Monitoring Programmes, Multiple Stress Analysis and Decision Support for River Basin Management

The identification of plausible causes for water body status deterioration will be much easier if it can build on available, reliable, extensive and comprehensive biogeochemical monitoring data (preferably aggregated in a database). A plausible identification of such causes is a prerequisite for well-informed decisions on which mitigation or remediation measures to take. In this chapter, first a rationale for an extended monitoring programme is provided; it is then compared to the one required by the Water Framework Directive (WFD). This proposal includes a list of relevant parameters that are needed for an integrated, a priori status assessment. Secondly, a few sophisticated statistical tools are described that subsequently allow for the estiation of the magnitude of impairment as well as the likely relative importance of different stressors in a multiple stressed environment. The advantages and restrictions of these rather complicated analytical methods are discussed. Finally, the use of Decision Support Systems (DSS) is advocated with regard to the specific WFD implementation requirements.

[1]  Young-Seuk Park,et al.  Application of a self-organizing map to select representative species in multivariate analysis: A case study determining diatom distribution patterns across France , 2006, Ecol. Informatics.

[2]  E. Heugens,et al.  Predicting effects of multiple stressors on aquatic biota. , 2003 .

[3]  L. Guilhermino,et al.  Multiple stress effects on marine planktonic organisms: Influence of temperature on the toxicity of polycyclic aromatic hydrocarbons to Tetraselmis chuii , 2012 .

[4]  Peter M. Chapman,et al.  Sediment quality criteria from the sediment quality triad: An example , 1986 .

[5]  Dick de Zwart,et al.  Quantitative lines of evidence for screening-level diagnostic assessment of regional fish community impacts: a comparison of spatial database evaluation methods. , 2008, Environmental science & technology.

[6]  F. Recknagel,et al.  Artificial neural network approach for modelling and prediction of algal blooms , 1997 .

[7]  Mike T. Furse,et al.  The prediction of the macro‐invertebrate fauna of unpolluted running‐water sites in Great Britain using environmental data , 1987 .

[8]  Joseph M. Culp,et al.  Integrating mesocosm experiments with field and laboratory studies to generate weight‐of‐evidence risk assessments for large rivers , 2000 .

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

[10]  Sabine E Apitz,et al.  Conceptualizing the role of sediment in sustaining ecosystem services: Sediment-ecosystem regional assessment (SEcoRA). , 2012, The Science of the total environment.

[11]  L. Meester,et al.  Synergistic, antagonistic and additive effects of multiple stressors: predation threat, parasitism and pesticide exposure in Daphnia magna , 2008 .

[12]  Daren M. Carlisle,et al.  Use of predictive models for assessing the biological integrity of wetlands and other aquatic habitats , 2001 .

[13]  Willem Goedkoop,et al.  Distinguishing the effects of habitat degradation and pesticide stress on benthic invertebrates using stressor-specific metrics. , 2013, The Science of the total environment.

[14]  Mike T. Furse,et al.  A preliminary classification of running‐water sites in Great Britain based on macro‐invertebrate species and the prediction of community type using environmental data , 1984 .

[15]  Sabine E. Apitz,et al.  Prioritisation at River Basin Scale, Risk Assessment at Site-Specific Scale: Suggested Approaches , 2007 .

[16]  H. Hawkes,et al.  Origin and development of the biological monitoring working party score system , 1998 .

[17]  Peter M. Chapman,et al.  The sediment quality triad approach to determining pollution-induced degradation , 1990 .

[18]  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.

[19]  Werner Brack,et al.  Toward an Integrated Assessment of the Ecological and Chemical Status of European River Basins , 2009, Integrated environmental assessment and management.

[20]  Wayne G. Landis,et al.  Environmental Risk Assessment and Management from a Landscape Perspective: Kapustka/Environmental Risk , 2010 .

[21]  Werner Brack,et al.  MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity (5 pp) , 2005, Environmental science and pollution research international.

[22]  Glenn W Suter,et al.  A methodology for inferring the causes of observed impairments in aquatic ecosystems , 2002, Environmental toxicology and chemistry.

[23]  S. Giove,et al.  Integrated Risk Assessment for WFD Ecological Status classification applied to Llobregat river basin (Spain). Part II - Evaluation process applied to five environmental Lines of Evidence. , 2011, The Science of the total environment.

[24]  D. de Zwart,et al.  Predictive models attribute effects on fish assemblages to toxicity and habitat alteration. , 2006, Ecological applications : a publication of the Ecological Society of America.

[25]  Werner Brack,et al.  Toward a Holistic and Risk-Based Management of European River Basins , 2009, Integrated environmental assessment and management.

[26]  James R. Karr,et al.  Assessing biological integrity in running waters : a method and its rationale , 1986 .

[27]  Sovan Lek,et al.  Application Of Artificial Neural Network Models To Analyse The Relationships Between Gammarus pulex L. (Crustacea, Amphipoda) And River Characteristics , 2005, Environmental monitoring and assessment.

