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Author: Grant Humphries
Publisher: Springer
ISBN: 3319969781
Category : Science
Languages : en
Pages : 442
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Book Description
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.
Author: Grant Humphries
Publisher: Springer
ISBN: 3319969781
Category : Science
Languages : en
Pages : 442
Get Book Here
Book Description
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.
Author: Moriz Steiner
Publisher: Springer Nature
ISBN: 3031235479
Category : Science
Languages : en
Pages : 380
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Book Description
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.
Author:
Publisher: Academic Press
ISBN: 0128146761
Category : Nature
Languages : en
Pages : 496
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Book Description
Tree Kangaroos: Science and Conservation, a volume in the Biodiversity of the World: Conservation from Genes to Landscapes series, provides an overview of tree kangaroo species and their relationship with humans. This exciting, interdisciplinary work on tree kangaroo science and conservation is divided into six major sections: (1) tree kangaroo evolution, genetics, taxonomy, ecology, behavior, and conservation status; (2) current and emerging threats to the species; (3) conservation programs in Australia and New Guinea with an emphasis on the human aspect of conservation; (4) the role of zoos in conservation solutions; (5) techniques and technologies to study this elusive marsupial; and (6) what is needed to keep tree kangaroos and their landscapes healthy in the future. The series on Biodiversity of the World: Conservation from Genes to Landscapes includes titles focused on specific species or taxa across disciplinary boundaries and spatial scales—from genes to landscapes. Volumes are edited and written by prominent scholars and practitioners to illuminate and advance biodiversity science and conservation. - Includes coverage of all known tree kangaroo species - Features contributions edited and written by the world's leading researchers and practitioners focusing on these scientifically mysterious marsupials - Provides accessible scientific and general information to a wide audience including students, academics, researchers, conservation professionals, policy makers, business leaders, zoo professionals, health professionals, and people interested in community-based conservation - Presents the current knowledge of tree kangaroos, helping to lay the foundations and best practices for future conservation and research in Australia and New Guinea
Author: Saeid Eslamian
Publisher: Elsevier
ISBN: 012821970X
Category : Technology & Engineering
Languages : en
Pages : 484
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Book Description
Classic Soft-Computing Techniques is the first volume of the three, in the Handbook of HydroInformatics series.? Through this comprehensive, 34-chapters work, the contributors explore the difference between traditional computing, also known as hard computing, and soft computing, which is based on the importance given to issues like precision, certainty and rigor. The chapters go on to define fundamentally classic soft-computing techniques such as Artificial Neural Network, Fuzzy Logic, Genetic Algorithm, Supporting Vector Machine, Ant-Colony Based Simulation, Bat Algorithm, Decision Tree Algorithm, Firefly Algorithm, Fish Habitat Analysis, Game Theory, Hybrid Cuckoo–Harmony Search Algorithm, Honey-Bee Mating Optimization, Imperialist Competitive Algorithm, Relevance Vector Machine, etc.?It is a fully comprehensive handbook providing all the information needed around classic soft-computing techniques. This volume is a true interdisciplinary work, and the audience includes postgraduates and early career researchers interested in Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources, and Chemical Engineering. - Key insights from global contributors in the fields of data management research, climate change and resilience, insufficient data problem, etc. - Offers applied examples and case studies in each chapter, providing the reader with real world scenarios for comparison. - Introduces classic soft-computing techniques, necessary for a range of disciplines.
