阿什河底栖动物群落特征及影响因子

阿什河作为松花江的一级支流,全境包含了从Ⅰ类到劣Ⅴ类的各种类型水质。通过对阿什河沿线底栖动物群落构成进行调查,结合典范对应性分析(CCA)对底栖动物群落与环境因子进行相关性分析得出结论,溶解氧和高锰酸盐指数为研究区域内底栖动物群落构成的主要限制因子。为分析不同水质条件下底栖动物种群变化成因和从生物学角度提出阿什河治理方法提供技术依据。     

一种淡水大型底栖无脊椎动物采样器研究

研制出一种长方体的十字筐采样器,在采样器内分别填装石、砂、底泥和水草4种基质,利用大型底栖无脊椎动物对生境的选择性进行样本被动采集。基质越多,采样器采集的生物种类越多,生物量也更丰富。用新研制的十字筐采样器和传统的篮式采样器对松花江流域7个采样点进行大型底栖无脊椎动物对比采样,结果显示:十字筐采样器是一种优良的采样器,适合在松花江流域乃至全国推广应用。     

应用底栖动物为指示生物的松花江干流水生态预警研究

指示生物监测及水生态预警是利用水环境中指示物种的数量、群落结构指标和个体生理指标等描述水生态系统的健康状态,其相比于常规理化监测和预警更直接地反映水体的生态质量。本研究在松花江干流2012—2015年大型底栖无脊椎动物监测结果的基础上,结合各监测点生态质量管理目标,通过分析物种的种类、出现的频次、物种污染敏感性(耐污值),尝试提出了松花江干流监控断面以底栖动物为指示生物的水生态预警模式,研究思路和结果对流域水环境风险管理指标的拓展有积极作用。     

连云港主要河流大型底栖无脊椎动物水质生物评价

于2008年5月采用D形网半定量采样法调查了连云港市5条河流7个点位的大型底栖无脊椎动物群落多样性,共获得67个大型底栖无脊椎动物分类单元;其中,昆虫纲双翅目18属、蜻蜓目11属;软体动物24种;环节动物4科4属5种。应用典范对应分析(CCA)排序结果将7个样点分成高TN低DO、高电导率和低TN以及高DO和低电导率3组。Shannon-W iener多样性指数、生物指数和COD水质评价结果表明,多样性指数与生物指数和COD评价结果有较大差异,生物指数和COD评价结果较相似。综合评价结果为青口河的水质属于清洁;蔷薇河、淮沭新河、鲁兰河和新沭河属于轻污至中污。生物指数与TN极显著正相关(r=0.913,p=0.004),多样性指数与TN无相关性(r=0.257,p=0.578)。     

Benthic Fluxes and Pore Water Profiles in the Tigullio Gulf

Diffusive fluxes of elements (NO^-₂, NO^-₃, NH⁺₄, SiO₂, PO^3-₄, Cl^-, SO^2-₄, Fe, Mn) have been measured by applying the Fick's first law in two stations of the Tigullio Gulf: the first one characterized by sandy sediments rich in vegetal detritus and the second one, located to within the tourist harbour, characterized by a silty-clay sediments.

Benthic fluxes were measured only in the second station by means of benthic chamber experiments. Although the significant presence of dissolved oxygen in the surface sediments, and the evidence of processes usually occurring in oxidised sediments such as nitrification, both stations also presented characteristics of anoxic sediments such as high oxygen consumption rate and high pore water concentrations of ion, manganese and N-ammonia and reactive orthophosphate.

In both stations, sediments seemed to represent a potential source for most of the chemical species studied, although fluxes were not confirmed for ion, manganese and reactive orthophosphate in benthic chamber experiments.

Diffusive fluxes presented a general agreement for both stations, with higher fluxes of N-nitrate and N-nitrite at the first station were oxidative processes of N-ammonia in the upper layer of the sediments seemed to be more active. the comparison between diffusive and benthic fluxes showed a possible contribution of bioturbation.     

