Water Quality Assessment

Water Quality Assessment 13 A. Goldenberg-Vilar, R. Álvarez-Troncoso, V. Roldán, and Saúl Blanco Abstract Diatom metrics methods are becoming important tools for the assessment of environmental conditions in aquatic systems. Diatoms have several advantages as bioindicators: their ubiquitous distribution across world aquatic environments, their ability to integrate multiple water quality features, and the relatively simple and standardized sampling and preparation methods. To date, several diatom indices have been developed, most of which are general pollution indices, especially indicative of eutrophication and organic pollution. This chapter reviews the literature concerning diatom-based analyses for biomonitoring purposes, with a first overview on available methods (microscopy-based, automatic identification, and DNA barcoding), and an account on bioassessment tools using phytobenthos in EU countries, with a special focus on the Spanish experience. 13.1 Introduction The first tools for ecosystem health diagnosis in rivers were established ca. 100 years ago [1], and the use of organisms as indicators of water quality largely originated from Europe, A. Goldenberg-Vilar () IHCantabria - Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Santander, Spain Cimera Estudios Aplicados S.L. Science to Business, Madrid, Spain e-mail: alejandra.goldenberg@unican.es R. Álvarez-Troncoso · V. Roldán Cimera Estudios Aplicados S.L. Science to Business, Madrid, Spain S. Blanco Facultad de Ciencias Biológicas y Ambientales, Departamento de Biodiversidad y Gestión Ambiental, Universidad de León, León, Spain Laboratorio de diatomología y calidad de aguas, Instituto de Investigación de Medio Ambiente, Recursos Naturales y Biodiversidad, León, Spain e-mail: degsbl@unileon.es mainly devoted to monitoring organic pollution [2]. Traditionally, water quality assessment has been based on physicochemical analysis, although it has been largely demonstrated that this approach does not provide a temporally integrated picture of the response of ecosystems to impairment [3, 4]. On the contrary, biological monitoring has been proven to be useful especially in running waters, where concentrations can fluctuate notably even within a few hours, reflecting the overall quality status of a river during a certain period [5]. Particularly, changes in species composition reflect variations in water quality in a more integrated manner than mere chemical sampling [6]. In this regard, diatom-based methods are becoming important tools for the assessment of environmental conditions in aquatic systems. Diatoms have several advantages as bioindicators: their ubiquitous distribution across world aquatic environments, their ability to integrate multiple water quality features, and the relatively simple and standardized sampling and preparation methods [7, 8]. Additionally, diatoms exhibit high diversities both locally and regionally, but with comparatively narrow ecological profiles and short generation times, thus responding rapidly to environmental changes [1, 9]. Diatom-based methods are increasingly becoming important tools for assessment of ecological conditions in lotic systems. To date, several diatom indices have been developed, most of which are general pollution indices, especially indicative of eutrophication and organic pollution [10]. The output of these methods is usually a single score that permits rapid assessment of the overall condition of a stream in a manner that is easily understood by nontechnical resource managers [11]. Differences between indices scores are related to the taxonomic spectrum considered, the autecological parameters assigned, and the main environmental stressor that is being monitored [3, 12]. Diatom literature stresses the importance of ion concentration and trophic status as major environmental drivers of diatom distribution in aquatic ecosystems. Available metaanalyses [9, 13] show that diatom communities respond © Springer Nature Switzerland AG 2020 G. Cristóbal et al. (eds.), Modern Trends in Diatom Identification, Developments in Applied Phycology 10, https://doi.org/10.1007/978-3-030-39212-3_13 221 222 A. Goldenberg-Vilar et al. mainly to chemical variables [5, 10], overriding the effect of physiographical or geographical factors. The results of different diatom-based indices frequently result, however, in contrasting water quality diagnoses. To date, little effort has been done to elucidate the major drivers of diatom indices scores. The sensitivity of diatoms to environmental conditions can make them highly valuable indicators only if the effects of specific factors can be distinguished: while trophic conditions do have an influence on species composition, it is difficult to distinguish specific nutrients causing the effect [14, 15]. For instance, it is important for a diatom metric to discriminate the influence of nutrients from that of organic pollution, in general [16, 17]. Organic pollution is frequently associated with high nutrient concentrations, but under such conditions, nutrients are not necessarily the primary factor influencing community composition [18]. Moreover, naïve use of diatom indices might indicate changing nutrient status when, in fact, it is the degree of acid stress which is fluctuating [8]. Ecological assessment of freshwaters can be accomplished in situ in some cases (e.g., QBR or FHI indices, see Fornells et al. [19] and Pardo et al. [20], respectively) or with a minimal resource investment (e.g., methods using benthic macroinvertebrates). However, the computation of diatombased metrics requires expensive optical equipment, skilled microscopists, and access to specialized literature. During the last years, several attempts to simplify the protocols have been proposed, either by reducing the number of individuals necessary to provide an accurate result (e.g., [21]) or reducing the taxonomic level of identifications, e.g., genus-based indices [22] of trait-based methods [23]. Two alternative approaches have emerged thanks to the current availability of modern computation facilities, namely computer-assisted automatic identification based on image analysis and DNA barcoding. This chapter presents a brief review of these diatom-based water quality assessment approaches, focusing first on the available methods in current usage for freshwater biomonitoring, and then summarizing the results obtained during the last years, exemplified with field studies carried out in the Iberian Peninsula. references of Utermöhl [26] and Lund et al. [27]. In the case of benthic diatoms, the current EU standard protocols are regulated through the European Norms 13946 [28], which deals with the collection, preservation, and laboratory treatment of samples, and 14407 [29], which covers the identification and quantification of diatoms for samples coming from lotic epilithon. Kelly [30] offers a historical account of the development of these standards. The complete methodology had been previously summarized and made accessible to a general audience in the seminal paper by Kelly et al. [31]. Since then, these norms have been incorporated into the national legislations. In Spain, for instance, Water Authorities have published protocols and guidelines to be followed in river biomonitoring studies (e.g., [32, 33]). European protocols are in general congruent with international standards (mainly ISO 5667, which regulates water quality), except for some minor details (e.g., EN allows the fixation of field samples with formalin, whereas ISO recommends only ethanol or Lugol’s solution). The interested reader is referred to Stevenson and Bahls [34] for details on the protocols followed in other countries. Some authors have presented methodological proposals to either (a) apply the existing standards to other aquatic environments covered by the WFD, or (b) amend certain methodological aspects nod sufficiently detailed in the available protocols. In this regard, Blanco et al. [35] tested some improvements in the treatment of periphyton samples. Noticeably, CEN [29] recommends a systematic scanning of the microscopic slide starting from the coverslip edge. Moss [36] and Battarbee [37] already showed that valves are not randomly distributed due to the effects of water surface tension, which leads to a heterogeneous distribution of the different size classes [38, 39]. Alverson et al. [40] showed also that cell density is usually higher in the central area of the coverslips. It is therefore advisable that the use of random fields rather than “transverses,” which is proposed only as an alternative in the European Norm. Table 13.1 summarizes some protocols and methodological proposals concerning diatom-based biomonitoring and ecological studies available in the literature, arranged chronologically. 13.2 13.2.2 Automatic Diatom Identification Sampling and Analytical Protocols 13.2.1 EU Standards Until the implementation of the Water Framework Directive (WFD), the application of methods based on phytobenthic organisms for ecological monitoring followed the guidance provided in general standard references such as Rice et al. [24]. The basic protocols for the analysis of microscopic slides are inspired in the methods developed for planktonic organisms [25], which in turn are based in the classical Automatic identification of organisms is based on the recognition of shapes of interest based on outline matching against a large reference database. In the case of diatoms, first efforts raised in the late 1990s in the wake of the implementation of the ADIAC (Automatic Diatom Identification And Classification) project, financed by the European MAST (Marine Science and Technology) program. ADIAC involved the creation of large image databases linked to taxonomic and ecological information, together with the development 13 Water Quality Assessment 223 Table 13.1 Non-exhaustive compilation of available methods dealing with diatom-based biomonitoring and ecological studies Ref Fossil Marine [41] [42] Genetic Sampling • Processing • • [45] • • • • • [47] • • • • • [49] • • [50] • • • • [52] • [53] • [54] • • [55] • [56] [57] [58] • • • • • • • [59] • [60] • • [61] • [62] [63] [64] • • • • • • [65] [66] • • • [67] • [68] • [69] • [70] [71] • • • • [72] • [73] • • [74] • • [75] • • • • [76] [77] Soil • • [51] Forensic • [44] [48] Culture • • [148] [46] Microscopy • • [43] [37] Freshwater • • [78] [79] of automatic slide-scanning and autofocusing software allowing unsupervised scanning of