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.
Autorentext
Nathaniel K Newlands
Zusammenfassung
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.
Inhalt
Sustaining Our Ecosystems
Risk and Our Sustainable Future
Building Adaptive Capacity and Opportunity
Sustainability Assessment Frameworks, Metrics, Indicators
A Planet Under Pressure
The Rise of Anthromes
Stressed Ecosystems
Pertubed Cycles
Harmful Emissions
Depletion of Finite Resources
Crop Yield Gaps, Food Losses and Wastes
Future Sustainable Development Pathways
Modelling Complex, Adaptive Systems
Systems Theory and Consilience
Complex, Adaptive Systems (CAS)
Alternative Approaches, Models, Uses
Real-World Application of Integrated Methods
Perspective
Ecosystem Observation, Experimentation and Modelling
Geospatial Intelligence and Planning
Integrating Causality
Statistical Attributes of Integrated Risk
Stochastic Sustainability
Cumulative Impacts and Sensitive Trade-offs
Future Outlook
Perspective
Transformation Paths and Transition Dynamics
Causality and Forecasting
Adaptive Science, Policy and Institutions
Public Good Science
Super-Intelligent, Sustainability Tools
Acronyms
Glossary
Author Index
Subject Index
Bibliography