Distance Sampling

In this book, the authors cover the basic methods and advances within distance sampling that are most valuable to practitioners and in ecology more broadly. This is the fourth book dedicated to distance sampling. In the decade since the last book published, there have been a number of new developments. The intervening years have also shown which advances are of most use. This self-contained book covers topics from the previous publications, while also including recent developments in method, software and application. Distance sampling refers to a suite of methods, including line and point transect sampling, in which animal density or abundance is estimated from a sample of distances to detected individuals. The book illustrates these methods through case studies; data sets and computer code are supplied to readers through the book’s accompanying website. Some of the case studies use the software Distance, while others use R code. The book is in three parts. The first part addresses basic methods, the design of surveys, distance sampling experiments, field methods and data issues. The second part develops a range of modelling approaches for distance sampling data. The third part describes variations in the basic method; discusses special issues that arise when sampling different taxa (songbirds, seabirds, cetaceans, primates, ungulates, butterflies, and plants); considers advances to deal with failures of the key assumptions; and provides a check-list for those conducting surveys.

Our environment and natural food resources are continually coming under threat so that the monitoring of population trends is essential today. Whaling is a good example. Here politics and conservation often clash, and over the years more and more restrictions have been applied through the efforts of the International Whaling Commission in an endeavour to save some of our whale species from extinction. Localized fisheries also need to be monitored and quotas set each year. In some countries, sports fishing and hunting are popular so that information is needed about the populations being exploited in order to determine such things as the duration of hunting season and bag limits. Methods of estimating animal abundance have been developing steadily since the 1940s but over the last 20 years activity in this area has intensified and of this growth were two the subject has begun to blossom. At the centre of the authors of this book, David Anderson and Kenneth Burnham, who have widely published in this field. The need for computers in this area was soon recognized and David and Ken were joined by Jeffrey Laake who, with his computing expertise, helped to develop suitable software packages for implementing some of the new techniques. In the 1980s Stephen Buckland entered the arena and began to make his presence felt. Among other contributions, he firmly established the role of Monte Carlo and bootstrapping techniques in population estimation where the unique role of the computer could be fully exploited.

This advanced text focuses on the uses of distance sampling to estimate the density and abundance of biological populations. It addresses new methodologies, new technologies and recent developments in statistical theory and is the follow up companion to Introduction to Distance Sampling (OUP, 2001). In this text, a general theoretical basis is established for methods of estimating animal abundance from sightings surveys, and a wide range of approaches to analysis of sightings data is explored. These approaches include: modelling animal detectability as a function of covariates, where the effects of habitat, observer, weather, etc. on detectability can be assessed; estimating animal density as a function of location, allowing for example animal density to be related to habitat and other locational covariates; estimating change over time in populations, a necessary aspect of any monitoring programme; estimation when detection of animals on the line or at the point is uncertain, as often occurs for marine populations, or when the survey region has dense cover; survey design and automated design algorithms, allowing rapid generation of sound survey designs using geographic information systems; adaptive distance sampling methods, which concentrate survey effort in areas of high animal density; passive distance sampling methods, which extend the application of distance sampling to species that cannot be readily detected in sightings surveys, but can be trapped; and testing of methods by simulation, so that performance of the approach in varying circumstances can be assessed.

The highly pathogenic avian influenza H5N1 strain has spread from domestic poultry to a large number of species of free-ranging wild birds, including non-migratory birds and migratory birds that can travel thousands of kilometers each year. The regular contact and interaction between poultry and wild birds has increased the urgency of understanding wild bird diseases and the transmission mechanisms that exist between the poultry and wild bird sectors, with a particular emphasis on avian influenza. Monitoring techniques, surveillance, habitat use and migration patterns are all important aspects of wildlife and disease ecology that need to be better understood to gain insights into disease transmission between these sectors. This manual contains chapters on the basic ecology of avian influenza and wild birds, capture and marking techniques (ringing, color marking and satellite telemetry), disease sampling procedures, and field survey and monitoring procedures.--Publisher's description.

This study concerns the use of distance sampling to estimate the density or abundance of biological populations. Line and point transect sampling are the primary distance methods. Here, lines or points are surveyed in the field and the observer records a distance to those objects of interest that are detected. The sample data are the set of distances of detected objects and any relevant covariates; however, many objects may remain undetected during the course of the survey. Distance sampling provides a way to obtain reliable estimates of density of objects under fairly mild assumptions. Distance sampling is an extension of plot sampling methods where it is assumed that all objects within sample plots are counted.

This thorough revision of the classic Encyclopedia of Marine Mammals brings this authoritative book right up-to-date. Articles describe every species in detail, based on the very latest taxonomy, and a host of biological, ecological and sociological aspects relating to marine mammals. The latest information on the biology, ecology, anatomy, behavior and interactions with man is provided by a cast of expert authors – all presented in such detail and clarity to support both marine mammal specialists and the serious naturalist. Fully referenced throughout and with a fresh selection of the best color photographs available, the long-awaited second edition remains at the forefront as the go-to reference on marine mammals. More than 20% NEW MATERIAL includes articles on Climate Change, Pacific White-sided Dolphins, Sociobiology, Habitat Use, Feeding Morphology and more Over 260 articles on the individual species with topics ranging from anatomy and behavior, to conservation, exploitation and the impact of global climate change on marine mammals New color illustrations show every species and document topical articles FROM THE FIRST EDITION “This book is so good...a bargain, full of riches...packed with fascinating up to date information. I recommend it unreservedly it to individuals, students, and researchers, as well as libraries." --Richard M. Laws, MARINE MAMMALS SCIENCE "...establishes a solid and satisfying foundation for current study and future exploration" --Ronald J. Shusterman, SCIENCE

This is an updated version of the best selling first edition, Ecological Census Techniques, with updating, some new chapters and authors. Almost all ecological and conservation work involves carrying out a census or survey. This practically focussed book describes how to plan a census, the practical details and shows with worked examples how to analyse the results. The first three chapters describe planning, sampling and the basic theory necessary for carrying out a census. In the subsequent chapters international experts describe the appropriate methods for counting plants, insects, fish, amphibians, reptiles, mammals and birds. As many censuses also relate the results to environmental variability, there is a chapter explaining the main methods. Finally, there is a list of the most common mistakes encountered when carrying out a census.

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site