microscope slides and automatic location of valves [80]. Its main goal was to develop algorithms for an automatic identification of diatoms using image information, both valve shape and ornamentation [81]. ca. 6000 images, covering approximately 500 diatom taxa, • • were acquired, including large test sets which were used for the testing of prototype software packages. The system developed allowed the identification of 37 species with an accuracy of 97% (see the results of this project in Du Buf [82]). An outstanding improvement of automated classification methods was accomplished in 2014 with SHERPA 224 software. SHERPA consists of image processing algorithm that allows the identification and measurement of diatom valves and other objects, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results [83]. By combining SHERPA with slide-scanning microscopes, mass-analyses of diatom cells mounted on permanent slides can be performed [84]. More recently, DiaOutline [85] has been proposed as a tool for valve outline extraction using MATLAB and R to perform elliptic Fourier analysis to identify several diatom taxa. In parallel, other methods based on the morphometric characterization of diatom individuals have been successfully employed for species delimitation. Pappas et al. [86] present a review of the history of usage of morphometric methods of outline shape analysis, pattern recognition, and landmarkbased analysis. Particularly, geometric morphometrics, combined with discriminant/classification analysis, is a powerful tool used to disentangle species complexes and compare specimens with type materials (e.g. [87–89], see Chap. 9). As an attempt to continue ADIAC philosophy with modern computational techniques, AQUALITAS project aims at developing an integrated system based on the development of an open mobile low-cost microscope and advanced image analysis techniques for diatom life cycle and polymorphism modeling as well as standardizing protocols for environmental diagnosis and monitoring (see this volume). In the frame of this project, the characterization of diatom valves by means of local binary patterns together with a log Gabor implementation led to an overall accuracy of 98.11% using bagging decision trees and combinations of descriptors for diatom identification [90]. Besides, the application of convolutional neural networks over a set of 160,000 images reached an overall accuracy of 99% [91]. Applying applies a single neural network (YOLO) over a certain image leads to remarkable results, with an average of 0.84 recall [92]. 13.2.3 Diatom DNA Metabarcoding Modern molecular techniques allow cost-effective a complementary approach to ecosystem health diagnosis, with scope for improved efficiency and reduced analytical error through automation and standardization [93]. In this regard, there is an increasing use of DNA barcoding for water quality monitoring. DNA barcoding has not only improved biomonitoring protocols but has revolutionized also biodiversity studies facilitating the understanding of biogeography, community assembly, and ecological processes [94], allowing to trace the species distribution and ranges in their natural habitats A. Goldenberg-Vilar et al. [95]. DNA barcoding is based on the premise that the divergence in small DNA fragments mirrors biological separation of species [96]; this fragment is compared with reference sequences stored in a database to assign an organism name to it [97]. Thus, a good quality reference database is the keystone to any barcoding approach that requires taxonomy assignment [93]. The combination of DNA barcoding with next-generation sequencing (NGS) enables the simultaneous sequencing of DNA from whole communities or “metabarcoding,” which leads to species identification from a standardized DNA barcode and high-throughput sequencing (HTS), using DNA reference libraries [98, 99]. This approach has proven a more refined taxon detection than the microscopical approach [99]; for instance, Moniz & Kaczmarska [96] report a 99.5% success rate in separating biologically defined diatom species. Recent attempts to develop taxonomy-free metabarcoding-based biomonitoring protocols for aquatic habitats are showing promising results. For instance, Vasselon et al. [100, 101] found that ecological quality assessment using both molecular and morphology-based (SPI scores) were congruent at the scale of a whole biomonitoring network. In a similar study, 77% of the sampling sites were correctly assigned to their ecological quality status using diatom metabarcoding [102]. In general, the sequence-based technology leads to a higher number of identified diatom taxa in natural samples when compared to light microscopy methods [99]. Despite its successful application, the application of molecular techniques for chromists and, particularly, for eukaryotic microalgae, has still numerous pitfalls and limitations. DNA metabarcoding has thus been subject to criticism in the literature. For instance, it has been demonstrated that DNA barcoding has no discriminating success within species complexes (e.g., [103]), probably as a consequence of low variation rate at the plastid genome level. These authors show that species-rich genera (as in the case of many diatoms) may prove exceptionally difficult to barcode. There are no fast and easy bypasses for systematics and DNA barcoding which can be currently recommended for protistan researchers because automatic species delimitation methods tested proved to be highly dependent in taxon sampling and prone to artifacts [104]. In an extremely diversified group such as diatoms, barcoding therefore has clear limitations and it is inherently incapable of identifying all taxa [105]. For instance, Frustulia species cannot be resolved without the use of additional nonmolecular evidences [106]. Besides, maintaining diatom reference databases often implies culturing diatom species, which is a specialized, resource intensive exercise. Actually, as stressed by Rivera et al. [98], differences in molecular and morphologybased environmental diagnoses are due mainly to the incompleteness of the DNA reference libraries. Vasselon 13 Water Quality Assessment et al. [101] estimate that up to 82% of “morphological” species are not represented in the molecular databases, especially rare taxa occurring in oligotrophic waters [99]. Molecular inventories are also strongly influenced by the DNA extraction method used [100, 107]. In view of these limitations, Kelly et al. [93] recommend in their recent review that the combined use of molecular techniques and “classic” taxonomy since both methods offer alternative views of the river ecosystem status. 13.3 Distribution and Frequency of Diatoms in the Iberian Peninsula The distribution of diatom communities depends on the species-specific physiological and ecological demands. From the myriad of environmental factors affecting diatom distribution, several studies and scientific reviews [9] highlighted the role of major ion concentrations in both lotic and lentic systems. The primacy of major ion concentrations affecting community composition reflects the fact that water pH is a highly important variable for aquatic biota, regulating many physiological processes, and consequently, water conductivity, alkalinity, or calcium concentration. These environmental variables are highly dependent on river geology, substrate, and physical conditions. Specific diatom assemblages can be found according to the natural differences in river physical features, so to increase the accuracy of anthropogenic impact assessment we may first account for the natural variability among sites. For that purpose, the use of a typology to classify streams (according to their geology, substrate, and physical conditions) has become an accepted part of ecological assessment [108]. The EU Water Framework Directive fixed typology, i.e., “System A” is defined by ecoregions, size based on the catchment area (small 10– 100, medium 100–1000, large 1000–10,000, and very large >10,000 km2), catchment geology (calcareous, siliceous, and organic), and altitude (lowland, <200, mid-altitude 200–800, and high altitude >800 m a.s.l.). Within any given part of the WFD typology, it is assumed that biological communities at undisturbed sites will be broadly similar and will therefore constitute a type-specific biological target. The EU Water Framework Directive also allows each member state to adopt an alternative characterization “System B” with 5 obligatory factors (altitude, latitude, longitude, geology, and size), and an additional 15 optional factors (e.g., distance from river source, mean water depth, and mean substratum composition). No specific categories of value ranges are suggested for each factor in “System B” and the member state is left to decide how many of the optional factors they wish to use. In consequence, a very extensive set of stream types could be defined by individual Member States for each ecoregion within their territorial limits [109]. 225 13.3.1 River Typologies: Siliceous and Calcareous The general methodology for the establishment of types and reference conditions in Spanish rivers has been regulated by the IPH (Sects. 