Macroinvertebrate and diatom communities as indicators for the biological assessment of river Picentino (Campania, Italy)

Ecological Indicators 64 (2016) 85–91

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Short Communication

Macroinvertebrate and diatom communities as indicators for the biological assessment of river Picentino (Campania, Italy) Antonella Giorgio, Salvatore De Bonis ∗ , Marco Guida Department of Biology, University of Naples Federico II, Complesso Universitario di Monte S. Angelo, Via Cinthia ed. 7, Naples, Italy

a r t i c l e

i n f o

Article history: Received 20 April 2015 Received in revised form 1 December 2015 Accepted 3 December 2015 Keywords: Diatom Macroinvertebrate Ecological water quality Water Framework Directive Monitoring rivers Bioindicators

a b s t r a c t Pollution of rivers is an increasing problem that affects biological diversity and structure of natural ecosystem. The present study reported the results of the preliminary analysis of diatom and macroinvertebrate communities of river Picentino (Italy, Campania) in respect of the WFD/60/2000/EC. Because of the sensitive to a variety of environmental factors the two categories of organism are used as excellent indicators of changes taking place in water ecosystems, especially eutrophication. Sampling of benthic diatoms and macroinvertebrates has been carried out in five stations along the river during April–May 2014 in order to apply the ICMi and the STAR ICMi and assess river quality. The data showed a diversification in diatomic and macroinvertebrate communities in relation to environmental stresses and level of pollution, with the disappearance of species higher sensitive to eutrophication and organic load in the upper course of the river. River water quality was found to deteriorate from the upperstream to the downstream because of the increasing of human impact and the intensive agriculture activity along the river. We conclude that the monitoring of diatomic and macroinvertebrate communities could give detailed information about the ecological status of rivers. However it is necessary to increase the achieved data by monitoring other biological communities in order to define adequated strategies to save and preserve the rivers habitat. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction A great number of human activities, such as agriculture, industries and urbanization affect the integrity of hydrographical basins. The most evident effects of human pressure on rivers are pollution by organic residues and heavy metals, acidification and alterations of hydrology and morphology, modification of chemical parameters and variation in biological communities (Malmqvist and Rundle, 2002; Salomoni et al., 2006). In recent decades the direct study of the effects of pollution on biota is of great interest because of the correlation between pollutants and alteration of biota. In this context the European Union’s Water Framework Directive (WFD, 60/2000) adopted in Italy with Legislative Decree 152/2006 and Ministerial Decree 260/2010, provides an opportunity to plan and accomplish a better water environment through river basin management planning, focusing on ecology. The Directive wants to prevent a further deterioration of the aquatic ecosystems, to protect and improve their status, to reduce the effects of anthropic impacts

∗ Corresponding author. Tel.: +39 081 679183/679184; fax: +39 081 679233. E-mail addresses: [email protected] (A. Giorgio), [email protected] (S. De Bonis), [email protected] (M. Guida). http://dx.doi.org/10.1016/j.ecolind.2015.12.001 1470-160X/© 2015 Elsevier Ltd. All rights reserved.

on the ecosystems, to ease a sustainable water use based on the long-term protection of the sustainable water resources. According to the Directive, Member States are obliged to achieve a good ecological status of the surface waters and to keep the high status where it already exists (WFD, 60/2000; Mancini and Sollazzo, 2009). The Directive aims to establish the protection of all categories of waters (rivers, lakes, transitional waters, and coastal waters) to assess ecological water quality, using two different approaches. Physical and chemical methods (such as oxygen dissolved, salinity, pH, nutrient availability, temperature) are used for instantaneous measurements, allowing only short-term analysis, in order to control water conditions present at the time of sampling and analysis. Biological methods are used to monitor long-term environmental variation of water quality in order to complete the information given by physical and chemical analysis (De Pauw et al., 1992; WFD, 60/2000; Lobo et al., 2004). The biological quality elements or BQE (i.e. phytoplankton, macroalgae, phytobenthos, macroinvertebrates and fish) were used to assess the ecological status of a water bodies and to detect the effects of general pollution in the community (Mancini, 2005; Hering et al., 2006). Macroinvertebrates were widely used in monitoring rivers because of their sensitive to pollution and rapid response to external disturbance (Sharma and Rawat, 2009;

