Jens Krause

Bio: Jens Krause is an academic researcher from Leibniz Association. The author has contributed to research in topics: Population & Animal ecology. The author has an hindex of 77, co-authored 250 publications receiving 24820 citations. Previous affiliations of Jens Krause include University of Bath & Mount Allison University.

Effective leadership and decision-making in animal groups on the move

Abstract: For animals that forage or travel in groups, making movement decisions often depends on social interactions among group members. However, in many cases, few individuals have pertinent information, such as knowledge about the location of a food source, or of a migration route. Using a simple model we show how information can be transferred within groups both without signalling and when group members do not know which individuals, if any, have information. We reveal that the larger the group the smaller the proportion of informed individuals needed to guide the group, and that only a very small proportion of informed individuals is required to achieve great accuracy. We also demonstrate how groups can make consensus decisions, even though informed individuals do not know whether they are in a majority or minority, how the quality of their information compares with that of others, or even whether there are any other informed individuals. Our model provides new insights into the mechanisms of effective leadership and decision-making in biological systems.

Living in groups

Abstract: 1. Introduction 2. The benefits of group formation 3. Some costs of grouping 4. The size of a group 5. Spatial heterogeneity of costs and benefits within groups 6. Heterogeneity and homogeneity of group membership 7. Evolutionary considerations 8. Environmental effects on grouping behaviour 9. Mechanisms 10. Conclusions

Self-Organization and Collective Behavior in Vertebrates

Abstract: Publisher Summary The chapter discusses an emerging area of study: that of applying self-organization theory to mobile vertebrate groups composed of many interacting individuals such as bird flocks, ungulate herds, fish schools, and human crowds in an attempt to improve our understanding of underlying organizational principles. Mathematical modeling is becoming increasingly recognized as an important research tool when studying collective behavior. The chapter presents the interaction dynamics among individuals result in the formation, internal structuring, and collective behaviors of vertebrate groups. The chapter explores the distribution of grouping individuals over larger spatial and temporal scales, and discusses how individual behaviors lead to population-level dynamics. Behavioral differences among individuals within a group may have an important internal structuring influence. By using simulation models, it can be shown how individuals can modify their positions relative to other group members without necessitating information about their current position within the group. In considering self-organization within vertebrate groups it is evident that the organization at one level, for example, that of the group relates to that at higher levels. For example, self-sorting processes that lead to internal structuring within groups also result in population-level patterns when such groups fragment, thus affecting the probability that an individual will be in a group of a given size and composition at any moment in time. These population properties then feed back to the individual interactions by changing the probability of encounters among different members of a population. The chapter concludes that to understand collective behaviors fully, these properties cannot necessarily be considered in isolation.

Exploring Animal Social Networks

Abstract: Preface vii Chapter 1: Introduction to Social Networks 1 Chapter 2: Data Collection 19 Chapter 3: Visual Exploration 42 Chapter 4: Node-Based Measures 64 Chapter 5: Statistical Tests of Node-Based Measures 88 Chapter 6: Searching for Substructures 117 Chapter 7: Comparing Networks 141 Chapter 8: Conclusions 163 Glossary of Frequently Used Terms 173 References 175 Index 187

Modern Applied Statistics With S

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Integrating animal temperament within ecology and evolution.

Abstract: Temperament describes the idea that individual behavioural differences are repeatable over time and across situations. This common phenomenon covers numerous traits, such as aggressiveness, avoidance of novelty, willingness to take risks, exploration, and sociality. The study of temperament is central to animal psychology, behavioural genetics, pharmacology, and animal husbandry, but relatively few studies have examined the ecology and evolution of temperament traits. This situation is surprising, given that temperament is likely to exert an important influence on many aspects of animal ecology and evolution, and that individual variation in temperament appears to be pervasive amongst animal species. Possible explanations for this neglect of temperament include a perceived irrelevance, an insufficient understanding of the link between temperament traits and fitness, and a lack of coherence in terminology with similar traits often given different names, or different traits given the same name. We propose that temperament can and should be studied within an evolutionary ecology framework and provide a terminology that could be used as a working tool for ecological studies of temperament. Our terminology includes five major temperament trait categories: shyness-boldness, exploration-avoidance, activity, sociability and aggressiveness. This terminology does not make inferences regarding underlying dispositions or psychological processes, which may have restrained ecologists and evolutionary biologists from working on these traits. We present extensive literature reviews that demonstrate that temperament traits are heritable, and linked to fitness and to several other traits of importance to ecology and evolution. Furthermore, we describe ecologically relevant measurement methods and point to several ecological and evolutionary topics that would benefit from considering temperament, such as phenotypic plasticity, conservation biology, population sampling, and invasion biology.

Effective leadership and decision-making in animal groups on the move

Abstract: For animals that forage or travel in groups, making movement decisions often depends on social interactions among group members. However, in many cases, few individuals have pertinent information, such as knowledge about the location of a food source, or of a migration route. Using a simple model we show how information can be transferred within groups both without signalling and when group members do not know which individuals, if any, have information. We reveal that the larger the group the smaller the proportion of informed individuals needed to guide the group, and that only a very small proportion of informed individuals is required to achieve great accuracy. We also demonstrate how groups can make consensus decisions, even though informed individuals do not know whether they are in a majority or minority, how the quality of their information compares with that of others, or even whether there are any other informed individuals. Our model provides new insights into the mechanisms of effective leadership and decision-making in biological systems.

Temporal Networks

Abstract: A great variety of systems in nature, society and technology -- from the web of sexual contacts to the Internet, from the nervous system to power grids -- can be modeled as graphs of vertices coupled by edges The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems In many cases, however, the edges are not continuously active As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts In some cases, edges are active for non-negligible periods of time: eg, the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks