Exploring the robustness of macrophyte-based classification methods to assess the ecological status of coastal and transitional ecosystems under the Water Framework Directive

Identifying and quantifying the factors that contribute to the potential misclassification of the ecological status of water bodies is a major challenge of the Water Framework Directive (WFD). The present study compiles extensive biomonitoring data from a range of macrophyte-based classification methods developed by several European countries. The data reflect spatial and temporal variation as well as inter-observer variation. Uncertainty analysis identified that factors related to the spatial scale of sampling generally contributed most to the uncertainty in classifying water bodies to their ecological status, reflecting the high horizontal and depth-related heterogeneity displayed by macrophyte communities. In contrast, the uncertainty associated with temporal variation was low. In addition, inter-observer variation, where assessed, did not contribute much to overall uncertainty, indicating that these methods are easily transferable and insensitive to observer error. The study, therefore, suggests that macrophyte-based sampling schemes should prioritize large spatial replication over temporal replication to maximize the effectiveness and reliability of water body classification within the WFD. We encourage conducting similar uncertainty analyses for new/additional ecological indicators to optimize sampling schemes and improve the reliability of classification of ecological status.     

Estimating confidence of European WFD ecological status class and WISER Bioassessment Uncertainty Guidance Software (WISERBUGS)

The Water Framework Directive (WFD) requires estimates of the confidence and precision associated with any scheme for assessing and monitoring the ecological status class of any European rivers, lakes, transitional or coastal waters. This is a complex important issue, especially for waterbody assessments based on multiple metrics and/or two or more taxonomic groups. This paper aims to contribute towards improving understanding and providing practical approaches to assessing confidence of class by (i) discussing the various sources and causes of uncertainty, (ii) using UK rivers macroinvertebrate datasets to illustrate the estimation of replicate, temporal and spatial variance components and the implications for water body metric precision, confidence of class and optimal sampling design, (iii) introducing new freely available general software WISER Bioassessment Uncertainty Guidance Software (WISERBUGS) which uses prior sampling uncertainty estimates with user-specified metrics, class limits and metric combination rules to simulate the joint sampling uncertainty in metric EQR values and provide estimates of confidence of class based on individual metrics, (optionally weighted) multi-metric indices and/or multi-metric classification rules (worst case, mean or median class) based on one or more WFD biological quality elements.     

Effects of sampling and sub-sampling variation using the STAR-AQEM sampling protocol on the precision of macroinvertebrate metrics

As part of the extensive field sampling programme within the European Union STAR project, replicate macroinvertebrate samples were taken using the STAR-AQEM sampling method at each of 2–13 sites of varying ecological quality within each of 15 stream types spread over 12 countries throughout Europe. The STAR-AQEM method requires the sub-sampling and taxonomic identification of at least one-sixth of the sample and at least 700 individuals. Replicate sub-samples were also taken at most of these sites. Sub-sampling effects caused more than 50% of the overall variance between replicate samples values for 12 of the 27 macroinvertebrate metrics analysed and was generally greatest for metrics that depend on the number of taxa present. The sampling precision of each metric was estimated by the overall replicate sampling variance as a percentage P_samp of the total variance in metric values within a stream type. Average over all stream types, the three Saprobic indices had the lowest percentage sampling variances with median values of only 3–6%. Most of the metrics had typical replicate sampling variances of 8–18% of the total variability within a stream type; this gives rise to estimated rates of mis-classifying sites to ecological status class of between 22 and 55% with an average of about 40%. This suggests that the precision of such metrics based on the STAR-AQEM method is only sufficient to indicate gross changes in the ecological status of sites, but there will be considerable uncertainty in the assignment of sites to adjacent status classes. These estimates can be used to provide information on the effects of STAR-AQEM sampling variation on the expected uncertainty in multi-metric assessments of the ecological status of sites in the same or similar stream types, where only one sample has been taken at a point in time and thus there is no replication.     

Hydrologic sources of carbon cycling uncertainty throughout the terrestrial–aquatic continuum

Linking hydrologic interactions with global carbon cycling will reduce the uncertainty associated with scaling-up empirical studies and facilitate the incorporation of terrestrial–aquatic linkages within global and regional change models. Much of the uncertainty in estimates of carbon fluxes associated with precipitation and hydrologic transport results from the extensive spatial and temporal heterogeneity in both intrinsic functioning and anthropogenic modification of hydrological cycles. To better understand this variation we developed a landscape ecological approach to coupled hydrologic–carbon cycling that merges local mechanisms with multiple-scale spatial heterogeneity. This spatially explicit framework is applied to examine variability in hydrologic influences on carbon cycling along a continental scale water availability gradient with an explicit consideration of human sources of variability. Hydrologic variation is an important component of the uncertainty in carbon cycling; accounting for this variation will improve understanding of current conditions and projections of future ecosystem responses to global change.     