2.2.1.3 and 2.2.1.4 and Annexes II and III) following a technical proposal by Spanish Research Center CEDEX based on the WFD system B (European Commission report, 2015). The first step in the classification process was to distinguish between the two main biogeographical areas present in the Iberian Peninsula: Eurosiberian area with an oceanic climate and evenly dispersed precipitation through the year, and Mediterranean area, with much lower precipitation volume and dry summers. The variables selected for the classification of river typologies in Spain are specific flow, mean annual flow, average basin slope, altitude and conductivity and GIS modeling has been used for the classification of Spanish River types. As a result, the IPH establishes 32 river types. Additional types have been established by River Basin Authorities (RBAs) (e.g., river types in ES110—this latter still in process) [110]. Although regional classifications of streams have been established throughout the world, little is known about their correspondence with freshwater biota biogeography [111]. Hence, recently researchers began to evaluate the correspondence between ecoregional classifications and biological assemblages. For diatom communities, several approaches have been developed, proving that using biological communities for stream classification greatly reduce the number of river typologies, and thus, simplifying ecological assessment to a few ecologically relevant types [112]. Following a similar methodology developed for the Canadian Diatom Index (IDEC), the Spanish Diatom Index—SDI, and lately iDIAT-ES (Alvarez-Troncoso et al., in prep.) have been developed in 2016 by the Spanish Ministry of Environment. Based on a correspondence analysis (CA) iDIAT-ES developed a chemistry-free index where the position of the sites along the gradient of maximum variance (first axis) is strictly determined by diatom community structure and it is therefore independent of measured environmental variables (Fig. 13.1) (for more information see Sect. 13.4). Based on diatom data at national level comprising 975 sites and around 400 species, the iDIAT-ES resulted in three final river typologies based on catchment geology: siliceous (values for 381 species), calcareous (values for 342), and one for Tinto river (values for 5 species). Diatom community structure according to siliceous and calcareous typologies as defined by the iDIAT-ES with an Ecological Quality Ratio (EQR) higher than 0.8 is represented in Fig. 13.2. Similarly, a predictive diatom-based model to assess the ecological status of streams and rivers of Northern Spain (NORTIDIAT) [113], significantly characterized four different diatom groups with obligatory and optional descriptors of the WFD typology 226 A. Goldenberg-Vilar et al. Fig. 13.1 Representative diatom species from siliceous and calcareous typologies. These species show the highest dissimilarity in average abundance between the groups in the same set of samples as used for Fig. 13.2. Abbreviations for calcareous ADMI: Achnanthidium minutissimum; APED: Amphora pediculus; CEUG: Cocconeis eug- lypta; NCTE: Navicula cryptotenella; CAFF: Cymbella affinis; ECPM: Encyonopsis minuta; and for siliceous CLNT: Cocconeis lineata; GRHO: Gomphonema rhombicum; ADRI: Achnanthidium rivulare; COPL: Cocconeis pseudolineata; ENMI: Encyonema minutum; ESLE: Encyonema silesiacum that corresponded to a four river type’s typology B. These four groups represented existing gradients in calcareous geology, catchment size, altitude, and other characteristics of main river types existing in the studied area. The four species group’s composition evidenced the correspondence between the diatom assemblages across the N–S and W– E direction, catchment’s geology (from 100% siliceous to 100% calcareous) and size (from 2 to 2196 km) and site elevation (from 15 to 1356 m). between current conditions and reference condition status [112]. The indices are usually expressed as a value along an alteration gradient (e.g., 0–100) or as an overall statistical difference from reference conditions. To facilitate the interpretation of the biological “distance” of a site from its reference status, the alteration gradient is often divided into classes reflecting qualitative levels of biological integrity. These approaches allow for a rapid and easy overall picture of the ecosystem status and are particularly interesting for water quality managers. Although the creation of biological integrity classes is useful, the approaches used to define the number of classes and the limits between these classes are arbitrary and lack meaningful biological considerations [112]. Indeed, the number of classes is usually arbitrarily determined with widths of either equal proportion (e.g., [3]) or unequal proportion as occurs within the SPI (e.g., [119]), the diatom index currently used in Spain. Indeed, the SPI diatom metric is used as the national classification system for all stream and rivers types in Spain (RD 817/2015), in spite of strong regional differences in the Spanish climate and geomorphological characteristics. A reference value for the SPI is defined for each of the river typologies officially used in Spain under the WFD. Much of the progress made in the science of ecological assessment emerged from research that advanced our understanding of how the spatial and temporal distributions of freshwater biota are related to naturally occurring environmental features and how those relationships can be most accurately and precisely described and predicted. In that way, similarly than for the definition of river typologies, gradient tools such as iDIAT-ES and NORTIDIAT, also demonstrate their validity for the definition of ecologically relevant referent conditions. In this way, the samples composed of the most 13.3.2 Reference Conditions The assessment of biological quality is based on the degree of deviation from a reference biological population. Biological integrity [114] is measured by comparing a given site with reference ecosystems that lie in similar geomorphological and climatic settings but are not exposed to human impact [115]. Critical to the efficacy of ecological status assessment in rivers is the ability to characterize biological assemblages at reference sites. In Spain many Mediterranean regions, particularly lowland areas, have been substantially modified by human activities [116–118]. The challenge lies in identifying adequate numbers of reference sites within a river type, which ensures the incorporation of the intrinsic variability of environmental conditions within the river type [116]. Over the last decades, numerous bioassessment tools have been developed to evaluate the biological integrity of aquatic ecosystems and to determine the effect of a wide range of stressors on this integrity. Most of these tools are based on the Reference Condition Approach (RCA), where the biological integrity of a site is defined by the “distance” 13 Water Quality Assessment Fig. 13.2 CCA (Canoco 5) of diatom species and environmental variables measured under Spanish routine monitoring programs (Data from the Ministry of Environment MITECO, Spain) divided in siliceous and calcareous typologies. Data span the 31 Spanish River typologies (except Tinto) and 442 sampling locations with EQR > 0.8 collected be- different biological communities, compared with reference communities, determine the maximum alteration level. Figures 13.1 and 13.3 show some representative species of the siliceous and calcareous typologies as defined by the iIDIATES in sites under “High” water quality category (EQR > 0.8). The difference from reference communities and similarity with altered communities are used then to assess the degree of alteration of a test site. The performance of ecological assessments is critically linked to how well we characterize freshwater environments. The knowledge produced from future collaborations between ecologists and watershed scientists coupled with the application of modern modeling techniques will largely determine progress in characterizing and predicting biota-environment relationships and, thus, the accuracy and precision of future ecological assessments [120]. 227 tween 2004–2008. Only significant environmental variables are shown from conductivity, pH, oxygen, biological oxygen demand, nitrate, nitrite, and orthophosphate. Explanatory variables account for 14.74% of the total variation. The cumulative explained variation of first axis is 66.7% and second 85.63% from the total explained variation 13.4 Diatom-Based Bioassessment Tools 13.4.1 European Autoecological Indexes: SPI, TDI, Rott, and ICM (Intercalibration Common Metric) The Water Framework Directive (WFD) was declared in 2003 and provides a legal basis for water management in the European Union (EU). The WFD requires that ecological status assessments of rivers and lakes are based on evaluations of phytoplankton, macrophytes and phytobenthos, benthic invertebrates and fish. The objective of the WFD is to protect inland and coastal waters and promote sustainable water use in Europe (Article 1) with “ecological status” used as a benchmark against which progress toward this objective is assessed. Ecological status is defined as “an 228 A. Goldenberg-Vilar et al. Fig. 13.3 Images of some representative species in each group: Siliceous (a—CLNT; b—GRHO; c—COPL) and calcareous (d—APED; e—ADMI; f—CEUG). Sources (a), (b) and (c): bit.ly/ 2UDf6fk, (d): bit.ly/2KYieCK, (e): bit.ly/2DwayBy, (f): bit.ly/ 2UXPjDk. All bars denote 10 µm expression of the quality of the structure and functioning of aquatic ecosystems associated with surface waters [ . . . ]” (Article 2). This assumes that a healthy ecosystem is a good indicator that a water body is being exploited in a sustainable manner. Ecological status is a holistic concept, not confined to any single organism group (or “biological quality elements” [BQEs] in the terminology of the WFD); the use of “functioning” in the definition suggests a need to understand both the state of a BQE and its interactions with other BQEs and the catchment. For rivers and lakes, four BQEs are defined, one of which is “macrophytes and phytobenthos,” although most member states have treated these as two separate sub-elements, with diatoms frequently employed as representatives of the phytobenthos [121]. Epilithic diatoms have been widely used as efficient indicators for evaluating water quality, considering that they respond quickly to environmental changes, especially organic pollution and eutrophication, with a broad spectrum of tolerance, from oligotrophic to eutrophic conditions [122– 124]. Diatoms are one of the key groups of organisms recommended by the WFD for the identification of ecological quality gradients in rivers. Among the biological methods developed to indicate the trophic level of running waters, the trophic diatom index (TDI) proposed by Kelly and Whitton [125], has been widely used in the European Community, especially after the publication of the Municipal Sewage Treatment Plants policy in 1991. The TDI uses the equation of the weighted average of Zelinka and Marvan [126] to interpret the structure of epilithic diatom biocenoses in terms of nutrient concentrations in rivers, mainly phosphate. However, since 2006 when the intercalibration exercise among geographical areas 13 Water Quality Assessment in Europe was introduced, the SPI (Specific Polusensibility Index, [127]) was selected for that purpose by the scientific community. This index has been intercalibrated at European level in the different regional groups. At the beginning of the WFD implementation, those states that have now reported phytobenthos methods, 15 (58%) have chosen to use weighted average metrics developed prior to the WFD, with the SPI (9 states, 35%) being the most