, Volume 806, Issue 1, pp 347–361 | Cite as

Introducing nested spatial scales in multi-stress models: towards better assessment of human impacts on river ecosystems

  • Delphine Corneil
  • Bertrand Villeneuve
  • Jérémy Piffady
  • André Chandesris
  • Philippe Usseglio-Polatera
  • Yves Souchon
Primary Research Paper


We investigated the relationships between the ecological status of wadeable rivers and the intensity of various stressors related with hydromorphological alterations, nutrient, and organic matter contaminations. The French invertebrate-based multimetric index (I2M2), which efficiently responds to the effects of both physical and chemical and hydromorphological stressors, was used as descriptor of river reach ecological status. We developed a model focusing on the effects of hydromorphological and physical and chemical stressor gradients on the I2M2 in different physiographic contexts. The potential confounding effects of natural geographic conditions and watershed scale pressure gradients were taken into account and neutralized by gathering watersheds into homogeneous clusters integrated as an interaction factor in the model. Whatever effects were considered (general or within-spatial clusters), the I2M2 was impaired similarly by the same stressor types, being negatively influenced by an increase in BOD5, ammonium, nitrite, nitrate, and total phosphorus concentrations. The I2M2 was also negatively influenced by variables describing hydromorphology at the reach scale, especially by the ‘loss of sinuosity,’ ‘increasing rates of bank erosion,’ ‘flow reductions,’ and ‘alteration of pool/riffle succession.’ The I2M2 was generally more strongly impaired by physical and chemical pressures than by hydromorphological alterations.


Ecological status Pressure–impact relationship Macroinvertebrates Stream monitoring Stressors 



This research was made possible by grants and the support of the French Agency for Biodiversity (AFB-Onema; Action 32, convention Onema-Irstea 2013-2015). We greatly thank Peter W. Downs, for his review of the manuscript.