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Narangarvuu et al., 2014). Furthermore disappearance or loss of biodiversity in macroinvertebrate communities, could be easily assigned to anthropogenic pressure (Johnson et al., 1993; Torrisi et al., 2010; Bertoli et al., 2014). On the other hand due to its reduced mobility and short generation times, phytobenthos has shown a rapid response to environmental changes and can integrate environmental conditions better than other bioindicators, being commonly used in the assessment of the ecological status and monitoring of anthropogenic impacts (McCormick and Cairns, 1994; Della Bella et al., 2007; Kelly et al., 2009). Diatoms are the main component of phytobenthos, being one of the most important algae groups used for ecological assessment. Their ubiquity, their direct and sensitive response to physicochemical changes, and their preservation in sediments for a long time makes them good water quality indicators for the evaluation of phenomena such as eutrophication, acidification and to integrate the impact of organic pollution and the trophic level (Round, 1991; Delgado et al., 2012). Relatively to the macrobenthic community the existing National law provides the use of MacrOper classification system, based on the index STAR ICMi. The index is based on the analysis of the benthonic macroinvertebrate community structure for the evaluation of the river ecological status and the definition of the quality class (Buffagni and Erba, 2007a, 2008). In order to express numerically the flowing waters quality using diatoms Italy has proposed a representative method for the national situation, the Intercalibration Common Metrix Index (ICMI) that comprises the diatomic community identification on species level. A sensitivity value for pollution and a reliability value as indicator are attributed to each of diatomic communities. According to the classification and the intercalibration guidance, the quality judgement is expressed through the relationship between the observed value and the one detected in the reference sites (Ecological Quality Ratio, EQR) in which the anthropic impact is absent (Simboura et al., 2005). This work proposes a case study in which the Star ICMi and the ICMi Indices (Intercalibration Common Metrix Index), were applied to assess the ecological status of River Picentino (Campania, Italy) that flows through agriculturally and urban used areas. The goal of the ecological monitoring is to programme possible measures mitigating the anthropic damages and to assess suitable protective strategies respecting the objectives of the applicable legislation.

2. Material and methods 2.1. Study area The river Picentino originates Mount Polveracchio in the Picentini mountains of the Apennine chain (Region Campania), at an elevation above 1.500 m and flow independently 20 km north of the River Sele. The Picentini mountains encompass four large mountain groups: Terminio/Tuoro, Cervialto, Polveracchio/Raione and Accellica/Licinici/Mai and consist of limestones, dolomitic limestones and dolomites from the Upper Trias to the Upper Cretaceous. Carbonate sediments are covered by flysch-facies terrains consisting of interbedded sandstone, calcareous sandstone, marl and clay. These deposits crop out widely at the foot of the Picentini Mountains along the northern border and between the Cervialto Mountain and the Terminio-Tuoro group (Corniello et al., 2010). The Picentino river, which lies uphill on a mountainous carbonatic substrate and then on alluvial and pyroclastic sediments, has an overall length of 28 km and a catchment area of 52 km2 (Budillon et al., 2012). The most important perturbations of Picentino river are overirrigation, overexploitation of the fish stock, point and non-point

Fig. 1. Location and distribution of sites sampled.

