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Future Sustainable Ecosystems: Complexity, Risk, and Uncertainty
Barnes and Noble
Future Sustainable Ecosystems: Complexity, Risk, and Uncertainty
Current price: $61.99
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Barnes and Noble
Future Sustainable Ecosystems: Complexity, Risk, and Uncertainty
Current price: $61.99
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Future Sustainable Ecosystems: Complexity, Risk, Uncertainty
provides an interdisciplinary, integrative overview of environmental problem-solving using statistics. It shows how statistics can be used to solve diverse environmental and socio-economic problems involving food, water, energy scarcity, and climate change risks.
It synthesizes
interdisciplinary theory, concepts, definitions, models and findings involved in
complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership.
Discussions include a broad, integrated perspective on sustainability, integrated risk, multi-scale changes and impacts taking place within ecosystems worldwide. State-of-the-art statistical techniques, including Bayesian hierarchical, spatio-temporal, agent-based and game-theoretic approaches are explored. The author then focuses on the real-world integration of observational and experimental data and its use within statistical models.
provides an interdisciplinary, integrative overview of environmental problem-solving using statistics. It shows how statistics can be used to solve diverse environmental and socio-economic problems involving food, water, energy scarcity, and climate change risks.
It synthesizes
interdisciplinary theory, concepts, definitions, models and findings involved in
complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership.
Discussions include a broad, integrated perspective on sustainability, integrated risk, multi-scale changes and impacts taking place within ecosystems worldwide. State-of-the-art statistical techniques, including Bayesian hierarchical, spatio-temporal, agent-based and game-theoretic approaches are explored. The author then focuses on the real-world integration of observational and experimental data and its use within statistical models.