Author: Emil Faure
Publisher: Springer Nature
ISBN: 3031718011
Category :
Languages : en
Pages : 521
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Book Description
Author: Falk Huettmann
Publisher: Springer Nature
ISBN: 3031202627
Category : Science
Languages : en
Pages : 705
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Book Description
This book aims to present a reality view for Papua New Guinea based on many years of first-hand field work and research accounts. It further assesses sustainability in the light of 47,000 years of a self-sustained type of civilization without bad global impacts. This book contrasts the modern sustainable development failures from the colonial times onwards, as promoted by the ‘western world’, namely Australia, the UK, EU and the U.S as well as Japan and now, China, in times of globalization, Trump’ism and royal governance (Papua New Guinea is still part of the British Dominion and of the Antarctic Treaty etc). This assessment and book is the first of its kind also employing modern data analysis, Landscape Ecology principles (patterns and processes, telecoupling) and Geographic Information Systems (GIS) with Open Access data focusing on ecological economics, marxism, socialism and contrasting it with current capitalism and neoliberalism that Papua New Guinea is fully exposed to. Throughout the 31 book chapters various aspects are covered how a further insistence on the ‘new’ Sustainable Development Goals (SDGs) and so-called Development Aid will result in unwanted side effects and perverse outcomes for Papua New Guinea and for the world in times of wider ‘global change’ and unprecedented man-made crisis.
Author: Eddie John Van Etten
Publisher: Frontiers Media SA
ISBN: 2832502431
Category : Science
Languages : en
Pages : 153
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Book Description
Author: Ilona Paweloszek
Publisher: CRC Press
ISBN: 1040152066
Category : Computers
Languages : en
Pages : 319
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Book Description
It is with great pleasure that I present to you the proceedings of our Recent Advances in Management and Engineering held on November 24 – 27, 2023 in Male. Maldives. This conference represents a milestone in our ongoing journey towards academic excellence where we aspire to become a renowned platform for the exchange of ideas, collaboration, networking, and learning. These proceedings contain contributions that are very amazing in innovations in management. It covers a wide range of issues, ranging from the most recent trends in business to innovations in fundamentals of management. A broad collection of scholars, practitioners, and thought leaders from four continents across the world worked together to produce these results, which are a reflection of their combined efforts.
Author: Ulrich Frey
Publisher: Oxford University Press
ISBN: 0197502237
Category : Nature
Languages : en
Pages : 335
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Book Description
What can be done to ensure natural resources aren't exploited? Is it possible to determine how to sustainably manage them? What makes some systems successful? In Sustainable Governance of Natural Resources, Ulrich Frey delves deep into unanswered questions like these about resource management. The book explains the current state of biological cooperation mechanisms, case studies in the field, findings from economic-behavioral experiments, common-pool resource dilemmas, and how these are all relevant to these questions surrounding the best way to sustainably manage natural resources. There are many case studies within the field of social-ecological systems, but there are few large-N studies conducted in a methodologically rigorous manner. Frey does just this and takes readers step-by-step through the preparation of datasets like the CPR, NIIS, and IFRI. He also grounds his research through the development of an indicator system which operationalizes 24 individually-synthesized success factors that influence the management of natural resources. The book reveals the practical and operational uses of measuring ecological success in this way, showcasing various statistical and machine learning methods to develop highly predictive, robust, and empirically-sound models. Three different methods, multivariate linear regressions, random forests, and artificial neural networks are compared to achieve robust results. The book sheds new light on factors that have previously been investigated, allowing readers to build off of Frey's system and use his methods to determine whether or not their way of managing natural resources will yield ecological success in practice.
Author: Kaunert, Christian
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 392
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Book Description
The destruction of millions of acres of forest land through wildfires is a global cause of concern. Artificial intelligence (AI), transformative in nature, has the potential to transcend and significantly mitigate risk factors of wildfires. AI-driven monitoring systems can detect early signs of wildfire activity, allowing for faster, more targeted responses that can minimize damage and save lives. Machine Learning and Internet of Things in Fire Ecology elucidates and explores the interface of fire ecology with AI, machine learning, and internet of things, as these technologies emerged as a pivotal domain with transformative potential. It will assist environmental-related industries in understanding the paraphernalia and dynamics of the fire ecology ecosystem. Covering topics such as AI, unmanned aerial vehicles (UAVs), and wildlife conservation, this book is an excellent resource for government officials, ecologists, academicians, policymakers, researchers, environmental specialists, industry experts, graduate and postgraduate students, and more.