滦河秋季大型底栖动物群落结构空间格局与关键环境影响因子识别

掌握水生生物的空间分布特征及其关键影响因子是科学制定生物多样性保护策略的基础.于2016年秋季对滦河53个样点开展了大型底栖动物和环境因子的现场调查,分析了大型底栖动物群落结构与空间分布特征,并识别出影响大型底栖动物物种空间分布的关键环境因子.结果表明:①滦河（河北省）共采集并鉴定出大型底栖动物206种,隶属于8纲22目70科144属,以纹石蚕（Hydropsyche sp.）和东方蜉蝣（Ephemera orientalis）为优势种.②根据滦河大型底栖动物群落结构相似性,53个样点在空间上被分为3组.第1组分布在滦河干流的中下游及支流下游,无指示物种;第2组分布在支流上游,指示种为纹石蚕、朝大蚊（Antocha sp.）和中华小长臂虾（Palaemonetes sinensis）;第3组分布在滦河干流中上游,指示种为东方蜉蝣和中华齿米虾（Neocaridina denticulate sinensis）.③第3组的分类单元数显著高于第1组和第2组;第1组的多样性指数显著高于第2组;第1组的均匀度指数显著高于其他2组.单因素方差分析（one-way ANOVA）发现,pH、TN、底质、河道变化、水质状况和河岸土地利用类型等环境因子在第2组与第3组之间差异显著,第2组明显高于第3组.典范对应分析（CCA）表明,栖境复杂性、河水水量状况和河岸土地利用类型是影响滦河大型底栖动物空间分布的关键环境因子.研究显示,降低河岸带干扰强度、恢复河道生境多样性是未来滦河大型底栖动物多样性保护恢复的重要管理措施.      

Potential influence of overwintering benthic algae on water quality

Overwintering benthic algae not only directly impact drinking water safety, but also affect the algae recruitment in warm spring seasons. Thus, understanding the characteristics of overwintering benthic algae can provide scientific references for formulating preventative strategies of reasonable water resource. However, they have received less attention. In this study, the spatiotemporal variation of benthic algae and their harmful secondary metabolites were studied from autumn to summer in Qingcaosha Reservoir. Benthic algae (picophytobenthos accounting for 55.42%) had a high biomass during overwintering, and the groups of overwintering benthic algae included pico-Cyanobacteria, pico-Cryptomonas, pico-Chlorophyta, pico-Diatoms, Cyanobacteria, Chlorophyta, Cryptomonas and Diatoms, which were consistent with the planktonic algae species in warm seasons. In oligotrophic or mesotrophic water bodies, micronutrients of iron and manganese were key nutrient factors influencing the biomass of benthic algae. Furthermore, picophytobenthos were important potential contributors of harmful secondary metabolites. The content of microcystins, anatoxin-a, geosmin and 2-methylisoborneol in sediment were 15.75 µg/kg·FW, 48.16 µg/kg·FW, 3.91 ng/kg·FW, and 11.76 ng/kg·FW during winter, which had potential to be released into water bodies to impact water quality. These findings indicate that water quality monitoring programs need to consider sediment in winter as a potential source of toxins and preventative measures to prevent excessive proliferation of algae should be implemented in winter.     

Comparison of macroinvertebrate community structure in urban (Shenzhen City) streams with typical habitat characteristics北大核心CSCD

