动物的种数和个体数随着卵石表面积的增加呈幂指数增加,对数函数相关系数R~2分别为0.589、0.655(P0.01)。卵石河床上,卵石夹沙层和大卵石层的物种丰富度(10～13种)差别不大,卵石夹沙层的密度(706～868个/m~2)远高于大卵石层(194～360个/m~2)。大卵石不易随水流运动,更适合附石类底栖动物尤其是毛翅目(Trichoptera)生存,大卵石层毛翅目的物种数(2～5种)和密度(12～87个/m~2)均高于卵石夹沙层(1～2种、1～9个/m~2)。毛翅目对河流生态具有重要意义,大卵石层对维持河流生态健康具有重要作用。     

应用底栖动物完整性指数评价水源地水库溪流健康状态

及时了解水源地水库入库溪流的水生态健康状态对保障供水安全十分重要。依据2010-2011年对浙江省水源地汤浦水库的环境和底栖动物观测资料建立了底栖动物完整性指数(B-IBI)。根据Shannon-Wiener指数、百分比模式相似性指数(PMA)和多元统计分析结果对参照条件进行量化并确立参照点群。从60个候选参数中筛选出6个核心参数参与构建B-IBI指标体系,采用四分法进行量纲的统一,以参照点群25%分位值作为水生态系统健康与否的阈值,并对小于25%的分位值分布范围进行2等分,确立了水源地汤浦水库入库溪流健康评价标准:B-IBI>25.50,健康;B-IBI 12.75～25.50,亚健康;B-IBI<12.75,差。B-IBI分值与溶氧水平和pH显著正相关(P<0.05)。     

小五台水域浮游植物和底栖动物多样性调查分析

基于2016年8月对小五台山的河流、水库、池塘等水体14个样点进行的浮游植物和底栖动物调查,对小五台水生生物的种类组成、均匀度、丰富度及其多样性现状进行了研究,并据此评价小五台水体的水质状况。研究结果表明:小五台水域采集到的浮游植物共有8门109种,其中硅藻门种类占主要优势,占所有物种数的40.3%,绿藻和蓝藻次之。主要底栖动物调查采用定性与定量相结合的方法,鉴定出底栖无脊椎动物34种,隶属于28科32属,并对它们的多样性及分布进行了初步分析。以多样性指数为指标对水体作评价,结果显示大多数采样点水体营养化程度不高,水质总体良好。     

湟水河流域秋季大型底栖动物群落结构及关键影响因子识别

为了解湟水河流域大型底栖动物群落结构特征并识别影响其空间分布的关键环境因子，于2020年9月对湟水河流域25个样点进行了大型底栖动物和环境因子调查采样。结果显示，本次共采集并鉴定出大型底栖动物109（属）种；聚类分析（Bray-Curtis距离）结果显示，依据大型底栖动物群落结构相似性，湟水河25个样点在空间上可以分为3组：第1组样点主要分布在中上游支流，该组指示物种为朝大蚊属1种（Antocha sp.）；第2组样点分布比较广泛，中上游干、支流均有，该组的指示物种为四节蜉属1种（Baetis sp.），第3组样点主要分布在中下游干流，该组指示物种为瑞士水丝蚓（Limnodrilus helveticusi）。大型底栖动物的物种丰度、香农威纳指数、Margalef丰富度指数、四节蜉属1种和瑞士水丝蚓的相对丰度在上下游和干支流之间的空间差异性较大。冗余分析（RDA）结果表明栖息地评分、电导率、亚硝态氮、总磷、浊度和水深是影响湟水河大型底栖动物的关键环境因子。湟水河水生态保护修复策略应当更多地关注次生盐化和营养盐污染防治以及水土保持来提升流域水生态健康状况。     

永定河流域水生态环境质量综合评价

永定河流域是京津冀区域重要水源涵养区和生态屏障。通过对流域30个站点的物理生境、水质理化、水生生物等指标进行评价参数选取、指标赋分及加权求和,获得永定河流域各站点水生态环境质量综合指数,基本可以代表永定河流域水生态环境质量状况。评价结果表明,永定河流域不存在清洁站点,除少数监测站点水生态状况为较清洁外,轻度污染和中度污染站点占据了永定河流域的大部分,可以看出永定河流域整体水生态状况不容乐观,这与该区域生态环境所受外部胁迫程度较强有关。对比了水生态环境质量综合指数与大型底栖动物完整性指数评价结果的吻合性,探讨了利用对永定河流域进行水生态系统状况综合评价的可行性和合理性,以期为河流管理和健康评价提供参考依据。     

