This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.

Part I: Introduction; Part II: Valuation of ecosystem services and biophysical indicators of NRM impacts; Part III: Methodological advances for a comprehensive impact assessment; Part IV: NRM impact assessment in practice.

Indigenous Knowledge (IK) reviews cutting-edge research and links theory with practice to further our understanding of this important approach's contribution to natural resource management. It addresses IK's potential in solving issues such as coping with change, ensuring global food supply for a growing population, reversing environmental degradation and promoting sustainable practices. It is increasingly recognised that IK, which has featured centrally in resource management for millennia, should play a significant part in today's programmes that seek to increase land productivity and food security while ensuring environmental conservation. An invaluable resource for researchers and postgraduate students in environmental science and natural resources management, this book is also an informative read for development practitioners and undergraduates in agriculture, forestry, geography, anthropology and environmental studies.

For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate. More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face. Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030).

To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. Statistics in Natural Resources: Applications with R focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines. This is a book well suited for current or aspiring natural resource professionals who are required to analyze data and perform statistical analyses in their daily work. More seasoned professionals who have previously had a course or two in statistics will also find the content familiar. This text can also serve as a bridge between professionals who understand statistics and want to learn how to perform analyses on natural resources data in R. The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. If you dedicate considerable time to this book, you will: Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data. Become competent in importing, analyzing, and visualizing complex data sets in the R environment. Recode, combine, and restructure data sets for statistical analysis and visualization. Appreciate probability concepts as they apply to environmental problems. Understand common distributions used in statistical applications and inference. Summarize data effectively and efficiently for reporting purposes. Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results. Understand which modeling frameworks are appropriate for your data and how to interpret predictions. Includes over 130 exercises in R, with solutions available on the book’s website.

This book presents possible solutions for a circuler economy (CE) in the water and wastewater sector through an inventory of multidisciplinary knowledge with high scientific and practical importance which can contribute to support the transition to the CE model in water and wastewater sector. Water in modern studies exceeds being an important source for irrigation and drinking. It is now a significant source of renewable energy and a catalyst in most industrial and manufacturing products. The protection and sustainable management of water resources and water-based waste (as wastewater, sewage sludge, or sewage sludge ash) are important aspects of the CE, which is defined as a regenerative growth model that gives back to the planet more than it takes. Our book, entitled "Water in Circular Economy", delivers a comprehensive overview of the latest research covering the following aspects of water management from the perspective of the CE implementation: · Water as a key resource in the circular economy; · Innovative solutions in transition to the circular economy in water and wastewater sector; · Monitoring of circular economy implementation in water and wastewater sector.

Data visualization has emerged as a serious scholarly topic, and a wide range of tools have recently been developed at an accelerated pace to aid in this research area. Examining different ways of analyzing big data can result in increased efficiency for many corporations and organizations. Data Visualization and Statistical Literacy for Open and Big Data highlights methodological developments in the way that data analytics is both learned and taught. Featuring extensive coverage on emerging relevant topics such as data complexity, statistics education, and curriculum development, this publication is geared toward teachers, academicians, students, engineers, professionals, and researchers that are interested in expanding their knowledge of data examination and analysis.

This book presents a comprehensive overview of a range of concepts, methods, strategies and policies in agriculture and natural resource management, environmental economics, production economics and sustainable agricultural development. It explores effective analytical tools and science, innovations, and management solutions to enhance yields, manage the supply chain, strengthen institutional mechanisms, and service and support systems for farmers. It highlights the importance of enabling policies which can benefit farmers, resulting in cost-efficient and quality-improving farm practices, increased profits and income for farmers, and better management of natural resources. The essays in the book honour the academic, teaching, and research contributions of Professor R. Ramanna in the field of agricultural economics. They also address issues which are relevant to the growing research in sustainable agricultural development and natural resource management including the use of new concepts, tools, analyses, technologies, innovations, and policy strategies modelled in local contexts that can easily be scaled and applied to similar contexts elsewhere. This book will be of interest and use to students, researchers, practitioners,and policymakers working in varied fields of agricultural economics, sustainable development, public policy, rural sociology, political economy, economics of innovation, institutional economics, and industrial organisation.