长山列岛邻近海域鱼类群落种类组成和多样性时空变化

为了解黄、渤海生态系统交错带长山列岛邻近水域鱼类群落种类组成和多样性,根据2016年10月,2017年1月、5月及8月进行的鱼类资源底拖网调查数据,应用相对重要性指数、物种多样性指数、k优势度曲线等方法,研究了长山列岛邻近海域鱼类群落种类组成、物种多样性时空变化及其与环境因子的关系。结果表明: 该海域共计捕获鱼类77种,以温水性、底层、洄游性鱼类为主,优势种组成季节变化明显,春季、冬季主要优势种为黄鮟鱇,夏季以日本鲭、鳀等中上层鱼类为主。全年共计出现洄游性鱼类46种,季节间物种迁移指数均在100以上,其中秋季物种迁移指数最大。鱼类群落物种丰富度指数在春季最高、Shannon多样性指数和均匀度指数在秋季最高。夏季物种丰富度指数与表层水温呈显著负相关;冬季物种丰富度指数与水深、底层水温呈极显著正相关,Shannon多样性指数与底层水温呈极显著正相关。长山列岛邻近海域作为黄、渤海两大生态系统的交错带,鱼类群落表现出高物种多样性、洄游种多以及明显的时空异质性。     

环境DNA技术在长江口鱼类多样性分析中的应用

研究采用高通量测序技术对长江口水域环境DNA(Environmental DNA, eDNA)样品进行分析,并与传统渔业资源调查结果对比,阐述长江口鱼类群落在其生境内的多样性特征,探讨eDNA技术在长江口水域鱼类多样性研究中的应用前景。结果显示, eDNA技术共检测到10目21科41属45种鱼类,各站点鱼类丰富度之间无显著差异,而多样性之间存在显著差异性。底拖网法共捕获11目16科29属33种鱼类。有18种鱼类在两种方法中均检测到,占鱼类总数的30%。两种方法检测到的鱼类中均以鲈形目(Perciformes)最多,其次是鲤形目(Cypriniformes),两种方法的结果均表明刀鲚(Coilia nasus)和凤鲚(Coilia mystus)为优势物种。研究表明环境DNA技术在长江口水域渔业资源监测中具有可行性,在禁捕环境下可根据实际情况采用不同方法对渔业资源进行监测。     

不同环境样本类型对蚌类环境DNA监测的差异研究

为了阐明在使用环境DNA宏条形码技术时不同环境样本类型如何影响蚌类物种的可检测性,于2021年冬季和春季在鄱阳湖分别采集表层水、底层水和沉积物进行环境DNA宏条形码分析,并结合传统方法采集验证。基于环境DNA宏条形码技术共检测到鄱阳湖蚌类33种,传统方法共采集蚌类18种,环境DNA宏条形码技术能检测出传统方法采集到的所有蚌类物种。表层水和底层水注释到的蚌类物种数均分别高于沉积物的,且表层水和底层水注释到的蚌类物种分别完全覆盖沉积物的。基于环境DNA宏条形码技术的蚌类α多样性水平季节差异不显著,但蚌类β多样性水平季节差异显著。表层水和底层水的蚌类多样性均显著高于沉积物样本的, Beta多样性分析也显示水体样本(表层水和底层水分别)和沉积物样本存在显著性差异。但表层水和底层水的蚌类多样性和群落结构均无显著差异。鄱阳湖蚌类群落结构与环境因子的关联分析表明水深(WD)、透明度(SD)、水温(WT)和总氮(TN)显著影响蚌类群落结构。环境DNA宏条形码技术在蚌类的多样性监测中可行,且采水样比采沉积物效果好,表层水和底层水无显著差异。     

