基于浮游植物生物完整性指数的湖泊生态系统评价——以2012年冬季太湖为例

依据2012年12月对太湖29个样点和同一地理区划4个湖、库的浮游植物和环境变量的监测结果,应用生物完整性理论和方法,构建冬季太湖浮游植物生物完整性指数,评价冬季太湖水生态健康质量。采用干扰程度最小系统法定义筛选确定参照点,对51个候选参数进行分布范围筛选、判别能力分析、参数间相关性分析,获得了太湖枯水期P-IBI指数的6个构成参数:总分类单元数、硅藻门分类单元%、细胞Simpson指数、细胞密度、硅藻门细胞密度%和绿藻门个体密度%。采用比值法统一各参数的量纲,累加后得到枯水期太湖P-IBI分值,并划分健康评价标准。应用P-IBI对冬季太湖水生态进行评价,8个参照点中1个点位评价结果为健康其余7个为亚健康;25个受损点中,2个点位为亚健康,9个点位为一般,12个点位为差,2个点位为极差。太湖总体受到了不同程度的人为干扰,东太湖湖区水生态状况最好,评价结果多为亚健康或一般;竺山湖、贡湖、东部沿岸和西部沿岸次之;南部沿岸和湖心区最差,湖心区有2个点位评价结果为极差。与冬季太湖P-IBI指数显著相关的水化学因子是氨氮和总磷含量。     

着生藻类和浮游藻类在三峡库区河流健康评价中的适宜性比较研究

藻类对水体环境变化敏感,其种类和数量与环境因素有密切联系并因环境的变化而发生变化,因此藻类常作为河流健康评价的指示生物。水体中的藻类根据生活习性不同分为着生藻类和浮游藻类,在河流健康评价中,以往的工作中有的采用浮游藻类用于河流健康评价,有的采用着生藻类用于评价,但浮游藻类和着生藻类究竟何者用于河流健康评价更适宜,抑或是二者在用于评价的适宜性上没有明显差别,迄今为止未开展过深入研究。选择三峡库区内的两条河流嘉陵江和乌江作为研究对象,于2015年9月,在两条河流上共布设11个研究断面,对嘉陵江、乌江的水环境理化因子、着生藻类和浮游藻类群落进行调查研究,应用着生藻类生物完整性指数(Periphytic algal index of biological integrity,Pe-IBI)和浮游藻类生物完整性指数(Phytoplankton index of biological integrity,Ph-IBI),并结合水体综合污染指数(Comprehensive pollution index,CPI),对嘉陵江、乌江的健康状况进行评价。研究结果表明,采用着生藻类生物完整性评价(Pe-IBI)能筛选出7个核心生物参数(藻类总分类单元数、蓝藻总分类单元数、绿藻总分类单元数、菱形藻比例、优势分类单元比例、香农多样性指数、均匀度)用于河流健康评价,着生藻类生物完整性指数(Pe-IBI)与水体综合污染指数(CPI)具有极显著的负相关关系,并且与水体中总氮、铅含量也有极显著的负相关关系,表明水环境质量越低则着生藻类的生物完整性越差;当采用浮游藻类生物完整性(Ph-IBI)用于河流健康评价时却只能筛选出1个核心生物参数(藻类密度),而且浮游藻类生物完整性指数(Ph-IBI)与水体综合污染指数(CPI)及12个水体环境指标并无明显的相关性。本研究表明,在河流水体中,与浮游藻类相比,着生藻类更能反映水体环境的状况,对河流水体环境的反映更为准确。因此,在以流动水体为特征的河流的健康评价中,采用着生藻类比采用浮游藻类更为适宜。     

适应白洋淀湿地健康评价的IBI方法

IBI指数法是美国湿地生态系统健康评价的常用方法之一,在国内应用较少,目前为止只有少数学者尝试了底栖动物完整性指数(B-IBI)和鱼类完整性指数进行河流生态系统健康评价。试图建立适合白洋淀地区的生物完整性指数湿地健康状况评价的方法。在白洋淀的23个淀区进行土壤、水体、植物的实地调查与采样分析。根据已有研究所选择的植物属性,选择了30个植物属性作为备选参数。通过考察备选参数与人类干扰的相关性,最后确定了9个对人类干扰敏感的IBI参数。通过分析,建立了适合白洋淀湿地健康评价的标准:IBI,35-45,好;27-34,一般;19-26,差;＜18,极差。评价结果表明,白洋淀23个淀区中,6个健康状况好,5个一般,7个差,5个很差。     

