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。     

秦淮河上游水体大型底栖无脊椎动物群落结构及水质生物评价

2009年4月用D形网半定量采样法调查秦淮河上游25个点位的大型底栖无脊椎动物群落多样性,共获得63个大型底栖无脊椎动物分类单元;其中,水生昆虫5目12科30属,软体动物9科11属19种,寡毛纲2科7属9种。结果表明,生物指数(Biotic Index,BI)比Shannon-Wiener多样性指数的评价结果更接近实际情况,BI与ρ(TN)(r=0.44,p0.05)和ρ(NH3-N)(r=0.40,p0.05)之间显著相关,Shannon-Wiene多样性指数与ρ(TN)(r=-0.19,p0.05)和ρ(NH3-N)(r=0.44,p0.05)无显著性相关。生物评价表明秦淮河上游水质受到严重污染,句容地区的水质要优于南京。     

江苏地表水体大型底栖无脊椎动物生物多样性状况研究

大型底栖无脊椎动物群落结构与水体水质和水生态系统健康状况关系密切,其受外界干扰后群落结构的变化趋势可以反映水体受污染的性质和程度。2008年,对江苏省主要饮用水源地,长江、京杭大运河等主要河流及太湖等重点湖泊开展底栖动物调查与评价研究,共设置调查点位154个。江苏主要饮用水源地底栖动物的物种数量为78种,主要河流发现底栖动物96种,主要湖泊底栖动物发现65种。从物种多样性指数评价结果看,主要湖泊的底栖生物多样性状况优于地表水源地和主要河流,丰富和较丰富所占比例合计达58%;主要河流的评价结果最差,丰富和较丰富所占比例合计仅达30.7%,存在11.3%物种多样性极贫乏的点位,且大部分水体底栖动物组成以耐污种为主,优势种为极耐污的霍甫水丝蚓,水质状况劣于饮用水源地和主要湖泊。     

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)。     

温榆河底栖大型无脊椎动物与水质评价

2006年10月对北京市温榆河12个采样点底栖大型无脊椎动物调查,并设立十三陵水库为对照点.结果表明,温榆河底栖大型无脊椎动物有三大类组成:水栖寡毛类、水生昆虫幼虫和软体动物等13种,水栖寡毛类中的颤蚓科种类和水生昆虫中的羽摇蚊幼虫为优势种,这些均为耐污种类,耐污染指数都在5以上,平均耐污值为8.底栖动物数量也很高,说明温榆河水体受有机污粢较为严重.通过1HB指数评价结果,认为对照点水质为一般水体,温榆河为污染水体到严重污染水体.     

江苏省太湖流域大型底栖无脊椎动物完整性业务化评价指数构建

为支撑流域水生态目标的业务化管理,提高水生态监测和评价的可操作性,突破物种分类鉴定的技术瓶颈,以大型底栖无脊椎动物为研究对象,在江苏省太湖流域布设120个采样点,于2013年1—3月、7—8月和10—11月开展3次监测。以最小干扰为参照状态,对涉及物种丰度、物种多度组成、耐污能力和摄食类群的72个候选指数进行分布范围、判别能力及相关性分析,结合指数获取的便利性及物种分类的难易程度,最终筛选出3个核心指数构成大型底栖无脊椎动物完整性业务化评价指数,其中湖荡、河流和水库的指数为软体动物分类单元数、优势分类单元相对多度和BMWP指数,溪流的指数为ETO分类单元数、前三位优势分类单元相对多度和BMWP指数。经验证,业务化指数与环境梯度有较好的响应关系,且可操作性强,具备开展业务化应用的前景。但目前的流域水生态目标管理尚处于摸索阶段,技术体系还须在业务化过程中不断修正和完善。     

辽宁省大型底栖无脊椎动物耐污值修订研究

收集整理了2011—2021年辽宁省47个点位的水质理化监测数据和大型底栖无脊椎动物定量监测数据,水质理化监测数据27 368个,大型底栖无脊椎动物样本总量632个,定量监测数据3 180个。合计监测到大型底栖无脊椎动物4门9纲23目85科188属297种,以水生昆虫为主(226种),占总种类数的76.1%;其次为软体动物、环节动物和甲壳动物,分别占12.5%、7.1%和4.0%;扁形动物仅1种,占0.3%。采用累积百分位数法、直接引用法和专家经验法,修订了辽宁省85科188属(合计273个)大型底栖无脊椎动物耐污值。其中,通过计算法得到耐污值135个,直接引用其他地区已建立的耐污值100个,根据专家经验确定耐污值38个。采用参照点位和受损点位的BI箱线图法对该研究和以往辽宁省建立的大型底栖无脊椎动物耐污值数据进行判别能力分析,结果表明,通过计算法确定的耐污值能更好地反映不同环境梯度,其适应性好于仅仅通过专家经验法确定的耐污值。     