sources of pollution from surrounding agricultural areas, cattle wastes, urban and industrial untreated wastes. The hydrographic basin of the river Picentino is comprised in the hydroecoregions 18 and classified in the river type M4, within the small and medium rivers (10–1000 km2 ) of the Mediterranean area (Mancini and Sollazzo, 2009). The five sampling sites were chosen upstream and downstream of the principal anthropogenic pressure and most populated areas considering also the possibility to apply both indices (Fig. 1). The first station named P.1 was located very closed to the Parco Regionale dei Monti Picentini (40◦ 44 55.30 N 14◦ 57 31.99 E); the second one named P.2 was located further downstream (40◦ 42 28.91 N 14◦ 56 41.91 E). The third and fourth station, named P.3 and P.4 were chosen in the central part of the river (40◦ 41 10.63 N 14◦ 53 39.58 E; 40◦ 39 24.22 N 14◦ 52 22.77 E); the last one was located very closed to the mouth of river Picentino (40◦ 37 36.42 N 14◦ 50 27.12 E). Samples were collected between April and May 2014 (early summer). Physical parameters included dissolved oxygen, pH, conductivity and temperature were measured in the field during sampling (APHA, 1998). 2.2. Macroinvertebrate sampling and laboratories analyses Sampling method used for analysis of macroinvertebrates communities was based on a multihabitat approach, which required the proportional allocation of sampling units in relation to the occurrence of microhabitats in the river and the collection of quantitative samples (Buffagni and Erba, 2007b; Buffagni et al., 2007). The samples were collected using Surber net (size 0.5 m × 0.5 m, mesh size 900 ␮m) and considering a sampling area of 0.5 m2 . According to the protocol the sampled area has been divided into ten different units (0.05 m2 ). Macroinvertebrates were collected by sampling habitats in proportion to their occurrence in order to obtain a sample more representative of the organisms present in the entire area.

A. Giorgio et al. / Ecological Indicators 64 (2016) 85–91

Field sorting was performed in order to remove large organic debris and stones from the samples. At the same time we performed a preliminary reconnaissance programme for assessing benthos richness (Ghetti, 1997; APAT IRSA-CNR, 2003). The samples were preserved in 90% ethanol and transported to laboratory in a cold box (4 ◦ C). The subsequent analysis was performed within 24 h. Large-volume samples were random subsampled to make sample processing more economical and rapid. Taxonomical identification was conducted to the family or genera level using different identification keys (Sansoni, 1988; Campaioli et al., 1999; Tachet et al., 2000, 2006), in order to apply the STAR ICMi Index using Macroper software (Buffagni and Belfiore, 2007). 2.3. Diatom sampling and laboratories analyses The sampling of epilithic diatoms was carried out as recommended by European Standard EN 13946:2003 and according to Kelly et al. (1998) guidelines. All samples were collected scratching with a toothbrush the surface of natural rocks of about 15–20 cm to cover a total area of 100 cm2 . The samples were preserved in Ethanol 100X until the following treatment. In order to identify the diatom frustules the diatom valves were cleaned using the Hydrogen Peroxide Method (30% H2 O2 solution) to eliminate organic matter. Each sample was homogenized by shaking and then 5–10 ml of the suspension was transferred to a beaker. The hydrogen peroxide (20 ml) was added and heated on a hotplate at about (90 ± 5) ◦ C until all organic material has been oxidized. At the end of the oxidation a few drops of hydrochloric acid were added to remove remaining hydrogen peroxide. After washing the sides of beaker with distilled water the contents of beakers were transferred to centrifuge tube and centrifuged. The supernatant was discarded and pellet resuspended with distilled water. The washing process was repeated at least three times; when all traces of hydrogen peroxide have been removed the diatom pellet was mixed and transferred to a clean vial. Few drops of ethanol were added to prevent fungal growth. Clean diatom frustules were then mounted on permanent slides with a synthetic resin with high refraction index (Naphrax, Northern Biological Supplies Ltd., UK; RI = 1.74) following manufacturers guidelines. According to the European Standard EN 14407:2004 for the quantitative evaluation of the diatomic species in the sample, is necessary the counting of about 400 valve using a light microscope with 1000× magnification. The taxa were identified following mainly the Krammer and LangeBertalot, 1986, Krammer and Lange-Bertalot, 1988, Krammer and Lange-Bertalot, 1991a, Krammer and Lange-Bertalot monographs (1986, 1988, 1991a, 1991b), as well as Krammer (1992, 2000, 2002), Lange-Bertalot (1993, 2001) and Werum and Lange-Bertalot (2004) ones. The water quality assessment was performed using OMNIDIA software version 5 (Lecointe et al., 1993). For each taxa identified wad used the nomenclature accepted by OMNIDIA.

