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 of Ecological Model Types will cover both process-based models and data-driven models which are fundamental and popular in ecological modelling studies with theories and applications. It will also explain how ecological modelling 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.
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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