  1. Abell, R. & J. D. Allan, 2002. Riparian shade and stream temperatures in an agricultural catchment, Michigan, USA. Internationale Vereinigung fur Theoretische und Angewandte Limnologie Verhandlungen, Stuttgart 2002(28): 232–237.Google Scholar
  2. Allan, J. D., 2004. Landscapes and riverscapes: the influence of land use on stream ecosystems. Annual Review of Ecology, Evolution, and Systematics 35: 257–284.CrossRefGoogle Scholar
  3. Allan, J. D. & L. B. Johnson, 1997. Catchment-scale analysis of aquatic ecosystems. Freshwater Biology 37: 107–111.CrossRefGoogle Scholar
  4. Biggs, B. J. F., S. N. Francoeur, A. D. Huryn, R. G. Young, C. J. Arbuckle & C. R. Townsend, 2000. Trophic cascades in streams: effects of nutrient enrichment on autotrophic and consumer benthic communities under two different fish predation regimes. Canadian Journal of Fisheries and Aquatic Sciences 57: 1380–1394.CrossRefGoogle Scholar
  5. Büttner, G. & B. Kosztra, 2007. CLC 2006 technical guidelines. Technical Report, European Environment Agency.Google Scholar
  6. Camargo, J. A. & A. Alonso, 2006. Ecological and toxicological effects of inorganic nitrogen pollution in aquatic ecosystems: a global assessment. Environment International 32: 831–849.CrossRefPubMedGoogle Scholar
  7. Chandesris, A., N. Mengin, J. R. Malavoi, J. G. Wasson & Y. Souchon, 2008. SYRAH-CE: SYstème Relationnel d’Audit de l’Hydromorphologie des Cours d’Eau. A relational, multi-scale system for auditing the hydro-morphology of running waters: diagnostic tool to help the WFD implementation in France. 4th International Conference on River Restoration, Venice: 4.Google Scholar
  8. Cramer, R. D., J. D. Bunce, D. E. Patterson & I. E. Frank, 1988. Crossvalidation, bootstrapping, and partial least squares compared with multiple regression in conventional QSAR studies. Quantitative Structure-Activity Relationships 7: 18–25.CrossRefGoogle Scholar
  9. Dahm, V., D. Hering, D. Nemitz, W. Graf, A. Schmidt-Kloiber, P. Leitner, A. Melcher & C. K. Feld, 2013. Effects of physics and chemistry, land use and hydromorphology on three riverine organism groups: a comparative analysis with monitoring data from Germany and Austria. Hydrobiologia 704: 389–415.CrossRefGoogle Scholar
  10. Dodds, W. K. & E. B. Welch, 2000. Establishing nutrient criteria in streams. Journal of the North American Benthological Society 19: 186–196.CrossRefGoogle Scholar
  11. Donohue, I., M. L. McGarrigle & P. Mills, 2006. Linking catchment characteristics and water chemistry with the ecological status of Irish rivers. Water Research 40: 91–98.CrossRefPubMedGoogle Scholar
  12. Dosskey, M. G., P. Vidon, N. P. Gurwick, C. J. Allan, T. P. Duval & R. Lowrance, 2010. The role of riparian vegetation in protecting and improving chemical water quality in streams. Journal of the American Water Resources Association 46: 261–277.CrossRefGoogle Scholar
  13. Efron, B. & G. Gong, 1983. A leisurely look at the bootstrap, the jackknife, and cross-validation. The American Statistician 37: 36–48.Google Scholar
  14. European Environment Agency (ed.), 1999. Environmental Indicators: Typology and Overview. European Environment Agency, Copenhagen.Google Scholar
  15. Feio, M. J. & S. Dolédec, 2012. Integration of invertebrate traits into predictive models for indirect assessment of stream functional integrity: a case study in Portugal. Ecological Indicators 15: 236–247.CrossRefGoogle Scholar
  16. Feld, C. K., 2013. Response of three lotic assemblages to riparian and catchment-scale land use: implications for designing catchment monitoring programmes. Freshwater Biology 58: 715–729.CrossRefGoogle Scholar
  17. Frissell, C. A., W. J. Liss, C. E. Warren & M. D. Hurley, 1986. A hierarchical framework for stream habitat classification: viewing streams in a watershed context. Environmental Management 10: 199–214.CrossRefGoogle Scholar
  18. Gallant, A. L., T. R. Loveland & T. L. Sohl, 2004. Using an ecoregion framework to analyze land-cover and land-use dynamics. Environmental Management 34: S89–S110.CrossRefPubMedGoogle Scholar
  19. Gieswein, A., D. Hering & C. K. Feld, 2017. Additive effects prevail: the response of biota to multiple stressors in an intensively monitored watershed. Science of the Total Environment 593–594: 27–35.CrossRefPubMedGoogle Scholar
  20. Hering, D., C. Meier, C. Rawer-Jost, C. K. Feld, R. Biss & A. Zenker, 2004. Assessing streams in Germany with benthic invertebrates: selection of candidate metrics. Limnologica 34: 398–415.CrossRefGoogle Scholar
  21. Hering, D., R. K. Johnson, S. Kramm, S. Schmutz, K. Szoszkiewicz & P. F. M. Verdonschot, 2006. Assessment of European streams with diatoms, macrophytes, macroinvertebrates and fish: a comparative metric-based analysis of organism response to stress. Freshwater Biology 51: 1757–1785.CrossRefGoogle Scholar
  22. Johnson, R. K. & D. Hering, 2009. Response of taxonomic groups in streams to gradients in resource and habitat characteristics. Journal of Applied Ecology 46: 175–186.CrossRefGoogle Scholar
  23. Kail, J. & D. Hering, 2009. The influence of adjacent stream reaches on the local ecological status of Central European mountain streams. River Research and Applications 25: 537–550.CrossRefGoogle Scholar
  24. King, R. S., M. E. Baker, D. F. Whigham, D. E. Weller, T. E. Jordan, P. F. Kazyak & M. K. Hurd, 2005. Spatial considerations for linking watershed land cover to ecological indicators in streams. Ecological Applications 15: 137–153.CrossRefGoogle Scholar
  25. Kristensen, P., 2004. The DPSIR Framework. National Environmental Research Institute, Denmark.Google Scholar
  26. Lammert, M. & J. D. Allan, 1999. Assessing biotic integrity of streams: effects of scale in measuring the influence of land use/cover and habitat structure on fish and macroinvertebrates. Environmental Management 23: 257–270.CrossRefPubMedGoogle Scholar
  27. Lorenz, A. W. & C. K. Feld, 2013. Upstream river morphology and riparian land use overrule local restoration effects on ecological status assessment. Hydrobiologia 704: 489–501.CrossRefGoogle Scholar