基于环境DNA宏条形码技术研究黄河三角洲典型潮沟系统鱼类多样性及其对水文连通性的响应

水文连通对于维护滨海湿地生物多样性至关重要,鱼类多样性作为生物多样性的重要组成部分,了解其对不同水文连通强度的响应具有重要意义。本研究基于环境DNA宏条形码技术(e DNA metabarcoding)检测黄河三角洲典型潮沟系统鱼类多样性,分析鱼类物种分布对不同水文连通强度潮沟生境差异的响应特征。利用12S r RNA经典鱼类引物对采集自三级潮沟系统的水样进行高通量测序,共检测出鱼类55种,其中本地鱼类27种、非本地鱼类28种,物种组成以鲈形目为主。各样点序列丰度均较高的鱼类有矛尾刺虾虎鱼(Acanthogobius hasta)、鮻(Planiliza haematocheilus)、长体刺虾虎鱼(Acanthogobius elongatus)等。鱼类多样性在不同水文连通性潮沟间差异明显,其中,二级潮沟群落多样性水平、丰富度指数、物种种类及各种鱼类类群中的个体均匀程度等都明显高于其他两级潮沟。RDA分析显示有6种环境因子与鱼类群落结构显著相关(P<0.05),分别为:硅酸盐(Si O₃^2––Si)、硝酸盐(NO₃     

胶州湾中部海域春、夏季鱼类群落结构特征

根据2009年3-8月在胶州湾中部海域逐月进行的定点底拖网调查数据,分析了胶州湾春、夏季鱼类群落种类组成,采用生态多样性指数分析了群落物种多样性,并用典范对应分析法研究了鱼类组成与主要环境因子的关系.结果表明：该海域共捕获鱼类43种,隶属于8目24科38属.种类数随底层水温的升高而增加.种类丰富度指数D变化范围为2.440～2.770,多样性指数H变化范围为1.322～2.346,均匀度指数J 变化范围为0.416～0.771,t检验表明春、夏季间各物种多样性指数均差异不显著(P>0.05).种类组成的秩相关性分析表明相邻月份鱼类组成及生物量大小的顺位基本稳定.典范对应分析结果表明影响胶州湾中部海域鱼类种类组成月间变化的主要环境因子为底层水温.     

海州湾及邻近海域冬季鱼类群落结构及其与环境因子的关系

根据2011年冬季在海州湾及邻近海域进行的渔业资源底拖网和环境调查数据,应用物种多样性指数和多元分析等方法,对该海域鱼类种类组成、多样性和群落结构及其与环境因子的关系进行了研究.结果表明: 该海域冬季捕获鱼类共60种,隶属于10目34科51属,以暖温性和暖水性底层鱼类为主.站位间物种丰富度指数介于1.14～2.84,多样性指数介于1.08～2.64,均匀度指数介于0.41～0.83之间.经聚类分析和非度量多维标度(MDS)分析,该海域鱼类群落在空间上可分为站位组Ⅰ(35° N以北水域站位)、站位组Ⅱ(靠近湾顶的近岸水域站位)和站位组Ⅲ(35° N以南水域站位).鱼类群落种类组成在站位组间及两两间的比较均差异极显著(R=0.45～0.91).典范对应分析表明,底层水温、水深和表层盐度是影响海州湾及邻近海域冬季鱼类群落结构的主要环境因子.     

基于环境DNA宏条形码技术的北京地区鱼类多样性调查和外来鱼种入侵风险评估

【目的】调查北京地区鱼类多样性和群落分布及评估外来鱼种的入侵风险。【方法】选取北京地区水库、湖泊和河流3种水体类型共33个采样点,于2020年6月10—17日开展水生态监测,利用环境DNA宏条形码技术对各样点的鱼类多样性和群落结构进行监测和分析,对目前北京地区水生态系统中本地鱼种和外来鱼种进行分类汇总,并评估典型外来入侵鱼种的入侵风险。【结果】本次调查共检测到52种淡水鱼类,隶属于7目22科43属。首先,物种多样性和群落结构(主坐标PCOA分析和相似性ANOSIM分析)结果表明,水库、湖泊和河流3种水体类型的所有鱼类物种多样性和群落结构没有显著差异,不同水体类型中鱼类物种存在同质化现象。优势度分析结果显示,3种水体类型的优势种绝大部分是交叠的,不同水体类型特有的优势种较少。山区自然水体样点的鱼类物种多样性和生物量高于城区各样点,表明人类活动和城市化进程等可能对北京市河流鱼类多样性和群落空间分布产生影响。其次,通过与历史记载比较,北京地区的本地鱼类多样性呈下降趋势。本次检测到39种北京地区的本地原生鱼种,远远低于历史记载(83种)。此外,本次调查发现北京地区外来鱼种的比例大大增加,共检测到13种外来鱼种。其中,尼罗罗非鱼、大口黑鲈、蟾胡鲶、加蓬胡鲶、饰妆铠弓鱼和坦噶尼喀口孵非鲫6种属于外来入侵鱼种。最后,借助FISK V2指标体系对外来入侵鱼类入侵风险进行评估,结果表明,上述6种外来入侵鱼种在北京地区均具有高入侵风险,可对当地物种多样性产生严重影响,需密切关注其种群动态。【结论】本研究利用环境DNA宏条形码技术对北京地区的鱼类多样性开展调查,有助于了解现阶段北京地区鱼类资源的本底数据,同时为原生鱼类的保护和外来入侵鱼类的监管提供科学指导。     