城镇化对西苕溪大型底栖动物群落的影响

于2004—2010年5月对西苕溪流域20个参照点,5个中度干扰点以及2个重度干扰点的底栖动物进行了调查,共鉴定出74科190属226个种;受干扰后,底栖动物群落物种丰富度、EPT物种丰富度、Shannon-wiener多样性指数和B-IBI指数显著下降,BI指数显著升高。CCA分析结果表明,参照、中度和重点干扰样点的底栖动物群落差异明显。城镇化引起的溪流水温上升、营养盐升高、泥沙输入量增多和堤岸固化是导致溪流底栖动物群落退化的主要原因。     

淡水大型底栖无脊椎动物监测数据质量的风险管理

基于风险管理方法,从质量管理体系和监测过程两个角度,梳理识别影响淡水大型底栖无脊椎动物监测数据质量的风险事件。通过专家问卷调查对风险事件发生的可能性和严重度评级,建立风险矩阵开展风险综合评价,并制定防控对策。结果共识别出24个风险事件,5个高风险事件,主要与专业技能有关;18个中风险事件,主要与标准规范执行力度和工作经验有关;1个低风险事件,与实验室标准化建设有关。从风险分布上看,高、中风险事件集中在样品采集过程,其次为样品鉴定过程。对此,提出应重点提升监测人员专业技能,全面完善质量管理体系,严格开展样品采集和样品鉴定质控检查,持续改进风险管理方法,形成识别与防控的良性循环。     

瓯江源头区龙泉溪底栖大型无脊椎动物多样性和群落特征

源头区溪流是河流生态系统最脆弱的部分,也是淡水底栖大型无脊椎动物(简称底栖动物)集中分布的热点区域,在流域物种库的形成和生态系统的多样性维持过程中具有不可忽视的作用。然而,目前国内对源头区溪流底栖动物多样性的系统调查研究较少。笔者对位于浙江省丽水市瓯江源头区的龙泉溪进行了底栖动物多样性调查研究,分别于2021年丰水期和平水期在覆盖龙泉溪主要山溪河流的18个样点采样,共采集获得底栖动物标本3 700余号。通过联合使用传统形态分类和DNA条形码技术,共鉴定出底栖动物165种,隶属5门、9纲、19目、68科、124属。联合使用DNA条形码可使底栖动物科、种水平的分辨力提升28.3%和34.1%。调查研究表明:龙泉溪底栖动物多样性丰富,物种组成以节肢动物为主(占比高达87.9%,145种),其中水生昆虫占绝大多数(共计8目、48科、140种,占84.8%),主要优势种为鞘翅目的狭溪泥甲属1种Stenelmis sp.1、毛翅目的纹石蛾属Hydorpsyche和短脉纹石蛾属Cheumatopsyche各1种;底栖动物群落多样性丰富,且在丰水期和平水期均维持在较高的水平;海拔和底质类型等微生境条件对底栖动物多样性分布的影响分析显示,底质类型对底栖动物分布密度的影响显著。对水生态状况的生物评估结果显示:Biotic Index污染生物指数更适合龙泉溪流域的水质健康状况评估,龙泉溪流域整体的水生态状况健康,水质属清洁或极清洁。该研究使用传统形态学和DNA条形码技术相结合的鉴定方式,提高了底栖动物物种鉴定的精度,所获得的多样性调查和水质评价结果为瓯江源头区溪流乃至整个流域的生态保护和长期监测提供了本底基础资料。     

浙江浦阳江大型底栖无脊椎动物物种多样性和生态功能恢复研究

为科学评估河流修复效果,研究修复河流中底栖动物物种多样性和生态功能恢复特征,以浙江省浦江县浦阳江干流为研究对象,分别对2个近自然河段、2个城区修复河段和3个郊区修复河段在修复后1,3,4和5年的水质和底栖动物恢复状况进行调查研究.采用广义最小二乘法(GLS)模型探索底栖动物物种多样性(总物种丰富度、EPT丰富度和Sha...     

基于大型无脊椎动物完整性的赤水河健康评价体系构建

作为长江上游珍稀鱼类国家自然保护区的核心区,赤水河流域水系的健康状况虽颇受关注,但相关评价工作却较少。笔者结合现场调查(2016年)和历史数据(2007年),初步构建基于大型无脊椎动物群落的健康评价体系,对赤水河干流和部分支流的不同季节(春季和秋季)和不同河段(上中下游)的健康状况进行评估。指标筛选结果显示:赤水河上游河段在春季和秋季分别包括6、2个核心参数,中游河段分别包括5、4个,下游包括3、2个核心参数。通过四分法将健康状态划分为4个等级:健康、亚健康、一般和不健康。从整体上看,赤水河处于亚健康状态,且春季和秋季河流不同采样点健康状况有所差异,春季健康状况好于秋季。回归分析显示,BOD_5、COD_(Mn)以及NH~+_4-N是影响赤水河健康的主要环境因子。研究所构建的B-IBI评价指标较好地评估了赤水河的健康状况,可作为赤水河流域水体环境监测的有效手段之一。     