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Table 1 Sampling parameters monitored in the 5 stations along the river Picentino. Sampling site

pH

Conductivity (␮S/cm)

Oxygen (mg/L)

Temperature (◦ C)

P.1 P.2 P.3 P.4 P.5

8.08 7.68 8.12 7.74 8.26

541 664 545 675 1178

10 9.6 9.2 8.7 8.5

14.6 15.2 15.5 15.8 16.2

Table 2 Results of ICMi index calculated for each site, with correspondent judgement and class of quality. Sampling Site

ICMi value

Judgement

Quality class

P.1 P.2 P.3 P.4 P.5

0.74 0.65 0.58 0.53 0.32

Good Good Moderate Moderate Poor

II II III III IV

The genera of diatoms containing the highest number of species were Nitzschia, Navicula, Gomphonema, Achnantidium, Amphora and Fragilaria. The biological quality evaluated by applications of the diatomic index is summarized in Table 2. In Fig. 2 were summarized the relative abundance of taxa at each sampling site. Considering the diatomic index, the results revealed a good water quality in the stations P.1 and P.2 where the waters are cold and rich in oxygen (Class II). The most representative diatoms in both sites were Achnantidium minutissimum, Achnantidium subatomus, Cocconeis placentula var. euglypta, Amphora pediculus, Diatoma mesodon, Meridion circulare, Fragilaria capucina and Hannaea arcus. In the station P.1 were found some species typical of great quality environment, such as Achnantidium biasolettianum and Diatoma hyemalis. They are rare, with relative abundance lower than 4%. In P.2 station the species with relative abundance higher than 60% were Cymbella affinis and Gomphonema olivaceum, both typical of good quality environment. A. pediculus, Navicula cryptotenella, Diatoma vulgaris, Encyonema minutum, Navicula lanceolata, Nitzschia dissipata, Nitzschia fonticola, were the best representatives of the moderate water quality category at the stations P.3 and P.4 (Class III). Some species typical of low quality environments such as Nitzschia incospicua e Navicula gregaria were identified in P.4 sample. A. pediculus specie reaches relative abundance values close to 70% in the sample site P.3, characterized by good and moderate water quality. The biological quality worsens in the station P.5 (Class IV). The most abundant taxa in this station were Nitzschia frustulum, N. incospicua, Encyonema caespitosum, Gomphonema minutum, Gomphonema parvulum, Fistulifera saprophila, Mayamaea atomus var. permitis and N. gregaria.

3. Results 3.1. Physical parameters The physical variables of the water measured in the field at each sample site were summarized in Table 1 The water of the river Picentino are close to neutral, in all the points analyzed, with values near to 8. The dissolved oxygen has values ranging from 8.5 to 10 mg/L throughout the river. Conductivity increase gradually moving towards the lowest points of the river. 3.2. Analysis of diatomic communities and ICMi Index A total of 80 species and varieties of diatoms were identified, belonging to 25 genera (Appendix 1).

