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  • 1
    Monograph available for loan
    Monograph available for loan
    Princeton [u.a.] : Princeton Univ. Press
    Call number: PIK M 490-16-89502
    Description / Table of Contents: Agent-based modeling is a new technique for understanding how the dynamics of biological, social, and other complex systems arise from the characteristics and behaviors of the agents making up these systems. This innovative textbook gives students and scientists the skills to design, implement, and analyze agent-based models. It starts with the fundamentals of modeling and provides an introduction to NetLogo, an easy-to-use, free, and powerful software platform. Nine chapters then each introduce an important modeling concept and show how to implement it using NetLogo. The book goes on to present strategies for finding the right level of model complexity and developing theory for agent behavior, and for analyzing and learning from models. Agent-Based and Individual-Based Modeling features concise and accessible text, numerous examples, and exercises using small but scientific models. The emphasis throughout is on analysis--such as software testing, theory development, robustness analysis, and understanding full models--and on design issues like optimizing model structure and finding good parameter values. The first hands-on introduction to agent-based modeling, from conceptual design to computer implementation to parameterization and analysis Filled with examples and exercises, with updates and supplementary materials at www.railsback-grimm-abm-book.com Designed for students and researchers across the biological and social sciences Written by leading practitioners.
    Type of Medium: Monograph available for loan
    Pages: XVIII, 329 S. , Ill., graph. Darst.
    ISBN: 9780691136745 (pbk.) , 9780691136738 (hardback)
    Language: English
    Branch Library: PIK Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    Princeton, NJ [u.a.] : Princeton Univ. Press
    Call number: PIK N 531-10-0007
    Description / Table of Contents: Contents: PART 1.MODELING ; Chapter 1. Introduction ; 1.1 Why Individual-based Modeling and Ecology? ; 1.2 Linking Individual Traits and System Complexity: Three Examples ; 1.3 Individual-based Ecology ; 1.4 Early IBMs and Their Research Programs ; 1.5 What Makes a Model an IBM? ; 1.6 Status and Challenges of the Individual-based Approach ; 1.7 Conclusions and Outlook ; Chapter 2. A Primer to Modeling ; 2.1 Introduction ; 2.2 Heuristics for Modeling ; 2.3 The Modeling Cycle ; 2.4 Summary and Discussion ; Chapter 3. Pattern-oriented Modeling ; 3.1 Introduction ; 3.2 Why Patterns, and What Are Patterns? ; 3.3 The Tasks of Pattern-oriented Modeling ; 3.4 Discussion ; PART 2.INDIVIDUAL-BASED ECOLOGY ; Chapter 4. Theory in Individual-based Ecology ; 4.1 Introduction ; 4.2 Basis for Theory in IBE ; 4.3 Goals of IBE Theory ; 4.4 Theory Structure ; 4.5 Theory Development Cycle ; 4.6 Example: Development of Habitat Selection Theory for Trout ; 4.7 Summary and Discussion ; Chapter 5. A Conceptual Framework for Designing Individual-based Models ; 5.1 Introduction ; 5.2 Emergence ; 5.3 Adaptive Traits and Behavior ; 5.4 Fitness ; 5.5 Prediction ; 5.6 Interaction , 5.7 Sensing , 5.8 Stochasticity ; 5.9 Collectives ; 5.10 Scheduling ; 5.11 Observation ; 5.12 Summary and Conclusions , 5.13 Conceptual Design Checklist ; 9Chapter 6. Examples ; 6.1 Introduction ; 6.2 Group and Social Behavior ; 6.3 Population Dynamics of Social Animals ; 6.4 Movement: Dispersal and Habitat Selection , 6.5 Regulation of Hypothetical Populations ; 6.6 Comparison with Classical Models ; 6.7 Dynamics of Plant Populations and Communities ; 6.8 Structure of Communities and Ecosystems ; 6.9 Artificially Evolved Traits ; 6.10 Summary and Conclusions ; PART 3.THE ENGINE ROOM ; Chapter 7. Formulating Individual-based Models ; 7.1 Introduction ; 7.2 Contents of an IBM Formulation ; 7.3 Formulating an IBM's Spatial Elements ; 7.4 Formulating Logical and Probabilistic Rules ; 7.5 Formulating Adaptive Traits ; 7.6 Controlling Uncertainty ; 7.7 Using Object-oriented Design and Description ; 7.8 Using Mechanistic and Discrete Mathematics ; 7.9 Designing Superindividuals ; 7.10 Summary and Conclusions ; Chapter 8. Software for Individual-based Models ; 8.1 Introduction ; 8.2 The Importance of Software Design for IBMs ; 8.3 Software Terminology and Concepts ; 8.4 Software Platforms ; 8.5 Software Testing ; 8.6 Moving Software Development Forward ; 8.7 Important Implementation Techniques ; 8.8 Some Favorite Software Myths ; 8.9 Summary and Conclusions ; Chapter 9. Analyzing Individual-based Models ; 9.1 Introduction ; 9.2 Steps in Analyzing an IBM ; 9.3 General Strategies for Analyzing IBMs ; 9.4 Techniques for Analyzing IBMs ; 9.5 Statistical Analysis ; 9.6 Sensitivity and Uncertainty Analysis ; 9.7 Robustness Analysis ; 9.8 Parameterization ; 9.9 Independent Predictions ; 9.10 Summary and Conclusions ; Chapter 10. Communicating Individual-based Models and Research ; 10.1 Introduction ; 10.2 Types of IBE Work to Communicate ; 10.3 Complete and Efficient Model Description ; 10.4 Common Review Comments ; 10.5 Visual Communication of Executable Models ; 10.6 Communicating Software ; 10.7 Summary and Conclusions ; PART 4.CONCLUSIONS AND OUTLOOK ; Chapter 11. Using Analytical Models in Individual-based Ecology ; 11.1 Introduction ; 11.2 Classifications of Ecological Models ; 11.3 Benefits of Analytical Models ; 11.4 Analytical Approximation of IBMs ; 11.5 Using Analytical Models to Understand and Analyze IBMs ; 11.6 Summary and Discussion ; Chapter 12. Conclusions and Outlook for Individual-based Ecology ; 12.1 Introduction ; 12.2 Why Do We Need IBE? ; 12.3 How Is IBE Different From Traditional Ecology? ; 12.4 What Can Ecology Contribute to the Science of Complex Systems? ; 12.5 A Visit to the Individual-based Ecology Laboratory