commonly employed. The apparent popularity of the SPI, however, disguises many national variants and constitutes a “family” of closely related indices, rather than a wholly consistent approach to ecological status assessment among these states. The use of weighted average metrics as SPI assumes that nutrient or organic pollution is the main pressure encountered within the territory. There is a risk of missing pressures that these indices do not detect [8]. These problems should be overcome by indices based on the actual species expected to be encountered in a particular region and stream type. Over half of EU states have methods based wholly or partly on weighted average metrics developed before the onset of the WFD, with nine choosing the SPI. Such metrics generally have high correlations with the predominant nutrient or organic pollution gradient and, as such, represent pragmatic solutions to ecological status assessments. However, their widespread use raises questions about what, exactly, “ecological status” means. Strong relationships with chemical pressure gradients may be a mixed blessing as pressure gradients are often composed of several intercorrelated variables, making it difficult to disentangle correlation and causation in the absence of ecophysiological studies of individual species. Moreover, the focus on strong relationships with chemical gradients means that most phytobenthos metrics describe the scale of hazard at a site rather than the risk posed to other trophic levels and to ecosystem services. This first generation of phytobenthos assessment tools may be inadequate when catchment managers need guidance on remediation strategies for particular water bodies. A second generation of assessment tools is needed if the goal is to achieve good ecological status, focusing on the fitness of the phytobenthos as part of aquatic ecosystems, rather than just as indicators of chemical conditions. Diatom indices developed in certain geographic regions are frequently used elsewhere. There are strong evidences that such metrics are less useful when applied in regions other than that where species-environment relationships were originally assessed, showing that species have particular autoecological requirements in different geographic areas. For example, although the SPI index has been developed in France, it has been used in many other European countries under their routine water quality monitoring programs, and it is the recommended diatom index in Spanish rivers [128]. As some authors have already pointed out, there are certain disadvantages when 229 using metrics developed in another region when studying the ecological state of local characteristics [3, 129, 130]. One of the problems detected is an overestimation or, on the contrary, underestimation of the ecological status. The environmental differences from one region to another cause differences in the identity of the species present and also the response of the same species to changes in water quality [31]. In Spain, other diatom indices have been developed like MDIAT [131] that is a multimetric method and DDI [122] that is a method based on specific autoecologies, similar to SPI. During 2016 a new index iDIAT-ES (Álvarez-Troncoso et al., in prep.) was developed for Spain based on ecological distances for the Tagus hydrographic demarcation, the TADI (TAgus Diatom Index) [132]. There are numerous indexes in Europe for calculating trophic conditions in freshwaters ecosystems, and in the last years new diatom indexes have arisen. These indexes were developed independently for both lotic and lentic ecosystems, more often originated from regional datasets, and served mostly as a basis for regional water quality assessments [133]. Some of the indexes have been rescaled under the Diatom Indicator Database that uses a standardized taxonomic diatom list (CEMAGREF taxa list, updated version May 2008). 13.4.1.1 SPI (Specific Pollution Sensitivity Index) The SPI, Pollution Sensitivity Index [127] has been regarded as one of the most precise indices because it incorporates approximately 2000 species in its database, the largest among all diatom indices [134]. More than 70% of the common species could be found in the SPI list. Most of the variation (82%) in the SPI index is explained by parameters such as conductivity and salt concentration and percentage of urban area, which is consistent with the finding that SPI responds to water quality parameters related to conductivity and eutrophication [134]. These examples support the view that the performance of diatom-based indices in part depends on the degree of overlap between the taxa list in the index development and those that occur in the sampled streams. Calculation of this index relies on the Zelinka & Marvan [126] formula derived from the saprobic system:  Aj vj ij (13.1) SPI =  Aj vj where Aj is the relative abundance of the species j, vj is its indicative value (1 ≤ vj ≤ 3), and ij its pollution sensitivity (1 ≤ ij ≤ 5). The values initially falling in the range between 1 and 5 are transformed into values comprised between 1 and 20 in order to make comparisons between the various existing indices easier. Five categories of water quality can be distinguished according to the value of the index: SPI ≥ 16: zero pollution or low eutrophication; 13.5 ≤ SPI < 16: mod- 230 A. Goldenberg-Vilar et al. alive within 48 h. Afterward, the samples are preserved following the standard instructions for diatom preparation. After the identification, the relationship between taxon and environment is defined by examining graphs summarizing percent count versus Filterable Reactive Phosphorus (FRP for each taxon). “Sensitivity” values of between 1 and 5 were assigned to each taxon depending upon the concentration at which taxa were most abundant. Calculation of the index uses the weighted average equation of Zelinka and Marvan [126]:  Aj vj ij TDI =  Aj vj Fig. 13.4 Representative diatom taxa of the different water quality categories recognized in the Water Framework Directive (from left to right: zero, low, moderate, high, and very heavy pollution levels, respectively) erate eutrophication; 11 ≤ SPI < 13.5: moderate pollution or heavy eutrophication; 7 ≤ SPI < 11: high pollution; SPI < 7: very heavy pollution (Fig. 13.4). However, the SPI index has two main obstacles: it requires data at a specific or even intraspecific level, and it is based on constantly changing systematics. 13.4.1.2 TDI (Trophic Diatom Index) This index was created for monitoring the trophic status of rivers based on diatom composition. It was developed in response to the National Rivers Authority (England & Wales)’s needs under the terms of the Urban Wastewater Treatment Directive of the European Community. TDI represents a useful monitoring tool for site assessments prior to the designation of sensitive areas. It was conceived with the purpose of designing an index to monitor eutrophication in rivers that seemed more appropriate. The sampling methodology developed to apply this index requires the collection of epilithic diatom samples following the method of Round [135]. The samples are then transported to the laboratory in an icebox and the material is examined (13.2) The value of TDI can range from one (very low nutrient concentrations) to five (very high nutrient concentrations). Proportion of valves under each category and its interpretation: <20% total valves belonging to tolerant taxa: free of significant organic pollution; 21–40% total valves belonging to tolerant taxa: some evidence of organic pollution; 41–60% total valves belonging to tolerant taxa: organic pollution likely to contribute significantly to eutrophication of site; >61% total valves belonging to tolerant taxa: site is heavily contaminated with organic pollution. In conclusion, the TDI represents a useful monitoring tool for site assessments prior to the designation of sensitive areas. Nevertheless, the TDI index will require careful interpretation of the results being aware that its assessment is based on the effect of FRP on diatom community composition. 13.4.1.3 Rott’s Index Rott et al. [130] created an extended database of samples collected in 450 sampling sites in rivers, including approximately 1000 species from 9 different classes of algae. Levels of saprobity and trophy were defined for 650 diatom species. Through his intensive and extensive studies, he created a diatom collection that is housed in the National Institute for Water Research (CSIR) in Pretoria and is used as a reference for research of diatoms in this country [136]. Starting in the last decade, research related to diatoms in South Africa focused on the ecological aspect of the community to assess water quality, and testing was conducted by applying the European indices under South African conditions. 13.4.1.4 ICM (Intercalibration Common Metric) Intercalibration of methods ensures the comparability of biological elements across similar geographical areas. The WFD requires the national classifications of good ecological status to be harmonized through an intercalibration exercise. Most of the geographical intercalibration groups have finalized Intercalibration results but many Member States 13 Water Quality Assessment 231 have not joined the group or have not intercalibrated the methods due to some reasons. Those Member States will have to show that their methods are compliant with the WFD normative definitions and that their class boundaries are in line with the results of the intercalibration exercise. Many aspects can influence the outcome of intercalibration: data sampling, treatment methods, taxonomic reliability of databases, choice of metrics for ecological quality status classification, and criteria for selecting reference sites. Harmonization of diatom taxonomy and nomenclature was based on a previous ring test which took place at the European level. Four diatom indices (Indice de Polluosensibilité Spécifique—SPI, Indice Biologique Diatomées—IBD 2007, Intercalibration Common Metric Italy—ICMi and Slovenian Ecological Status assessment system) were intercalibrated using data from six European Mediterranean countries (Cyprus, France, Italy, Portugal, Slovenia, and Spain) [137]. Boundaries between High/Good and Good/Moderate quality classes were harmonized by means of the Intercalibration Common Metric (ICM). Comparability between countries was assured through boundary bias and class agreement. The national boundaries were adjusted when they deviated more than a quarter