Predicting reference conditions for river bioassessment by incorporating boosted trees in the environmental filters method

Abstract Contemporary bioassessment methods for water bodies require the description of “reference conditions” representing an absence or only “very minor” presence of human impacts on hydromorphological, physical and chemical properties. However, minimally disturbed reference sites are lacking in many European regions and other parts of the world because of pervasive anthropogenic influences. Here we describe the use of environmental filters modelling, incorporating boosted trees (BT), to derive reference data for abiotic variables and biological communities (diatoms and macroinvertebrates) for rivers in a highly disturbed region (Portuguese central-western lowland area), where minimally disturbed reference sites are non-existent. We also revise quality class boundaries for diatom and macroinvertebrate bioassessment in this region, and develop a new multimetric diatoms index (MDI). The new index includes not only the ‘ Indice de Polluosensibilite Specifique’ (IPS) based on species’ sensitivity to organic pollution and nutrients, but also the numbers of total and sensitive taxa. Our approach predicted significantly different communities under reference conditions from those observed, with a higher median reference number of taxa per site than the observed number (69 against 27 for diatoms; 53 against 22 for macroinvertebrates). In addition, the predicted communities for both biological groups were more similar among sites than the observed communities. Adjustment of index calculation and quality class boundaries to incorporate the new reference data resulted in more stringent site assessments that were better correlated with human pressures than assessments with previous methods. This study brings new insight to solve the problem of an absence of minimally disturbed reference sites.

[1]  Mike T. Furse,et al.  RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers , 2003 .

[2]  P. Verdonschot,et al.  Establishing reference conditions for European streams , 2004, Hydrobiologia.

[3]  N. Willby,et al.  Harmonising the bioassessment of large rivers in the absence of near‐natural reference conditions – a case study of the Danube River , 2012 .

[4]  M. Coste,et al.  “Omnidia”: software for taxonomy, calculation of diatom indices and inventories management , 1993 .

[5]  Y-S Park,et al.  Typology of diatom communities and the influence of hydro-ecoregions: a study on the French hydrosystem scale. , 2005, Water research.

[6]  P. Gleick.  The changing water paradigm. A look at twenty-first century water resources development. , 2000 .

[7]  K. Serieyssol.  Diatoms of Europe: Diatoms of the European Inland Waters and Comparable habitats , 2012 .

[8]  M. J. Servia,et al.  Multiple-Trait Analysis of Fluctuating Asymmetry Levels in Anthropogenically and Naturally Stressed Sites: A Case Study Using Chironomus Riparius Meigen, 1804 Larvae , 2004, Environmental monitoring and assessment.

[9]  A. Herlihy,et al.  Development of diatom indicators of ecological conditions for streams of the western US , 2008, Journal of the North American Benthological Society.

[10]  S. Almeida,et al.  Ecology of freshwater diatoms from the central region of Portugal , 2001 .

[11]  B. Chessman,et al.  Bioassessment without reference sites: use of environmental filters to predict natural assemblages of river macroinvertebrates , 2004, Journal of the North American Benthological Society.

[12]  G. De’ath.  Boosted trees for ecological modeling and prediction. , 2007, Ecology.

[13]  J. Friedman.  Special Invited Paper-Additive logistic regression: A statistical view of boosting , 2000 .

[14]  Donald F. Charles,et al.  Diatom metrics for monitoring eutrophication in rivers of the United States , 2007 .

[15]  S. Sabater,et al.  Water quality assessment of rivers using diatom metrics across Mediterranean Europe: a methods intercalibration exercise. , 2014, The Science of the total environment.

[16]  J. Foerster,et al.  Ecological classification of macrophytes and phytobenthos for rivers in Germany according to the water framework directive , 2004 .

[17]  John L Stoddard,et al.  Setting expectations for the ecological condition of streams: the concept of reference condition. , 2005, Ecological applications : a publication of the Ecological Society of America.

[18]  S. Dolédec,et al.  Integration of invertebrate traits into predictive models for indirect assessment of stream functional integrity: A case study in Portugal , 2012 .

[19]  Carlos Viana-Ferreira,et al.  COMBINING MULTIPLE MACHINE LEARNING ALGORITHMS TO PREDICT TAXA UNDER REFERENCE CONDITIONS FOR STREAMS BIOASSESSMENT , 2014 .

[20]  R. Norris,et al.  Water quality assessment of Portuguese streams: Regional or national predictive models? , 2009 .

[21]  C. Frissell,et al.  ECOSYSTEM MANAGEMENT AND THE CONSERVATION OF AQUATIC BIODWERSITY AND ECOLOGICAL INTEGRITY , 1996 .

[22]  I. Pardo,et al.  Diatom communities as indicators of ecological status in Mediterranean temporary streams (Balearic Islands, Spain) , 2012 .

[23]  T. Hastie,et al.  Variation in demersal fish species richness in the oceans surrounding New Zealand: an analysis using boosted regression trees , 2006 .

[24]  M. Coste,et al.  Diatomées invasives exotiques ou rares en France: principales observations effectuées au cours des dernières décennies , 2000 .

