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United States Department of Agriculture

Agricultural Research Service

Title: Spatial Nonlinearities: Cascading Effects in the Earth System

item Peters, Debra
item Bestelmeyer, Brandon
item Allen, Craig - USGS, JEMEZ MT RES STA
item Munson-Mcgee, Stuart - NEW MEXICO STATE UNIV
item Havstad, Kris

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: July 25, 2005
Publication Date: January 15, 2007
Citation: Peters, D.C., Pielke, R.A., Bestelmeyer, B.T., Allen, C.D., Munson-McGee, S., Havstad, K.M. 2007. Spatial nonlinearities: Cascading effects in the earth system. In: Canadell, J.G., Pataki, D.E., Pitelka, L.F., editors. Terrestrial Ecosystems in a Changing World. Berlin Heidelberg: Springer-Verlag. p. 165-174.

Interpretive Summary: Interpretive summary not required.

Technical Abstract: Nonlinear interactions and feedbacks associated with thresholds through time and across space are common features of biological, physical and materials systems. These spatial nonlinearities generate surprising behavior where dynamics at one scale cannot be easily predicted based on information obtained at finer or broader scales. These cascading effects often result in severe consequences for the environment and human welfare (i.e., catastrophes) that are expected to be particularly important under conditions of changes in climate and land use. In this chapter, we illustrate the usefulness of a general conceptual and mathematical framework for understanding and forecasting spatially nonlinear responses to global change. This framework includes cross-scale interactions, threshold behavior and feedback mechanisms. We focus on spatial nonlinearities produced by fine-scale processes that cascade through time and across space to influence broad spatial extents. Here we describe the spread of catastrophic events in the context of our cross-disciplinary framework using examples from biology (wildfires, desertification, infectious diseases) and engineering (structural failures) and discuss the consequences of applying these ideas to forecasting future dynamics under a changing global environment.

Last Modified: 4/22/2015
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