Measurements of uncertainty in macrophyte metrics used to assess European lake water quality

Uncertainty is an important factor in ecological assessment, and has important implications for the ecological classification and management of lakes. However, our knowledge of the effects of uncertainty in the assessment of different ecological indicators is limited. Here, we used data from a standardized campaign of aquatic plant surveys, in 28 lakes from 10 European countries, to assess variation in macrophyte metrics across a set of nested spatial scales: countries, lakes, sampling stations, replicate transects, and replicate samples at two depth-zones. Metrics investigated in each transect included taxa richness, maximum depth of colonisation and two indicators of trophic status: Ellenberg’s N and a metric based on phosphorus trophic status. Metrics were found to have a slightly stronger relationship to pressures when they were calculated on abundance data compared to presence/absence data. Eutrophication metrics based on helophytes were found not to be useful in assessing the effects of nutrient pressure. These metrics were also found to vary with the depth of sampling, with shallower taxa representing higher trophic status. This study demonstrates the complex spatial variability in macrophyte communities, the effect of this variability on the metrics, and the implications to water managers, especially in relation to survey design.     

Relative importance of temporal and spatial heterogeneity in the zooplankton community of an artificial reservoir

Zooplankton samples were collected monthly at three stations in Ogochi Reservoir during 1980, and the temporal and horizontal variations in the density of dominant taxa were evaluated by a standard 2-way ANOVA with random effects. The analysis revealed that horizontal is greater than temporal variation in the warm water season (> 18 °C), whereas temporal variation is greater in the cold water season (< 18 °C). Horizontal heterogeneity of the zooplankton community found in the warm water season seems to be associated with differences in site-specific conditions.     

Qualitative Risk Assessment of Surface Water Contamination with Cryptosporidium Sp. Oocysts: A Case Study of Three Agricultural Catchments

In recent years there have been a number of waterborne outbreaks of cryptosporidiosis in some major urban centers in Ireland. The Irish Environmental Protection Agency has adapted and modified the qualitative “Scottish Water Directions” to help prevent such outbreaks. When this risk assessment method was applied to three small agricultural river catchments in Ireland, the results suggested an equal risk of water contamination for each catchment. A survey was conducted in each catchment focusing on agricultural activity and surface waters. Fecal samples were collected from 1–8-week-old calves along with associated slurry and dung from beef and dairy farms and water samples were collected monthly at the outlet of the three catchments. Two of the catchments had much higher infection rates among neonatal calves as well as higher oocyst contamination of surface waters than the remaining one. It was concluded that the qualitative risk assessment could be more robust if cognizance was taken of the temporal and epidemiological aspects of cryptosporidiosis in beef and dairy herds.     

Temporal and Spatial Diversity of Bacterial Communities in Coastal Waters of the South China Sea

Bacteria are recognized as important drivers of biogeochemical processes in all aquatic ecosystems. Temporal and geographical patterns in ocean bacterial communities have been observed in many studies, but the temporal and spatial patterns in the bacterial communities from the South China Sea remained unexplored. To determine the spatiotemporal patterns, we generated 16S rRNA datasets for 15 samples collected from the five regularly distributed sites of the South China Sea in three seasons (spring, summer, winter). A total of 491 representative sequences were analyzed by MOTHUR, yielding 282 operational taxonomic units (OTUs) grouped at 97% stringency. Significant temporal variations of bacterial diversity were observed. Richness and diversity indices indicated that summer samples were the most diverse. The main bacterial group in spring and summer samples was Alphaproteobacteria, followed by Cyanobacteria and Gammaproteobacteria, whereas Cyanobacteria dominated the winter samples. Spatial patterns in the samples were observed that samples collected from the coastal (D151, D221) waters and offshore (D157, D1512, D224) waters clustered separately, the coastal samples harbored more diverse bacterial communities. However, the temporal pattern of the coastal site D151 was contrary to that of the coastal site D221. The LIBSHUFF statistics revealed noticeable differences among the spring, summer and winter libraries collected at five sites. The UPGMA tree showed there were temporal and spatial heterogeneity of bacterial community composition in coastal waters of the South China Sea. The water salinity (P=0.001) contributed significantly to the bacteria-environment relationship. Our results revealed that bacterial community structures were influenced by environmental factors and community-level changes in 16S-based diversity were better explained by spatial patterns than by temporal patterns.     