胶州湾海域鱼类群落种类组成及多样性

为了解胶州湾海域鱼类群落结构特征,根据2016—2017年间对胶州湾海域进行的4个航次底拖网调查数据,采用相对重要性指数、生态多样性指数和典范对应分析(canonical correspondence analysis,CCA)、非线性多维标度排序(non-metric multidimensional scaling,NMDS)等方法分析了胶州湾海域鱼类群落的种类组成和多样性特征。结果表明:调查共采集到鱼类46种,隶属2纲10目30科41属,以硬骨鱼纲鱼类为主(45种,97.83%)。其中,鲈形目(Perciformes)最多(22种,47.83%),其次是鲉形目(Scorpaeniformes),占15.22%。种类数季节变化明显,以夏季最高,23种;秋季最低,16种。优势种组成以赤鼻棱鳀(Thryssa kammalensis)、褐菖鲉(Sebastiscus marmoratus)、褐牙鲆(Paralichthys olivaceus)、大泷六线鱼(Hexagrammos otakii)、许氏平鮋(Sebastes schlegeli)和矛尾鰕虎鱼(Chaeturichthys stigmatias)等鱼类为主。多样性分析显示,鱼类物种多样性存在明显的季节差异。多样性指数(H′)季节变化范围为1.668—2.453,以夏季最高,春季最低;均匀度指数(J′)季节变化范围为0.577—0.808,以秋季最高,春季最低;丰富度指数(D′)季节变化范围为2.431—3.123,以冬季最高,秋季最低。典范对应分析表明,水温、盐度、水深和pH是影响胶州湾海域鱼类群落物种组成的主要环境因子,且水温和pH是影响鱼类群落结构及多样性时空变化的主要因子。与历史调查资料相比,由于人类活动对胶州湾生态系统的干扰,鱼类群落结构发生了较大变化,优势种组成更替明显,多样性水平降低,鱼类群落结构趋向简单化。     

太湖鱼类群落结构及多样性

为了解太湖鱼类群落结构和多样性的分布特征,于2009-2010年利用拖网等网具对该水域的鱼类资源进行了调查.结果表明:本次调查共采获鱼类50种,隶属10目15科40属,其中鲤形目种类最多,占总数的68％;鱼类生态类型以湖泊定居性种类为主,群落优势种为湖鲚(Coilia ectenes taihuensis)、间下鱵(Hyporhamphus intermedius)和陈氏短吻银鱼(Salangichthys jordani)等小型鱼类;与历史资料相比,太湖鱼类的物种数量下降,优势种组成发生较大变化,鱼类群落中体质量＜30 g的小型鱼类占绝对优势,渔业资源小型化趋势明显.由于过度捕捞和湖泊环境恶化,鱼类群落生物多样性指数均表现偏低,物种丰富度指数D为1.54,多样性指数H’N、H’w分别为0.21和0.46,均匀度指数J'N、.J'w分别为0.07和0.14;太湖各湖区间鱼类种群和多样性的差别一定程度上反映出鱼类群落结构与湖泊营养盐、透明度等环境特征相适应的特点.     