3.3. Analysis of macroinvertebrate communities and STAR ICMi index Among the macroinvertebrates the total number of recorded taxa at level of families and genera was 32. Macroinvertebrate communities at all 5 reaches consisted predominantly of taxa Diptera, Trichoptera, Plecoptera, Ephemeroptera, Oligochaeta and Coleoptera (Appendix 2). As revealed in Table 3, the biological quality estimated with the application of the STAR-ICMi index shown a deterioration at the end of the river.In Fig. 3 were summarized the relative abundance of macroinvertebrate taxa at each sampling site. At site P.1 we have found, such as representative taxonomic groups Perlidae, Perlodidae, Nemouridae, Capniidae. Between

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A. Giorgio et al. / Ecological Indicators 64 (2016) 85–91 P.1

ADBI ADEU ADMI ADPY ADSA ADSU ACOP AINA AOVA APED AVEN CLCT CPED CPLE CPLA CPLI COPL CMEN CSOL CAFF CCYM CAEX CHEL CLAN CPAR DHIE DMES DMON DVUL DELL DOCU ECAE ENMI ESLE ENVE EOMI ESBM FCAP FDEL FVAU FSAP GELG GLGN GMIN GMIC GOLD GOLI GPAR GPEL GPRI GYAC GYAT HARC MAAT MPMI MVAR MCIR NANT NCPR NGRE NCTE NLAN NRAD NTPT NVEN NAMP NDIS NFON NIFR NINC NPAL NPAD NSOC NSBL PLFR PTLA RABB SBRE SUMI UULN

0

P.2

P.3

P.4

P.5

Table 3 Results of STAR ICMi index calculated for each site, with correspondent judgement and class of quality. Sampling site

Star-ICMI value

Judgement

Quality class

P.1 P.2 P.3 P.4 P.5

0.98 0.70 0.42 0.38 0.20

High Moderate Poor Poor Bad

I III IV IV V

P.1

P.2

P.3

P.4

P.5

Perlidae Perlodidae Capniidae Leuctridae Nemouridae Heptageniidae Ephemeridae Ephemerellidae Caenidae Baetidae Rhyacophilidae Hydropsychidae Sericostomatidae Beraeidae Leptoceridae Dytiscidae Dryopidae Elminthidae Gyrinidae Chironomidae Simuliidae Ceratopogonidae Culicidae Tabanidae Asellidae Gammaridae Ancylidae Lymnaeidae Physidae Erpobdellidae Lumbricidae Lumbriculidae Naididae Tubificidae

0

<20%

21-40%

41-60%

61-80%

81-100%

Fig. 3. Heat map showing the abundance of macroinvertebrate taxa at sampling sites.

these Dinocras, Isoperla, Leuctra and Nemoura identifies best the high water quality (Class I) as also detected by application of the STAR ICMi index. At station P.2 the water quality decrease to moderate (Class III) as demonstrated by the different composition of macroinvertebrate community with Baetidae, Simuliidae, Chironomidae, Baetis and Rhyacophyla as more abundant taxa. Epeorus and Rithrogena genera were considered representative of water conditions. In the stations P.3 and P.4, the results revealed a high densities of more tolerant taxa such as Baetidae, Chironomidae, Elmintidae, Dryopidae and Simuliidae. In both sites the water quality is poor (Class IV). At sampling site P.5 the STAR ICMi index shown a bad water quality (Class V) and the more aboundant taxa recorded was Chironomidae, with genera Chironomous particularly resistant to pollution. There were not found other taxa with high abundance, but only a few families with a small number of individuals. Among these Simulidae and Tabanidae do not exceed the 20%. <20%

21-40%

41-60%

61-80%

81-100%

4. Discussion Fig. 2. Heat map showing the abundance of diatomic taxa at sampling sites.

The goal of this study was to identify relationship between the presence of pollutants and the changes in diatomic

