Nathaniel K. Newlands – författare
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5 produkter
5 produkter
865 kr
Skickas inom 10-15 vardagar
Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem, social, and infrastructure resilience, given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies.This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation, climate modeling, and long-term prediction; approach the problems of increasing frequency of extreme events, sea level rise, and forest fires, as well as economic losses, analysis of climate impacts for insurance, agriculture, fisheries, and electric and transport infrastructures. The reader will be exposed to the current research using a variety of methods from physical modeling, statistics, and machine learning, including the global circulation models (GCM) and ocean models, statistical generalized additive models (GAM) and generalized linear models (GLM), state space and graphical models, causality networks, Bayesian ensembles, a variety of index methods and statistical tests, and machine learning methods. The reader will learn about data from various sources, including GCM and ocean model outputs, satellite observations, and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.
2 187 kr
Skickas inom 10-15 vardagar
Evaluating Climate Change Impacts discusses assessing and quantifying climate change and its impacts from a multi-faceted perspective of ecosystem, social, and infrastructure resilience, given through a lens of statistics and data science. It provides a multi-disciplinary view on the implications of climate variability and shows how the new data science paradigm can help us to mitigate climate-induced risk and to enhance climate adaptation strategies.This book consists of chapters solicited from leading topical experts and presents their perspectives on climate change effects in two general areas: natural ecosystems and socio-economic impacts. The chapters unveil topics of atmospheric circulation, climate modeling, and long-term prediction; approach the problems of increasing frequency of extreme events, sea level rise, and forest fires, as well as economic losses, analysis of climate impacts for insurance, agriculture, fisheries, and electric and transport infrastructures. The reader will be exposed to the current research using a variety of methods from physical modeling, statistics, and machine learning, including the global circulation models (GCM) and ocean models, statistical generalized additive models (GAM) and generalized linear models (GLM), state space and graphical models, causality networks, Bayesian ensembles, a variety of index methods and statistical tests, and machine learning methods. The reader will learn about data from various sources, including GCM and ocean model outputs, satellite observations, and data collected by different agencies and research units. Many of the chapters provide references to open source software R and Python code that are available for implementing the methods.
717 kr
Skickas inom 10-15 vardagar
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.
1 304 kr
Skickas inom 10-15 vardagar
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.
1 486 kr
Skickas inom 10-15 vardagar
The world will likely exceed 9 billion people by 2050 and is unlikely to stabilize in the 21st century, requiring 70–100% more food production, while an increasing number of countries are reaching alarming levels of water scarcity. Water for irrigation and food production constitutes one of the greatest pressures on freshwater resources. Agriculture accounts for around 70% of global freshwater withdrawals (up to 90% in some fast-growing economies), impacting environmental flows, downstream access to water, groundwater levels, and reducing the extent and functions of wetlands including the ecological functions of biodiversity, nutrient retention, and flood control. Agriculture is also one of the largest contributors to non-point source pollution. Rapid population growth combined with changing diets due to increased income levels will likely result in an 70% increase in food demand by 2050. Urbanization will also concentrate the portions of populations needing meat, dairy products, and processed food.The corona pandemic has ravaged economies, lives, livelihoods, availability, affordability, and access to food the world over. Its negative consequences will likely escalate and spread widely. Invigorating urban food systems is seen as a feasible and necessary strategy to mitigate the many negative consequences of the pandemic by strengthening community resilience buttressed by environmentally friendly programs. Agriculture and Agri-Food Canada (AAFC, Government of Canada) and The Food and Agriculture Organization of the United Nations (UN-FAO) bring together a distinguished group of authors to analyse and prescribe policies and measures that can effectively meet and sustain the sustainable development goals not only in the area of food security, but also in several areas within the nexus of food, energy, green economy and health.The book provides a synthesis of perspectives, knowledge, and insights within the urban-food-water nexus. Each chapter guides reads through the complex nexus landscape citing a wide body of recent, relevant literature sources (print and open access, online) for readers. Literature sources include peer-reviewed journal publications, books, as well as governmental and UN reports.