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.

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.

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.

A comprehensive theoretical synthesis of the various success factors required to successfully and sustainably manage natural resources, 'Sustainable Governance of Natural Resources' offers a quantitative model to predict the success of natural resource management.

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.

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

This book describes the myriad components of the Hindu Kush-Himalaya (HKH) region. The contributors elaborate on challenges, failures, and successes in efforts to conserve the HKH, its indigenous plants and animals, and the watershed that runs from the very roof of the planet via world-rivers to marine estuaries, supporting a human population of some two billion people. Readers will learn how the landforms, animal species and humans of this globally fascinating region are connected, and understand why runoff from snow and ice in the world’s tallest mountains is vital to inhabitants far downstream. The book comprises forty-five chapters organized in five parts. The first section, Landscapes, introduces the mountainous watersheds of the HKH, its weather systems, forests, and the 18 major rivers whose headwaters are here. The second part explores concepts, cultures, and religions, including ethnobiology and indigenous regimes, two thousand years of religious tradition, and the history of scientific and research expeditions. Part Three discusses policy, wildlife conservation management, habitat and biodiversity data, as well as the interaction of animals and humans. The fourth part examines the consequences of development and globalization, from hydrodams, to roads and railroads, to poaching and illegal wildlife trade. This section includes studies of animal species including river dolphins, woodpeckers and hornbills, langurs, snow leopards and more. The concluding section offers perspectives and templates for conservation, sustainability and stability in the HKH, including citizen-science projects and a future challenged by climate change, growing human population, and global conservation decay. A large assemblage of field and landscape photos, combined with eye-witness accounts, presents a 50-year local and wider perspective on the HKH. Also included are advanced digital topics: data sharing, open access, metadata, web portal databases, geographic information systems (GIS) software and machine learning, and data mining concepts all relevant to a modern scientific understanding and sustainable management of the Hindu Kush-Himalaya region. This work is written for scholars, landscape ecologists, naturalists and researchers alike, and it can be especially well-suited for those readers who want to learn in a more holistic fashion about the latest conservation issues.

This book presents case studies to analyse the relationship between sustainability – environmental, social, institutional and economic – and digital innovation. The respective contributions offer a contextualisation of the main present and future trends concerning these two elements, and present analyses from economic, technical, managerial, and social perspectives alike. The individual sections of the book focus on interactions between sustainability and digital innovation in existing organisations and highlight the new opportunities, challenges and threats that may emerge as a result. The contributions are mainly based on case studies and research conducted in Europe and Africa, with a few focusing on Southeast Asia and Central America, and were prepared by experts in the fields of Information Systems, Computer Science, Social Development, and Economics.

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.

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.