Community structure and restoration of ecosystems - Predicting Aquatic Ecosystems Quality using Artificial Neural Networks

Title:

Resource Type:

document --> technical publication --> book / book chapter(s)

Country:

EU Projects

Year of publication:

2003

Availability:

Paequann Consortium,Book «Community structure and restoration of ecosystems»

Author 1/Producer:

Paequann Consortium

Author / Producer Type:

EC Project

Report / download web link (=direct link):

http://aquaeco.ups-tlse.fr/index2.htm

EUGRIS Keyword(s):

Sediments
Water and sanitation-->Water and sanitation Overview
Water resources and their management -->Water resources and their management Overview

Long description:

This book focuses on modelling applications in aquatic community ecology, with special reference to those that have been recently developed on the basis of Artificial Intelligence techniques and in particular using Artificial Neural Networks in the PAEQANN project. It will include a short general overview of the State-of-the Art on aquatic community studies for ecosystem management and an introduction to Artificial Neural Networks theory. It will also present several applications, in many cases based on the outcomes of ongoing EU projects, focusing on different groups of organisms. In fact, most of the presented applications will be aimed at predicting the community composition for those groups of organisms that are mentioned in the EU directive 60/2000 and that will be used as benchmarks for evaluating the environmental quality. Different chapters will also address specific issues in community studies (pattern recognition, classification, diagnosis and monitoring, etc.). A CD-Rom illustrating the use of these modern modelling techniques will be included in the book. The aim of this book is to present approaches and methodologies for predicting structure and diversity of key aquatic communities (namely diatoms, benthic macroinvertebrates and fish), under natural conditions and under man-made disturbance. Such an approach will make it possible to: i) set up robust and sensitive ecosystem evaluation procedures, based on the prediction of the expected community structure; ii) modelling community structure in disturbed ecosystems, taking into account all relevant ecological variables; iii) test ecosystem sensitivity to natural and anthropic disturbance; iv) explore specific actions to be taken for restoration of ecosystem integrity.

Link to Project(s):

PAEQANN Predicting Aquatic Ecosystem Quality using Artificial Neural Networks: Impact of Environmental characteristics on the Structure of Aquatic Communities (Algae, Benthic and Fish Fauna).

Submitted By:

Dr Stefan Gödeke WhoDoesWhat? Last update: 27/09/2006