Nutrient Indicator Models for Determining Biologically Relevant Levels: A case study based on the Corn Belt and Northern Great Plain Nutrient Ecoregion (SpringerBriefs in Environmental Science)

Morris, Charles Clarence, Simon, Thomas Paul

ISBN 10: 9400741286 / ISBN 13: 9789400741287

Verlag: Springer, 2012

Beschreibung

Like New.

Bestandsnummer des Verkäufers ERICA78794007412866

Bibliografische Details

• Titel: Nutrient Indicator Models for Determining Biologically Relevant Levels: A case study based on the Corn Belt and Northern Great Plain Nutrient Ecoregion (SpringerBriefs in Environmental Science)
• Verlag: Springer
• Erscheinungsjahr: 2012
• Sprache: Englisch
• ISBN-10: 9400741286
• ISBN-13: 9789400741287
• Einband: Paperback
• Zustand: Like New
• Buchtyp: book

Über diesen Titel

Inhaltsangabe

The first publication to provide strategies for managing nutrients in the context of changing environmental biology, this text describes in detail a case study resulting from a large-scale research project in the Corn Belt and Great Plains region of America.

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Nutrient Indicator Models for Determining Biologically Relevant Levels: A case study based on the Corn Belt and Northern Great Plain Nutrient Ecoregion is the first book to provide answers to the management of nutrients based on changes in biological communities. The text describes a case study that is the result of a large scale project in the Corn Belt and Great Plains Nutrient Ecoregion. This study is the first to identify relationships between fish assemblages and nutrient concentrations by Nitrogen species. Species optima based on sensitvity and tolerance to nutrients is modeled. Nutrient Biotic indices calibrated for application are based on the results of years of biological indicator development. Test response intervals and Shift response intervals are formulated and validated against relevant biological assemblage shifts. This case study is the first to suggest recommended values for the nitrogen and phosphorus cycle with identifiable shifts caused in biological assemblages. This will provide watershed and environmental managers with the information needed to manage the inputs into the world s dead zones.