  28. Martens, H. & M. Martens, 2000. Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR). Food Quality and Preference 11: 5–16.CrossRefGoogle Scholar
  29. Marzin, A., 2013. Indicateurs biologiques de la qualité écologique des cours d’eau: variabilités et incertitudes associées. PhD thesis, AgroParisTech.Google Scholar
  30. Marzin, A., V. Archaimbault, J. Belliard, C. Chauvin, F. Delmas & D. Pont, 2012. Ecological assessment of running waters: do macrophytes, macroinvertebrates, diatoms and fish show similar responses to human pressures? Ecological Indicators 23: 56–65.CrossRefGoogle Scholar
  31. Marzin, A., P. F. M. Verdonschot & D. Pont, 2013. The relative influence of catchment, riparian corridor, and reach-scale anthropogenic pressures on fish and macroinvertebrate assemblages in French rivers. Hydrobiologia 704: 375–388.CrossRefGoogle Scholar
  32. Mondy, C. P., B. Villeneuve, V. Archaimbault & P. Usseglio-Polatera, 2012. A new macroinvertebrate-based multimetric index (I2M2) to evaluate ecological quality of French wadeable streams fulfilling the WFD demands: a taxonomical and trait approach. Ecological Indicators 18: 452–467.CrossRefGoogle Scholar
  33. Montier, C., J. Daroussin, D. King & Y. Le Bissonnais, 1998. Cartographie de l’aléa “Erosion des Sols” en France. INRA, Orléans.Google Scholar
  34. Naiman, R. J., 1992. Watershed Management: Balancing Sustainability and Environmental Change. Springer, New York.CrossRefGoogle Scholar
  35. Omernik, J. M., 1987. Ecoregions of the conterminous United States. Annals of the Association of American Geographers 77: 118–125.CrossRefGoogle Scholar
  36. Parsons, M., M. C. Thoms & R. H. Norris, 2003. Scales of macroinvertebrate distribution in relation to the hierarchical organization of river systems. Journal of the North American Benthological Society 22: 105–122.CrossRefGoogle Scholar
  37. Parsons, M., M. C. Thoms & R. H. Norris, 2004. Using hierarchy to select scales of measurement in multiscale studies of stream macroinvertebrate assemblages. Journal of the North American Benthological Society 23: 157–170.CrossRefGoogle Scholar
  38. Piscart, C., R. Genoel, S. Dolédec, E. Chauvet & P. Marmonier, 2009. Effects of intense agricultural practices on heterotrophic processes in streams. Environmental Pollution 157: 1011–1018.CrossRefPubMedGoogle Scholar
  39. Poff, N. L., 1997. Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. Journal of the North American Benthological Society 16: 391–409.CrossRefGoogle Scholar
  40. Reyjol, Y., C. Argillier, W. Bonne, A. Borja, A. D. Buijse, A. C. Cardoso, M. Daufresne, M. Kernan, M. T. Ferreira, S. Poikane, P. Narcís, A.-L. Solheim, S. Stroffek, P. Usseglio-Polatera, B. Villeneuve & W. Van de Bund, 2014. Assessing the ecological status in the context of the European Water Framework Directive: where do we go now? Science of the Total Environment 497: 332–344.CrossRefPubMedGoogle Scholar
  41. Roth, N. E., J. D. Allan & D. L. Erickson, 1996. Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landscape Ecology 11: 141–156.CrossRefGoogle Scholar
  42. Sponseller, R. A., E. F. Benfield & H. M. Valett, 2001. Relationships between land use, spatial scale and stream macroinvertebrate communities. Freshwater Biology 46: 1409–1424.CrossRefGoogle Scholar
  43. Sundermann, A., M. Gerhardt, H. Kappes & P. Haase, 2013. Stressor prioritisation in riverine ecosystems: which environmental factors shape benthic invertebrate assemblage metrics? Ecological Indicators 27: 83–96.CrossRefGoogle Scholar
  44. Thorp, J. H., 2014. Metamorphosis in river ecology: from reaches to macrosystems. Freshwater Biology 59: 200–210.CrossRefGoogle Scholar
  45. Thorp, J. H., M. C. Thoms & M. D. Delong, 2006. The riverine ecosystem synthesis: biocomplexity in river networks across space and time. River Research and Applications 22: 123–147.CrossRefGoogle Scholar
  46. Townsend, C. R., S. Dolédec, R. H. Norris, K. Peacock & C. Arbuckle, 2003. The influence of scale and geography on relationships between stream community composition and landscape variables: description and prediction. Freshwater Biology 48: 768–785.CrossRefGoogle Scholar
  47. Van Looy, K., C. Cavillon, T. Tormos, J. Piffady, P. Landry & Y. Souchon, 2013. A scale-sensitive connectivity analysis to identify ecological networks and conservation value in river networks. Landscape Ecology 28: 1239–1249.CrossRefGoogle Scholar
  48. Villeneuve, B., Y. Souchon, P. Usseglio-Polatera, M. Ferréol & L. Valette, 2015. Can we predict biological condition of stream ecosystems? A multi-stressors approach linking three biological indices to physico-chemistry, hydromorphology and land use. Ecological Indicators 48: 88–98.CrossRefGoogle Scholar
  49. Wasson, J. G., A. Chandesris, H. Pella & L. Blanc, 2002. Définition des Hydro-écorégions françaises métropolitaines. Approche régionale de la typologie des eaux courantes et éléments pour la définition des peuplements de référence d’invertébrés. Ministère de l’Aménagement du Territoire et de l’Environnement, Cemagref Lyon BEA/LHQ p190.Google Scholar
  50. Wasson, J. G., B. Villeneuve, A. Iital, J. Murray-Bligh, M. Dobiasova, S. Bacikova, H. Timm, H. Pella, N. Mengin & A. Chandesris, 2010. Large-scale relationships between basin and riparian land cover and the ecological status of European rivers. Freshwater Biology 55: 1465–1482.CrossRefGoogle Scholar
  51. Wold, S., M. Sjöström & L. Eriksson, 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems 58: 109–130.CrossRefGoogle Scholar
  52. Yates, A. G. & R. C. Bailey, 2010. Covarying patterns of macroinvertebrate and fish assemblages along natural and human activity gradients: implications for bioassessment. Hydrobiologia 637: 87–100.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.UR MALY, Irstea Lyon-VilleurbanneVilleurbanne CedexFrance
  2. 2.Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC)UMR 7360 CNRS–Université de LorraineMetzFrance

Personalised recommendations