Skip to main content

Advertisement

Log in

Water quality assessment of a neotropical pampean lowland stream using a phytoplankton functional trait approach

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

The aim of this study was to test whether the water quality phytoplankton assemblage index adapted for rivers (Qr index) is useful to characterize the water quality of a neotropical stream. We were interested also in inferring the main pollutants through a phytoplankton functional trait characterization and assessing the phytoplankton groups which may influence the Qr index final estimations. Monthly sampling of environmental variables and phytoplankton were done in three sites (S1, S2, and S3). Phytoplankton was classified according to Reynolds Functional Groups (RFG) and water quality estimation was performed using the Qr index. Principal coordinates (PCO) and PERMANOVA were applied to identify the main pollutants through the RFG. RFG linkage to Qr values was assessed by general linear models (GLM). “Moderate” water quality was found in S1 the whole year, in all sampling stations during the winter, and in summer–autumn in S2. “Regular” water quality was found in S3 during the summer–autumn, and S2–S3 during the spring. S1 and S2 showed eutrophic, standing, or mix waters whereas S3 had high organic matter content and eutrophic conditions. Despite some RFG (X1 and MP) being linked to high Qr values and some other (M, S1 and Z) to low, their dominance did not influence water quality estimation performed by the Qr. We conclude that the Qr index was useful for assessing the water quality. Though RFG were valuable for inferring eutrophication, organic pollution, and mixing, but their dominance does not necessarily have a direct effect on the final Qr estimation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Abonyi, A., Leitão, M., Lancon, A. N., & Padisák, J. (2012). Phytoplankton functional groups as indicators of human impacts along the River Loire (France). Hydrobiologia, 698, 233–249.

    Article  Google Scholar 

  • Abonyi, A., Leitão, M., Stanković, I., Borics, G., Várbíróc, G., & Padisák, J. (2014). A large river (River Loire, France) survey to compare phytoplankton functional approaches: do they display river zones in similar ways? Ecological Indicators, 46, 11–22.

    Article  Google Scholar 

  • Allan, J. D. (2004). Landscapes and riverscape: the influence of land use on stream ecosystems. Annual Review of Ecology, Evolution, and Systematics, 35, 257–284.

    Article  Google Scholar 

  • APHA. (2005). Standard methods for the examination of water and wastewater (21st ed.). USA: American Public Health Association.

    Google Scholar 

  • Arias, A. R., Forsin Buss, D., Ferreira, I. A., Moreira Freire, M., Egler, M., Mugnai, R., & Fernades, B. D. (2007). Use of bioindicators for assessing and monitoring pesticides contamination in streams and rivers. Ciência & Saúde Coletiva, 12, 61–72.

    Article  Google Scholar 

  • Battista, J. J. (2004). Manejo de Vertisoles en Entre Ríos. Revista Científica Agropecuaria, 8, 37–43.

    Google Scholar 

  • Bennett, M. G., Schofield, K. A., Lee, S. S., & Norton, S. B. (2017). Response of chlorophyll a to total nitrogen and total phosphorus concentrations in lotic ecosystems: a systematic review protocol. Environmental Evidence, 6, 1–13.

    Article  Google Scholar 

  • Bolgovics, A., Várbíró, G., Ács, E., Trábert, Z., Kiss, K. T., Pozderka, V., & Borics, G. (2017). Phytoplankton of rhithral rivers: its origin, diversity and possible use for quality-assessment. Ecological Indicators, 81, 587–596.

    Article  Google Scholar 

  • Borics, G., Várbíró, G., Grigorszky, I., Krasznai, E., Szabó, S., & Kiss, K. T. (2007). A new evaluation technique of potamoplankton for the assessment of the ecological status of rivers. Large Rivers, 17. Archiv für Hydrobiologie Supplement, 161, 465–486.

    Google Scholar 

  • Borics, G., Görgényi, J., Grigorszky, I., László-Nagy, Z., Tóthmérész, B., Krasznai, E., & Várbíró, G. (2014). The role of phytoplankton diversity metrics in shallow lake and river quality assessment. Ecological indicators, 45, 28–36.