2020年12月在深圳市城市区域典型生境特征溪流——城市山区源头溪流金龟河、国家地质公园保护区入海溪流杨梅坑河与黑臭水体治理后溪流石溪河,开展底栖动物多样性与生境质量状况取样,通过多元统计分析探明各溪流底栖动物群落结构差异及其主要环境影响因子.结果表明:(1)金龟河底质异质性(SI)最高;杨梅坑河水质最好且流态异质性(Fr)最优,石溪河水质最差且底质异质性(Fr)最低.(2)共采集鉴定大型底栖动物118个分类单元,隶属于3门6纲14目87科.水生昆虫均占绝对优势,其中金龟河67属(81.7%),杨梅坑河62属(95.4%),石溪河12属(52.2%).金龟河中底栖动物Shannon-Wiener多样性指数、改进的Shannon-Wiener多样性指数、Pielou均匀度均高于杨梅坑河与石溪河.(3)金龟河的主要功能摄食类群是滤食者(45.5%),杨梅坑河(38.3%)与石溪河(58.7%)的主要功能摄食类群均为收集者.(4)冗余分析(RDA)结果显示,氨氮、海拔、湿宽、水温、溶氧、底质异质性(SI)、电导率和流态异质性(Fr)为影响深圳市溪流的大型底栖动物群落结构的主要环境因子.研究表明:(1)深圳市的山区溪流可作为深圳市生物多样性保护的重点区域.(2)在城市溪流生态系统中,水环境化学因子并非为主要影响因子,生境多样性发挥了重要作用.(图6表3参43)     

应用O/E模型评价淮河流域典型水体底栖动物完整性健康的研究

本研究尝试采用我国已有的季风气候区底栖动物观测值(O)/期望值(E)比值模型,在无足够数量参照样点的情况下,建立淮河流域O/E指数健康评价指标体系,评价淮河流域典型水体底栖动物物种组成完整性现状.于2014年夏季(8月)和秋季(11月)分别调查了淮河流域20和25个典型水体的底栖动物和水质指标.O/E模型评价结果表明,监测点位在PC(Probabilities of Capture)0和PC≥0.5条件下,夏季和秋季的物种期望丰富度分别约为25和9.所有25个点位中,仅1个点位为健康,其余为一般或较差;模型控制自然梯度后O/E0和O/E50值均没有显著的季节性差异(p=0.565和0.229).环境胁迫因子(TN、EC、CODCr和p H)和土地覆盖数据(水体比例、湿地比例、裸地比例、森林比例和草地比例)对秋季O/E50和O/E50-null的解释量高于夏季,TN是能够解释淮河流域典型水体夏季O/E指数变异最多的环境因子,p H和CODCr是能够解释秋季O/E指数变异最多的环境因子.研究表明,在缺少有效参照点位构建评价指标体系的情况下,在淮河流域应用已经构建的季风气候区底栖动物O/E指数模型进行健康评价是比较可靠的方法.     

Linkages Between Nutrients and Assemblages of Macroinvertebrates and Fish in Wadeable Streams: Implication to Nutrient Criteria Development

We sampled 240 wadeable streams across Wisconsin for different forms of phosphorus and nitrogen, and assemblages of macroinvertebrates and fish to (1) examine how macroinvertebrate and fish measures correlated with the nutrients; (2) quantify relationships between key biological measures and nutrient forms to identify potential threshold levels of nutrients to support nutrient criteria development; and (3) evaluate the importance of nutrients in influencing biological assemblages relative to other physicochemical factors at different spatial scales. Twenty-three of the 35 fish and 18 of the 26 macroinvertebrate measures significantly correlated (P < 0.05) with at least one nutrient measure. Percentages of carnivorous, intolerant, and omnivorous fishes, index of biotic integrity, and salmonid abundance were fish measures correlated with the most nutrient measures and had the highest correlation coefficients. Percentages of Ephemeroptera–Plecoptera–Trichoptera individuals and taxa, Hilsenhoff biotic index, and mean tolerance value were macroinvertebrate measures that most strongly correlated with the most nutrient measures. Selected biological measures showed clear trends toward degradation as concentrations of phosphorus and nitrogen increased, and some measures showed clear thresholds where biological measures changed drastically with small changes in nutrient concentrations. Our selected environmental factors explained 54% of the variation in the fish assemblages. Of this explained variance, 46% was attributed to catchment and instream habitat, 15% to nutrients, 3% to other water quality measures, and 36% to the interactions among all the environmental variables. Selected environmental factors explained 53% of the variation in macroinvertebrate assemblages. Of this explained variance, 42% was attributed to catchment and instream habitat, 22% to nutrients, 5% to other water quality measures, and 32% to the interactions among all the environmental variables.