Catastrophic Thresholds: A Synthesis of Concepts, Perspectives, and Applications
David D. Briske, Department of Ecosystem Science and Management, Texas A&M University
Robert A. Washington-Allen, Department of Ecosystem Science and Management, Texas A&M University
Craig R. Johnson, School of Zoology, University of Tasmania
Jeffrey A. Lockwood, Department of Philosophy, University of Wyoming
Dale R. Lockwood, Biology Department, Colorado State University
Tamzen K. Stringham, Department of Animal Biotechnology, University of Nevada-Reno
Herman H Shugart, Department of Environmental Sciences, University of Virginia
Full Text: HTML
Research reported in this feature identifies a convergence of interpretations regarding the threshold dynamics of complex ecological systems. This convergence has arisen from a diverse set of investigations addressing rangeland ecosystem dynamics, disease transmission, and fluctuations in the populations of insect pests. Effective application of the threshold concept to ecosystem management will require development of more robust linkages between non-equilibrium theory and protocols to identify triggers that initiate threshold conditions, feedback loops that establish system resilience, and developmental trajectories and attributes of potential alternative stable states. Successful implementation of these theory/application linkages has the potential to underpin an operational framework of resilience-based ecosystem management that is founded upon the identification of structural indicators that are correlated with vulnerability or proximity to thresholds, rather than threshold identification per se. Several investigations indicate that thresholds are strongly influenced by scale; multiple cross-scale interactions demonstrate the need for greater knowledge and analyses to address scale-dependent processes, i.e., critical scales and scaling laws. This feature emphasizes the relevance of thresholds and non-equilibrium dynamics in multiple natural resource management applications and in so doing demonstrates the need for a more comprehensive and integrated ecological framework capable of quantitatively assessing dynamics at multiple scales to inform management and policy recommendations for optimal management and risk assessment.
complexity science, ecological resilience, non-equilibrium ecology, self-organized systems, systems theory
Copyright © 2010 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution-NonCommercial 4.0 International License. You may share and adapt the work for noncommercial purposes provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.