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At least since Darwin argued that the difference in cognitive abilities between animals and humans is one of degree and not of kind, the study of animal cognition has been an active and dynamic subfield of behavioral sciences. It has, however, been based almost entirely on experimental studies of animals in captivity and belongs - as a field - more snugly in the realm of Psychology (or Ethology), with relatively little application to understanding the behavior of animals in the wild. Movement Ecology, in contrast, is a more recent branch of Ecology devoted almost entirely to the analysis of animal movements in the wild. Technological developments allow for animals to be tracked in the wild in ever-increasing numbers, precision, and duration. Movement ecology has, to some extent, “chased the data”, reflecting the practical need to analyze and interpret those data. Much of the most important developments of recent decades are devoted to dealing with the trickier aspects of the statistical analysis of movement data - which in their multidimensionality, autocorrelation, gappiness and measurement error, and behavioral complexity pose no shortage of hairy statistical problems.
Cognitive Ecology lays the foundations for a field of study that integrates theory and data from evolutionary ecology and cognitive science to investigate how animal interactions with natural habitats shape cognitive systems, and how constraints imposed on nervous systems limit or bias animal behavior. Using critical literature reviews and theoretical models, the contributors provide new insights and raise novel questions about the adaptive design of specific brain capacities and about optimal behavior subject to the computational capabilities of brains.
This book brings a unique perspective to animal movement studies because all studies come from African tropical environments where the great diversity, either biological and structurally (trees, shrubs, vines, epiphytes), present the animals with several options to fulfil their basic needs. These conditions have forced the evolution of unique movement patterns and ecological strategies. The book follows on our previous book “Movement Ecology of Neotropical Forest Mammals” but focuses on tropical African forests. Movement is an essential process in the life of all organisms. Animals move because they are looking for primary needs such as food, water, cover, mating and to avoid predators. Understanding the causes and consequences of animal movement is not an easy task for behavioural ecologists. Many animals are shy, move in secretive ways and are very sensible to human presence, therefore, studying the movements of mammals in tropical environments presents logistical and methodological challenges. However, researchers have recently started to be solved these challenges and exciting new information is emerging. In this book we are compiling a set of extraordinary studies where researchers have used new technology and the strongest methodological approaches to understand movement patterns in wild African forest mammals. This second book should inspire early career researchers to investigate wild mammal ́s movements in some of the most amazing forest in the world: African tropical forests.
Edwin Hutchins combines his background as an anthropologist and an open ocean racing sailor and navigator in this account of how anthropological methods can be combined with cognitive theory to produce a new reading of cognitive science. His theoretical insights are grounded in an extended analysis of ship navigation—its computational basis, its historical roots, its social organization, and the details of its implementation in actual practice aboard large ships. The result is an unusual interdisciplinary approach to cognition in culturally constituted activities outside the laboratory—"in the wild." Hutchins examines a set of phenomena that have fallen in the cracks between the established disciplines of psychology and anthropology, bringing to light a new set of relationships between culture and cognition. The standard view is that culture affects the cognition of individuals. Hutchins argues instead that cultural activity systems have cognitive properties of their own that are different from the cognitive properties of the individuals who participate in them. Each action for bringing a large naval vessel into port, for example, is informed by culture: the navigation team can be seen as a cognitive and computational system. Introducing Navy life and work on the bridge, Hutchins makes a clear distinction between the cognitive properties of an individual and the cognitive properties of a system. In striking contrast to the usual laboratory tasks of research in cognitive science, he applies the principal metaphor of cognitive science—cognition as computation (adopting David Marr's paradigm)—to the navigation task. After comparing modern Western navigation with the method practiced in Micronesia, Hutchins explores the computational and cognitive properties of systems that are larger than an individual. He then turns to an analysis of learning or change in the organization of cognitive systems at several scales. Hutchins's conclusion illustrates the costs of ignoring the cultural nature of cognition, pointing to the ways in which contemporary cognitive science can be transformed by new meanings and interpretations. A Bradford Book
It is more and more evident that our living system is completely disturbed by human intrusion. Such intrusion affects the functioning of entire systems in ways we do not yet fully understand. We use paradigms such as the disturbance to cover large and deep gaps in our scienti?c knowledge. Human ecology is an uncertain terrain for anthropologists, geographers, and ecologists and rarely is expanded to include the social and economic realms. The integration of different disciplines and the application of their many paradigms to problems of environmental complexity remains a distant goal despite the many efforts that have been made to achieve it. Philosophical and semantic barriers are erected when such integration is pursued by pioneering scientists. Recently, evolutionary ecology has shown great interest in the spatial processes well described by the emerging discipline of landscape ecology. But this interest takes the form of pure curiosity or at worst, of skepticism toward the real capacity of landscape ecology to contribute to the advancement of ecological science. The past two centuries have been characterized by huge changes occurring in the entire ecosphere. Global changes are the effects of human intervention at a planetary scale, with consequent degradation of the environment creating an e- logical debt for future generations. On the other side of the issue, new technologies have improved the welfare of billions of people and have given hope to many other billions that they may also see such improvement in the near future.
This edited volume is the first of its kind to bridge the epistemological gap between primate ethologists and primate neurobiologists. Leading experts in several fields review work ranging from primate foraging behavior to the neurophysiology of motor control, from vocal communication to the functions of the auditory cortex.
Movement ecology thrives from a successful synergy of data and models. In a field where experiments are difficult or impossible, linking field data with mathematical and statistical models allows us to test hypotheses and increase our quantitative understanding of movement processes. Owing to technological progress, data availability and quality are growing rapidly, inspiring new questions and challenging methodology. In my thesis, I address two modelling challenges, one at the forefront of current research on memory-based movement and the other long-standing, yet prevailing, in movement data analysis. Movement serves needs, such as foraging, but also requires time and energy. Therefore, we expect animals to have evolved strategies for efficient movement, likely drawing on cognitive abilities. Indeed, one of the current challenges in movement ecology is to understand the role of cognition, including memory, for movement. To date, very few models that include memory mechanisms have been confronted with data. In my thesis, I present a new cognitive-based model, in which an individual's travel history feeds back to future movement decisions. I focused on the pure spatio-temporal aspect of the travel history, assuming that an individual keeps track of elapsed times since last visits to locations and uses this information during the movement process. I showed that, despite the dynamic interplay of information gain and use, statistical inference can successfully identify this mechanism. I further applied the new modelling framework to wolf (Canis lupus) movement data to test whether wolves adopt a prey management strategy, based on memory, that is directed at reducing impacts of behavioural depression of prey through optimal timing of returns to hunting sites. I found support for the hypothesis but also point out the need to analyze a larger number of individuals to reach stronger conclusions. Data collection methods, as well as standard modelling approaches, discretize the temporal dimension of movement processes. This discretization is a challenge for data analysis, because results may be affected by data sampling rate. In my thesis, I develop the formal concept of movement models' robustness against varying temporal resolution. I provide a series of definitions for movement model robustness. These definitions vary in their strength of conditions but all rest on the same requirement that a model can validly be applied to data with varying resolutions, while parameters change in a systematic way that can be predicted. In an analysis of random walks and spatially-explicit extensions thereof, I found that while true robustness is rare, approximate robustness is more widely present in models. I further demonstrate how robustness can be used to mitigate the influence of temporal resolution on statistical inference.