天津市典型湖库湿地生态完整性评价

对湖库湿地进行生态健康评价,可为湖库湿地生态系统修复和管理提供决策依据。本文以天津市为例,选取20个典型的湖库湿地采样点,基于2018年8—9月期间调查获取的物理、化学和生物群落指标(浮游动物、浮游植物、底栖动物、鱼类、水生大型植物、河岸带植物)数据,构建包含物理完整性、化学完整性和生物完整性在内的生态完整性指数(IEI)对采样点生态健康状况进行评价。根据栖息地环境质量(QHEI)、水质状况和人类活动干扰3方面选取参照点,采用标准化方法筛选候选指标,应用层次分析法计算各指标权重,最终得出天津市典型湖库湿地生态完整性评价结果。结果表明: 1)所有样点中,“健康”点位占5.0%,“较好”点位占20.0%,“一般”点位占35.0%,“较差”点位占30.0%,“差”点位占10.0%。天津市典型湖库湿地生态健康状况整体处于一般水平,呈现出西部优于东部的趋势,空间差异显著;2)基于栖息地评分、水质状况与人类活动干扰相结合选取参照点是可行的,依据水质指标可降低选择参照点时的主观性;3)适用性验证结果表明,IEI可较好表征各点位的健康状况,区分效率明显,适用于评价研究区湖库湿地生态健康状况。     

基于大型底栖无脊椎动物完整性指数的鄱阳湖湿地生态健康评价

湿地生态健康评价对于掌握湿地的健康状况、理解人类活动干扰对其影响及实施生态预警等有重要意义。鄱阳湖对于维持其流域甚至长江中下游的生态平衡十分重要,目前尚未建立起其较完善的生态健康评价指标体系。大型底栖无脊椎动物完整性指数(benthic macroinvertebrate-based index of biotic integrity, B-IBI)是广泛应用的湿地生态健康评价方法。基于30个采样点(7个参照点,23个受损点)的大型底栖无脊椎动物采样数据,构建鄱阳湖湿地的B-IBI指数,采用自然断点法划分非常健康、健康、一般、差和极差5个健康等级标准,据此评价湿地生态健康状况。研究表明:(1)基于B-IBI指数的鄱阳湖湿地生态健康评价结果为一般;(2)就采样点B-IBI分值而言,呈现出西部健康状况优于东部的格局,其中国家级自然保护区内状况较好,而工业区、城镇、农田及河流入湖口附近状况较差;(3)B-IBI指数与前期构建的景观发展强度指数(LDI)、栖息地环境质量指数(QHEI)以及植被完整性指数(V-IBI)具有显著相关性,表明基于不同指数的评价结果较为一致。本研究构建的B-IBI指数能为鄱阳湖湿地的生态健康评价和监测提供重要方法。     

应用生物完整性指数评价水生态系统健康的研究进展

生物完整性指数(IBI)法是评价水生态系统健康的一种重要且被广泛应用的方法.本文综述了生物完整性指数的指示物种选择原因、构建方法以及在水生态系统健康评价中的应用,并总结了现阶段生态系统评估常用的鱼类完整性指数（F_IBI）、底栖无脊椎动物完整性指数（B_IBI）和着生藻类完整性指数（P_IBI)中候选生物状况参数指标,提出了使用微生物完整性指数(M_IBI)评价水生态系统健康的可行性和必要性.     