Microplate fecal coliform method to monitor stream water pollution.

A study has been carried out on the Moselle River by means of a microtechnique based on the most-probable-number method for fecal coliform enumeration. This microtechnique, in which each serial dilution of a sample is inoculated into all 96 wells of a microplate, was compared with the standard membrane filter method. It showed a marked overestimation of about 14% due, probably, to the lack of absolute specificity of the method. The high precision of the microtechnique (13%, in terms of the coefficient of variation for log most probable number) and its relative independence from the influence of bacterial density allowed the use of analysis of variance to investigate the effects of spatial and temporal bacterial heterogeneity on the estimation of coliforms. Variability among replicate samples, subsamples, handling, and analytical errors were considered as the major sources of variation in bacterial titration. Variances associated with individual components of the sampling procedure were isolated, and optimal replications of each step were determined. Temporal variation was shown to be more influential than the other three components (most probable number, subsample, sample to sample), which were approximately equal in effect. However, the incidence of sample-to-sample variability (16%, in terms of the coefficient of variation for log most probable number) caused by spatial heterogeneity of bacterial populations in the Moselle River is shown and emphasized. Consequently, we recommend that replicate samples be taken on each occasion when conducting a sampling program for a stream pollution survey.     

Microplate fecal coliform method to monitor stream water pollution

A study has been carried out on the Moselle River by means of a microtechnique based on the most-probable-number method for fecal coliform enumeration. This microtechnique, in which each serial dilution of a sample is inoculated into all 96 wells of a microplate, was compared with the standard membrane filter method. It showed a marked overestimation of about 14% due, probably, to the lack of absolute specificity of the method. The high precision of the microtechnique (13%, in terms of the coefficient of variation for log most probable number) and its relative independence from the influence of bacterial density allowed the use of analysis of variance to investigate the effects of spatial and temporal bacterial heterogeneity on the estimation of coliforms. Variability among replicate samples, subsamples, handling, and analytical errors were considered as the major sources of variation in bacterial titration. Variances associated with individual components of the sampling procedure were isolated, and optimal replications of each step were determined. Temporal variation was shown to be more influential than the other three components (most probable number, subsample, sample to sample), which were approximately equal in effect. However, the incidence of sample-to-sample variability (16%, in terms of the coefficient of variation for log most probable number) caused by spatial heterogeneity of bacterial populations in the Moselle River is shown and emphasized. Consequently, we recommend that replicate samples be taken on each occasion when conducting a sampling program for a stream pollution survey.     

基于景观结构的北京市顺义区生态风险时空特征

以1997、2001、2005、2009和2013年遥感影像为基础数据,对快速城市化地区——北京市顺义区进行景观分类,构建基于景观干扰度和景观脆弱度的生态风险指数,利用GS⁺和ArcGIS软件进行空间自相关和地统计学分析,研究景观生态风险的时空变化特征.结果表明:研究区内的生态风险指数存在一定的空间正相关关系,随着粒度的增大,呈现下降的趋势;在一定的粒度范围内(<12 km),空间自相关性具有明显的尺度依赖特征.1997—2013年,空间异质性中的随机变异均小于空间自相关变异,由空间自相关部分引起的空间异质性占据主导地位.研究期间,研究区生态风险水平一直以中等生态风险程度为主,较高生态风险和较低生态风险区域面积增加,而中等生态风险区域面积逐渐减少.低生态风险区主要位于顺义区机场区域及东南部的林地;高生态风险区主要位于水域景观区域,如潮白河两岸.     

Development & application of Conceptual Framework Model (CFM) for environmental risk assessment of contaminated lands

