Description
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.- Discusses modelling theory and application- Illustrates process-based models as well as machine learning models- Explains practical guides to apply models
Table of Contents
1. Introduction: An OverviewSection 1: Process-based models2. Biogeochemical models3. Dynamic Population Models4. Ecotoxicological Models5. Structurally Dynamic Models (SDMs)6. Steady State Models7. Spatially Explicit Models8. Fugacity Models9. Network model: Econet10. Process-based Modelling in EcologySection 2: Data-driven models11. Artificial Neural Networks (Multilayer Perceptron) in Ecology12. Decision Tree Models13. Ensemble Models14. Support Vector Machines for Ecological Modelling15. Deep learning: Long short-term memory networks16. Automated Machine Learning