[28]  Marek J. Patyra,et al.  Book review: Fuzzy logic and Neuro Fuzzy Applications Explained by Constantin von Altrock (Prentice Hall 1995) , 1997, SGAR.

[29]  Markus A. Wetzel,et al.  Status and Causal Pathway Assessments Supporting River Basin Management , 2014 .

[30]  Peter M. Chapman,et al.  Should the Sediment Quality Triad Become a Tetrad, a Pentad, or Possibly even a Hexad? , 2006 .

[31]  M. Hill,et al.  Data analysis in community and landscape ecology , 1987 .

[32]  Matthias Liess,et al.  An indicator for effects of organic toxicants on lotic invertebrate communities: Independence of confounding environmental factors over an extensive river continuum. , 2008, Environmental pollution.

[33]  Joseph M. Culp,et al.  A weight‐of‐evidence approach for Northern river risk assessment: Integrating the effects of multiple stressors , 2000 .

[34]  Dick de Zwart,et al.  Modeling the chemical and toxic water status of the Scheldt basin (Belgium), using aquatic invertebrate assemblages and an advanced modeling method. , 2010, Environmental pollution.

[35]  It Istituto Superiore di Sanit,et al.  Common implementation strategy for the water framework directive (2000/60/EC). Guidance document on euthrophication assessment in the context of European water policies. (Technical report 2009-030; Guidance document 23) , 2009 .

[36]  Susan P. Worner,et al.  Prediction of Global Distribution of Insect Pest Species in Relation to Climate by Using an Ecological Informatics Method , 2006 .

[37]  Robin A. Matthews,et al.  A test of the community conditioning hypothesis: Persistence of effects in model ecological structures dosed with the jet fuel jp‐8 , 2000 .

[38]  D. Nacci,et al.  Risks of Endocrine-Disrupting Compounds to Wildlife: Extrapolating from Effects on Individuals to Population Response , 2001 .

[39]  Daniel P. Faith,et al.  Monitoring Ecological Impacts: Inferential uncertainty and multiple lines of evidence , 2002 .

[40]  Marten Scheffer,et al.  The determination of ecological status in shallow lakes - a tested system (ECOFRAME) for implementation of the European Water Framework Directive , 2003 .

[41]  S. Lek,et al.  Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters , 2003 .

[42]  Young-Seuk Park,et al.  Stream fish assemblages and basin land cover in a river network. , 2006, Science of the Total Environment.

[43]  K. Siimes,et al.  Effects of pesticides on community structure and ecosystem functions in agricultural streams of three biogeographical regions in Europe. , 2007, The Science of the total environment.

[44]  Sabine E. Apitz,et al.  Parsing Ecological Impacts in Watersheds , 2006 .

[45]  Sabine E. Apitz,et al.  Conceptual and strategic frameworks for sediment management at the river basin scale , 2008 .

[46]  Antonio Marcomini,et al.  Decision Support Systems for Contaminated Land Management: A Review , 2009 .

[47]  I Czerniawska-Kusza,et al.  Use of Artificial Substrates for Sampling Benthic Macroinvertebrates in the Assessment of Water Water W Quality of Large Lowland Rivers , 2004 .

[48]  R. Kolkwitz,et al.  Ökologie der tierischen Saprobien. Beiträge zur Lehre von der biologischen Gewässerbeurteilung , 1909 .

[49]  Peter Haase,et al.  The STAR project: context, objectives and approaches , 2006, Hydrobiologia.

[50]  H Segner,et al.  Preexposure temperature acclimation and diet as modifying factors for the tolerance of golden ide (Leuciscus idus melanotus) to short-term exposure to 4-chloroaniline. , 1992, Ecotoxicology and environmental safety.

[51]  Katherine E Kapo,et al.  A Geographic Information Systems–based, weights‐of‐evidence approach for diagnosing aquatic ecosystem impairment , 2006, Environmental toxicology and chemistry.

[52]  Claudio Carlon,et al.  Strategic Framework for Managing Sediment Risk at the Basin and Site-Specific Scale , 2007 .

[53]  J. M. Hellawell Biological indicators of freshwater pollution and environmental management , 1986 .

[54]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[55]  Glenn W. Suter,et al.  Ecological risk assessment , 2006 .

[56]  Wayne G. Landis,et al.  Environmental risk assessment and management from a landscape perspective , 2010 .

[57]  J. Karr Assessment of Biotic Integrity Using Fish Communities , 1981 .

[58]  Andrea Buffagni,et al.  The Development of a System to Assess the Ecological Quality of Streams Based on Macroinvertebrates – Design of the Sampling Programme within the AQEM Project , 2003 .

[59]  Glenn W. Suter Definitive Risk Characterization by Weighing the Evidence , 2016 .

[60]  Susanne Heise,et al.  Sediment risk management and communication , 2007 .