标准化方法筛选参照点构建大型底栖动物生物完整性指数

依据浑太河流域340个样点的栖息地和水质评价结果,采用标准化方法筛选参照点与受损点,构建大型底栖动物生物完整性评估指数(Benthic Macroinvertebrate Index of Biological Integrity,B-IBI),开展河流健康生物评价研究。标准化方法共筛选出参照点和6个受损点构建B-IBI指数。B-IBI指数包括8个大型底栖动物核心生物指标,涵盖了分类单元、相对丰度、耐污特征、优势类群和功能摄食类群的生物指标。利用构建的完整性指数开展浑太河河流健康评价结果显示,所有样点中"极好"与"好"占24.8%,"一般"占27.8%,"差"与"极差"的占47.4%,表明浑太河健康状况整体上偏差。B-IBI指数分值在参照、测试和受损点间的箱线图分布表明验证结果较为可靠;同时与2009年5月太子河全流域70个样点采用专家经验法构建的大型底栖动物生物完整性指数进行了对比,结果表明两种方法的评价结果一致性较高,健康等级完全一致的占58%,健康等级只相差一个等级的占40.6%。B-IBI与环境要素的回归分析显示,B-IBI指数与栖息地具有较高的直线线性回归关系(R2=0.25,P<0.01),与电导、高锰酸盐指数和氨氮(R2=0.23—0.34,P<0.01)均具有极显著的曲线相关关系。3个水质指标与B-IBI指数的回归方程的拐点分别约为1000μs/cm,5ml/L和1.0mg/L,当3个水质指标低于拐点值时,B-IBI指数表现为显著的下降趋势,当高于拐点值时,B-IBI指数的下降趋势明显减弱。表明高锰酸盐指数和氨氮在从清洁水体下降为III类的过程中,对大型底栖动物生物完整性的影响最为强烈。利用标准化方法筛选参照点构建的大型底栖动物完整性指数及其核心参数具有较好的敏感性,能够指示随人为活动强度增加河流生态系统健康状况的下降,适用于浑太河流域开展河流健康评估研究。     

基于微藻多量度指标法提高河流和湖泊生物学状态评价准确性的研究进展

多量度指标(multimetric index, MMI)是一种广泛应用于淡水生态系统生态评价的方法,它能综合各种与生态有关的量度信息,并为进一步评价和管理提供一个易于理解的分值.准确评估淡水生态系统的生物学状态必须扣除自然变异的影响和解决自然环境因子与人为干扰因子之间的协变问题.最近几年,研究人员在上述两个方面取得了诸多进展.当下主要利用三种方法提高湖泊和溪流生物评价的准确性:按生态区或藻类物种组成对样点进行建模前分类、对样点的参考状态进行样点特异性建模分析和在不同的分组中采用不同的量度指标.所有已有的研究结果都支持对样点进行特异性建模法可以有效地扣除自然变异的影响,并最终通过模型计算出具有良好表现的MMI.然而,在扣除湖泊或河流中的自然变异方面,目前没有足够的证据表明依据硅藻/蓝藻物种组成的样点分类法优于依据生态区的分类法.另外,区分对样点特异性建模法和在不同样点组中采用不同量度指标法所解释的自然变异百分数,对于全面、准确地评价按藻类物种组成进行样点分组方法的作用是十分必要的.在不同样点组中使用不同量度指标法在溪流和湖泊中的表现不同,这很可能是由于硅藻量度指标对溪流和湖泊的生物学状态代表性不足,而不是由溪流和湖泊中复杂的多重胁迫因子造成的.本文的目的是回顾近年来利用藻类的MMI分析方法在确定湖泊和河流生物学状态方面的研究进展,以及在比较MMI表现过程中应注意的一些统计学问题.     

应用底栖动物完整性指数B-IBI评价溪流健康

B-IBI指数是溪流生态系统健康评价常用指标之一。据安徽黄山地区溪流的33个底栖动物样点数据(11个参照点,22个受损点),对21个生物参数进行分布范围、Pearson相关性和判别能力分析,确定B-IBI指数由总分类单元数、EPT分类单元数、前3位优势分类单元%、粘附者%、敏感类群%和BI指数构成。分别用3分制、4分制和比值法统一各参数量纲,B-IBI指数值即为累加各构成指数的分值或比值。B-IBI箱线图分析表明,上述3种方法计算出的B-IBI值有较高判别能力(IQ=3),能很好地判别参照水体和受损水体,且3者之间具高相关性(r>0.90)。分别依据参照样点和所有样点B-IBI值建立健康评价标准,比较3分制、4分制和比值法对评价结果的准确性,表明用比值法统一各参数量纲并依据所有样点的B-IBI值建立的健康评价标准的准确性优于3分制和4分制法。建立了适合祁门县溪流生态系统健康评价B-IBI标准B-IBI>3.59健康,2.7～3.59亚健康,1.8～2.69一般,0.9～1.79差,B-IBI<0.9极差。祁门县21个样点的水体,14个健康,6个亚健康,1个一般。B-IBI与电导率(r=-0.62,p<0.01)和生境质量(r=0.65,p<0.01)显著相关。     

