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Understanding Complex Ecosystem Dynamics: A Systems and Engineering Perspective takes a fresh, interdisciplinary perspective on complex system dynamics, beginning with a discussion of relevant systems and engineering skills and practices, including an explanation of the systems approach and its major elements. From this perspective, the author formulates an ecosystem dynamics functionality-based framework to guide ecological investigations. Next, because complex system theory (across many subject matter areas) is crucial to the work of this book, relevant network theory, nonlinear dynamics theory, cellular automata theory, and roughness (fractal) theory is covered in some detail. This material serves as an important resource as the book proceeds. In the context of all of the foregoing discussion and investigation, a view of the characteristics of ecological network dynamics is constructed. This view, in turn, is the basis for the central hypothesis of the book, i.e., ecological networks are ever-changing networks with propagation dynamics that are punctuated, local-to-global, and perhaps most importantly fractal. To analyze and fully test this hypothesis, an innovative ecological network dynamics model is defined, designed, and developed. The modeling approach, which seeks to emulate features of real-world ecological networks, does not make a priori assumptions about ecological network dynamics, but rather lets the dynamics develop as the model simulation runs. Model analysis results corroborate the central hypothesis. Additional important insights and principles are suggested by the model analysis results and by the other supporting investigations of this book – and can serve as a basis for going-forward complex system dynamics research, not only for ecological systems but for complex systems in general. Provides a fresh interdisciplinary perspective, offers a broad integrated development, and contains many new ideas Clearly explains the elements of the systems approach and applies them throughout the book Takes on the challenging and open issues of complex system network dynamics Develops and utilizes a new, innovative ecosystem dynamics modeling approach Contains over 135 graphic illustrations to help the reader visualize and understand important concepts
As scientific understanding about ecological processes has grown, the idea that ecosystem dynamics are complex, nonlinear, and often unpredictable has gained prominence. Of particular importance is the idea that rather than following an inevitable progression toward an ultimate endpoint, some ecosystems may occur in a number of states depending on past and present ecological conditions. The emerging idea of “restoration thresholds” also enables scientists to recognize when ecological systems are likely to recover on their own and when active restoration efforts are needed. Conceptual models based on alternative stable states and restoration thresholds can help inform restoration efforts. New Models for Ecosystem Dynamics and Restoration brings together leading experts from around the world to explore how conceptual models of ecosystem dynamics can be applied to the recovery of degraded systems and how recent advances in our understanding of ecosystem and landscape dynamics can be translated into conceptual and practical frameworks for restoration. In the first part of the book, background chapters present and discuss the basic concepts and models and explore the implications of new scientific research on restoration practice. The second part considers the dynamics and restoration of different ecosystems, ranging from arid lands to grasslands, woodlands, and savannahs, to forests and wetlands, to production landscapes. A summary chapter by the editors discusses the implications of theory and practice of the ideas described in preceding chapters. New Models for Ecosystem Dynamics and Restoration aims to widen the scope and increase the application of threshold models by critiquing their application in a wide range of ecosystem types. It will also help scientists and restorationists correctly diagnose ecosystem damage, identify restoration thresholds, and develop corrective methodologies that can overcome such thresholds.
Can physics be an appropriate framework for the understanding of ecological science? Most ecologists would probably agree that there is little relation between the complexity of natural ecosystems and the simplicity of any example derived from Newtonian physics. Though ecologists have long been interested in concepts originally developed by statistical physicists and later applied to explain everything from why stock markets crash to why rivers develop particular branching patterns, applying such concepts to ecosystems has remained a challenge. Self-Organization in Complex Ecosystems is the first book to clearly synthesize what we have learned about the usefulness of tools from statistical physics in ecology. Ricard Solé and Jordi Bascompte provide a comprehensive introduction to complex systems theory, and ask: do universal laws shape the structure of ecosystems, at least at some scales? They offer the most compelling array of theoretical evidence to date of the potential of nonlinear ecological interactions to generate nonrandom, self-organized patterns at all levels. Tackling classic ecological questions--from population dynamics to biodiversity to macroevolution--the book's novel presentation of theories and data shows the power of statistical physics and complexity in ecology. Self-Organization in Complex Ecosystems will be a staple resource for years to come for ecologists interested in complex systems theory as well as mathematicians and physicists interested in ecology.
