New Models for Ecosystem Dynamics and Restoration

Richard J. Hobbs, Katharine N. Suding, Peter Society for Ecological Restoration International, Richard J. Hobbs, Katharine N. Suding, Peter Society for Ecological Restoration International

• Publisher: Island Press
• Year: 2013
• Print ISBN: 9781597261852, 9781597261845
• eBook ISBN: 9781610911382
• Topic: Biological Sciences
• Subtopic: Environmental Science
• Index: Biological Sciences

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.

PART ONE

Background: Concepts and Models

Our objective in putting together this book was to collectively evaluate threshold modeling approaches as applied to ecological restoration. It was our aim not to develop a new suite of models but rather to examine when and where state transition, alternative state, and other threshold approaches are being used; how effective they are; and what types of evidence are being used to derive and apply the models. There are many ways to explore the nexus between the demand for strong inference and statistically robust approaches required by these models and the need to get something that works practically. In this emerging junction between theoretical and quantitative ecology and practical ecological restoration, it was our goal to explore both the potential and the pitfalls of this meshing of theory and practice as well as to develop innovative ways to maximize the potential and minimize the pitfalls. In this part, experts in the theoretical and quantitative aspects of these ecosystem models examine the possible ways of assessing ecosystem dynamics. These six chapters highlight the conceptual relevance of these models to restoration as well as the problems of rigorously testing the models in a restoration setting.

Chapter 1

Models of Ecosystem Dynamics as Frameworks for Restoration Ecology

KATHARINE N. SUDING AND RICHARD J. HOBBS

As rates of exotic species invasion, fragmentation, and climate change continue to accelerate, restoration faces increasingly greater challenges. Restoration must address the substantial, long-lasting reorganizations of ecosystems driven by these impacts. Among practitioners and scientists alike, there is increasing recognition that ecosystem dynamics can be complex, nonlinear, and often unpredictable (Wallington et al. 2005). Of particular importance is the recognition that some ecosystems may occur in a number of different states, which may be contingent on the history of disturbance, human intervention, or past restoration actions (Beisner et al. 2003; Suding et al. 2004). Complementary approaches using modifications of classical succession theory and the concept of assembly rules have also recently been investigated in the context of managing and restoring ecosystems (Young et al. 2001; Temperton et al. 2004; Hobbs et al. 2007). Adding further complexity, we better understand the importance of broad-scale processes and interactions between adjoining ecosystems; impacts in one place may be the result of events or management decisions elsewhere (Hobbs 2002). Taken together, these advances yield an exciting body of theory on which to rest restoration ecology (D’Antonio and Thomsen 2004; Hobbs and Norton 2004; Holl and Crone 2004; Young et al. 2005).

This book addresses how recent advances in our understanding of ecosystem and landscape dynamics can be translated into the conceptual and practical frameworks for restoration, adding to a number of excellent recent books developing linkages between ecological theory and restoration (Whisenant 1999; Walker and del Moral 2003; Temperton et al. 2004; Falk et al. 2006; van Andel and Aronson 2006; Walker et al. 2007). We explore how ecosystem models, particularly those that encompass nonlinear and complex dynamics, can be applied to the recovery of degraded systems (Hobbs and Norton 1996; Prober et al. 2002; Lindig-Cisneros et al. 2003; Suding et al. 2004). In this introductory chapter, we trace the development of these “new” ecosystem models in restoration, describe the main restoration approaches that would be taken based on the different type of ecosystem dynamics, and provide a synopsis of suitable evidence and approaches that can be used to determine what models of ecosystem dynamics may be applicable for particular systems and restoration situations. Lastly, we delineate the limitations and important considerations of this evidence that will affect inference, starting a discussion that continues in the contributed works that follow.

We also include a definitions of terms used throughout this book. Many terms have very precise definitions as they relate to ecosystem models. To avoid misperceptions and oversimplification, it is important to maintain very clear and unambiguous terminology as application of these models increase. We italicize our first use of terms throughout this chapter that we define in box 1.1.

BOX 1.1 Definitions of Terms

Sources for terminology include the glossary at the Resilience Alliance Web page (http://www.resal-liance.org), Gunderson (2000), and Carpenter et al. (2001).

Alternative stable states. A regime shift involving alternate stable states occurs when a threshold level of a controlling variable in a system is passed, such that the nature and extent of feedbacks change, resulting in a change of direction (the trajectory) of the system. A shift occurs when internal processes of the system (rates of birth, mortality, growth, consumption, decomposition, leaching, and so on) have changed and the state of the system (as indicated by system state variables) begins to change in a different direction toward a different attractor or domain of attraction. The system changes direction when it crosses an unstable equilibrium or repellor into another basin of attraction. While the S-shaped curve (fig. 1.1c) is a common way of visualizing these dynamics, there are many types of relationships between system state variables and environmental conditions. Other terms that are synonymous with alternative stable states include alternative attractors, alternative basins of attraction, multiple stable states, and multiple stable equilibria.