A. Giorgio et al. / Ecological Indicators 64 (2016) 85–91

communities by calculation of ICMi index. At the same time we valuated ecological status of river Picentino monitoring macroinvertebrate communities and calculating STAR ICMi index. River Picentino is characterized by water close to neutral. A reduction of dissolved oxygen quantity for the decrease of the downstream current is observed. Higher conductivity values, caused by the higher anthropic impact, were measured in the downstream points (P.4 and P.5). Agricultural, industrial activities and urban settlements increase near the lower river parts. The consequence is a greater presence of flows and waste materials in the bordering territories and a deterioration of water quality. Analysis of diatoms communities has shown an high biodiversity in upperstream for that genus (i.e. Cymbella) very sensitive to the environmental disturbances. On the other hands several taxa defined as tolerant and belonging to Nitzschia and Amphora genus has shown higher abundances in the lower quality sites, that is the downstream sites (P.4 and P.5). The majority of the species found in central and downstream points has to be considered as eutraphentic from the ecological point of view. This demonstrates the high level of throphy due to the farming and agricultural activities (Van Dam et al., 1994). Some taxa can be classified as ubiquitous, considering their presence in all sampling sites. Among these Planothidium lanceolatum, A. minutissimum, N. lanceolata, A. pediculus, N. incospicua, Nitzschia palea, Gomphonema parvulum and Cocconeis placentula var. lineata were the more abundant. The relative abundance of taxa depends on the ecological status of water. Gomphonema parvulum, Planothidium frequentissimum, N. incospicua and N. palea were more abundant in moderate quality sites as less sensitive to water pollution. A. pediculus, A. biasolettianum, Fragilaria capucina and A. minutissimum affect the biocenosis in good quality points. According to other authors (Feio et al., 2007; Torrisi et al., 2010) the presence of A. minutissimum seems to be associated to oligosaprobic and oligotrophic conditions. The macroinvertebrate community in the upper reache of Picentino river showed the greater biodiversity and was dominated by taxa more sensitive to pollution than those identified downstream. The community structure in the upper river is dominated by taxon Plecoptera while more pollution-tolerant such as Chironomidae, Simulidae and Tabanidae become numerically dominant downstream, where water quality decrease. Less tolerant taxa in the middle river contributed to the moderate ad poor water quality. The genus Baetis was found in all sampled site except in the latter one, because of the high level of pollution. Both indices shown a degradation of the ecologic quality of the Picentino river upstream and downstream. Turning to the ICMi index samples P.1 and P.2 presented good ecological status, whereas sample P.5 has been classified as poor. The other sampling points (P.3 and P.4) presented a moderate ecological status. A different gradient derived from the calculation of STAR ICMi Index. The results revealed a high water quality at Site P.1 and a rapid deterioration to moderate, poor and bad quality in the stations P.2–P.5. Apart from the first sampling sites, the ICMi Index give a better quality of waters when compared with results of STAR ICMi Index. Macroinvertebrates seem to be more sensitive to pollutions and more influenced that diatoms to stressors in aquatic environments. The organic pollution and the habitat degradation mainly caused by the agriculture, farm, industries are the main stress elements for the river as aim of the study. In upstream sites where the good quality status highlights a small deviation from the high quality with a minimal disturbance, the anthropic pressure turns out as marginal. It is important to consider that the upstream sampling point is inside the Parco Regionale of Monti Picentini established in 1995 for the territory conservation.