[25]  L. Hoffmann,et al.  Regional distribution of diatom assemblages in the headwater streams of Luxembourg , 2004, Hydrobiologia.

[26]  Young-Seuk Park,et al.  Predicting diatom reference communities at the French hydrosystem scale : A first step towards the definition of the good ecological status , 2007 .

[27]  D. Pont,et al.  Ecological assessment of running waters: Do macrophytes, macroinvertebrates, diatoms and fish show similar responses to human pressures? , 2012 .

[28]  D. Charles,et al.  Benthic diatoms in USA rivers: distributions along spatial and environmental gradients , 2002 .

[29]  DIATMOD: diatom predictive model for quality assessment of Portuguese running waters , 2012, Hydrobiologia.

[30]  J Ferreira,et al.  Least Disturbed Condition for European Mediterranean rivers. , 2014, The Science of the total environment.

[31]  F. Rahel,et al.  Hierarchical faunal filters: an approach to assessing effects of habitat and nonnative species on native fishes , 2005 .

[32]  M. T. Ferreira,et al.  AQUAFLORA: A predictive model based on diatoms and macrophytes for streams water quality assessment , 2012 .

[33]  J. Webster,et al.  The role of macroinvertebrates in stream ecosystem function. , 1996, Annual review of entomology.

[34]  M. Feio,et al.  Diatoms and macroinvertebrates provide consistent and complementary information on environmental quality , 2007 .

[35]  Robert J. Naiman,et al.  Global alteration of freshwaters: influences on human and environmental well-being , 2011, Ecological Research.

[36]  S. Sabater,et al.  Determination of the biological diatom index (IBD NF T 90–354): results of an intercomparison exercise , 2002, Journal of Applied Phycology.

[37]  J. Sinkeldam,et al.  A coded checklist and ecological indicator values of freshwater diatoms from The Netherlands , 1994, Netherland Journal of Aquatic Ecology.

[38]  Frédéric Rimet,et al.  Benthic diatom assemblages and their correspondence with ecoregional classifications: case study of rivers in north-eastern France , 2009, Hydrobiologia.

[39]  Andrea Buffagni,et al.  The European reference condition concept: A scientific and technical approach to identify minimally-impacted river ecosystems. , 2012, The Science of the total environment.

[40]  K. R. Clarke,et al.  Change in marine communities : an approach to statistical analysis and interpretation , 2001 .

[41]  Christian K. Feld,et al.  Cook book for the development of a Multimetric Index for biological condition of aquatic ecosystems: experiences from the European AQEM and STAR projects and related initiatives , 2006 .

[42]  N. LeRoy Poff,et al.  Landscape Filters and Species Traits: Towards Mechanistic Understanding and Prediction in Stream Ecology , 1997, Journal of the North American Benthological Society.

[43]  T. Reynoldson,et al.  An invertebrate predictive model (NORTI) for streams and rivers: Sensitivity of the model in detecting stress gradients , 2014 .

[44]  R. W. Bode,et al.  A nutrient biotic index (NBI) for use with benthic macroinvertebrate communities , 2007 .

[45]  C. Townsend,et al.  Light, nutrients and grazing interact to determine stream diatom community composition and functional group structure , 2011 .

[46]  P. Armitage,et al.  The Chironomidae: the biology and ecology of non-biting midges. , 1995 .

[47]  M. Feio,et al.  Determining useful benchmarks for the bioassessment of highly disturbed areas based on diatoms , 2015 .

[48]  John R. Olson,et al.  The reference condition: predicting benchmarks for ecological and water-quality assessments , 2010, Journal of the North American Benthological Society.

[49]  Paul A. Keddy,et al.  Assembly and response rules: two goals for predictive community ecology , 1992 .

[50]  María Rosario Vidal-Abarca Gutiérrez,et al.  Caracterización del estado ecológico de ríos mediterráneos ibéricos mediante el índice IBMWP (antes BMWP , 2002 .

[51]  Frédéric Rimet,et al.  Life-forms, cell-sizes and ecological guilds of diatoms in European rivers , 2012 .

[52]  D. Goffaux,et al.  Assessing river biotic condition at a continental scale: a European approach using functional metrics and fish assemblages , 2006 .

[53]  M. Kelly,et al.  Establishing expectations for pan-European diatom based ecological status assessments , 2012 .

[54]  J. Wiens.  Riverine landscapes: taking landscape ecology into the water , 2002 .

[55]  T. Reynoldson,et al.  The Reference Condition: A Comparison of Multimetric and Multivariate Approaches to Assess Water-Quality Impairment Using Benthic Macroinvertebrates , 1997, Journal of the North American Benthological Society.

[56]  Ralph T. Clarke.  Estimating confidence of European WFD ecological status class and WISER Bioassessment Uncertainty Guidance Software (WISERBUGS) , 2012, Hydrobiologia.

[57]  Piet F. M. Verdonschot,et al.  Uncertainty in diatom assessment: Sampling, identification and counting variation , 2006 .

[58]  B. Malmqvist,et al.  Threats to the running water ecosystems of the world , 2002, Environmental Conservation.

[59]  J Elith,et al.  A working guide to boosted regression trees. , 2008, The Journal of animal ecology.