    Type of Medium: Monograph available for loan
    Pages: XVI, 428 S. : Ill., graph. Darst.
    ISBN: 069109666X
    Series Statement: Princeton series in theoretical and computational biology
    Branch Library: PIK Library
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  • 3
    Call number: AWI Bio-20-93988
    Type of Medium: Dissertations
    Pages: x, 181 Seiten , Illustrationen, Diagramme
    Language: English
    Note: Dissertation, Universität Potsdam, 2017 , Contents Abstract Kurzfassung Contents 1. List of figures 2. List of tables Chapter 1. General introduction 1. Motivation 2. Scientific background 3. Objectives of the thesis 4. Thesis outline Chapter 2. Manuscript 1: Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix 1. Abstract 2. Introduction 3. Material and Methods 4. Results 5. Discussion 6. Acknowledgements Chapter 3. Manuscript 2: Field and simulation data reveal dissimilar responses of Larix gmelinii stands to increasing temperature across the Siberian treeline ecotone 1. Abstract 2. Introduction 3. Methods 4. Results 5. Discussion 6. Acknowledgements Chapter 4. Manuscript 3: High gene flow and complex treeline dynamics on the Taymyr Peninsula (north-central Siberia), revealed by nuclear microsatellites of Larix 1. Abstract 2. Introduction 3. Materials and methods 4. Results 5. Discussion 6. Acknowledgements Chapter 5. Manuscript 4: Dispersal distances at treeline in Siberia - genetic guided model improvement 1. Abstract 2. Introduction 3. Methods 4. Results 5. Discussion 6. Acknowledgements Chapter 6. Synopsis 1. Towards a better understanding of Siberian treeline dynamics 2. Methodological challenges to reconstruct and predict the treeline advance 3. Conclusions 4. Outlook Appendix 1. Supplementary information for manuscript 1 (Chapter 2) 2. Supplementary information for manuscript 2 (Chapter 3) 3. Supplementary information for manuscript 3 (Chapter 4) 4. Supplementary information for manuscript 4 (Chapter 5) Bibliography Acknowledgements - Danksagung Declaration
    Location: AWI Reading room
    Branch Library: AWI Library
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  • 4
    Publication Date: 2015-03-26
    Description: The Southern Ocean ecosystem is characterized by extreme seasonal changes in environmental factors such as day length, sea ice extent and food availability. The key species Antarctic krill (Euphausia superba) has evolved metabolic and behavioural seasonal rhythms to cope with these seasonal changes. We investigate the switch between a physiological less active and active period for adult krill, a rhythm which seems to be controlled by internal biological clocks. These biological clocks can be synchronized by environmental triggers such as day length and food availability. They have evolved for particular environmental regimes to synchronize predictable seasonal environmental changes with important life cycle functions of the species. In a changing environment the time when krill is metabolically active and the time of peak food availability may not overlap if krill's seasonal activity is solely determined by photoperiod (day length). This is especially true for the Atlantic sector of the Southern Ocean where the spatio-temporal ice cover dynamics are changing substantially with rising average temperatures. We developed an individual-based model for krill to explore the impact of photoperiod and food availability on the growth and demographics of krill. We simulated dynamics of local krill populations (with no movement of krill assumed) along a south-north gradient for different triggers of metabolic activity and different levels of food availability below the ice. We also observed the fate of larval krill which cannot switch to low metabolism and therefore are likely to overwinter under ice. Krill could only occupy the southern end of the gradient, where algae bloom only lasts for a short time, when alternative food supply under the ice was high and metabolic activity was triggered by photoperiod. The northern distribution was limited by lack of overwintering habitat for krill larvae due to short duration of sea ice cover even for high food content under the ice. The variability of the krill's length-frequency distributions varied for different triggers of metabolic activity, but did not depend on the sea ice extent. Our findings suggest a southward shift of krill populations due to reduction in the spatial sea ice extent, which is consistent with field observations. Overall, our results highlight the importance of the explicit consideration of spatio-temporal sea ice dynamics especially for larval krill together with temporal synchronization through internal clocks, triggered by environmental factors (photoperiod and food) in adult krill for the population modelling of krill.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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  • 5
    Publication Date: 2018-02-26