Dumping sites are the most common types of contaminated lands as they pollute the environment. Environmental management of contaminated sites cannot be delivered effectively and efficiently without robust holistic & integrated risk assessment. Previous studies reveal the absence of a risk assessment model that holistically integrates all essential factors progressively and categorically. The study aimed to develop a holistic & integrated Conceptual Framework Model (CFM) for environmental risk assessment and to apply developed CFM on real-world existing Mahmood Booti Open Dumping Site (MBODS). CFM developed in this study had three main tiers i.e., baseline study, hazard identification & exposure assessment, and risk estimation. For the application of CFM, baseline data were collected and assessed. Water, leachate & soil samples were collected within 1000 m across the site and analyzed for physio-chemical parameters and heavy metals to estimate risk. Results of applied CFM depicted that Physico-chemical analysis of leachate, water, and soil revealed significant pollution levels. Heavy metal analysis exhibited that Ni, Pb, Mn, and Cr levels exceeded the allowable limits of the “World Health Organization” in leachate, water, and soil samples. It also revealed the existence of metals at the source (dumping site itself), pathway, and receptor of the dumping site. Eⁱ_r value for Ni, Pb and Cd from the study area manifested a serious probable risk to ecological integrities. Results for PERI from dumpsite demonstrated a serious ecological risk. It can be concluded that although Mahmood Booti dumping site has been at post-closure stage, it is a momentous source of hazardous toxic contaminants to the nearby inhabitants. The work presented in this paper may reproduce repeatedly to create site-specific risk assessment models of other contaminated lands in a cost-effective, consistent and cohesive manner. Application of CFM at Mahmood Booti Dumping site described detailed risk assessment which helps further in risk management.     

Towards the development of multifunctional molecular indicators combining soil biogeochemical and microbiological variables to predict the ecological integrity of silvicultural practices

The impact of mechanical site preparation (MSP) on soil biogeochemical structure in young larch plantations was investigated. Soil samples were collected in replicated plots comprising simple trenching, double trenching, mounding and inverting site preparation. Unlogged natural mixed forest areas were used as a reference. Analysis of soil nutrients, abundance of bacteria and gas exchanges unveiled no significant difference among the plots. However, inverting site preparation resulted in higher variations of gas exchanges when compared with trenching, mounding and unlogged natural forest. A combination of the biological and physicochemical variables was used to define a multifunctional classification of the soil samples into four distinct groups categorized as a function of their deviation from baseline ecological conditions. According to this classification model, simple trenching was the approach that represented the lowest ecological risk potential at the microsite level. No relationship was observed between MSP method and soil bacterial community structure as assessed by high‐throughput sequencing of bacterial 16S rRNA gene; however, indicator genotypes were identified for each multifunctional soil class. This is the first identification of multifunctional molecular indicators for baseline and disturbed ecological conditions in soil, demonstrating the potential of applied microbial ecology to guide silvicultural practices and ecological risk assessment.     

Confidence in ecological indicators: A framework for quantifying uncertainty components from monitoring data

The value of an ecological indicator is no better than the uncertainty associated with its estimate. Nevertheless, indicator uncertainty is seldom estimated, even though legislative frameworks such as the European Water Framework Directive stress that the confidence of an assessment should be quantified. We introduce a general framework for quantifying uncertainties associated with indicators employed to assess ecological status in waterbodies. The framework is illustrated with two examples: eelgrass shoot density and chlorophyll a in coastal ecosystems. Aquatic monitoring data vary over time and space; variations that can only partially be described using fixed parameters, and remaining variations are deemed random. These spatial and temporal variations can be partitioned into uncertainty components operating at different scales. Furthermore, different methods of sampling and analysis as well as people involved in the monitoring introduce additional uncertainty. We have outlined 18 different sources of variation that affect monitoring data to a varying degree and are relevant to consider when quantifying the uncertainty of an indicator calculated from monitoring data. However, in most cases it is not possible to estimate all relevant sources of uncertainty from monitoring data from a single ecosystem, and those uncertainty components that can be quantified will not be well determined due to the lack of replication at different levels of the random variations (e.g. number of stations, number of years, and number of people). For example, spatial variations cannot be determined from datasets with just one station. Therefore, we recommend that random variations are estimated from a larger dataset, by pooling observations from multiple ecosystems with similar characteristics. We also recommend accounting for predictable patterns in time and space using parametric approaches in order to reduce the magnitude of the unpredictable random components and reduce potential bias introduced by heterogeneous monitoring across time. We propose to use robust parameter estimates for both fixed and random variations, determined from a large pooled dataset and assumed common across the range of ecosystems, and estimate a limited subset of parameters from ecosystem-specific data. Partitioning the random variation onto multiple uncertainty components is important to obtain correct estimates of the ecological indicator variance, and the magnitude of the different components provide useful information for improving methods applied and design of monitoring programs. The proposed framework allows comparing different indicators based on their precision relative to the cost of monitoring.     