生态考核指标: 水生动物种类指数

为满足关于建立长江流域水生态考核机制的国家需求, 文章构建了水生动物种类指数。该指数以鱼类和底栖动物等动物的种数和重要类群的资源量为评价参数, 以同类水体可达的最高水平或评价元年数据为参照。与多参数指数和预测模型等常用的生态健康评价方法相比, 水生动物种类指数法有简单易行的特点, 便于全面推广应用。     

A multi-assemblage,multi-metric biological condition index for eastern Amazonia streams

Multimetric indices (MMIs) are widely used for assessing ecosystem condition and they have been developed for a variety of biological assemblages. However, when multiple assemblages are assessed at sites, the assessment results may differ because of differing physiological sensitivities to particular stressor gradients, different organism size and guilds, and the effects of different scales of disturbances on the assemblages. Those differences create problems for managers seeking to avoid type-1 and type-2 statistical errors. To alleviate those problems, we used an anthropogenic disturbance index for selecting and weighting metrics, modeled metrics against natural variability to reduce the natural variability in metrics, and developed an MMI based on both fish and aquatic insect metrics. We evaluated eight different ways of calibrating and combining candidate metrics and found that MMIs with unweighted and modeled aquatic insect and fish metrics were the preferred MMI options.     

Constructing multimetric indices and testing ability of landscape metrics to assess condition of freshwater wetlands in the Northeastern US

Using data collected for the Environmental Protection Agency's (EPA) 2011 National Wetland Condition Assessment (NWCA), we developed separate multimetric indices (MMIs) for vegetation, soil, algae taxa, and water to assess condition of freshwater wetlands in the northeastern US. This study represents the first attempt at developing multiple biotic and abiotic MMIs of wetland condition over this large of an area, and is only possible because of the high quality data collected by the NWCA. We chose metrics that distinguished between reference and most disturbed sites, had a signal:noise ratio > 2, and were not strongly correlated with other metrics, latitude, or longitude. The vegetation and soil MMIs were the best performing indices, with good separation between reference and most disturbed sites, and included commonly used condition metrics (e.g., pH and P concentration for soil, and percent cover of exotic species for vegetation). The algae MMI was the weakest index, with considerable overlap between reference and most disturbed sites. For areas smaller than our study, algae taxa may be suitable for wetland MMIs. However, in our study area, many algae taxa followed strong latitudinal or longitudinal gradients, and could not be considered for the algae MMI. Small sample size and several metrics with a high signal:noise ratio were the major limitations of the water MMI. We also examined how well landscape (level 1) and rapid assessment (level 2) metrics predicted MMIs using random forest regression. Agricultural land use surrounding wetlands was an important predictor for all four MMIs, although the soil, algae and water MMI models performed best when intensive (level 3) vegetation metrics were also included in the random forest regression models. Based on these results, we recommend wetland assessment programs employ a combination of landscape and rapid assessment monitoring at many sites, along with level 3 monitoring at a subset of sites. We developed these MMIs to evaluate freshwater wetland condition for a long-term monitoring program in Acadia National Park. These MMIs are also applicable to a range of wetland types covering 11 states in the northeastern United States and can be calculated using a downloadable spreadsheet that calculates and rates each MMI using raw metric values.     

Incorporating natural variability in the bioassessment of stream condition in the Atlantic Forest biome,Brazil

Most bioassessment programs in Brazil face difficulties when scaling up from small spatial scales because larger scales usually encompass great environmental variability. Covariance of anthropogenic pressures with natural environmental gradients can be a confounding factor in the evaluation of biologic responses to anthropogenic pressures. The objective of this study was to develop a multimetric index (MMI) with macroinvertebrates for two stream types and two ecoregions in the Atlantic Forest biome in Rio de Janeiro state, Brazil. We hypothesized that by using two approaches – (1) testing and adjusting metrics to landscape parameters, and (2) selecting metrics using a cluster analysis to avoid metrics redundancy – the final MMI would perform better than the traditional approach (unadjusted metrics, one metric representing each category). Four MMIs were thus developed: MMI-1 – adjusted MMI with metrics selected after cluster analysis); MMI-2 – adjusted MMI with one metric from each category; MMI-3 – unadjusted MMI with metrics selected after cluster analysis; MMI-4 – unadjusted MMI with one metric from each category. We used three decision criteria to assess MMI’s performance: precision, responsiveness and sensitivity. In addition, we tested the MMI’s by using an independent set of sites to validate the results. Although all MMIs performed well in the three criteria, adjusting metrics to natural variation increased MMI response and sensitivity to impairment. In addition, the selected MMI-2 was able to classify sites of two stream types and two ecoregions. The use of cluster analysis, however, did not avoid high redundancy between metrics of different branches. The MMI-4 had the poorest performance among all tested MMIs and it was not able to distinguish adequately reference and impaired sites from both ecoregions. We present some considerations on the use of metrics and on the development of MMI’s in Brazil and elsewhere.     