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The anthropic impact significantly grows in the middle points until reaching the maximum levels in the downstream. A worst health of water course is a consequence of a greater population density, a greater proximity to residential areas, industrial complex and to more intense farming practices, all those as factors with inevitable repercussions on diatomic and macroinvertebrate communities. In this section of river the STAR ICMi index give a results that better harmonize to real conditions. Considering the lower dimensions of the water body, the anthropic pressures have a cumulative impact. The self-depurative effect of the water body is compromised, with a quality deterioration from upstream to downstream. So, it would be appropriate to extend the limits of the Park in order to preserve a greater part of fluvial and perifluvial environment, keeping the neutrality of the monitored area and reducing the anthropic damages. Even though biological parameters and taxonomic index indicate bad and poor water quality for some sampling points, the dissolved oxygen concentration is almost at saturation level throughout the studied river. The river system is mainly influenced by untreated industrial wastewater containing significant levels of inorganic compounds (i.e. heavy metals). This class of compounds could alter the structure of biological communities determining bad and poor water quality while dissolved oxygen were unchanged. Furthermore as reported by Wang et al. (2009), the ecological and hydraulic features of similar step-pool systems seems to be the principle responsible of the higher dissolved oxygen level. 5. Conclusions One of the main objectives of the fluvial ecology is the evaluation of the relationship between environmental alterations and organisms. With the present study we have evaluated the importance of the biological monitoring which proves that pollution phenomena are ongoing and so strong as to negatively affect the integrity of the fluvial ecosystem. In Italy, as for the others Member States in the EU, the WFD achieve its purposes reaching a good ecological status for all the rivers. For this reason, it is necessary an intensive monitoring programme to evaluate the present situation and to apply suitable strategies for an environmental recovery. From the analysis of the collected data was revealed that diatom and macroinvertebrate communities provide preliminary information on the status of quality tending to a realistic evidence. However it is necessary to examine in depth the other biological communities of fluvial ecosystems, expanding the survey to the fluvial districts on basin scale. The use of other biological indicators belonging to different taxonomic levels, such as fishes and macrophytes, can increase the number of information related to the threats to the ecosystem because of their differentiated response to stressor. It is necessary a sustainable water quality monitoring taking into account the general conditions of the river ecosystem, the supervision of all the pressures, the study of mitigations and control of restoration activities. Appendix 1. List of diatoms collected at the sampling sites

Codes

Taxa

ADBI

Achnanthidium biasolettianum (Grunow in Cl. & Grun.) Lange-Bertalot Achnanthidium eutrophilum (Lange-Bertalot) Lange-Bertalot Achnanthidium minutissimum (Kützing) Czarnecki Achnanthidium pyrenaicum (Hustedt) Kobayasi Achnanthidium saprophilum (Kobayasi et Mayama) Round & Bukhtiyarova Achnanthidium subatomus (Hustedt) Lange-Bertalot Amphora copulata (Kütz) Schoeman & Archibald

ADEU ADMI ADPY ADSA ADSU ACOP

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A. Giorgio et al. / Ecological Indicators 64 (2016) 85–91

Codes

Taxa

AINA AOVA APED AVEN CLCT CPED CPLE CPLA CPLI COPL CMEN CSOL CAFF CCYM CAEX CHEL CLAN CPAR DHIE DMES DMON DVUL DELL DOCU ECAE ENMI ESLE ENVE EOMI ESBM FSAP FCAP FDEL FVAU GELG GLGN GMIN GMIC GOLD GOLI GPAR