of a class equivalent (0.25) from the global mean. All national methods correlated well with the ICM, which was sensitive to water quality (negatively correlated to nutrients). Achnanthidium minutissimum sensu lato was the most discriminative species of Good ecological status class. Planothidium frequentissimum, Gomphonema parvulum, and Nitzschia palea were the most contributive to Moderate ecological status class. This intercalibration exercise allowed the establishment of common water quality goals across Mediterranean Europe, which is substantiated with the ICM. The ICM is an index that results from the combination of two widely applied diatom indices, the SPI and Rott’s Trophic Index—TI [130]. The SPI accounts for general water quality estimates, low values corresponding to high-pressure levels and low EQRs. The TI measures nutrient load and was adjusted so that high values represented high EQR values. The ICM is thus defined as: ICM = (EQRSPI + EQRTI ) 2 (13.3) where EQRSPI = observed value/reference value (This reference value is the median SPI value of reference sites for a national dataset) and EQRTI = (4 − observed value)/(4 − reference value) (This reference value is the median TI value of reference sites for a national dataset). However, another requisite for intercalibration to proceed was that there should be a significant correlation between the ICM and the national indices, in addition to the ICM response to pressures. Pearson correlation was calculated to estimate the relationship between partner country indices and the ICM, with the criterion that Pearson’s correlation coefficient (r) should be equal or higher than 0.5. From 1031 samples analyzed to define the index, 205 were considered representative of least disturbed and, therefore, used as part of the reference sites in subsequent analyses. Nonsignificant Spearman rank correlations characterized the relationship between diatom data and the environmental pressures in the least disturbed sites. The ICM was responsive to nutrient enrichment, especially ammonia, total phosphorus, and phosphates when considering the entire quality gradient. The ICM proved robust and adequate for intercalibration purposes and reliably reflected national water quality. Intercalibration of diatom assessment methods was attained despite the difficulties encountered during the process, including the taxonomic inconsistencies and different data acquisition due to the robustness of these methods. 13.4.2 Diatom Indexes Developed for the Iberian Peninsula There are different experiences designing and preparing new indexes for Iberian rivers. They arose from the need of developing more sensitive indicators that are specific for Iberian regions and typologies. The new metrics are based on diatom communities present in the reference conditions of the different Iberian typologies, and thus, provide more sensitive indicators than the ones provided by other European geographical areas [17, 125, 138]. 13.4.2.1 Multimetric Index: MDIAT MDIAT is a diatom multimetric index created as a combination of metric values. The sensitivity of the MDIAT to organic and nutrient stressors supports the use of this index to classify the ecological status of Galician rivers (NW, Spain). This index has been designed only for Galician granitic rivers (NW Spain) and has been intercalibrated at the European level in the Central Baltic Rivers GIG (Geographical Intercalibration Group) due to the need of finding an index that could fit this need. The Northwest of the Iberian Peninsula is influenced by the Atlantic climate, and it is characterized by rainy weather with mild temperatures throughout the year, similar to the rest of Western Europe. The region of Galicia lies in this area of Spain with the Cantabrian Sea to the north and the Atlantic Ocean to the west [131]. The geology is dominated by siliceous rocks: granite in the west and metamorphic rocks in the east. The selection of diatom indices and metrics for the new index followed the procedure described by Barbour et al. 232 [139] with some modifications as follows (1) Assessing redundancy, (2) Relation with the physicochemical variables, and (3) Estimating discrimination efficiency. After discrimination and selection of the most suitable indexes, six indexes and two metrics were combined in the multimetric MDIAT. After rescaling, eight rescaled values were summed to the MDIAT. According to the authors, diatom multimetric index (MDIAT) had the highest discriminatory efficiency and highest correlations with the physical–chemical variables of all indices and metrics tested in the NW Spanish region. The new index, the MDIAT has a complex composition that includes newly developed metrics which are more sensitive and specific for Galician oligotrophic waters than the intercalibration index. In conclusion, MDIAT constitutes a very good tool to evaluate the ecological status of Galician coastal rivers. The multimetric values were better correlated with the physicochemical variables than with the individual indices, integrating the effects of the pressures studied (organic pollution enrichment and eutrophication). The index may be improved and, ideally, further simplified in the future. 13.4.2.2 Autoecological Index: DDI The goal of this new metric, the Duero Diatom Index (DDI), aimed at monitoring water quality in Duero basin watercourses (NW Spain). DDI was developed as a method of monitoring the integral status of watercourses, in order to realize a comprehensive assessment of water quality in the Duero Basin Rivers. DDI assesses the degree of water pollution as a measure of pH, salinity, organic pollution, and eutrophication, the last being the main factor controlling the distribution of the dominant diatom species in the Duero basin according to Blanco et al. [128]. The authors chose the weighted average method to develop the DDI index since it combines ecological credibility with empirical predictive power and simplicity. 13.4.2.3 Ecological Distance Index: iDIAT-ES The iDIAT-ES value indicates the distance (or similarity) of each diatom community to their specific community of departure or reference. In this way, a high value represents a site with no or very little impact regarding its reference condition (very similar), while low values represent sites with greater impact due to contamination (low similarity to reference conditions). The weight of each species in the model was obtained by adding the abundances of a species in all the stations for a specific group. The weights of each species were calculated according to the percent of valves of each species in the seasons in which it was present with respect to the total valves of all the species for that set of stations that made up a certain group. The model used to calculate the value of the index of new samples is the formula presented below, based on the work of Lavoie et al. [140] and A. Goldenberg-Vilar et al. also on the formula of Zelinka and Marvan [126]:  k Wk Aik Xk iDIAT.ES =  k Wk Aik (13.4) where iDIAT-ES is the position of the sample on the main axis and, therefore, its index value, Wk is the weight of the species k, Xk is the value of the species k in the first axis of the CA, and Aik is the abundance of species k in the sample i. Before calculating the iDIAT-ES index, it is essential to know the river typology that we are studying to choose the right iDIAT-ES group according to the natural conditions of the sampled region. There is an ordination method who allowed to create and designed the iDIAT-ES (Spanish Diatom Index), with values between 0 and 5, where the position of the species of each group is placed over the maximum variation gradient (horizontal axis, X) which it is described by the diatom community composition. A high value of the index (close to 5) represents low impacted or not impacted site, whereas low value of the index means high perturbation or impact in the waterbody. The index represents three different groups corresponding to three ecologically different diatom communities: calcareous, siliceous, and a group for the typology 19 (Río Tinto) that is a very distinctive group in terms of diatom composition. It has been verified that there is a good correlation between the iDIAT-ES index and other indices such as SPI, BDI, CEE, and with other indicators of land uses and physical–chemical variables associated with pollution and pressures of different origin. Therefore, it is considered appropriate to use this new index as a tool for the evaluation of the ecological status in Spanish rivers and also a suitable index for the intercalibration exercise in relation to the rest of European indexes. The iDIAT-ES has been developed with data from Spanish basins and adapted to the conditions of the Iberian river ecosystems. Its development at the national level has allowed us to consider the particularities of each of the basins and obtain values for each species that are typical of local conditions. Its application is relatively simple given the low number of taxa to be considered, from a database of approximately 18,000 species for the SPI to one of about 400 species for the iDIAT-ES. 13.4.3 Complementary Metrics Based on Diatoms (Growth Forms, Ecological Guilds, Teratologies) Besides the metrics based on species identities, there are also other diatom metrics that are based on morphological traits such as growth forms, cell sizes, or biovolumes. Functional traits are proxies of adaptation strategies under particular environmental conditions, and life-strategies occupying a 13 Water Quality Assessment similar niche can be collected in functional groups. Relationships between the abundances of such functional groups such growth forms and nutrients were established in experimental contexts [141, 142] and gave satisfactory results in largescale studies to assess nutrient and global pollution (e.g., [143]). One of the most used and simplified classifications of diatom functional groups was developed by the ecological guilds published by Passy [144]. Guild refers to a group of species that exploit resources in a similar way, resulting in stronger competition within the guilds than between them. Passy’s classification can be regarded as functional, including the way species attached to the substrate, thus how they cope with disturbance (e.g., flow velocity, grazing) and the way they utilize resources. Some of these relationships are proposed for bioassessment tools [139]. Diatom traits are derived from the Irstea database (bit.ly/2XCAe74) for biovolume and pioneer forms, from Kelly et al. [145] for growth forms and from Passy [144] for guilds. Regarding the teratology, some authors suggested that they should be taken into account in the diatom indexes. By displaying deformities (teratologies) in their siliceous valves, diatoms have the potential to reflect sublethal responses to a wide range of toxic stressors including EU priority substances such as metals and organic compounds (see Chap. 3). Lower percentages of teratology, on the other hand, (<0.5%) [146] are commonly observed in natural diatom assemblages, due to changing environmental conditions. The presence of multiple stressors, however, can significantly increase the proportions of deformed individuals. Diatoms have fast growth rates (from hours to days), and thus respond very quickly to variations in their environment. The observation that valve aberrations are routinely found in extremely contaminated conditions led Coste et al. [147] to include the occurrence and abundance of deformed individuals in the calculation of the biological diatom index BDI. In the BDI, observed deformities were assigned the worst water quality profile, meaning that their presence tends to lower the final water quality score. Further development of teratologicalbased bioassessment tools have been already emphasized [146] and are under development. 