泉州湾海域鱼类多样性及营养级变化

利用2008年5月和10月在泉州湾进行的拖网渔业资源调查资料, 探讨了该海域鱼类群落结构和物种多样性特征。结果表明, 两次拖网调查共鉴定鱼类54种, 隶属于2纲13目32科。其中中上层鱼类12种, 近底层鱼类19种, 底层鱼类23种; 暖水性鱼类40种, 暖温性鱼类14种, 未发现冷温性和冷水性种类; 杂食性鱼类4种, 低级肉食性鱼类37种, 中级肉食性鱼类8种, 高级肉食性鱼类5种。白姑鱼(Argyrosomus argentatus)和叫姑鱼(Johnius belengerii)是5月份最主要的优势种, 凤鲚(Coilia mystus)和龙头鱼(Harpodon nehereus)是10月份最主要的优势种。与1985年的调查资料相比, 泉州湾鱼类组成和优势种发生了很大的变化, 多样性指数由3.05下降到2.32, 均匀度指数由0.76下降到0.58, 营养级指数由2.79下降到2.54。泉州湾鱼类多样性下降的主要原因可能是过度捕捞、水域污染和栖息地丧失等。     

基于eDNA metabarcoding探究北京市主要河流鱼类分布及影响因素

使用eDNA宏条形码(eDNA metabarcoding)和地笼法检测了北京市3条水系在夏季和秋季两个季节的鱼类多样性, 旨在研究北京市鱼类群落的空间格局特征, 探索适用于北京鱼类生物多样性监测及保护的新方法。结果表明: 在北京市的34个采样点中, 利用eDNA metabarcoding共检测出鱼类55种, 显著高于传统方法所捕获的鱼类种数(35种), 鱼类组成以鲤形目和鲈形目为主。山区河流清水鱼的多样性要显著高于城区河流, 城区河流(北运河水系)群落结构较为单一, 以鲫(Carassius auratus)、麦穗鱼(Pseudorasbora parva)、泥鳅(Misgurnus anguillicaudatus)等耐污种为优势种; 山区河流(潮白河水系及大清河水系)以宽鳍鱲(Zacco platypus)、拉氏鱥(Rhynchocypris lagowskii)、马口鱼(Opsariichthys uncirostris)等为优势种。不同季节影响清水鱼群落结构的环境因子不同, 夏季主要是总溶解固体和电导率, 秋季主要是海拔和温度。清水鱼丰富度与环境因子及人类活动的相关性表明, 清水鱼的丰富度随着总溶解固体及灯光指数增加而显著降低, 且均与海拔、温度等存在显著相关性。本研究证明了eDNA metabarcoding方法用于监测北京市鱼类多样性及其时空分布的可行性。     

Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries

The extraction and characterization of DNA from aquatic environmental samples offers an alternative, noninvasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next‐generation sequencing (“metabarcoding”), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom‐designed group‐specific primer set and next‐generation sequencing for the detection of three species at risk (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada: the Grand River and the Sydenham River. Of 82 fish species detected in both rivers using capture‐based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co‐occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture‐based methods, for improved mapping of species distribution patterns.     

Estimating species richness using environmental DNA

The foundation for any ecological study and for the effective management of biodiversity in natural systems requires knowing what species are present in an ecosystem. We assessed fish communities in a stream using two methods, depletion‐based electrofishing and environmental DNA metabarcoding (eDNA) from water samples, to test the hypothesis that eDNA provides an alternative means of determining species richness and species identities for a natural ecosystem. In a northern Indiana stream, electrofishing yielded a direct estimate of 12 species and a mean estimated richness (Chao II estimator) of 16.6 species with a 95% confidence interval from 12.8 to 42.2. eDNA sampling detected an additional four species, congruent with the mean Chao II estimate from electrofishing. This increased detection rate for fish species between methods suggests that eDNA sampling can enhance estimation of fish fauna in flowing waters while having minimal sampling impacts on fish and their habitat. Modern genetic approaches therefore have the potential to transform our ability to build a more complete list of species for ecological investigations and inform management of aquatic ecosystems.     

eDNA metabarcoding survey reveals fine‐scale coral reef community variation across a remote,tropical island ecosystem

