Renewable Energy and Wildlife Conservation

Renewable Energy and Wildlife Conservation

Author: Christopher E. Moorman

Publisher: JHU Press

Published: 2019-09-10

Total Pages: 279

ISBN-13: 1421432730

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Brings together disparate conversations about wildlife conservation and renewable energy, suggesting ways these two critical fields can work hand in hand. Renewable energy is often termed simply "green energy," but its effects on wildlife and other forms of biodiversity can be quite complex. While capturing renewable resources like wind, solar, and energy from biomass can require more land than fossil fuel production, potentially displacing wildlife habitat, renewable energy infrastructure can also create habitat and promote species health when thoughtfully implemented. The authors of Renewable Energy and Wildlife Conservation argue that in order to achieve a balanced plan for addressing these two crucially important sustainability issues, our actions at the nexus of these fields must be directed by current scientific information related to the ecological effects of renewable energy production. Synthesizing an extensive, rapidly growing base of research and insights from practitioners into a single, comprehensive resource, contributors to this volume • describe processes to generate renewable energy, focusing on the Big Four renewables—wind, bioenergy, solar energy, and hydroelectric power • review the documented effects of renewable energy production on wildlife and wildlife habitats • consider current and future policy directives, suggesting ways industrial-scale renewables production can be developed to minimize harm to wildlife populations • explain recent advances in renewable power technologies • identify urgent research needs at the intersection of renewables and wildlife conservation Relevant to policy makers and industry professionals—many of whom believe renewables are the best path forward as the world seeks to meet its expanding energy needs—and wildlife conservationists—many of whom are alarmed at the rate of renewables-related habitat conversion—this detailed book culminates with a chapter underscoring emerging opportunities in renewable energy ecology. Contributors: Edward B. Arnett, Brian B. Boroski, Regan Dohm, David Drake, Sarah R. Fritts, Rachel Greene, Steven M. Grodsky, Amanda M. Hale, Cris D. Hein, Rebecca R. Hernandez, Jessica A. Homyack, Henriette I. Jager, Nicole M. Korfanta, James A. Martin, Christopher E. Moorman, Clint Otto, Christine A. Ribic, Susan P. Rupp, Jake Verschuyl, Lindsay M. Wickman, T. Bently Wigley, Victoria H. Zero


Community Management of Natural Resources in Africa

Community Management of Natural Resources in Africa

Author: Dilys Roe

Publisher: IIED

Published: 2009

Total Pages: 207

ISBN-13: 1843697556

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Provides a pan-African synthesis of community-based natural resource management (CBNRM), drawing on multiple authors and a wide range of documented experiences from Southern, Eastern, Western and Central Africa. This title discusses the degree to which CBNRM has met poverty alleviation, economic development and nature conservation objectives.


Energy Cooperation in South Asia

Energy Cooperation in South Asia

Author: Mirza Sadaqat Huda

Publisher: Routledge

Published: 2021-12-13

Total Pages: 208

ISBN-13: 9781032236926

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This book analyses the key political challenges to regional energy cooperation in South Asia. It will be of great interest to students and scholars of energy security and geopolitics, natural resource governance and South Asian politics.


Sustainable Utilization of Natural Resources

Sustainable Utilization of Natural Resources

Author: Prasenjit Mondal

Publisher: CRC Press

Published: 2017-03-16

Total Pages: 624

ISBN-13: 1498761844

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Increased research is going on to explore the new cleaner options for the utilization of natural resources. This book aims to provide the scientific knowhow and orientation in the area of the emerging technologies for utilization of natural resources for sustainable development to the readers. The book includes production of energy and lifesaving drugs using natural resources as well as reduction of wastage of resources like water and energy for sustainable development in both technological as well as modeling aspects.


Handbook of the International Political Economy of Energy and Natural Resources

Handbook of the International Political Economy of Energy and Natural Resources

Author: Andreas Goldthau

Publisher: Edward Elgar Publishing

Published: 2018-01-26

Total Pages: 417

ISBN-13: 1783475633

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This Handbook offers a comprehensive overview of the latest research from leading scholars on the international political economy of energy and resources. Highlighting the important conceptual and empirical themes, the chapters study all levels of governance, from global to local, and explore the wide range of issues emerging in a changing political and economic environment.


Machine Learning for Ecology and Sustainable Natural Resource Management

Machine Learning for Ecology and Sustainable Natural Resource Management

Author: Grant Humphries

Publisher: Springer

Published: 2018-11-05

Total Pages: 442

ISBN-13: 3319969781

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Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.