13.5 ID-TAX: Identification Key for Biological Quality Elements Used in Routine Biological Monitoring in Spain The ID-TAX project started at the beginning of the twentyfirst century and it was developed by the Spanish Ministry for the Environment (MITECO) as a tool to standardize taxonomical criteria at national level in compliance with the European Water Framework Directive. The ID-TAX complements other open access tools developed earlier by 233 the Ministry of Environment such as the Tesauro taxonómico (TAXAGUA) and the standard protocols for routine biological monitoring in Spanish water bodies. By the use of these open access tools, water quality assessments based on biological quality elements (BQE) are standard and comparable through the Spanish national territory. The ID-TAX has developed a system able to classify all taxonomical information available for the BQE used for water quality assessments by the different Spanish water authorities. The results of ID-TAX were published in 2012 as printed books and as online and CD digital applications. The taxonomical information is divided into five sections, one per each BQE: macroinvertebrates, macrophytes, fish, phytobenthos, and phytoplankton. The species identification keys and species detailed information are available per each section. The ID-TAX tool has been developed by taxonomical experts who regularly check the taxonomical information providing an accurate and up to date tool. The ID-TAX identification key uses the taxonomical information present in Tesauro Taxonómico (TAXAGUA) which has been developed by the Ministry of Environment from 2004 to 2011. The ID-TAX was first published with 1549 taxa from the 25,000 present in TAXAGUA. The number of taxa has been increased since the ID-TAX first review in 2013. The taxa included in the ID-TAX are the ones who have an indicator value for the different ecological indices used for each of the BQE, although some dominant species without indicator value are present as well. The ID-TAX taxonomical information is divided into two parts: a dichotomous key for species identification and a catalog with detailed species information including, morphology, taxonomy, ecology, and the indicator value of each species for their respective ecological index. A digital map with the distribution of species is also available in the web version, located in the GIS and map services of the Spanish Ministry of Environment. 13.6 Conclusions Diatoms as unicellular eukaryotic algae characterize an organism group which has a number of prominent distinctive features that render diatom analysis as a useful tool for indication of present ecological conditions. Automatic species identification offers a promising tool to identify species complexes with high accuracy aiming at reducing bias in identification assessment. The near-term future of DNA metabarcoding, on the other hand has an enormous potential to boost data acquisition in biodiversity research and water quality assessments worldwide. To improve the accuracy of water quality assessments based on diatoms, not only the improvements of quantification methods are required but also the development of indices 234 that reflect climate and geomorphological driven regional variability of diatom assemblages. The information value of indicators depends largely on how they are developed and calibrated, and more precisely on how well the autoecological requirements of those taxa are quantified. New technologies in diatom species quantification and new regional developed diatom indices anticipate further developments toward this direction. References 1. Venkatachalapathy, R., Karthikeyan, P.: Application of diatombased indices for monitoring environmental quality of riverine ecosystems: a review. In: Environmental Management of River Basin Ecosystems, pp. 593–619. Springer (2015) 2. Taylor, J., Prygiel, J., Vosloo, A., Pieter, A., van Rensburg, L.: Can diatom-based pollution indices be used for biomonitoring in South Africa? A case study of the Crocodile West and Marico water management area. Hydrobiologia. 592(1), 455–464 (2007) 3. Lavoie, I., Campeau, S., Grenier, M., Dillon, P.J.: A diatom-based index for the biological assessment of eastern Canadian rivers: an application of correspondence analysis (CA). Can. J. Fish. Aquat. Sci. 63(8), 1793–1811 (2006) 4. Rakowska, B., Szczepocka, E.: Demonstration of the Bzura River restoration using diatom indices. Biologia. 66(3), 411–417 (2011) 5. Blanco, S., Bécares, E., Cauchie, H.-M., Hoffmann, L., Ector, L.: Comparison of biotic indices for water quality diagnosis in the Duero Basin (Spain). Archiv für Hydrobiologie Supplement Large Rivers. 161, 267–286 (2007) 6. Taylor, J., van Vuuren, M.J., Pieterse, A.: The application and testing of diatom-based indices in the Vaal and Wilge Rivers, South Africa. Water SA. 33(1), (2007) 7. Feio, M.J., Almeida, S.F., Craveiro, S.C., Calado, A.J.: A comparison between biotic indices and predictive models in stream water quality assessment based on benthic diatom communities. Ecol. Indic. 9(3), 497–507 (2009) 8. Schneider, S.C., Kahlert, M., Kelly, M.G.: Interactions between pH and nutrients on benthic algae in streams and consequences for ecological status assessment and species richness patterns. Sci. Total Environ. 444, 73–84 (2013) 9. Soininen, J.: Environmental and spatial control of freshwater diatoms—a review. Diatom Res. 22(2), 473–490 (2007) 10. Bere, T.: Are diatom-based biotic indices developed in eutrophic, organically enriched waters reliable monitoring metrics in clean waters? Ecol. Indic. 62, 312–316 (2016) 11. Atazadeh, I., Sharifi, M., Kelly, M.: Evaluation of the Trophic Diatom Index for assessing water quality in River Gharasou, western Iran. Hydrobiologia. 589(1), 165–173 (2007) 12. Stenger-Kovács, C., Buczko, K., Hajnal, E., Padisák, J.: Epiphytic, littoral diatoms as bioindicators of shallow lake trophic status: Trophic Diatom Index for Lakes (TDIL) developed in Hungary. Hydrobiologia. 589(1), 141–154 (2007) 13. Blanco, S.: Environmental factors controlling lake diatom communities: a meta-analysis of published data. Biogeosci. Discuss. 11(11), 15889–15909 (2014) 14. Bate, G., Smailes, P., Adams, J.: A water quality index for use with diatoms in the assessment of rivers. Water SA. 30(4), 493– 498 (2004) 15. Stevenson, R., Pan, Y.: Assessing environmental conditions in rivers and streams with diatoms. In: The Diatoms: Applications for the Environmental and Earth Sciences, pp. 57–85 (1999) A. Goldenberg-Vilar et al. 16. Kelly, M.: Use of the trophic diatom index to monitor eutrophication in rivers. Water Res. 32(1), 236–242 (1998) 17. Kelly, M.: Use of community-based indices to monitor eutrophication in European rivers. Environ. Conserv. 25(1), 22–29 (1998) 18. Kelly, M., et al.: The Trophic Diatom Index: A User’s Manual Revised edition R&D Technical Report E2/TR2. Environment Agency, Bristol (2001) 19. Fornells, N.P., Solà, C., Munné, A.: QBR: un índice rápido para la evaluación de la calidad de los ecosistemas de ribera. Tecnología del Agua. 175, 20–39 (1998) 20. Pardo, I., et al.: El hábitat de los ríos mediterráneos. Diseño de un índice de diversidad de hábitat. Limnetica. 21(3–4), 115–133 (2002) 21. Soeprobowati, T.R., Tandjung, S.D., Sutikno, S., Hadisusanto, S., Gell, P.: The minimum number of valves for diatoms identification in Rawapening Lake, Central Java. BIOTROPIA Southeast Asian J. Trop. Biol. 23(2), 97–100 (2017) 22. Chessman, B., Growns, I., Currey, J., Plunkett-Cole, N.: Predicting diatom communities at the genus level for the rapid biological assessment of rivers. Freshw. Biol. 41(2), 317–331 (1999) 23. Rimet, F., Bouchez, A.: Life-forms, cell-sizes and ecological guilds of diatoms in European rivers. Knowl. Manag. Aquat. Ecosyst. 406, 01 (2012) 24. Rice, A., Baird, E., Eaton, R.: Standard methods for examination of water and wastewater. American Public Health Association, Washington, DC (2017) 25. Sournia, A.: Phytoplankton Manual. UNESCO, Paris (1978) 26. Utermöhl, H.: Zur Vervollkommnung der quantitativen Phytoplankton-Methodik: Mit 1 Tabelle und 15 abbildungen im Text und auf 1 Tafel. Internationale Vereinigung für theoretische und angewandte Limnologie: Mitteilungen. 9(1), 1–38 (1958) 27. Lund, J., Kipling, C., Le Cren, E.: The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia. 11(2), 143–170 (1958) 28. CEN: Water quality-Guidance standard for the routine sampling and pretreatment of benthic diatoms from rivers. EN 13946: 2003. Comité Européen de Normalisation, Geneva (2003) 29. CEN: Water Quality–Guidance Standard for the Identification, Enumeration and Interpretation of Benthic Diatom Samples from Running Waters. EN 14407: 2004. Comité Européen de Normalisation, Geneva (2004) 30. Kelly, M.: International and European standards for algal-based monitoring. Oceanol. Hydrobiol. Stud. 1, 77–81 (2004) 31. Kelly, M., et al.: Recommendations for the routine sampling of diatoms for water quality assessments in Europe. J. Appl. Phycol. 