Environmental DNA (eDNA) metabarcoding, a technique for retrieving multispecies DNA from environmental samples, can detect a diverse array of marine species from filtered seawater samples. There is a growing potential to integrate eDNA alongside existing monitoring methods in order to establish or improve the assessment of species diversity. Remote island reefs are increasingly vulnerable to climate‐related threats and as such there is a pressing need for cost‐effective whole‐ecosystem surveying to baseline biodiversity, study assemblage changes and ultimately develop sustainable management plans. We investigated the utility of eDNA metabarcoding as a high‐resolution, multitrophic biomonitoring tool at the Cocos (Keeling) Islands, Australia (CKI)—a remote tropical coral reef atoll situated within the eastern Indian Ocean. Metabarcoding assays targeting the mitochondrial 16S rRNA and CO1 genes, as well as the 18S rRNA nuclear gene, were applied to 252 surface seawater samples collected from 42 sites within a 140 km² area. Our assays successfully detected a wide range of bony fish and elasmobranchs (244 taxa), crustaceans (88), molluscs (37) and echinoderms (7). Assemblage composition varied significantly between sites, reflecting habitat partitioning across the island ecosystem and demonstrating the localisation of eDNA signals, despite extensive tidal and oceanic movements. In addition, we document putative new occurrence records for 46 taxa and compare the efficiency of our eDNA approach to visual survey techniques at CKI. Our study demonstrates the utility of a multimarker metabarcoding approach in capturing multitrophic biodiversity across an entire coral reef atoll and sets an important baseline for ongoing monitoring and management.     

Unlocking biodiversity and conservation studies in high‐diversity environments using environmental DNA (eDNA): A test with Guianese freshwater fishes

Determining the species compositions of local assemblages is a prerequisite to understanding how anthropogenic disturbances affect biodiversity. However, biodiversity measurements often remain incomplete due to the limited efficiency of sampling methods. This is particularly true in freshwater tropical environments that host rich fish assemblages, for which assessments are uncertain and often rely on destructive methods. Developing an efficient and nondestructive method to assess biodiversity in tropical freshwaters is highly important. In this study, we tested the efficiency of environmental DNA (eDNA) metabarcoding to assess the fish diversity of 39 Guianese sites. We compared the diversity and composition of assemblages obtained using traditional and metabarcoding methods. More than 7,000 individual fish belonging to 203 Guianese fish species were collected by traditional sampling methods, and ~17 million reads were produced by metabarcoding, among which ~8 million reads were assigned to 148 fish taxonomic units, including 132 fish species. The two methods detected a similar number of species at each site, but the species identities partially matched. The assemblage compositions from the different drainage basins were better discriminated using metabarcoding, revealing that while traditional methods provide a more complete but spatially limited inventory of fish assemblages, metabarcoding provides a more partial but spatially extensive inventory. eDNA metabarcoding can therefore be used for rapid and large‐scale biodiversity assessments, while at a local scale, the two approaches are complementary and enable an understanding of realistic fish biodiversity.     

eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity

Because significant global changes are currently underway in the Arctic, creating a large‐scale standardized database for Arctic marine biodiversity is particularly pressing. This study evaluates the potential of aquatic environmental DNA (eDNA) metabarcoding to detect Arctic coastal biodiversity changes and characterizes the local spatio‐temporal distribution of eDNA in two locations. We extracted and amplified eDNA using two COI primer pairs from ~80 water samples that were collected across two Canadian Arctic ports, Churchill and Iqaluit, based on optimized sampling and preservation methods for remote regions surveys. Results demonstrate that aquatic eDNA surveys have the potential to document large‐scale Arctic biodiversity change by providing a rapid overview of coastal metazoan biodiversity, detecting nonindigenous species, and allowing sampling in both open water and under the ice cover by local northern‐based communities. We show that DNA sequences of ~50% of known Canadian Arctic species and potential invaders are currently present in public databases. A similar proportion of operational taxonomic units was identified at the species level with eDNA metabarcoding, for a total of 181 species identified at both sites. Despite the cold and well‐mixed coastal environment, species composition was vertically heterogeneous, in part due to river inflow in the estuarine ecosystem, and differed between the water column and tide pools. Thus, COI‐based eDNA metabarcoding may quickly improve large‐scale Arctic biomonitoring using eDNA, but we caution that aquatic eDNA sampling needs to be standardized over space and time to accurately evaluate community structure changes.     