供水型水库底栖动物完整性指数的构建

为给水源地水库的生态风险评估提供科学依据和决策支持,根据浙江省和湖北省几个典型水库的调查数据,构建了底栖动物完整性指数（B-IBI）。参考相关文献及调研选取了32个备选参数,经统计分析筛选出8个指示能力较强的参数,构建B-IBI指标体系,分别为香侬-维纳多样性指数（Shan₂）、捕食者类群数量百分比（Pred-Pct）、寡毛类物种数百分比（%OligoTax）、非水生昆虫数量百分比（NonInPct）、Hilsenhoff生物指数（HBI）、收集者物种数百分比（%CllctTax）、收集者数量百分比（CllctPct）和平均物种数量（RichnessPerTaxon）。确立了水库生态系统健康评价标准,并与潜在环境梯度进行了相关性分析。结果表明,该指数很好地反映了潜在环境梯度,用于供水型水库的水生态系统健康评估较为合适。     

A pseudo time‐series reveals the rapid recovery and high variability of benthic macroinvertebrate populations following catchment wildfire

1. The increasing risk of wildfire has focused attention on the timescale of the impact and recovery of river ecosystems and methods for their bioassessment.
2. An 18‐year pseudo time‐series was exploited to document patterns in benthic macroinvertebrate impact and recovery and evaluate the efficacy of alternative metrics to assess fire damage. Macroinvertebrates were surveyed by kick‐sampling and data were collected on river habitats. Details of river catchments and wildfire were collated as a GIS database.
3. Macroinvertebrate richness and abundance recovered rapidly, marked by a phase of dynamic increase, followed by relative stability (0–2 years and 3–18 years, respectively). Across sites, richness and abundance were best explained by time since fire.
4. A biotic index of general river quality was ineffective as an indicator of fire damage. While a metric of K‐selected taxa (Odonata richness) was generally indicative of fire‐affected assemblages, a contrasting metric of r‐selected taxa (percentage of chironomids, baetids, and simuliids) was not.
5. Ordination analysis revealed time as a significant determinant of community structure across sites; however, its overall statistical importance was eclipsed by habitat characteristics (water quality, shade, altitude, and latitude) that were associated with ecological variation across both recently affected sites and the putatively recovered communities.
6. These results highlight the stochastic processes – environmental and ecological – that frame the macroinvertebrate response to wildfire. This probabilistic context emphasizes the difficulties of developing indicator taxa for wildfire bioassessment and reinforces the importance of standardized survey protocols and the use of contrasting metrics in the assessment of wildfire impact on the ecological quality of rivers.

     

Linking geomorphic character,behaviour and condition to fluvial biodiversity: implications for river management

• 1. The River Styles^® framework is a geomorphic approach to the classification of river types, assessment of the physical condition of rivers, and planning of physical rehabilitation. However, the linkages between River Styles and aquatic biodiversity conservation are still only weakly developed.
• 2. In this study, 41 sites in the Bega River basin in New South Wales, Australia, were classified according to River Style and geomorphic condition, and surveyed for four biological assemblages: diatoms, aquatic and semi‐aquatic macrophytes, aquatic macroinvertebrates and fish.
• 3. Each assemblage differed significantly among River Styles. However, in the case of diatoms and fish, these differences could be accounted for by geographic clustering of sites in the same River Style, and a tendency for River Styles to occupy particular altitudinal zones and sizes of streams. This result was attributed to the overriding influences of water quality on diatoms and of altitude‐related variation in water temperature and distance from the ocean on fish. For macrophytes and macroinvertebrates, geomorphic river type appeared to exert a direct influence, probably via variation in physical habitat characteristics.
• 4. Geomorphic condition, judged as good, moderate or poor by reference to the inferred natural condition of each River Style, was also significantly associated with differences in biological assemblages other than fish. Twice as many taxa appeared to favour sites in good geomorphic condition as favoured sites in poor condition. Many of the taxa associated with sites in poor condition are alien taxa introduced to Australia since European settlement.
• 5. These findings imply that protection of reaches that are in good geomorphic condition is likely to be critical for the maintenance of indigenous biodiversity, and that rehabilitation of geomorphic condition can assist in the rehabilitation of native riverine biota.

Copyright © 2006 John Wiley & Sons, Ltd.     

Environmental assessment of boreal rivers using fish data – a contribution to the Water Framework Directive

Abstract A fish‐based assessment method was developed to estimate the ecological status of boreal rivers. Electric fishing data were collected from 902 rapids, together with information on the land use, channel modification and water chemistry. Discriminant function analysis was used to select fish variables that most correctly classified the undisturbed reference sites and human impacted sites into exact classes. The relationship between the level of human alteration and fish metrics was examined. Five metrics were selected for the index: the number of fish species, proportion of sensitive species, proportion of tolerant species, density of cyprinid individuals and the density of age‐0+ salmonids. The value for each metric (between 0 and 1) was calculated according to a point estimate for classical probability. The index is used to estimate the ecological classification of rivers according to the EU Water Framework Directive.