Controlling variable. The factor (or combination of factors) that drives the change in responding state variables (e.g., grazing intensity, fire frequency, pollution, or nutrient loading). They are sometimes called slow variables. For alternative stable states, controlling variables are assumed to be external to the system (i.e., that changes to the state variables will not change the controlling variables), and the term cross-scale interactions is used when external factors drive transitions.

A variation of these ideas, termed slow–fast cycles (also called relaxation oscillations or oscillatory behavior) may occur if the state variable (the fast variable) is internally coupled to the controlling variable (the slow variable) and responds discontinuously to it. Such behavior can describe dynamics like the regular spruce-budworm outbreak in boreal forests and differs from alternative stable state behavior, which assumes that the fast state variable does not affect the slow controlling variable.

Disturbances are changes in the system state variable or in the controlling variable (either of which could be affected by management). It is important to clarify what is being altered as part of a disturbance. For instance, disturbances to the system state variable are sometimes termed perturbations and distinguished from disturbances to the controlling environmental variable, which are sometimes called external shocks.

Gradual continuum models describe system dynamics without thresholds. In this case, change in the controlling variable is proportionate to change in the state variable. A state variable would not be paired in this case (e.g., no dichotomy of grass versus shrub domination) but rather a continuum of more or less grasses and shrubs in the system. These models imply unassisted recovery following the removal of adverse disturbances (or given the natural disturbance regime) to a desired set point.

Hysteresis refers to how a system responds or, more specifically, the return path taken following some disturbance or change due to cumulative effects. When the system follows a different path on return to its former state, this is called a hysteresis effect. Hysteresis would occur in alternative stable states and relaxation oscillations but not other types of regime shifts or nonregime behavior (gradual continuous and stochastic models). For instance, a system exhibiting threshold behavior but not alternative stable states should respond discontinuously but similarly to disturbance regardless of whether it is moving forward or backward.

Persistence. One criterion for stability is that a state is persistent: maintained beyond one complete turnover of individuals. As the time frame of vegetation dynamics generally exceeds the time scales of human observation or management goals, restoration decisions may often need to be made without the certain documentation of persistence. States without strong evidence of persistence are sometimes termed transient states.

Positive feedbacks. One important consideration about whether a system has crossed a threshold is whether feedbacks affecting internal processes (rates of birth, mortality, growth, consumption, decomposition, leaching, and so on) have changed. When a threshold is crossed, positive feedback loops (the output of a process influences the input of the same process in a way that amplifies the process) result in disproportionate changes relative to the controlling variable. Near a regime or attractor, negative feedbacks increase in importance to stabilize the system.

Resilience is the capacity of a system to absorb disturbance and reorganize so to retain essentially the same function, structure, identity, and feedbacks (i.e., remain in the same regime). Resilience is also defined as the width of the basin of attraction. The resilience of a system can change; it is not static or defined solely by controlling variables. For instance, the controlling variable for grass- and shrub-dominated rangeland could be grazing intensity, but fire frequency could be a factor that influences how resilient the system is to changes in grazing (i.e., how much disturbance it takes to shift a grassland system to a shrub-dominated system).

State variables. Characteristics such as abundance, composition, or some ecosystem function are state variables that describe responses of the system. For example, crossing a threshold from clear to turbid water in lake systems brings about a sudden, large, and dramatic change in the responding state variables: the species shift from macrophytes to algae. Another example of system state variables is grass- or shrub-dominated rangeland. State variables are also sometimes called fast variables because they respond to changes in a controlling variable.

Stochastic dynamics are nonequilibrium with few relationships between environment and system condition (i.e., there is no well-defined controlling variable). Often these systems have been found to be controlled mainly by random processes, chance events, or climate variation.

Threshold. A breakpoint between two states of a system. A characteristic feature of a threshold is a change in system feedbacks. As resilience declines, the amount of disturbance needed to cross the threshold declines. Restoration thresholds indicate breakpoints that need to be addressed by restoration efforts for recovery to occur, and degradation thresholds indicate the point where environmental change precludes recovery to the same state without management or restoration actions.

Threshold dynamics. The term alternate states is commonly used to describe the phenomenon whereby systems can exhibit a big change from one kind of regime to another. However, this terminology can be confusing because this would include what truly are alternate stable states (i.e., two or more stable point attractors separated by unstable thresholds) and the various other kinds of big changes that systems may exhibit. To avoid confusion over terminology, we suggest using threshold dynamics to include all the various kinds of thresholds and multiple system regimes that occur, including alternate st...

Table of contents

• About Island Press
• ABOUT THE SOCIETY FOR ECOLOGICAL RESTORATION INTERNATIONAL
• SOCIETY FOR ECOLOGICAL RESTORATION INTERNATIONAL - The Science and Practice of Ecological Restoration
• Title Page
• Copyright Page
• Table of Contents
• PREFACE
• PART ONE - Background: Concepts and Models
• PART TWO - Dynamics and Restoration of Different Ecosystem Types
• PART THREE - Synthesis: Implications for Theory and Practice
• EDITORS
• CONTRIBUTORS
• INDEX
• Island Press. Board of Directors