10(2), 215 (1998) 32. CHD: Metodología para el establecimiento del estado ecológico según la Directiva Marco del Agua. Protocolos de muestreo y análisis para fitobentos (microalgas bentónicas), pp. 1–33. CHD, Zaragoza (2005) 33. Pardo, I., García, L., Delgado, C., Costas, N., Abraín, R.: Protocolos de muestreo de comunidades biológicas acuáticas fluviales en el ámbito de las Confederaciones Hidrográficas del Miño-Sil y Cantábrico. MARM, Madrid (2010) 34. Stevenson, R., Bahls, L.: Periphyton protocols: revision to rapid bioassessment protocols for use in streams and rivers: periphyton, benthic macroinvertebrates and fish. EPA, Washington, DC (1999) 35. Blanco, S., Álvarez, I., Cejudo, C.: A test on different aspects of diatom processing techniques. J. Appl. Phycol. 20(4), 445–450 (2008) 36. Moss, B., et al.: The estimation of numbers and pigment content in epipelic algal populations. Limnol. Oceanogr. 11(4), 584–595 (1966) 13 Water Quality Assessment 37. Battarbee, R.W.: A new method for the estimation of absolute microfossil numbers, with reference especially to diatoms. Limnol. Oceanogr. 18(4), 647–653 (1973) 38. McBride, T.P.: Preparing random distributions of diatom valves on microscope slides. Limnol. Oceanogr. 33, 1627–1629 (1988) 39. Schrader, H.: Proposal for a standardized method of cleaning diatom-bearing deep-sea and land-exposed marine sediments. Nova Hedwig. Beih. 45, 403–409 (1973) 40. Alverson, A.J., Manoylov, K.M., Stevenson, R.J.: Laboratory sources of error for algal community attributes during sample preparation and counting. J. Appl. Phycol. 15(5), 357–369 (2003) 41. Van der Werff, A.: A new method of concentrating and cleaning diatoms and other organisms. Internationale Vereinigung für theoretische und angewandte Limnologie: Verhandlungen. 12(1), 276–277 (1953) 42. Setty, M.A.P.: Preparation and method of study of fossil diatoms. Micropaleontology. 12, 511–514 (1966) 43. Brown, S.-D., Austin, A.: A method of collecting periphyton in lentic habitats with procedures for subsequent sample preparation and quantitative assessment. Internationale Revue der gesamten Hydrobiologie und Hydrographie. 56(4), 557–580 (1971) 44. Ma, J.C.W., Jeffrey, L.M.: Description and comparison of a new cleaning method of diatom frustules for light and electron microscope studies. J. Microsc. 112(2), 235–238 (1978) 45. Carr, J.M., Hergenrader, G.L., Troelstrup Jr., N.H.: A simple, inexpensive method for cleaning diatoms. Trans. Am. Microsc. Soc. 152–157 (1986) 46. Scherer, R.P.: A new method for the determination of absolute abundance of diatoms and other silt-sized sedimentary particles. J. Paleolimnol. 12(2), 171–179 (1994) 47. Charles, D.F., Knowles, C., Davis, R.S.: Protocols for the analysis of algal samples collected as part of the US Geological Survey National Water-Quality Assessment Program. Patrick Center for Environmental Research Report, Philadelphia, PA (2002) 48. Rings, A., Lücke, A., Schleser, G.H.: A new method for the quantitative separation of diatom frustules from lake sediments. Limnol. Oceanogr. Methods. 2(1), 25–34 (2004) 49. Schaumburg, J., Schranz, C., Stelzer, D., Hofmann, G., Gutowski, A., Foerster, J.: Instruction protocol for the ecological assessment of running waters for implementation of the EC Water Framework Directive: macrophytes and phytobenthos. Bavarian Environment Agency, Augsburg (2006) 50. Blanco, S., Becares, E.: Metodo de muestreo de diatomeas epífitas en lagunas para la aplicación de la Directiva Marco del Agua. Tecnología del Agua. 261, 48–53 (2006) 51. Li, J., Chen, J.: An effective cleaning method for producing pure diatom samples from lake sediments. Earth Environ. 35(1), 91–96 (2007) 52. Metfies, K., et al.: An optimized protocol for the identification of diatoms, flagellated algae and pathogenic protozoa with phylochips. Mol. Ecol. Notes. 7(6), 925–936 (2007) 53. Debenest, T., Silvestre, J., Coste, M., Delmas, F., Pinelli, E.: A new cell primo-culture method for freshwater benthic diatom communities. J. Appl. Phycol. 21(1), 65 (2009) 54. Evans, K.M., Mann, D.G.: A proposed protocol for nomenclaturally effective DNA barcoding of microalgae. Phycologia. 48(1), 70–74 (2009) 55. Díaz-Palma, P., Alucema, A., Hayashida, G., Maidana, N.: Development and standardization of a microalgae test for determining deaths by drowning. Forensic Sci. Int. 184(1–3), 37–41 (2009) 56. Fetscher, A.E., Busse, L., Ode, P.R.: Standard operating procedures for collecting stream algae samples and associated physical habitat and chemical data for ambient bioassessments in California. California State Water Resources Control Board Surface Water Ambient Monitoring Program (SWAMP) Bioassessment SOP 2 (2009) 235 57. Watanabe, T., Kodama, Y., Mayama, S.: Application of a novel cleaning method using low-temperature plasma on tidal flat diatoms with heterovalvy or delicate frustule structure. Proc. Acad. Natl. Sci. Phila. 160(1), 83–87 (2010) 58. Serieyssol, K., et al.: Diatom fossils in mires: a protocol for extraction, preparation and analysis in palaeoenvironmental studies. Mires Peat. 7(12), 1–11 (2010) 59. Lang, I., Kaczmarska, I.: A protocol for a single-cell PCR of diatoms from fixed samples: method validation using Ditylum brightwellii (T. West) Grunow. Diatom Res. 26(1), 43–49 (2011) 60. Zoto, G.A., Dillon, D.O., Schlichting Jr., H.E.: A rapid method for clearing diatoms for taxonomic and ecological studies. Phycologia. 12(1), 69–70 (1973) 61. Friedrichs, L., Maier, M., Hamm, C.: A new method for exact three-dimensional reconstructions of diatom frustules. J. Microsc. 248(2), 208–217 (2012) 62. Mendes, T., Almeida, S.F., Feio, M.J.: Assessment of rivers using diatoms: effect of substrate and evaluation method. Arch. Hydrobiol. 179(4), 267–279 (2012) 63. MacDonald, L.A., Balasubramaniam, A.M., Hall, R.I., Wolfe, B.B., Sweetman, J.N.: Developing biomonitoring protocols for shallow Arctic lakes using diatoms and artificial substrate samplers. Hydrobiologia. 683(1), 231–248 (2012) 64. Vermeulen, S., Lepoint, G., Gobert, S.: Processing samples of benthic marine diatoms from Mediterranean oligotrophic areas. J. Appl. Phycol. 24(5), 1253–1260 (2012) 65. Gautam, S., Arya, A., Vinayak, V.: Protocol to establish axenic cultures for diatoms of fresh water. Int. J. Sci. Res. 5(11), 410– 418 (2016) 66. Tennant, R.K., et al.: A new flow cytometry method enabling rapid purification of fossil pollen from terrestrial sediments for AMS radiocarbon dating. J. Quat. Sci. 28(3), 229–236 (2013) 67. Seo, Y., Sato, S., Kuroki, K., Kishida, T.: A simple DNA coprecipitation method for the detection of diatoms in heart blood. Forensic Sci. Int. 232(1–3), 154–159 (2013) 68. Kimura, K., Tomaru, Y.: A unique method for culturing diatoms on agar plates. Plankton Benthos Res. 8(1), 46–48 (2013) 69. Zhao, J., et al.: Application of the microwave digestion-vacuum filtration-automated scanning electron microscopy method for diatom detection in the diagnosis of drowning. J. Forensic Legal Med. 33, 125–128 (2015) 70. Jiang, W., Pan, H., Wang, F., Jiang, M., Deng, X., Li, J.: A rapid sample processing method to observe diatoms via scanning electron microscopy. J. Appl. Phycol. 27(1), 243–248 (2015) 71. Warnock, J.P., Scherer, R.P.: A revised method for determining the absolute abundance of diatoms. J. Paleolimnol. 53(1), 157– 163 (2015) 72. Wang, H., et al.: A simple digestion method with a Lefort aqua regia solution for diatom extraction. J. Forensic Sci. 60, S227– S230 (2015) 73. Stancheva, R., Busse, L., Kociolek, J., Sheath, R.: Standard operating procedures for laboratory processing and identification of stream algae. California State Water Resources Control Board Surface Water Ambient Monitoring Program (SWAMP) Bioassessment SOP 0003 (2015) 74. Morin, S., Gómez, N., Tornés, E., Licursi, M., Rosebery, J.: Benthic diatom monitoring and assessment of freshwater environments: standard methods and future challenges. In: Aquatic Biofilms, Ecology, Water Quality and Wastewater Treatment, pp. 111–124 (2016) 75. Ferrara, M.A., De Tommasi, E., Coppola, G., De Stefano, L., Rea, I., Dardano, P.: Diatom valve three-dimensional representation: a new imaging method based on combined microscopies. Int. J. Mol. Sci. 17(10), 1645 (2016) 76. Mansilla, C., Novais, M.H., Faber, E., Martínez-Martínez, D., De Hosson, J.T.: On the 3D reconstruction of diatom frustules: a 236 77. 78. 79. 80. 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. 91. 92. 93. 94. 95. 96. A. Goldenberg-Vilar et al. novel method, applications and limitations. J. Appl. Phycol. 28(2), 1097–1110 (2016) Saba, F., et al.: A rapid and reproducible genomic DNA extraction protocol for sequence-based identification of archaea, bacteria, cyanobacteria, diatoms, fungi and green algae. J. Med. Bacteriol. 5(3–4), 22–28 (2017) Rojas-Camacho, O., Forero, M.G., Menéndez, J.M.: A tuning method for diatom segmentation techniques. Appl. Sci. 7(8), 762 (2017) Barragán, C., Wetzel, C.E., Ector, L.: A standard method for the routine sampling of terrestrial diatom communities for soil quality assessment. J. Appl. Phycol. 30(2), 1095–1113 (2018) Bayer, M., et al.: ADIAC: Using computer vision technology for automatic diatom identification. In: Proceedings of the 16th International Diatom Symposium, Athens, pp. 537–562 (2000) Du Buf, H., et al.: Diatom identification: a double challenge called ADIAC. In: International Conference on Image Analysis and Processing, Venice, pp. 734–739 (1999) Du Buf, H., Bayer, M. (eds.): Automatic diatom identification. World Scientific, Singapore (2002) Kloster, M., Kauer, G., Beszteri, B.: SHERPA: an image segmentation and outline feature extraction tool for diatoms and other objects. BMC Bioinf. 15(1), 218 (2014) Kloster, M., Esper, O., Kauer, G., Beszteri, B.: Large-scale permanent slide imaging and image analysis for diatom morphometrics. Appl. Sci. 7(4), 330 (2017) Wishkerman, A., Hamilton, P.B.: Shape outline extraction software (DiaOutline) for elliptic Fourier analysis application in morphometric studies. Appl. Plant Sci. 6(12), (2018) Pappas, J., Kociolek, P., Stoermer, E.: Quantitative morphometric methods in diatom research. Nova Hedwig. Beih. 143, 281–306 (2014) Delgado, C., Novais, M.H., Blanco, S., Almeida, S.F.: Examination and comparison of Fragilaria candidagilae sp. Nov. with type material of Fragilaria recapitellata, F. capucina, F. perminuta, F. intermedia and F. neointermedia (Fragilariales, Bacillariophyceae). Phytotaxa. 231(1), 1–18 (2015) Poulíčková, A., Neustupa, J., Hašler, P., Tomanec, O., Cox, E.J.: A new species, Navicula lothargeitleri sp. nov., within the Navicula cryptocephala complex (Bacillariophyceae). Phytotaxa. 