基于环境DNA宏条形码技术的辽东湾典型围海养殖池塘内水母多样性研究

研究使用环境DNA宏条形码技术(eDNA metabarcoding)检测辽东湾东北部河口区围海养殖池塘水母种类多样性,探索适用于水母种类物种鉴定和监测的新方法。利用环境DNA宏条形码技术,分别基于18S rDNA和COI宏条形码检测了辽东湾东北部河口区围海养殖池塘水母种类多样性,通过水样采集、过滤、eDNA提取、遗传标记扩增、测序与生物信息分析的环境DNA宏条形码标准化分析流程,从围海养殖池塘7个采样点中获得可检测的采样点数据。结果显示,基于18S rDNA宏条形码检测出8种水母种类,其中钵水母纲大型水母2种、水螅水母总纲小型水母6种;基于COI宏条形码技术共检测出19种水母种类,其中钵水母纲大型水母5种、水螅水母总纲小型水母14种;两种DNA条形码标记都显示养殖种类海蜇(Rhopilema esculentum)为优势种。研究结果表明,环境DNA宏条形码技术作为一种新兴的生物多样性监测手段可用于快速检测水母种类多样性,在水母类物种鉴定、监测及早期预警中有较大的应用潜能。     

Marine water environmental DNA metabarcoding provides a comprehensive fish diversity assessment and reveals spatial patterns in a large oceanic area

Current methods for monitoring marine fish (including bony fishes and elasmobranchs) diversity mostly rely on trawling surveys, which are invasive, costly, and time‐consuming. Moreover, these methods are selective, targeting a subset of species at the time, and can be inaccessible to certain areas. Here, we used environmental DNA (eDNA), the DNA present in the water column as part of shed cells, tissues, or mucus, to provide comprehensive information about fish diversity in a large marine area. Further, eDNA results were compared to the fish diversity obtained in pelagic trawls. A total of 44 5 L‐water samples were collected onboard a wide‐scale oceanographic survey covering about 120,000 square kilometers in Northeast Atlantic Ocean. A short region of the 12S rRNA gene was amplified and sequenced through metabarcoding generating almost 3.5 million quality‐filtered reads. Trawl and eDNA samples resulted in the same most abundant species (European anchovy, European pilchard, Atlantic mackerel, and blue whiting), but eDNA metabarcoding resulted in more detected bony fish and elasmobranch species (116) than trawling (16). Although an overall correlation between fishes biomass and number of reads was observed, some species deviated from the common trend, which could be explained by inherent biases of each of the methods. Species distribution patterns inferred from eDNA metabarcoding data coincided with current ecological knowledge of the species, suggesting that eDNA has the potential to draw sound ecological conclusions that can contribute to fish surveillance programs. Our results support eDNA metabarcoding for broad‐scale marine fish diversity monitoring in the context of Directives such as the Common Fisheries Policy or the Marine Strategy Framework Directive.     

Responses of foraminifera communities to aquaculture‐derived organic enrichment as revealed by environmental DNA metabarcoding

Current monitoring methods to assess benthic impacts of marine finfish aquaculture are based on complex biological indices and/or geochemistry data. The former requires benthic macrofauna morpho‐taxonomic characterization that is time‐ and cost‐intensive, while the latter provides rapid assessment of the organic enrichment status of sediments but does not directly measure biotic impacts. In this study, sediment samples were collected from seven stations at six salmon farms in British Columbia, Canada, and analyzed for geochemical parameters and by eDNA metabarcoding to investigate linkages between geochemistry and foraminifera. Sediment texture across farm sites ranged from sand to silty loam, while the maximum sediment pore‐water sulphide concentration at each site ranged from 1,000 to 13,000 μM. Foraminifera alpha diversity generally increased with distance from cage edge. Adonis analyses revealed that farm site explained the most variation in foraminifera community, followed by sediment type, enrichment status, and distance from cage edge. Farm‐specific responses were observed in diversity analyses, taxonomic difference analyses, and correlation analyses. Results demonstrated that species diversity and composition of foraminifera characterized by eDNA metabarcoding generated signals consistent with benthic biodiversity being impacted by finfish farming activities. This substantiates the validity of eDNA metabarcoding for augmenting current approaches to benthic impact assessments by providing more cost‐effective and practicable biotic measures than traditional morpho‐taxonomy. To capitalize on this potential, further work is needed to design a new nomogram that combines eDNA metabarcoding data and geochemistry data to enable accurate monitoring of benthic impacts of fish farming in a time‐ and cost‐efficient way.