VIII
Preface
3 Vollenweider RA (1968) Scientific fundamentals of eutrophication of lakes and flowing
waters with special reference to phosphorus and nitrogen. OECD, Paris.
OECDIDAS/SCII68.27
4 Straskraba M, Gnauck A (1985) Freshwater Ecosystems: Modelling and Simulation.
Elsevier, Amsterdam
5 Park RA, O'Neill RV, Bloomfield JA, Shugart HH, Booth RS, Goldstein RA, Mankin JB,
Koonce JF, Scavia D, Adams MS, Clesceri LS, Colon EM, Dettman EH, Hoopes JA,
Huff DD, Katz S, Kitchell JF, Koberger RC, La Row EJ, McNaught DC, Petersohn L,
Titus JE, Weiler PR, Wilkinson JW, Zahorcak CS (1974) A generalized model for
simulating lake ecosystems. Simulation 33-50
6Bierman VJ (1976) Mathematical model of the selective enhancement of blue-green algae
by nutrient enrichment. In: Canale RP (eds) Modelling Biochemical Processes in
Aquatic Ecosystems. Ann Arbour Science Publishers Inc., Ann Arbour, 1-32
7 Jorgensen SE (1976) A eutrophication model for a lake. Ecol. Modelling 2, 147-162
8 Recknagel F, Benndorf J (1982) Validation of the ecological simulation model SALMO.
Int. Revue Ges.Hydrobiol. 67, 1, 113-125
9 Lek S, Delacoste M, Baran P, Dimonopoulos I, Lauga J, Aulagnier J (1996) Application
of neural networks to modelling nonlinear relationships in ecology. Ecol. Modelling
90,39-52
10 Chon TS, Park YS, Moon KR, Cha EY (1996) Pattemizing communities by using
artificial neural network. Ecol. Modelling 90, 69-78
II Recknagel F, Petzoldt T, Jaeke 0, Krusche F (1995). Hybrid expert system DELAQUA -
a toolkit for water quality control oflakes and reservoirs. Ecol. Modelling 71, 1-3, 1736
12 Recknagel F (1997) ANNA - artificial neural network model predicting species
abundance and succession of blue-green algae. Hydrobiologia, 349, 47-57
l' Bobbin J, Recknagel F (2001) Knowledge discovery for prediction and explanation of
blue-green algal dynamics in lakes by evolutionary algorithms. Ecol. Modelling 146,
1-3,253-264
14 Whigham P, Recknagel F (2001) An inductive approach to ecological time series
modelling by evolutionary computation. Ecol. Modelling 146, 1-3,275-287
15 Whigham P, Recknagel F (2001) Predicting chlorophyll-a in freshwater lakes by
hybridising process-based models and genetic algorithms. Ecol. Modelling 146, 1-3,
243-251
16 Holland JH (1992) Adaptation in Natural and Artificial Systems. Addison-Wesley, New
York
17 Booth G (1997) Gecko: A continuous 2-D world for ecological modeling. Artif. Life 3,
147-163
The present book focuses on the computational approach for ecosystems
analysis, synthesis and forecasting called ecological informatics. It provides the
scope and case studies of ecological informatics exemplary for applications of
biologically-inspired computation to a variety of areas in ecology.
Ecological Informatics is defined as interdisciplinary framework promoting the
use of advanced computational technology for the elucidation of principles of
information processing at and between all levels of complexity of ecosystems -
from genes to ecological networks -, and the provision of transparent decisions
targeting ecological sustainability, biodiversity and global warming.
Preface
3 Vollenweider RA (1968) Scientific fundamentals of eutrophication of lakes and flowing
waters with special reference to phosphorus and nitrogen. OECD, Paris.
OECDIDAS/SCII68.27
4 Straskraba M, Gnauck A (1985) Freshwater Ecosystems: Modelling and Simulation.
Elsevier, Amsterdam
5 Park RA, O'Neill RV, Bloomfield JA, Shugart HH, Booth RS, Goldstein RA, Mankin JB,
Koonce JF, Scavia D, Adams MS, Clesceri LS, Colon EM, Dettman EH, Hoopes JA,
Huff DD, Katz S, Kitchell JF, Koberger RC, La Row EJ, McNaught DC, Petersohn L,
Titus JE, Weiler PR, Wilkinson JW, Zahorcak CS (1974) A generalized model for
simulating lake ecosystems. Simulation 33-50
6Bierman VJ (1976) Mathematical model of the selective enhancement of blue-green algae
by nutrient enrichment. In: Canale RP (eds) Modelling Biochemical Processes in
Aquatic Ecosystems. Ann Arbour Science Publishers Inc., Ann Arbour, 1-32
7 Jorgensen SE (1976) A eutrophication model for a lake. Ecol. Modelling 2, 147-162
8 Recknagel F, Benndorf J (1982) Validation of the ecological simulation model SALMO.
Int. Revue Ges.Hydrobiol. 67, 1, 113-125
9 Lek S, Delacoste M, Baran P, Dimonopoulos I, Lauga J, Aulagnier J (1996) Application
of neural networks to modelling nonlinear relationships in ecology. Ecol. Modelling
90,39-52
10 Chon TS, Park YS, Moon KR, Cha EY (1996) Pattemizing communities by using
artificial neural network. Ecol. Modelling 90, 69-78
II Recknagel F, Petzoldt T, Jaeke 0, Krusche F (1995). Hybrid expert system DELAQUA -
a toolkit for water quality control oflakes and reservoirs. Ecol. Modelling 71, 1-3, 1736
12 Recknagel F (1997) ANNA - artificial neural network model predicting species
abundance and succession of blue-green algae. Hydrobiologia, 349, 47-57
l' Bobbin J, Recknagel F (2001) Knowledge discovery for prediction and explanation of
blue-green algal dynamics in lakes by evolutionary algorithms. Ecol. Modelling 146,
1-3,253-264
14 Whigham P, Recknagel F (2001) An inductive approach to ecological time series
modelling by evolutionary computation. Ecol. Modelling 146, 1-3,275-287
15 Whigham P, Recknagel F (2001) Predicting chlorophyll-a in freshwater lakes by
hybridising process-based models and genetic algorithms. Ecol. Modelling 146, 1-3,
243-251
16 Holland JH (1992) Adaptation in Natural and Artificial Systems. Addison-Wesley, New
York
17 Booth G (1997) Gecko: A continuous 2-D world for ecological modeling. Artif. Life 3,
147-163
The present book focuses on the computational approach for ecosystems
analysis, synthesis and forecasting called ecological informatics. It provides the
scope and case studies of ecological informatics exemplary for applications of
biologically-inspired computation to a variety of areas in ecology.
Ecological Informatics is defined as interdisciplinary framework promoting the
use of advanced computational technology for the elucidation of principles of
information processing at and between all levels of complexity of ecosystems -
from genes to ecological networks -, and the provision of transparent decisions
targeting ecological sustainability, biodiversity and global warming.