| 000 | 01959 a2200361 4500 | ||
|---|---|---|---|
| 001 | 131535666X | ||
| 005 | 20250317111611.0 | ||
| 008 | 250312042016xx 49 eng | ||
| 020 | _a9781315356662 | ||
| 037 |
_bTaylor & Francis _cGBP 45.99 _fBB |
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| 040 | _a01 | ||
| 041 | _aeng | ||
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_a577.82 _2bisac |
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| 100 | 1 | _aNathaniel K Newlands | |
| 245 | 1 | 0 |
_aFuture Sustainable Ecosystems _bComplexity, Risk, and Uncertainty |
| 250 | _a1 | ||
| 260 |
_bChapman and Hall/CRC _c20161003 |
||
| 300 | _a409 p | ||
| 520 | _bFuture 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. | ||
| 999 |
_c4942 _d4942 |
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