Monday, April 09, 2012, 12:00PM - 1:00PM
Arizona State University
ARC room 620
Humans are the primary driver of landscape change today, with more terrestrial sediment moved, more Nitrogen cycles, and more surface water used through anthropogenic than natural processes. Yet most widely used quantitative models of landscape change do not account for these anthropogenic drivers. Part of the problem is conceptual, but another is methodological. Natural surface dynamics are driven by a limited suite of physical forces, which are reasonably well understood and can be represented in equation form even though their interations can be complex. Social drivers of landscape change, on the other hand, are not well understood and commonly are characterized in the form of qualitative narratives. Moreover, both landscapes and social processes vary simultaneously in both temporal and spatial dimensions, a reality that is often ignored in common models (quantitative and qualitative) of these dynamics. This makes it very challenging to model combined human-landscape interactions.
Yet new computational modeling tools are becoming available to represent social processes in quantitative ways that incorporate rather than ignore diverse decision-making at individual and institutional levels. New approaches also can represent dynamics across space and time in ways that allow social inputs to landscape change to be better modeled. And there are beginning efforts to permit the coupling of very different kinds of modeling. Together, these offer the potential for significant new insights into the causes and consequences of change in the complex socio-ecological systems that dominate today's world. I present some examples of my recent work in exploring and applying these new approaches to understand long-term interactions between people and landscapes.