273(1), 23–33 (2016) Wengrat, S., Marquardt, G.C., de Campos Bicudo, D., de Mattos Bicudo, C.E., Wetzel, C.E., Ector, L.: Type analysis of Cymbella schubartii and two new Encyonopsis species (Bacillariophyceae) from southeastern Brazil. Phytotaxa. 221(3), 247–264 (2015) Bueno, G., Deniz, O., Pedraza, A., et al.: Automated diatom classification (Part A): handcrafted feature approaches. Appl. Sci. 7(8), 753 (2017) Pedraza, A., Bueno, G., Deniz, O., Cristóbal, G., Blanco, S., Borrego-Ramos, M.: Automated diatom classification (Part B): a deep learning approach. Appl. Sci. 7(5), 460 (2017) Pedraza, A., et al.: Lights and pitfalls of convolutional neural networks for diatom identification. Optics, Photonics and Digital Technologies for Imaging Applications V, International Society for Optics and Photonics 106790G (2018) Kelly, M., et al., A DNA based Diatom Metabarcoding Approach for Water Framework Directive Classification of Rivers (2018). Malviya, S.: Global Diatom Biodiversity: An Assessment Using Metabarcoding Approach. Ph.D. Dissertation, Paris (2015) Nanjappa, D., Audic, S., Romac, S., Kooistra, W.H., Zingone, A.: Assessment of species diversity and distribution of an ancient diatom lineage using a DNA metabarcoding approach. PLoS One. 9(8), e103810 (2014) Moniz, M.B.J., Kaczmarska, I.: Barcoding diatoms: is there a good marker? Mol. Ecol. Resour. 9, 65–74 (2009) 97. Zimmermann, J., Jahn, R., Gemeinholzer, B.: Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. Org. Divers. Evol. 11(3), 173 (2011) 98. Rivera, S., Vasselon, V., Jacquet, S., Bouchez, A., Ariztegui, D., Rimet, F.: Metabarcoding of lake benthic diatoms: from structure assemblages to ecological assessment. Hydrobiologia. 807(1), 37–51 (2018) 99. Zimmermann, J.: DNA barcoding and eDNA barcoding in diatoms. Ph.D. Dissertation, Giessen (2015) 100. Vasselon, V., Domaizon, I., Rimet, F., Kahlert, M., Bouchez, A.: Application of high-throughput sequencing (HTS) metabarcoding to diatom biomonitoring: do DNA extraction methods matter? Freshw. Sci. 36(1), 162–177 (2017) 101. Vasselon, V., Rimet, F., Tapolczai, K., Bouchez, A.: Assessing ecological status with diatoms DNA metabarcoding: scaling-up on a WFD monitoring network (Mayotte island, France). Ecol. Indic. 82, 1–12 (2017) 102. Apothéloz-Perret-Gentil, L., Cordonier, A., Straub, F., Iseli, J., Esling, P., Pawlowski, J.: Taxonomy-free molecular diatom index for high-throughput eDNA biomonitoring. Mol. Ecol. Resour. 17(6), 1231–1242 (2017) 103. Piredda, R., Simeone, M.C., Attimonelli, M., Bellarosa, R., Schirone, B.: Prospects of barcoding the Italian wild dendroflora: oaks reveal severe limitations to tracking species identity. Mol. Ecol. Resour. 11(1), 72–83 (2011) 104. Hoef-Emden, K.: Pitfalls of establishing DNA barcoding systems in protists: the Cryptophyceae as a test case. PLoS One. 7(8), e43652 (2012) 105. Fittipaldi, M., Codony, F., Adrados, B., Camper, A.K., Morató, J.: Viable real-time PCR in environmental samples: can all data be interpreted directly? Microb. Ecol. 61(1), 7–12 (2011) 106. Urbánková, P., Veselá, J.: DNA-barcoding: a case study in the diatom genus Frustulia (Bacillariophyceae). Nova Hedwigia. 142, 147–162 (2013) 107. Khan-Bureau, D., Ector, L., Morales, E.A., Wade, E.J., Lewis, L.A.: Contrasting morphological and DNA barcoding methods for diatom (Bacillariophyta) identification from environmental samples in the Eightmile River in Connecticut. Nova Hedwig. Beih. 146, 279–302 (2018) 108. Hering, D., Moog, O., Sandin, L., Verdonschot, P.F.: Overview and application of the AQEM assessment system. Hydrobiologia. 516(1–3), 1–20 (2004) 109. Sandin, L., Verdonschot, P.F.: Stream and river typologies—major results and conclusions from the STAR project. In: The Ecological Status of European Rivers: Evaluation and Intercalibration of Assessment Methods, pp. 33–37. Springer (2006) 110. CEDEX: Directiva 2000/60/CE. Análisis de las características de las demarcaciones. Caracterización de los tipos de ríos y lagos. MARM, Madrid (2004) 111. Tison, J., et al.: Typology of diatom communities and the influence of hydro-ecoregions: a study on the French hydrosystem scale. Water Res. 39(14), 3177–3188 (2005) 112. Grenier, M., Lavoie, I., Rousseau, A.N., Campeau, S.: Defining ecological thresholds to determine class boundaries in a bioassessment tool: the case of the Eastern Canadian Diatom Index (IDEC). Ecol. Indic. 10(5), 980–989 (2010) 113. Pardo, I., et al.: A predictive diatom-based model to assess the ecological status of streams and rivers of Northern Spain. Ecol. Indic. 90, 519–528 (2018) 114. Karr, J.R.: Biological integrity: a long-neglected aspect of water resource management. Ecol. Appl. 1(1), 66–84 (1991) 115. Leira, M., Sabater, S.: Diatom assemblages distribution in catalan rivers, NE Spain, in relation to chemical and physiographical factors. Water Res. 39(1), 73–82 (2005) 116. Dallas, H.F.: Ecological status assessment in Mediterranean rivers: complexities and challenges in developing tools for assess- 13 Water Quality Assessment 117. 118. 119. 120. 121. 122. 123. 124. 125. 126. 127. 128. 129. 130. 131. 132. ing ecological status and defining reference conditions. Hydrobiologia. 719(1), 483–507 (2013) Munné, A., Prat, N.: Effects of Mediterranean climate annual variability on stream biological quality assessment using macroinvertebrate communities. Ecol. Indic. 11(2), 651–662 (2011) Sánchez-Montoya, M., et al.: Defining criteria to select reference sites in Mediterranean streams. Hydrobiologia. 619(1), 39 (2009) Coste, M., Tison, J., Delmas, F.: Flores diatomiques des cours d’eau: proposition de valeurs limites du «Bon État» pour l’IPS et l’IBD. Document de travail–Unité de Recherche Qualité des Eaux–Cemagref, Bordeaux (2004) Hawkins, C.P., Olson, J.R., Hill, R.A.: The reference condition: predicting benchmarks for ecological and water-quality assessments. J. N. Am. Benthol. Soc. 29(1), 312–343 (2010) Kelly, M.: Data rich, information poor? Phytobenthos assessment and the Water Framework Directive. Eur. J. Phycol. 48(4), 437– 450 (2013) Álvarez-Blanco, I., Blanco, S., Cejudo-Figueiras, C., Bécares, E.: The Duero Diatom Index (DDI) for river water quality assessment in NW Spain: design and validation. Environ. Monit. Assess. 185(1), 969–981 (2013) Lobo, E.A., Schuch, M., Heinrich, C.G., et al.: Development of the Trophic Water Quality Index (TWQI) for subtropical temperate Brazilian lotic systems. Environ. Monit. Assess. 187(6), 354 (2015) Rimet, F.: Recent views on river pollution and diatoms. Hydrobiologia. 683(1), 1–24 (2012) Kelly, M., Whitton, B.A.: Biological monitoring of eutrophication in rivers. Hydrobiologia. 384(1–3), 55–67 (1998) Zelinka, M.: Zur Prazisierung der biologischen klassifikation der Reinheid fliessender Gewasser. Arch. Hydrobiol. 57, 389–407 (1961) CEMAGREF: Etude des méthodes biologiques quantitatives d’appréciation de la qualité des eaux. Rapport Division Qualité, Lyon (1982) Blanco, S., et al.: Diatom assemblages and water quality assessment in the Duero Basin (NW Spain). Belg. J. Bot. 39–50 (2008) Potapova, M., Charles, D.F.: Diatom metrics for monitoring eutrophication in rivers of the United States. Ecol. Indic. 7(1), 48– 70 (2007) Rott, E., Pipp, E., Pfister, P.: Diatom methods developed for river quality assessment in Austria and a cross-check against numerical trophic indication methods used in Europe. Algol. Stud. 110(1), 91–115 (2003) Delgado, C., Pardo, I., García, L.: A multimetric diatom index to assess the ecological status of coastal Galician rivers (NW Spain). Hydrobiologia. 644(1), 371–384 (2010) Barragán, C.: Desarrollo de un nuevo índice de diatomeas para la evaluación del estado ecológico de los ríos de la Demarcación Hidrográfica del Tajo. In: 18th Conference of the Iberian Association of Limnology (AIL 2016), Tortosa (2016) 237 133. Besse-Lototskaya, A., Verdonschot, P.F., Coste, M., Van de Vijver, B.: Evaluation of European diatom trophic indices. Ecol. Indic. 11(2), 456–467 (2011) 134. Descy, J.-P., Coste, M.: A test of methods for assessing water quality based on diatoms. Internationale Vereinigung für theoretische und angewandte Limnologie: Verhandlungen. 24(4), 2112–2116 (1991) 135. Round, F.: A review and methods for the use of epilithic diatoms for detecting and monitoring changes in river water quality. HMSO Publisher, London (1993) 136. Taylor, J., de la Rey, P.A., van Rensburg, L.: Recommendations for the collection, preparation and enumeration of diatoms from riverine habitats for water quality monitoring in South Africa. Afr. J. Aquat. Sci. 30(1), 65–75 (2005) 137. Almeida, et al.: Water quality assessment of rivers using diatom metrics across Mediterranean Europe: a methods intercalibration exercise. Sci. Total Environ. 476, 768–776 (2014) 138. Prygiel, J., et al.: Determination of the biological diatom index (IBD NF T 90–354): results of an intercomparison exercise. J. Appl. Phycol. 14(1), 27–39 (2002) 139. Barbour, A.M.T., Gerritsen, J., Snyder, B.D., Stribling, J.B.: Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates and fish. EPA, Washington (1998) 140. Lavoie, I., Campeau, S., Zugic-Drakulic, N., Winter, J., Fortin, C.: Using diatoms to monitor stream biological integrity in Eastern Canada: an overview of 10 years of index development and ongoing challenges. Sci. Total Environ. 475, 187–200 (2014) 141. Hoagland, K.D., Roemer, S.C., Rosowski, J.R.: Colonization and community structure of two periphyton assemblages, with emphasis on the diatoms (Bacillariophyceae). Am. J. Bot. 69(2), 188–213 (1982) 142. Pringle, C.M.: Nutrient spatial heterogeneity: effects on community structure, physiognomy and diversity of stream algae. Ecology. 71(3), 905–920 (1990) 143. Berthon, V., Bouchez, A., Rimet, F.: Using diatom life-forms and ecological guilds to assess organic pollution and trophic level in rivers: a case study of rivers in south-eastern France. Hydrobiologia. 673(1), 259–271 (2011) 144. Passy, S.: Diatom ecological guilds display distinct and predictable behavior along nutrient and disturbance gradients in running waters. Aquat. Bot. 86(2), 171–178 (2007) 145. Kelly, M., et al., “Common freshwater diatoms of Britain and Ireland: an interactive key”, (2005). 146. Lavoie, I., et al.: Diatom teratologies as biomarkers of contamination: are all deformities ecologically meaningful? Ecol. Indic. 82, 539–550 (2017) 147. Coste, M., Boutry, S., Tison-Rosebery, J., Delmas, F.: Improvements of the Biological Diatom Index (BDI): description and efficiency of the new version (BDI-2006). Ecol. Indic. 9(4), 621– 650 (2009)