As scientific understanding about ecological processes has grown, the idea that ecosystem dynamics are complex, nonlinear, and often unpredictable has gained prominence. Of particular importance is the idea that rather than following an inevitable progression toward an ultimate endpoint, some ecosystems may occur in a number of states depending on past and present ecological conditions. The emerging idea of “restoration thresholds” also enables scientists to recognize when ecological systems are likely to recover on their own and when active restoration efforts are needed. Conceptual models based on alternative stable states and restoration thresholds can help inform restoration efforts. New Models for Ecosystem Dynamics and Restoration brings together leading experts from around the world to explore how conceptual models of ecosystem dynamics can be applied to the recovery of degraded systems and how recent advances in our understanding of ecosystem and landscape dynamics can be translated into conceptual and practical frameworks for restoration. In the first part of the book, background chapters present and discuss the basic concepts and models and explore the implications of new scientific research on restoration practice. The second part considers the dynamics and restoration of different ecosystems, ranging from arid lands to grasslands, woodlands, and savannahs, to forests and wetlands, to production landscapes. A summary chapter by the editors discusses the implications of theory and practice of the ideas described in preceding chapters. New Models for Ecosystem Dynamics and Restoration aims to widen the scope and increase the application of threshold models by critiquing their application in a wide range of ecosystem types. It will also help scientists and restorationists correctly diagnose ecosystem damage, identify restoration thresholds, and develop corrective methodologies that can overcome such thresholds.
Model development is of vital importance for understanding and management of ecological processes. Identifying the complex relationships between ecological patterns and processes is a crucial task. Ecological modelling—both qualitatively and quantitatively—plays a vital role in analysing ecological phenomena and for ecological theory. This textbook provides a unique overview of modelling approaches. Representing the state-of-the-art in modern ecology, it shows how to construct and work with various different model types. It introduces the background of each approach and its application in ecology. Differential equations, matrix approaches, individual-based models and many other relevant modelling techniques are explained and demonstrated with their use. The authors provide links to software tools and course materials. With chapters written by leading specialists, “Modelling Complex Ecological Dynamics” is an essential contribution to expand the qualification of students, teachers and scientists alike.
This book presents current meta-ecosystem models and their derivation from classical ecosystem and metapopulation theories. Specifically, it reviews recent modelling efforts that have emphasized the role of nonlinear dynamics on spatial and food web networks, and which have cast their implications within the context of spatial synchrony and ecological stoichiometry. It suggests that these recent advances naturally lead to a generalization of meta-ecosystem theories to spatial fluxes of matter that have both a trophic and non-trophic impact on species. Ecosystem dynamics refers to the cycling of matter and energy across ecological compartments through processes such as consumption and recycling. Spatial dynamics established its ecological roots with metapopulation theories and focuses on scaling up local ecological processes through the limited movement of individuals and matter. Over the last 15 years, theories integrating ecosystem and spatial dynamics have quickly coalesced into meta-ecosystem theories, the focus of this book. The book will be of interest to graduate students and researchers who wish to learn more about the synthesis of ecosystem and spatial dynamics, which form the foundation of the theory of meta-ecosystems.