    Article  CAS  Google Scholar 

  • Conforti, V., Ohirko, E., & Gómez, N. (2009). Euglenophyta from a stream of pampean plain subjected to anthropic effects: A° Rodriguez. Algological studies, 131, 63–86.

    Article  Google Scholar 

  • Conzonno, V. H. (2009). Limnología Química. Argentina: Universidad Nacional de La Plata.

    Google Scholar 

  • Cortelezzi, A., Sierra, M. V., Gómez, N., Marinelli, C., & Rodrigues Capítulo, A. (2013). Macrophytes, epipelic biofilm, and invertebrates as biotic indicators of physical habitat degradation of lowland streams (Argentina). Environmental Monitoring Assessment, 185, 5801–5815.

    Article  CAS  Google Scholar 

  • de Petre, A. & Stephan, S. (1998). Características pedológicas y agronómicas de los Vertisoles de Entre Ríos, Argentina. Facultad de Ciencias Agropecuarias, Universidad Nacional de Entre Ríos.

  • de Tezanos Pinto, P., & Litchman, E. B. (2010). Eco-physiological responses of nitrogen-fixing cyanobacteria to light. Hydrobiologia, 639, 63–68.

    Article  CAS  Google Scholar 

  • del Giorgio, P., Vinocur, A., Lombardo, R. J., & Tell, G. (1991). Progressive changes in the structure and dynamics of the phytoplankton community along a pollution gradient: a multivariate approach. Hydrobiologia, 224, 129–154.

    Article  Google Scholar 

  • Farebrother, R. W. (1980). Pan's procedure for the tail probabilities of the Durbin-Watson statistic. Applied Statistics, 29, 224–227.

    Article  Google Scholar 

  • Food and Agriculture Organization (FAO). (2003). Review of world water resources by country. Italy: FAO.

    Google Scholar 

  • Frau, D., de Tezanos Pinto, P. & Mayora, G. (2018a). Are cyanobacteria total, specific and trait abundance regulated by the same environmental variables? Annales de Limnologie - International Journal of Limnology 54. https://doi.org/10.1051/limn/2017030.

  • Frau, D., Mayora, G., & Devercelli, M. (2018b). Phytoplankton based water quality metrics: feasibility of its application in a neotropical shallow lake. Marine and Freshwater Research, 69, 1746–1754.

    Article  CAS  Google Scholar 

  • Friedrich, G., & Pohlmann, M. (2009). Long term plankton studies at the lower Rhine/Germany. Limnologica, 39, 14–39.

    Article  CAS  Google Scholar 

  • Hammer, Ø., Harper, D. A., & Ryan, P. D. (2018). PAST-palaeontological statistics, version 3.18. Norway: University of Oslo.

    Google Scholar 

  • Hillebrand, H., Dürselen, C., Kirschtel, D., Pollingher, U., & Zohary, T. (1999). Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology, 35, 403–424.

    Article  Google Scholar 

  • Hilton, J., & Rigg, E. (1983). Determination of nitrate in lake water by the adaptation of the hydrazine-copper reduction method for use on a discrete analyzer: performance statistics and an instrument-induced difference from segmented flow conditions. Analyst, 108, 1026–1028.

    Article  CAS  Google Scholar 

  • Iriondo, M. H., Paggi, J. C., & Parma, M. J. (2007). The Middle Paraná River. Limnology of a Subtropical Wetland. Berlin: Springer.

    Book  Google Scholar 

  • Jakubowska, N., & Szeląg-Wasielewska, E. (2015). Toxic picoplanktonic cyanobacteria-review. Marine Drugs, 13, 1497–1518.

    Article  CAS  Google Scholar 

  • Koenings, J. P., & Edmundson, J. A. (1991). Secchi disk and photometer estimates of light regimes in Alaskan lakes: effects of yellow color and turbidity. Limnology and Oceanography, 36, 91–105.

    Article  Google Scholar 

  • Komárek, J. (2013). Cyanoprokaryota.Teil/3rd part: heterocytous genera. In G. L. Büdel, M. Krienitz, & M. Chagerl (Eds.), Süswasserflora von Mitteleuropa (Freshwater flora of Central Europe). Heidelberg: Springer Spektrum.

