This book, the first in the “Wildlife Research Monograph” series, defines “wildlife research” in a variety of contexts and reviews recent research trends. The authors present the current developments they have identified using bibliometric analyses of the most common, relevant and emerging topics in wildlife research over the last three decades. Diverse aspects of wildlife research are discussed, including wildlife demography, infections spread between wildlife, livestock and humans, habitat requirements and management, as well as the effects of renewable energy and pollutants on wildlife. Furthermore the authors explore topics like advances in the study of species distribution, invasive species, use of molecular markers in wildlife studies and the sustainability of wildlife exploitation and conservation conflicts. The book offers a comprehensive overview of advances in wildlife research in the last decades.

This text is a thorough treatment of the rapidly growing area of aerial manipulation. It details all the design steps required for the modeling and control of unmanned aerial vehicles (UAV) equipped with robotic manipulators. Starting with the physical basics of rigid-body kinematics, the book gives an in-depth presentation of local and global coordinates, together with the representation of orientation and motion in fixed- and moving-coordinate systems. Coverage of the kinematics and dynamics of unmanned aerial vehicles is developed in a succession of popular UAV configurations for multirotor systems. Such an arrangement, supported by frequent examples and end-of-chapter exercises, leads the reader from simple to more complex UAV configurations. Propulsion-system aerodynamics, essential in UAV design, is analyzed through blade-element and momentum theories, analysis which is followed by a description of drag and ground-aerodynamic effects. The central part of the book is dedicated to aerial-manipulator kinematics, dynamics, and control. Based on foundations laid in the opening chapters, this portion of the book is a structured presentation of Newton–Euler dynamic modeling that results in forward and backward equations in both fixed- and moving-coordinate systems. The Lagrange–Euler approach is applied to expand the model further, providing formalisms to model the variable moment of inertia later used to analyze the dynamics of aerial manipulators in contact with the environment. Using knowledge from sensor data, insights are presented into the ways in which linear, robust, and adaptive control techniques can be applied in aerial manipulation so as to tackle the real-world problems faced by scholars and engineers in the design and implementation of aerial robotics systems. The book is completed by path and trajectory planning with vision-based examples for tracking and manipulation.

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.

Offers advice on over 100 ways to help protect birds and their habitats, and explains how a pro-active approach to wildlife conservation can make a difference.

The New York Times–bestselling author of H is for Hawk explores the human relationship to the natural world in this “dazzling” essay collection (Wall Street Journal). In Vesper Flights, Helen Macdonald brings together a collection of her best loved essays, along with new pieces on topics ranging from nostalgia for a vanishing countryside to the tribulations of farming ostriches to her own private vespers while trying to fall asleep. Meditating on notions of captivity and freedom, immigration and flight, Helen invites us into her most intimate experiences: observing the massive migration of songbirds from the top of the Empire State Building, watching tens of thousands of cranes in Hungary, seeking the last golden orioles in Suffolk’s poplar forests. She writes with heart-tugging clarity about wild boar, swifts, mushroom hunting, migraines, the strangeness of birds’ nests, and the unexpected guidance and comfort we find when watching wildlife.