An algorithmic and information-theoretic approach to multimetric index construction

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a −0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.     

Development of a benthic macroinvertebrate multimetric index (MMI) for Neotropical Savanna headwater streams

Assessing the ecological impacts of anthropogenic pressures is a key task in environmental management. Multimetric indices (MMIs), based on aquatic assemblage responses to anthropogenic pressures, have been used increasingly throughout the world. The MMI approach is a low-cost, rapid field method that produces an aquatic condition index that responds precisely to anthropogenic pressures, making it useful for conservation and environmental management. We developed four candidate MMIs based on benthic macroinvertebrate assemblages sampled at 40 randomly selected sites to assess the environmental condition of streams upstream of a hydroelectric power plant in the Brazilian Neotropical Savanna biome. Those MMIs were built from landscape-adjusted and unadjusted biological metrics as well as two alternative ways of choosing metrics. The alternative MMIs performances were tested by comparing their precision to distinguish least-disturbed areas, responsiveness to discriminate least- and most-disturbed areas, and sensitivity to anthropogenic pressures at catchment and local scales. The best performing MMI had landscape-adjusted metrics and was produced through use of principal component analysis for metric selection. It included 4 metrics: Ephemeroptera richness, average tolerance score per taxon, percentage of predator individuals, and percentage of Odonata individuals adjusted by elevation. This index discriminated well the anthropogenic pressures at local- and catchment-scales, and at both scales simultaneously, as indicated by an integrated disturbance index. Our methodological development included statistical criteria for identifying least- and most-disturbed sites, calibrating for natural landscape variability, and use of non-redundant metrics. Therefore, we expect it will provide a model for environmental assessment of water resources elsewhere in Brazil and in other nations.     

An improved macroinvertebrate multimetric index for the assessment of wadeable streams in the neotropical savanna

Multimetric indices (MMIs) have been successfully used to assess ecological conditions in freshwater ecosystems worldwide, and provide an important management tool especially in countries where biological indicators are fostered by environmental regulations. Nonetheless, for the neotropics, the few published papers are limited to small local scales and lack standardized sampling protocols. To fill the gaps left by previous studies, we propose a stream MMI that reflects anthropogenic impacts by using macroinvertebrate assemblage metrics from a data set of 190 sites collected from four hydrologic units in the Paraná and São Francisco River Basins, southeastern Brazil. Sites were selected through use of a probabilistic survey design allowing us to infer ecological condition to the total of 9432 kilometers of wadeable streams in the target population in the four hydrologic units. We used a filtering process to determine the least- and most-disturbed sites based on their water quality, physical habitat structure, and land use. To develop the MMI, we followed a stepwise procedure to screen our initial set of biological metrics for influence of natural variation, responsiveness and discriminance to disturbances, sampling variability, and redundancy. The final MMI is the sum of 7 scaled assemblage metrics describing different aspects of macroinvertebrate assemblage characteristics: Ephemeroptera richness, % Gastropoda individuals, Shannon-Wiener diversity index, % sensitive taxa richness, % scraper individuals, temporarily attached taxa richness, and gill respiration taxa richness. The MMI clearly distinguished the least-disturbed sites from the most-disturbed sites and showed a significant negative response to anthropogenic stressors. Of the total length of wadeable streams in the study area, 38%, 35%, and 27% were classified by the MMI as being in good, fair, and poor condition, respectively. By reducing the subjectivity of site selection, rigorously selecting the set of reference sites, and following a standardized metric screening method, we developed a robust MMI to assess and monitor ecological condition in neotropical savanna streams. This improved MMI provides an effective ecological tool to guide decision makers and managers in developing and implementing improved, cost-effective environmental policies, regulations, and monitoring of those systems.     