    Google Scholar 

  • Komárek, J., & Anagnostidis, K. (1998). Cyanoprokaryota. Teil 1: Chroococcales. In H. Ettl, G. Gärtner, H. Heynig, & D. Mollenhauer (Eds.), Süsswasserflora von Mitteleuropa 19/1. Gustav Fisher Verlag: Jena.

    Google Scholar 

  • Komárek, J., & Anagnostidis, K. (2005). Cyanoprokaryota. Teil 2: Oscillatoriales. In B. Büdel, G. Gärtner, L. Krienitz, & M. Schagerl (Eds.), Süsswasserflora von Mitteleuropa 19/2. Germany: Elsevier.

    Google Scholar 

  • Komárek, J., & Fott, B. (1983). Chlorophyceae, chlorococcales. In G. Huber-Pestalozzi (Ed.), Das Phytoplankton des Sdwasswes. Die Binnenggewasser, Vol. 16(5)’. Germany: Schweizerbart’sche Verlagsbuchhandlung.

    Google Scholar 

  • Komárek, J., & Johansen, J. R. (2015). Coccoid cyanobacteria. In J. D. Wehr, R. G. Sheath, & R. P. Kociolek (Eds.), Freshwater algae from North America: ecology and classification (pp. 75–133). United Kingdom: Academic Press.

    Chapter  Google Scholar 

  • Krammer, K., & Lange-Bertalot, H. (1991). Bacillariophyceae. 3. Teil Centrales, Fragilariaceae, Eunotiaceae. In H. Ettl, J. Gerloff, H. Heynig, & D. Mollenhauer (Eds.), Süsswasserflora von Mitteleuropa. Germany: Gustav Fischer Verlag.

    Google Scholar 

  • Kruk, C., & Segura, A. M. (2012). The habitat template of phytoplankton morphology-based functional groups. Hydrobiologia, 698, 191–202.

    Article  CAS  Google Scholar 

  • Kruk, C., Huszar, V. L. M., Peeters, E. T. H. M., Bonilla, S., Costa, L., Lürling, M., Reynolds, C. S., & Scheffer, M. (2010). A morphological classification capturing functional variation in phytoplankton. Freshwater Biology, 55, 614–627.

    Article  Google Scholar 

  • Kruk, C., Devercelli, M., Huszar, V. L. M., Hernández, E., Beamud, G., Diaz, M., Silva, L. H. S., & Segura, A. M. (2017). Classification of Reynolds phytoplankton functional groups using individual traits and machine learning techniques. Freshwater Biology, 62, 1681–1692.

    Article  CAS  Google Scholar 

  • Lee, R. D. (2008). Phycology. United Kingdom: Cambridge University Press.

    Book  Google Scholar 

  • Licursi, M., & Gómez, N. (2002). Benthic in three diatoms and some environmental conditions lowland streams. Annales de Limnologie - International Journal of Limnology, 38, 109–118.

    Article  Google Scholar 

  • Licursi, M., Gómez, N., & Sabater, S. (2016). Effects of nutrient enrichment on epipelic diatom assemblages in a nutrient-rich lowland stream, Pampa Region, Argentina. Hydrobiologia, 766, 135–150.

    Article  Google Scholar 

  • Loez, C., & Salibián, A. (1990). Premieres données sur le phytoplancton et les caractéristiques physico-chimiques de río Reconquista (Buenos Aires, Argentine): une riviere urbaine pollué. Revue du Hydrobiologie Tropicale, 23, 283–296.

    Google Scholar 

  • Malmqvist, B., & Rund, S. (2002). Threats to the running water ecosystems of the world. Environmental Conservation, 29, 134–153.

    Article  Google Scholar 

  • Meichtry de Zaburlín, N., Vogler, R. E., Molina, M. J., & Llanao, V. M. (2016). Potential distribution of the invasive freshwater dinoflagellate Ceratium furcoides (Levander) Langhans (Dinophyta) in South America. Journal of Phycology, 52, 200–208.

