Ecological Model Types: Theories and Applications

by Elsevier Science, Sovan Lek (Editor)

Overview

Ecological Model Types: Theories and Applications, Second Edition presents an understanding of how to quantitatively analyze complex and dynamic ecosystems with the tools available today. Recently, besides process-based models, data driven models such as machine learning methods are popularly applied in ecological and environmental models. This second edition covers both process-based models and data-driven models which are fundamental and popular in ecological modeling studies with theories and applications. It also explains how ecological modeling can assist the implementation of sustainable development as well as how mathematical models and systems analysis can describe ecological processes, which can support sustainable management of resources.

Product Details

ISBN-13:	9780443363047
Publisher:	Elsevier Science
Publication date:	11/01/2025
Series:	Developments in Environmental Modelling
Edition description:	2nd ed.
Pages:	470
Product dimensions:	7.50(w) x 9.25(h) x 0.00(d)

About the Author

Young-Seuk Park is a Professor at the Department of Biology, Kyung University, Seoul, Republic of Korea. After completing a PhD at Pusan National University, he undertook post-doctoral research at CNRS, Université Paul Sabatier, and Cemagraf in France, and he obtained an HDR (Habilitation à Diriger des Recherches / Accreditation to Supervise Research) from the Université Paul Sabatier in Toulouse, France, before returning Korea to establish his independent reseach group at Kyung Hee University. His laboratory studies the effects of environmental changes on biological systems at different hierarchical levels from molecules, individuals, populations, and communities through ecological modelling and ecological informatics approaches. In particular, his research is focused on the effects of global changes on ecosystems, and ecological monitoring and assessment for sustainable ecosystem management. He is interested in computational approaches such as machine learning techniques and advanced statistical methods. He is an associate editor of two scientific journals Annales de Limnologie – International Journal of Limnology and Journal of Ecology and Environment, and he is also on the editorial boards of several journals including Ecological Informatics and Animal Cells and Systems. He was a guest editor for several Special Issues in scientific journals including Ecological Modelling, Ecological Informatics, Annales de Limnologie – International Journal of Limnology, Inland Waters, and Water. He is the recipient of the 2014 Yeocheon Ecology Award.

Sovan Lek is a Professor at the University of Toulouse. His research is mainly in Fish Community Ecology and Ecological Modelling.

In Fish Community Ecology, his research concerns the biodiversity and the spatial distribution of fish according to the environmental characteristics and the response of fish community to the human disturbances, especially land-use, hydromorphology, climate warming. The distribution of fish is considered according to the scale of variation, varying from local to regional and global scales, in relationship with the environmental variables.

In Ecological Modelling, he is mainly interested in the use of machine learning techniques. He is also familiar with the uses of classical modelling techniques like classical statistic methods (multiple linear regression, multi-variate analyses ) and modern statistical methods (CART, GAM, PLS ).

He has participated in several EU projects in the fields of Ecology and Global changes. He also participated in bilateral projects with several Asian countries. He is an editorial member of Ecological Modelling and associate editor of Ecological Informatics.

Table of Contents

1. Introduction: An overview Part I: Process-based models
2. Biocheochemical models
3. Dyanmic population model
4. Structurally Dynamic Models (SDMs)
5. Ecotoxicological Models
6. Biogeochemical Models
7. Steady State Models
8. Individual based model
9. Fugacity Models
10. Earth's surface model
11. Coastal Ecosystem Modeling in the Context of Climate Change An Overview With Case Studies
12. Network model: Econet Part II: Data-driven models
13. Artificial Neural Networks Multilayer Perceptron for Ecological Modelling
14. Tree-based models
15. Support vector machines
16. Deep learning
17. Ensemble modelling
18. Species distribution models
19. Ecological models in aquatic ecosystems

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From the Publisher

Explains both process-based and data-driven models within ecological modelling