The use of environmental assessment procedures within monitoring frameworks demands that there be some relevancy to the decisions that management agencies make using biological criteria. These biological criteria standards are the basis for environmental indicators, which provide a direct measure of environmental quality. Biological Response Signat

Biological Assessment and Criteria presents a state-of-the-art overview of the applications of biological assessments and biocriteria for water quality management in fresh waters. The book presents case studies which illustrate how bioassessment has been used to identify and diagnose water quality problems. It also provides examples of the use of qualitative and quantitative biocriteria as regulatory tools to complement water quality criteria and standards. The first book to present the technical foundation, rationale, program and policy relevance, and legal basis for the most accurate tools used to assess freshwater natural resource and regulatory efforts, this book provides useful and timely information for water quality managers.

This unique textbook takes a broad look at the rapidly expanding field of freshwater microbiology. Concentrating on the interactions between viruses, bacteria, algae, fungi and micro-invertebrates, the book gives a wide biological appeal. Alongside conventional aspects such as phytoplankton characterisation, seasonal changes and nutrient cycles, the title focuses on the dynamic and applied aspects that are not covered within the current textbooks in the field. Complete coverage of all fresh water biota from viruses to invertebrates Unique focus on microbial interactions including coverage of biofilms, important communities on all exposed rivers and lakes. New information on molecular and microscopical techniques including a study of gene exchange between bacteria in the freshwater environment. Unique emphasis on the applied aspects of freshwater microbiology with particular emphasis on biodegradation and the causes and remediation of eutrophication and algal blooms.

The field of ecosystem health explores the interactions between natural systems, human health, and social organization. As decision makers require a sound, modular approach to environmental management and sustainable development, ecosystem health assessment indicators are increasingly used across any number of applications. The Handbook of Ecologic

In the hierarchical river system, any deviation from the pristine state will be translated into disturbances that propagate and eventually reach its endpoints (i.e. the biologic community). Endpoints are indicative of the overall health or integrity of a water body. Integrity is usually measured with multi-metric indices that compare actual observations to reference scenarios. Despite strong agreement among experts about the importance of biological indicators, development of numeric biological standards similar to those used for water quality remains uncertain for several reasons: (1) the natural system is composed of highly intertwined and cross-correlated variables. Identification of simple stress-response relationships is not often possible; (2) the natural system is organized in a nested hierarchy of suitable habitats with very different geographic scales; (3) many environmental variables have a categorical evaluation, which introduces subjectivity and relativity into the system ; (4) true reference conditions may no longer exist; and (5) natural randomness. In order to address these issues, an attempt to predict or characterize biologic integrity was performed. In the first section, fish Indices of Biologic Integrity (IBI) were predicted using the K-nearest neighbor concept (KNN). This methodology was used because it allows a fast, step-wise approach easily implemented with highly dimensional environmental vectors. The KNN concept was tested with databases in Maryland, Ohio, and Minnesota. Subsequently, a slightly modified version of the algorithm was tested with a new database in Ohio which combined instream and offtstream features improving the results significantly. The second section consisted of a progressive, hierarchical separation of biological responses using Self-Organizing Maps (SOM) and subsequent clustering of sites using one environmental variable at a time in decreasing order of importance. This methodology attempted to replicate the nested hierarchy of habitats in nature. The biologic responses were characterized using a Gaussian probabilistic curve because it was assumed that IBI was a projection of the log-normal distribution of species onto an arithmetic scale. The best sites in each group were considered as truly reference conditions and compared to the remaining sites within the group. This was applied in Ohio (with only instream or only offstream data) and Maryland (instream and offstream data combined).