    Article  Google Scholar 

  • Mischke, U., Venohr, M., & Behrent, H. (2011). Using phytoplankton to assess the trophic status of German rivers. International Review of Hydrobiology, 96, 578–598.

    Article  CAS  Google Scholar 

  • Nõges, P., Mischke, U., Laugaste, R., & Solimini, A. G. (2010). Analysis of changes over 44 years in the phytoplankton of Lake Vo˜rtsja¨rv (Estonia): the effect of nutrients, climate and the investigator on phytoplankton-based water quality indices. Hydrobiologia, 646, 33–48.

    Article  CAS  Google Scholar 

  • O’Farrell, I., Lombardo, R. J., de Tezanos Pinto, P., & Loez, C. (2002). The assessment of water quality in the Lower Luján River (Buenos Aires, Argentina): phytoplankton and algal bioassays. Environmental Pollution, 120, 207–218.

    Article  Google Scholar 

  • Padisák, J., Borics, G., Grigorszky, I., & Soróczki-Pintér, E. (2006). Use of phytoplankton assemblages for monitoring ecological status of lakes within the Water Framework Directive: the assemblage index. Hydrobiologia, 553, 1–14.

    Article  Google Scholar 

  • Padisák, J., Crossetti, L. O., & Naselli-Flores, L. (2009). Use and misuse in the application of the phytoplankton functional classification: a critical review with updates. Hydrobiologia, 621, 1–19.

    Article  Google Scholar 

  • Pavé, P. J., & Marchese, M. (2005). Invertebrados bentónicos como indicadores de calidad del agua en ríos urbanos (Paraná-Entre Ríos, Argentina). Ecología Austral, 15, 183–197.

    Google Scholar 

  • Phillips, G., Pietiläinen, O. P., Carvalho, L., Solimini, A., Lyche Solheim, A., & Cardoso, A. C. (2008). Chlorophyll–nutrient relationships of different lake types using a large European dataset. Aquatic Ecology, 42, 213–226.

    Article  CAS  Google Scholar 

  • Piirsoo, K., Pall, P., Tuvikene, A., & Viik, M. (2008). Temporal and spatial patterns of phytoplankton in a temperate lowland river (Emajogi, Estonia). Journal of Plankton Research, 30, 1285–1295.

    Article  CAS  Google Scholar 

  • Prygiel, J., & Coste, M. (2000). Guide méthodologique pour la mise en oeuvre de l’Indice Biologique Diatomées. France: Agences de l’eau.

    Google Scholar 

  • Reynolds, C. S. (1994). The long, the short and the stalled: on the attributes of phytoplankton selected by physical mixing in lakes and rivers. Hydrobiologia, 289, 9–21.

    Article  Google Scholar 

  • Reynolds, C. (2006). Ecology of Phytoplankton. United Kingdom: University Press.

    Book  Google Scholar 

  • Reynolds, C. S., Huszar, V., Kruk, C., Naselli-Flores, L., & Melo, S. (2002). Towards a functional classification of the freshwater phytoplankton. Journal of Plankton Research, 24, 417–428.

    Article  Google Scholar 

  • Reynolds, C. S., Mberly, S. C., Parker, J. E., & De Ville, M. M. (2012). Forty years of monitoring water quality in Grasmere (English Lake District): separating the effects of enrichment by treated sewage and hydraulic flushing on phytoplankton ecology. Freshwater Biology, 57, 384–399.

    Article  CAS  Google Scholar 

  • Rodrigues Capítulo, A., Gómez, N., Giorgi, A., & Feijoó, C. (2010). Global changes in pampean lowland streams (Argentina): implications for biodiversity and functioning. Hydrobiologia, 657, 53–70.

    Article  Google Scholar 

  • Sabater, S. (2008). Alterations of the global water cycles and their effects on river structure, function and services. Freshwater Reviews, 1, 75–88.

    Article  Google Scholar 

  • Salmaso, N., & Padisák, J. (2007). Morpho-functional groups and phytoplankton development in two deep lakes (Lake Garda, Italy and Lake Stechlin, Germany). Hydrobiologia, 578, 97–112.