Investigating the causes of fish community change in the Dahan River (Taiwan) using an autecology matrix

Recent work in river restoration and water resources management has seen the need to change the focus of analysis from reach to watershed scales to better define causes of watershed impairment. However, comprehensive investigations at a watershed scale are hindered by difficulties in using reach data that was collected for analysis at small spatial and short temporal scales. This is especially true for ecological and biological data. The approach assembles assessment and monitoring data and uses an autecology matrix to identify the changes in environmental and ecological conditions that may be associated with community change over spatial and temporal scales appropriate for ecosystem analysis in watersheds. The analysis uses a weight-of-evidence approach based on the percent of the community associated with a matrix factor. We have used the autecology matrix to examine historical fish community data from the Dahan River, Taiwan. The results show that the method provides an improved understanding of historical influences on fish community structure and supports a process-based analysis of community change over watershed scales and historic time periods. Further the method helps identify habitat requirements for the fish communities at each sampling site, supporting management and ecological restoration objectives.     

Integrated assessment of ecological status and misclassification of lakes: The role of uncertainty and index combination rules

The European Water Framework Directive (WFD) requires that the ecological status of waterbodies is assessed using multiple biological quality elements (BQEs) that are combined into a single status class. The recommended combination rule (the “one-out, all-out” rule; OOAO) has been criticised for being unreasonably conservative and for being sensitive to uncertainty. In this study, the objective was to compare the sensitivity to uncertainty of four different combination rules: (1) OOAO, (2) OOAO with exclusion of one element, (3) average and (4) weighted average. Index values for 5 BQEs (phytoplankton, phytobenthos, macrophytes, macroinvertebrates and fish) sampled from 10 lakes in the Wel River catchment in Poland were used to classify the lakes according to the OOAO and the three alternative combination rules. Based on the mean and (where possible) standard deviation of these index values, we modelled the risk of misclassification by simulating 10,000 resamples for each BQEs in each lake, classifying each resample and calculating the proportion of misclassified resamples under each combination rule. For individual BQEs, the risk of misclassification increased both with higher uncertainty (standard deviation) and with the proximity of the index value to a class boundary. Under the OOAO rule, the risk of misclassification was more biased towards worse status (“underclassification”) than towards better status. Furthermore, risk of underclassification was more affected by uncertainty under the OOAO rule compared with the alternative combination rules. This analysis has demonstrated the weaknesses associated with the OOAO rule for integration of BQEs for lake classification. However, the alternative combination rules are associated with other shortcomings, such as the need for subjective judgement, and involve a higher risk of not protecting the most sensitive BQE and thus the whole ecosystem. We recommend that future versions of instructions for WFD implementation consider alternatives to the OOAO combination rule, and provide guidelines for weighting of individual BQEs.     

Ecological risk assessment of accidental release of flowback water: A conceptual framework

The aim of the study is to conduct an ecological risk assessment of accidental release of flowback water into freshwater body. Flowback water produced from the hydraulic fracturing process has a complex combination of high concentration of salts, organic compounds and metals. The toxicity of flowback water is assessed and an exposure assessment method for the inorganic constituents of the flowback water is developed. An equation for risk is derived to characterize the risk of the flowback water to the aquatic ecology. A case study is conducted for accidental release of hydraulic fracturing flowback water in Montney unconventional play trend in northern British Columbia. The flowback water quality data for 212 wells, including the concentrations of various salt ions, metal ions, and hydrogen sulfide, is collected for the assessment. The risk quotient is found to be 0.16 (<1), proving no significant risk to the aquatic ecosystem with 90% confidence. However, the overall results of the uncertainty and scenario analysis concludes that the risk to the ecology cannot be completely overlooked. Scenario analysis was done for monthly creek discharge and a relationship between risk quotient and the ratio of spill volume to the creek discharge was derived.     

流域生态风险评价研究进展

流域生态风险评价是流域生态环境保护与管理的重要研究内容,与一般的区域生态风险评价相比,具有其独特的流域特征。在已有研究基础上,对流域生态风险评价进行了概念界定与特征分析,并按照风险源、生态受体、生态终点的分类标准对流域生态风险评价进行了类型划分,简要评述了流域生态风险评价的相关研究主题,并尝试构建反映流域时空尺度变化规律的生态风险评价概念模型。最后针对流域生态风险评价的研究现状,重点讨论了目前存在的不足及未来的研究趋向。     

基于RS和GIS的南四湖生态风险评价

以南四湖为研究对象,基于遥感和地理信息系统技术选择干旱、洪涝和水体污染为生态风险源,用景观格局指数评价生态系统的地位和受体的易损性,并依据生态风险值的度量的原理,通过计算综合风险概率及生态综合损失度得到南四湖的生态风险值。研究结果显示南四湖区域生态风险存在上下级湖分异与湖滨带状分异两大空间规律,体现了南四湖区域生态风险的空间异质性。