Ecosystems in the modern world face a vast array of disturbances, from globally shifting abiotic conditions, to increasingly variable extreme natural events, to high intensity discrete human-caused disturbances. Well-developed, applicable theoretical frameworks on how ecosystems can respond to and withstand these disturbances are needed for adequate management of valued ecological systems. To date, the most promising theoretical development for understanding ecological response to complex sets of disturbances is resilience. Ecological resilience acknowledges non-linear ecosystem behavior, incorporates the role of slowly changing environmental parameters in ecological dynamics, and offers one of the few potential methods to predict, and avoid, impending ecological collapse. However, as ecological resilience has evolved conceptually to include social, political, and economic fields, it has become increasingly difficult to clearly define in, and apply to, managed ecosystems. This dissertation pairs ecological resilience with other, well-established attributes of ecological response to disturbance, namely resistance, persistence, and recovery. By doing so, we can clearly define and quantify each attribute in a range of ecosystem types and over a variety of ecological scales. In Chapter 1, we use microcosm communities to test the relationship between one potential mechanism, landscape connectivity, and multiple attributes of ecological response to disturbance including resistance, resilience, and recovery. We find that each attribute responds uniquely to connectivity, and that generalizing the role of connectivity over all three may give an inaccurate prediction of how ecosystems may respond to individual disturbances. In Chapter 2, we experimentally investigate the presence of early warning indicators of approaching critical thresholds. Using water table drawdown treatments in bog, we test for critical slowing and increased autocorrelation as the bog approaches a transition to forest. We find that critical slowing is clear in composition and moss cover, but that autocorrelation is not apparent. The decoupling of critical slowing and increased autocorrelation could be due to a number of complex ecosystem dynamics, all of which are common in ecosystem management globally. Thus, early warning indicators likely need further development if they are to become applicable. In Chapter 3, we observationally study how conservation management actions may increase or decrease ecological resilience. In particular, we explore how invasive species management intensity correlates with changes in functional redundancy, response diversity, and spatial occurrence of regime shifts in Garry oak meadows. We find that more intense management correlates with less area lost to woody encroachment and increases in functional redundancy through time. However, the relationship was strongly mediated by individual landscape settings. Finally, in Chapter 4, we scale up to a provincial study, investigating persistence of ecosystems and large mammal species in the face of the continuous pressures of land use change. In the results from all four chapters, it is clear that individual attributes of ecological response to disturbance, i.e. resistance, persistence, resilience, or recovery, all play unique roles in ecosystem dynamics. Additionally, the metric chosen to quantify each attribute can play a pivotal role in how we interpret observed dynamics. The work in this dissertation highlights that we cannot understand or predict ecological response to disturbance without clear, measurable concepts. Around a single state of interest, resilience is only one among a suite of attributes that are important to understand. Its additional strength, of potentially predicting the occurrence of ecological thresholds, is still being developed as we explore methods of quantification and application in individual ecosystems.
A central issue in economics is the optimal allocation of scarce resources. Is efficient allocation indeed optimal and does it lead to sustainable solutions? Lars Hein contributes to this discussion at the interface of ecology and economics, and provides interesting case studies to test various theoretical approaches. The book is a must for both economists with an interest in ecology and for ecologists with an interest in economics! Ekko van Ierland, Wageningen University, the Netherlands Economics and Ecosystems demonstrates how the concepts of economic efficiency, sustainability and equity can be applied in ecosystem management. The book presents an overview of these three concepts, a framework for their analysis and modelling, and three case studies. Specific attention is given to how complex ecosystem dynamics, such as thresholds or irreversible responses, influence ecosystem management options. The case studies focus on ecosystem dynamics and ecosystem services supply in a forest ecosystem, a Dutch wetland, and a rangeland in the Western Sahel. Integrating ecology and economics, this informative book will appeal to postgraduate students in environmental sciences and environmental economics as well as ecosystem managers.
Serengeti National Park is one of the world’s most diverse ecosystems, a natural laboratory for ecology, evolution, and conservation, with a history that dates back at least four million years to the beginnings of human evolution. The third book of a ground- breaking series, Serengeti III is the result of a long-term integrated research project that documents changes to this unique ecosystem every ten years. Bringing together researchers from a wide range of disciplines—ecologists, paleontologists, economists, social scientists, mathematicians, and disease specialists— this volume focuses on the interactions between the natural system and the human-dominated agricultural system. By examining how changes in rainfall, wildebeest numbers, commodity prices, and human populations have impacted the Serengeti ecosystem, the authors conclude that changes in the natural system have affected human welfare just as changes in the human system have impacted the natural world. To promote both the conservation of biota and the sustainability of human welfare, the authors recommend community-based conservation and protected-area conservation. Serengeti III presents a timely and provocative look at the conservation status of one of earth’s most renowned ecosystems.
In a seminal 1972 paper, Robert M. May asked: “Will a Large Complex System Be Stable?” and argued that stability (of a broad class of random linear systems) decreases with increasing complexity, sparking a revolution in our understanding of ecosystem dynamics. Twenty-five years later, May, Levin, and Sugihara translated our understanding of the dynamics of ecological networks to the financial world in a second seminal paper, “Complex Systems: Ecology for Bankers.” Just a year later, the US subprime crisis led to a near worldwide “great recession,” spread by the world financial network. In the present paper we describe highlights in the development of our present understanding of stability and complexity in network systems, in order to better understand the role of networks in both stabilizing and destabilizing economic systems. A brief version of this working paper, focused on the underlying theory, appeared as an invited feature article in the February 2020 Society for Chaos Theory in Psychology and the Life Sciences newsletter (Hastings et al. 2020).