    Article  Google Scholar 

  • Soares, M. C. S., Huszar, V. L. M., & Roland, F. (2007). Phytoplankton dynamics in two tropical rivers with different degrees of human impact (southern Brazil). River Research and Applications, 23, 698–714.

    Article  Google Scholar 

  • Srebotnjak, T., Carr, G., de Sherbininc, A., & Rickwood, C. (2012). A global water quality index and hot-deck imputation of missing data. Ecological Indicators, 17, 108–119.

    Article  CAS  Google Scholar 

  • Stanković, I., Vlahović, T., Gligora Udovič, M., Várbíró, G., & Borics, G. (2012). Phytoplankton functional and morpho-functional approach in large floodplain rivers. Hydrobiologia, 698, 217–231.

    Article  CAS  Google Scholar 

  • Tejerina-Garro, F. L., Maldonado, M., Ibañez, C., Pont, D., Roset, N., & Oberdorff, T. (2005). Effects of natural and anthropogenic environmental changes on riverine fish assemblages: a framework for ecological assessment of rivers. Brazilian Archives of Biology and Technology, 48, 91–108.

    Article  Google Scholar 

  • Tell, G., & Conforti, V. (1986). Euglenophyta pigmentadas de Argentina. Bibliotheca Phycologica, 75, 1–301.

    Google Scholar 

  • ter Braak, C. J., & Šmilauer, P. (2012). Canoco reference manual and user’s guide: software for ordination, version 5.0. Ithaca: Microcomputer Power.

    Google Scholar 

  • Thackeray, S. J., Nõges, P., Dunbarc, M. J., Dudleyd, B. J., et al. (2013). Quantifying uncertainties in biologically-based water quality assessment: a pan-European analysis of lake phytoplankton community metrics. Ecological Indicators, 29, 34–47.

    Article  CAS  Google Scholar 

  • UNESCO (2006). Evaluación de los Recursos Hídricos. Elaboración del balance hídrico integral por cuencas hidrográficas. Documentos Técnicos del PHI-LAC, N°4.

  • United Nations Environment Program (UNEP). (2002). Global environmental outlook 3: past, present and future perspectives. London: Earthscan Publications.

    Google Scholar 

  • Utermöhl, H. (1958). Zur Vervollkommnung der quantitative Phytoplankton: methodik. Mitt Int Verein Theor Angew, 9, 1–38.

    Google Scholar 

  • Venrick, E. L. (1978). How many cells to count? In A. Sournia (Ed.), Phytoplankton manual. Paris: UNESCO.

    Google Scholar 

  • Wang, C., B-Béres, V., Stenger-Kovács, C., Li, X., & Abonyi, A. (2018). Enhanced ecological indication based on combined planktic and benthic functional approaches in large river phytoplankton ecology. Hydrobiologia, 818, 163–175. https://doi.org/10.1007/s10750-018-3604-1.

    Article  CAS  Google Scholar 

  • Wilson, M.G. (2017). wManual de indicadores de calidad del suelo para las ecorregiones de Argentina. Ediciones INTA. Available in: https://inta.gob.ar.

  • Zalocar de Domitrovic, Y., & Maidana, N. I. (1997). Taxonomic and ecological studies of the Parana River diatom flora (Argentina). In F. Lange-Bertalot & P. Kociolek (Eds.), Bibliotheca Diatomologica. Berlin: J. Cramer.

    Google Scholar 

  • Zar, J. H. (1996). Biostatistical analysis. New York: Prentice Hall 918p.

    Google Scholar 

Download references

Acknowledgments

We thank C. De Bonis for his assistance in the field and Dr. P. de Tezanos Pinto for the language assistance.

Funding

This study was partially supported by the project PICT 1017/2014.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Diego Frau.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(XLSX 20 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Frau, D., Medrano, J., Calvi, C. et al. Water quality assessment of a neotropical pampean lowland stream using a phytoplankton functional trait approach. Environ Monit Assess 191, 681 (2019). https://doi.org/10.1007/s10661-019-7849-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-019-7849-6

Keywords