Amphora inariensis Krammer Amphora ovalis (Kützing) Kützing Amphora pediculus (Kützing) Grunow Amphora veneta Kützing Caloneis lancettula (Schulz) Lange-Bertalot & Witkowski Cocconeis pediculus Ehrenberg Cocconeis placentula Ehrenberg var.euglypta (Ehr.) Grunow Cocconeis placentula Ehrenberg var. placentula Cocconeis placentula Ehrenberg var. lineata (Ehr.) Van Heurck Cocconeis pseudolineata (Geitler) Lange-Bertalot Cyclotella meneghiniana Kützing Cymatopleura solea (Brebisson in Breb. & Godey) W.Smith var.solea Cymbella affinis Kützing var.affinis Cymbella cymbiformis Agardh Cymbella excisa Kützing Cymbella helvetica Kützing Cymbella lanceolata (Agardh?) Agardh var.lanceolata Cymbella parva (W. Smith) Kirchner Diatoma hyemalis (Roth) Heiberg var. hyemalis Diatoma mesodon (Ehrenberg) Kützing Diatoma moniliformis Kützing Diatoma vulgaris Bory Diploneis elliptica (Kützing) Cleve Diploneis oculata (Brebisson) Cleve Encyonema caespitosum Kützing Encyonema minutum (Hilse) D.G. Mann Encyonema silesiacum (Bleisch in Rabh.) D.G. Mann Encyonema ventricosum (Kützing) Grunow Eolimna minima (Grunow) Lange-Bertalot Eolimna subminuscula (Manguin) Moser Lange-Bertalot & Metzeltin Fistulifera saprophila (Lange-Bertalot & Bonik) Lange-Bertalot Fragilaria capucina Desmazieres var.capucina Fragilaria delicatissima (W.Smith) Lange-Bertalot Fragilaria vaucheriae (Kützing) Petersen Gomphonema elegans (Reichardt & Lange-Bertalot) Monnier & Ector Gomphonema lagenula Kützing Gomphonema minutum (Ag.) Agardh f. minutum Gomphonema micropus Kutzing var. micropus Gomphonema olivaceoides Hustedt Gomphonema olivaceum (Hornemann) Brébisson Gomphonema parvulum (Kützing) Kützing var. parvulum f. parvulum Gomphonema pumilum var. elegans Reichardt & Lange-bertalot Gomphonema pumilum var. rigidum Reichardt & Lange-Bertalot Gyrosigma acuminatum (Kützing) Rabenhorst Gyrosigma attenuatum (Kützing) Rabenhorst Hannaea arcus (Ehr.) Patrick. Mayamaea atomus (Kützing) Lange-Bertalot Mayamaea permitis (Hustedt) Bruder & Medlin Melosira varians Agardh Meridion circulare (Greville) C.A.Agardh var. circulare Navicula antonii Lange-Bertalot Navicula capitatoradiata Germain Navicula cryptotenella Lange-Bertalot Navicula gregaria Donkin Navicula lanceolata (Agardh) Ehrenberg Navicula radiosa Kützing Navicula tripunctata (O.F.Müller) Bory Navicula veneta Kützing Nitzschia amphibia Grunow Nitzschia dissipata(Kützing) Grunow var.dissipata Nitzschia fonticola Grunow in Cleve et Möller Nitzschia frustulum (Kützing) Grunow var.frustulum Nitzschia inconspicua Grunow Nitzschia palea (Kützing) W. Smith Nitzschia palea (Kützing) W.Smith var.debilis (Kützing) Grunow in Cl. & Grun Nitzschia sociabilis Hustedt Nitzschia sublinearis Hustedt Planothidium frequentissimum (Lange-Bertalot) Lange-Bertalot Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot Rhoicosphenia abbreviata (C.Agardh) Lange-Bertalot Surirella brebissonii Krammer & Lange-Bertalot var. brebissonii Surirella minuta Brébisson Ulnaria ulna (Nitzsch) Compère

GPEL GPRI GYAC GYAT HARC MAAT MPMI MVAR MCIR NANT NCPR NCTE NGRE NLAN NRAD NTPT NVEN NAMP NDIS NFON NIFR NINC NPAL NPAD NSOC NSBL PLFR PTLA RABB SBRE SUMI UULN

Appendix 2. List of macroinvertebrates collected at the sampling sites.

Orders/taxa

Family

Genera

Plecoptera

Perlidae

Dinocras Perla Isoperla Perlodes Capnia Leuctra Nemoura Protonemoura Ecdyonurus Epeorus Rithrogena Ephemera Ephemerella Caenis Baetis Cloeon Rhyacophila

Perlodidae Capniidae Leuctridae Nemouridae Ephemeroptera

Heptageniidae

Ephemeridae Ephemerellidae Caenidae Baetidae Trichoptera

Coleoptera

Diptera

Isopoda Amphipoda Gastropoda

Hirudinea Oligochaeta

Rhyacophilidae Hydropsychidae Sericostomatidae Beraeidae Leptoceridae Dytiscidae Dryopidae Elminthidae Gyrinidae Chironomidae Simuliidae Ceratopogonidae Culicidae Tabanidae Asellidae Gammaridae Ancylidae Lymnaeidae Physidae Erpobdellidae Lumbricidae Lumbriculidae Naididae Tubificidae

Ancylus Lymnaea Physa Dina

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