    Description: We investigate how individual growth and population structure of Antarctic krill (Euphausia superba) would be affected by changes in the spatio-temporal dynamics of the sea ice cover. This is of high interest since krill has adapted to a particular environmental regime which is likely to change dramatically over the coming years. The response of krill will in particular depend on its chronobiology: when and why does krill, after a period of decreased metabolic activity during winter, switch back to an active metabolic state? If this switch is purely triggered by the Zeitgeber day length, the metabolically active period of krill and the availability of food resources would become out of phase with potentially drastic consequences for krill populations. Alternatively, the switch might also be triggered by food availability. To explore the consequences of different environmental scenarios and assumptions about krill chronobiology, we developed a spatially explicit individual-based simulation model. The model operates on a daily time step. Each time step ice cover extent and day length for each grid cell in the model are updated. In the model demographic and behavioural processes are simulated every time step. Particularly all modelled krill individuals grow depending on food availability, move, reproduce given their reproductive and metabolic state, and die with a certain probability. Growth and reproduction are modelled according to a simplified version of dynamic energy budget theory (DEBKiss). Simulations run for several years until quasi-stationary population characteristics have emerged. Population metrics such as length distribution and heterogeneity in reproductive state within the population are observed. We will present the model and demonstrate its potential by contrasting results for selected environmental and chronobiological scenarios. The model’s design and implementation are open so that suggestions regarding alternative assumptions and scenarios can easily be implemented and explored.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 6
    ISSN: 1573-5052
    Keywords: Browsing ; Fire ; Long-term dynamics ; Microsites ; Stability concepts ; System boundaries
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Despite the large spatial extent and the obvious importance of the savanna biome, not to mention several decades of savanna research, the origin, age, nature, and dynamics of savannas are not well understood. Basically, the question surrounding the presence or existence of savannas focuses on the long-term coexistence of the dominating life forms – trees and grasses. How do these two very different components coexist, without one of them dominating the other, and what mechanisms determine the proportion of each? Earlier equilibrium concepts have recently been replaced by non-equilibrium concepts, and the current view is that tree-grass interactions in savannas cannot be predicted by a simple model. Instead, many interacting factors operating at various spatial and temporal scales contribute to creating and maintaining savanna physiognomy. In this paper we analyse a number of studies from savannas in different parts of the world and discuss whether a general pattern can be perceived behind the numerous factors influencing the presence of savannas systems. On the basis of this analysis we propose a new unifying concept of savanna existence, i.e., the concept of ecological buffering mechanisms. In contrast to previous approaches to explain tree-grass coexistence in savannas, the concept of buffering mechanisms does not focus on equilibria or non-equilibria, steady states of the system or domains of attraction. Instead, in the concept of ecological buffering mechanisms we suggest that it is much more useful to focus on the boundaries of savanna existence itself and to investigate the mechanisms that allow a savanna to persist in critical situations where this system is driven to its boundaries, e.g., pure grasslands or tropical forests. The concept of ecological buffering mechanisms integrates both earlier concepts of ecological theory and general ideas on savanna dynamics as well as specific studies of savannas in different parts of the world.
    Type of Medium: Electronic Resource
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  • 7
    Publication Date: 2018-01-03
    Description: A dominant Antarctic ecological paradigm suggests that winter sea ice is generally the main feeding ground for krill larvae. Observations from our winter cruise to the southwest Atlantic sector of the Southern Ocean contradict this view and present the first evidence that the pack-ice zone is a food-poor habitat for larval development. In contrast, the more open marginal ice zone provides a more favourable food environment for high larval krill growth rates. We found that complex under-ice habitats are, however, vital for larval krill when water column productivity is limited by light, by providing structures that offer protec- tion from predators and to collect organic material released from the ice. The larvae feed on this sparse ice-associated food during the day. After sunset, they migrate into the water below the ice (upper 20 m) and drift away from the ice areas where they have previously fed. Model analyses indicate that this behaviour increases both food uptake in a patchy food environment and the likelihood of overwinter transport to areas where feeding conditions are more favourable in spring.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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