Ecologist Developed Spatially Explicit Dynamic Landscape Models
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Ecologist-Developed Spatially-Explicit Dynamic Landscape Models
Author: James D. Westervelt
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-04-14
This book is written for ecologists interested in capturing their understandings of how natural systems work in software – to help inform their work and communicate the consequences of proposed management plans. Historically, ecologists had to rely on the skills of trained computer programmers to modeling natural systems, but now a new generation of software is allowing ecologists to directly capture their understandings of systems in software. This book is a compilation of spatially explicit simulation models developed by ecologists and planners without any formal computer programming skills. Readers will be inspired to believe that they too can create similar models of the systems with which they are familiar.
Agent-Based Modeling of Environmental Conflict and Cooperation
Conflict is a major facet of many environmental challenges of our time. However, growing conflict complexity makes it more difficult to identify win-win strategies for sustainable conflict resolution. Innovative methods are needed to help predict, understand, and resolve conflicts in cooperative ways. Agent-Based Modeling of Environmental Conflict and Cooperation examines computer modeling techniques as an important set of tools for assessing environmental and resource-based conflicts and, ultimately, for finding pathways to conflict resolution and cooperation. This book has two major goals. First, it argues that complexity science can be a unifying framework for professions engaged in conflict studies and resolution, including anthropology, law, management, peace studies, urban planning, and geography. Second, this book presents an innovative framework for approaching conflicts as complex adaptive systems by using many forms of environmental analysis, including system dynamics modeling, agent-based modeling, evolutionary game theory, viability theory, and network analysis. Known as VIABLE (Values and Investments from Agent-Based interaction and Learning in Environmental systems), this framework allows users to model advanced facets of conflicts—including institution building, coalition formation, adaptive learning, and the potential for future conflict—and conflict resolution based on the long-term viability of the actors’ strategies. Written for scholars, students, practitioners, and policy makers alike, this book offers readers an extensive introduction to environmental conflict research and resolution techniques. As the result of decades of research, the text presents a strong argument for conflict modeling and reviews the most popular and advanced techniques, including system dynamics modeling, agent-based modeling, and participatory modeling methods. This indispensable guide uses NetLogo, a widely used and free modeling software package, to implement the VIABLE modeling approach in three case study applications around the world. Readers are invited to explore, adapt, modify, and expand these models to conflicts they hope to better understand and resolve.
Spatial Uncertainty in Ecology
Author: Carolyn T. Hunsaker
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-12-01
The huge growth in the use of geographic information systems, remote sensing platforms and spatial databases have made accurate spatial data more available for ecological and environmental models. Unfortunately, there has been too little analysis of the appropriate use of this data and the role of uncertainty in resulting ecological models. This is the first book to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research. It brings the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences to the ecologist using spatial data. After describing the uses of spatial data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis. Carolyn T. Hunsaker is a research ecologist in the USDA Forest Service in Fresno, California. Michael F. Goodchild is Professor of Geography at the University of California, Santa Barbara. Mark A. Friedl is Assistant Professor in the Department of Geography and the Center for Remote Sensing at Boston University. Ted J. Case is Professor of Biology at the University of California, San Diego.