Machine Learning For Ecology And Sustainable Natural Resource Management
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Machine Learning for Ecology and Sustainable Natural Resource Management
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.
Climate Impacts on Sustainable Natural Resource Management
CLIMATE IMPACTS ON SUSTAINABLE NATURAL RESOURCE MANAGEMENT Climate change has emerged as one of the predominant global concerns of the 21st century. Statistics show that the average surface temperature of the Earth has increased by about 1.18°C since the late 19th century and the sea levels are rising due to the melting of glaciers. Further rise in the global temperature will have dire consequences for the survival of humans on the planet Earth. There is a need to monitor climatic data and associated drivers of changes to develop sustainable planning. The anthropogenic activities that are linked to climate change need scientific evaluation and must be curtailed before it is too late. This book contributes significantly in the field of sustainable natural resource management linked to climate change. Up to date research findings from developing and developed countries like India, Indonesia, Japan, Malaysia, Sri Lanka and the USA have been presented through selected case studies covering different thematic areas. The book has been organised into six major themes of sustainable natural resource management, determinants of forest productivity, agriculture and climate change, water resource management and riverine health, climate change threat on natural resources, and linkages between natural resources and biotic-abiotic stressors to develop the concept and to present the findings in a way that is useful for a wide range of readers. While the range of applications and innovative techniques is constantly increasing, this book provides a summary of findings to provide the updated information. This book will be of interest to researchers and practitioners in the field of environmental sciences, remote sensing, geographical information system, meteorology, sociology and policy studies related to natural resource management and climate change.
Sustainable Squirrel Conservation
This book attempts to move the family of squirrels (Sciuridae) out of the shadow of large charismatic mammals and to highlight management failures with the goal of moving towards an improved conservation approach. Particular attention is paid to the influence of taxonomic science on squirrel conservation. In addition, the authors show how human-driven climate change, global change and modern politics are shaping global squirrel populations as well as their surrounding environments and ecosystems. Squirrels are widespread around the globe, naturally occurring on every continent except Antarctica and Oceania, and they are certainly among the animals most commonly encountered in everyday life. Despite this, the authors of this volume identify worrying gaps in squirrel conservation. Squirrels are often hunted, trapped, poached, and stressed, and management strategies and legislation are often devised in the absence of proper knowledge of issues such as population sizes, taxonomies, and trends. Together, this can result in severe population declines and even species extinction. By assessing their taxonomic situation, ecology, the evolution and divergence of Sciuridae around the globe, and squirrels’ well-being across habitats, the authors set a baseline from which to launch future investigations into the conservation of squirrels and other species. Additionally, the authors highlight the influences of climate change, unsustainable growth, and various man-made threats to the future of this family.