[61]  Keying Ye,et al.  Weight-of-Evidence (WOE): Quantitative Estimation of Probability of Impairment for Individual and Multiple Lines of Evidence , 2002 .

[62]  Ord,et al.  Guidelines for Ecological Risk Assessment , 2014 .

[63]  Valery E. Forbes,et al.  Applying Weight-of-Evidence in Retrospective Ecological Risk Assessment When Quantitative Data Are Limited , 2002 .

[64]  T. Seager,et al.  Application of Multicriteria Decision Analysis in Environmental Decision Making , 2005, Integrated environmental assessment and management.

[65]  Sabine E. Apitz,et al.  Is risk-based, sustainable sediment management consistent with European policy? , 2008 .

[66]  Kate A. Brauman,et al.  Ecosystem Services and River Basin Management , 2014 .

[67]  Philippe Négrel,et al.  Soil–Sediment–River Connections: Catchment Processes Delivering Pressures to River Catchments , 2014 .

[68]  Peter Calow,et al.  The Rivers Handbook , 1993 .

[69]  Sebastian Birk,et al.  Direct comparison of assessment methods using benthic macroinvertebrates: a contribution to the EU Water Framework Directive intercalibration exercise , 2006, Hydrobiologia.

[70]  Christer Carlsson,et al.  Past, present, and future of decision support technology , 2002, Decis. Support Syst..

[71]  Valery E. Forbes,et al.  A Weight-of-Evidence Framework for Assessing Sediment (Or Other) Contamination: Improving Certainty in the Decision-Making Process , 2002 .

[72]  Mike T. Furse,et al.  The multimetric approach to bioassessment, as used in the United States of America. , 2000 .

[73]  Jaroslav Slobodnik,et al.  Identification of river basin specific pollutants and derivation of environmental quality standards: A case study in the Slovak Republic , 2012 .

[74]  F Bro-Rasmussen,et al.  Ecoepidemiology--a casuistic discipline describing ecological disturbances and damages in relation to their specific causes: exemplified by chlorinated phenols and chlorophenoxy acids. , 1984, Regulatory toxicology and pharmacology : RTP.

[75]  S. Norton,et al.  Framework for ecological risk assessment , 1992 .

[76]  Leon Metzeling,et al.  Can the Detection of Salinity and Habitat Simplification Gradients using Rapid Bioassessment of Benthic Invertebrates be Improved through Finer Taxonomic Resolution or Alternative Indices? , 2006, Hydrobiologia.

[77]  Young-Seuk Park,et al.  Patternizing communities by using an artificial neural network , 1996 .

[78]  Andrea Critto,et al.  Decision Support Systems for Risk-Based Management of Contaminated Sites , 2009 .

[79]  Werner Brack,et al.  Introduction: The Need for Risk-Informed River Basin Management , 2014 .

[80]  Matthias Liess,et al.  Thresholds for the effects of pesticides on invertebrate communities and leaf breakdown in stream ecosystems. , 2012, Environmental science & technology.

[81]  J. Metcalfe-Smith,et al.  Biological Water‐Quality Assessment of Rivers: Use of Macroinvertebrate Communities , 2009 .

[82]  Werner Brack,et al.  Risk-Informed Management of European River Basins , 2014 .

[83]  Werner Brack,et al.  Water quality indices across Europe--a comparison of the good ecological status of five river basins. , 2007, Journal of environmental monitoring : JEM.

[84]  V. G. Sigillito,et al.  Classifying soil structure using neural networks , 1996 .

[85]  Dick de Zwart,et al.  Diagnosis of Ecosystem Impairment in a Multiple-Stress Context—How to Formulate Effective River Basin Management Plans , 2009, Integrated environmental assessment and management.

[86]  K. Rose,et al.  Patterns of Life-History Diversification in North American Fishes: implications for Population Regulation , 1992 .

[87]  M. Gevrey,et al.  Review and comparison of methods to study the contribution of variables in artificial neural network models , 2003 .

[88]  G. Allen Burton,et al.  Weight-of-Evidence Approaches for Assessing Ecosystem Impairment , 2002 .

[89]  Glenn W. Suter,et al.  Decision Support Systems (DSSs) for Inland and Coastal Waters Management – Gaps and Challenges , 2009 .

[90]  M. Liess,et al.  Analyzing effects of pesticides on invertebrate communities in streams , 2005, Environmental toxicology and chemistry.

[91]  G. Schüürmann,et al.  Ecotoxicology : ecological fundamentals, chemical exposure, and biological effects , 1998 .

[92]  Sabine E. Apitz Managing Ecosystems: The Importance of Integration , 2008 .

[93]  D. de Zwart,et al.  Complex mixture toxicity for single and multiple species: Proposed methodologies , 2005, Environmental toxicology and chemistry.

[94]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[95]  I. Dimopoulos,et al.  Application of neural networks to modelling nonlinear relationships in ecology , 1996 .