Assessment of biotic condition of Atlantic Rain Forest streams: A fish-based multimetric approach

We developed a preliminary fish-based multimetric index (MMI) to assess biotic condition of Atlantic Rain Forest streams in Southeastern Brazil. We used least-disturbed sites as proxies of reference conditions for metric development. To determine the disturbance gradient we used an Integrated Disturbance Index (IDI) that summarized the multiple disturbances measured at local/regional catchment scales in a single index, describing the totality of exposure of the streams to human pressures. For our 48 sites, nine were least-disturbed (IDI < 0.25), five were most-disturbed (IDI > 1.35) and 34 were intermediate. Initially, we considered 41 candidate metrics selected primarily from previous studies. We screened this pool of candidate metrics using a series of tests: range test, signal-to-noise test, correlation with natural gradients, responsiveness test, and redundancy test. After screening, we selected six metrics for the MMI: % Characiform individuals, % water column native individuals, % benthic invertivorous individuals, % tolerant species, % intolerant species, and % detritivorous individuals. Metrics such as diversity, dominance, species richness and biomass that have been historically used for assessing ecosystem condition failed one or more screening tests. We conclude that an IDI and rigorous metric screening are critical to the MMI development process and for meaningful assessments of stream condition.     

A fish-based multimetric index for Brazilian savanna streams

Multimetric indices (MMI) have been widely used to assess ecosystem conditions because they are low-cost, employ a rapid field method, and can incorporate various biological metrics at different levels of biological organization. Our objective was to create a fish-based multimetric index applicable to all streams of the Brazilian savanna biome (Cerrado), the second largest biome in Brazil and deemed a global biodiversity hotspot. We evaluated 156 sites in two river basins (Paraná and São Francisco) and selected metrics capable of distinguishing stream-sites across a gradient of anthropogenic disturbances. We employed two different MMI approaches to determine if an MMI based on natural variation-adjusted metrics performed better than one based on unadjusted metrics. In addition, we assessed the performance of the two final MMIs and their sensitivity to anthropogenic pressures at local (LDI), catchment (CDI) and both scales integrated (IDI). Finally, we employed the power of a probability sample survey design to infer headwater stream conditions across a hydrologic region of approximately 47,000 km². Our final MMI for Brazilian savanna streams included six metrics: % common species; % characiform individuals; % loricariid individuals; % trichomycterid individuals; % invertivore species, and % Poecilia reticulata individuals. MMI₁ (unadjusted metrics) performed better than MMI₂ (natural variation-adjusted metrics) in discriminating least- and most-disturbed sites, but MMI₂ distinguished intermediate from most-disturbed sites better than MMI₁. Both indices were negatively correlated with the CDI scores; however, only MMI₂ was negatively correlated with the IDI scores. We inferred that 709 km (9.35%) of streams in the studied hydrologic region were in good condition, 8115 km (82.73%) were intermediate, and 641 km (7.91%) were in poor condition. We conclude that the MMIs proposed in this study have great potential for widespread application because they integrate data from two of the most important Brazilian river basins included in a biome that represents more than 20% of the country. Furthermore, the metrics retained in the indexes are easy to access with a rapid low-cost field method. However, their feasibility in areas influenced by mining, as well as in different biomes, should be tested.     

Regional fish community indicators of landscape disturbance to catchments of the conterminous United States

Biological assessments of river conditions are increasingly conducted at regional and continental scales that match the extent of large-scale river management efforts. Multimetric indices composed of biological community indicators are commonly used to assess ecological condition and indices have recently been applied in large regions. Methods for large-scale multimetric index creation emphasize repeatability, comparability across regions, and objective selection of candidate metrics. Here we used an extensive fish dataset to create a large pool of fish community metrics which were screened to create multimetric indices (MMIs) in eight ecoregions covering the conterminous U.S. Candidate metrics were tested for metric range, corrected for natural gradients using boosted regression trees, and then tested for repeatability and sensitivity to landscape disturbance. Temporally stable and repeatable metrics were then evaluated for redundancy and used to compose MMIs for each region. Our MMIs were significantly correlated to independently developed MMIs, accurately reproducing prior index values with moderate to high precision and little bias. Our study demonstrates the utility of boosted regression tree models for correcting metric values for natural abiotic gradients and shows that the order of screening tests has a potentially important influence on metric selection. The resultant regional indices and component metrics provide a basis for assessing condition and testing hypotheses about landscape influences on aquatic ecosystems at a national scale in the US.     

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.