滦河流域大型底栖动物生物完整性指数健康评价

生物完整性指数能够综合反映河流健康状况,是管理者制定科学保护恢复策略的有效评价工具。为全面了解滦河流域水生态健康状况,于2016年10—11月在滦河流域布设53个采样点,同时监测环境数据和大型底栖动物物种数据。通过构建底栖动物生物完整性指数(B-IBI)体系,对53个采样点进行生物完整性健康评价。B-IBI计算结果显示,滦河流域53个采样点中,\"健康\"和\"亚健康\"等级共有24个,\"一般\"等级有12个,\"差\"等级有10个,\"极差\"等级有7个。\"健康\"和\"亚健康\"的采样点多分布在承德市上游和冀东地区的部分干流和支流,而中下游大部分采样点表现为\"差\"和\"极差\"的健康状况。非参数检验结果显示,参照点B-IBI要显著高于受损点,表明所构建的B-IBI评价体系适用于在滦河流域开展河流健康评价。     

Spatial scales and probability based sampling in determining levels of benthic community degradation in the Chesapeake Bay

The extent of degradation of benthic communities of the Chesapeake Bay was determined by applying a previously developed benthic index of biotic integrity at three spatial scales. Allocation of sampling was probability-based allowing areal estimates of degradation with known confidence intervals. The three spatial scales were: (1) the tidal Chesapeake Bay; (2) the Elizabeth River watershed; and (3) two small tidal creeks within the Southern Branch of the Elizabeth River that are part of a sediment contaminant remediation effort. The areas covered varied from 10^–1 to 10⁴ km² and all were sampled in 1999. The Chesapeake Bay was divided into ten strata, the Elizabeth River into five strata and each of the two tidal creeks was a single stratum. The determination of the number and size of strata was based upon consideration of both managerially useful units for restoration and limitations of funding. Within each stratum 25 random locations were sampled for benthic community condition. In 1999 the percent of the benthos with poor benthic community condition for the entire Chesapeake Bay was 47% and varied from 20% at the mouth of the Bay to 72% in the Potomac River. The estimated area of benthos with poor benthic community condition for the Elizabeth River was 64% and varied from 52–92%. Both small tidal creeks had estimates of 76% of poor benthic community condition. These kinds of estimates allow environmental managers to better direct restoration efforts and evaluate progress towards restoration. Patterns of benthic community condition at smaller spatial scales may not be correctly inferred from larger spatial scales. Comparisons of patterns in benthic community condition across spatial scales, and between combinations of strata, must be cautiously interpreted.     

西北江下游河流底栖动物群落健康评价

2020年12月在西北江下游河流设置11个采样点,调查底栖动物群落结构,应用底栖动物完整性指数(B-IBI)评价河流健康状况,并分析B-IBI值与环境因子的关系.结果表明,参照点位的B-IBI值在0.59～4.00之间,处于中等—优状态;受损点位的B-IBI值在0～0.82之间,处于很差—良好状态,其中较差和很差状态占比为87.5％.氨氮浓度与B-IBI值呈现极显著的负相关性,降低水污染负荷是促进底栖动物群落恢复健康的有效途径.在水质已经实现好转的基础上,可通过营造河底卵石生境来促进底栖动物群落恢复,同时也应加强河岸带的修复.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Use of Maryland Biological Stream Survey Data to Determine Effects of Agricultural Riparian Buffers on Measures of Biological Stream Health

This study was undertaken to determine the importance of riparian buffers to stream ecology in agricultural areas. The original Maryland Biological Stream Survey (MBSS) data set was partitioned to represent agricultural sites in Maryland's Coastal Plain and Piedmont regions. ANOVA, multiple linear regression (MLR), and CART regression tree models were developed using riparian and site catchment landscape characteristics. MBSS data were both stratified by physiographic region and analyzed as a combined data set. All models indicated that land management at the site was not the controlling factor for fish IBIs (FIBI) at that site and, hence, using FIBI to evaluate site-scale factors would not be a prudent procedure. Measures of instream habitat and location in the stream network were the dominant explanatory factors for FIBI models. Both CART and MLR models indicated that forest buffers were influential on benthic IBIs (BIBI). Explanatory variables reflected instream conditions, adjacent landscape influence, and chemistry in the Coastal Plains sites, all of which are relatively site specific. However, for Piedmont sites, hydrologic factors were important, in addition to adjacent landscape influence, and chemistry. Both Coastal Plain and Piedmont CART models identified several hydrologic factors, emphasizing the dominant control of hydrology on the physical habitat index (PHI). Riparian buffers were a secondary influence on PHI in the Coastal Plain, but not in the Piedmont. Between 40% and 70% of the variation in FIBI, BIBI, and PHI was explained by the “easily obtainable” variables available from the MBSS data set. While these are empirical results specific to Maryland, the general findings are of use to other locations where the establishment of forest buffers is considered as an aquatic ecosystem restoration measure.     

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。