FINGERPRINTING DECISIONS IN CO-EVOLVING HUMAN-LANDSCAPE SYSTEMS (Invited Presentation)

Humans have altered landscapes throughout history and pre-history with activities that include agriculture, industrialization, urban development, mining, and the construction of dams and reservoirs. With an expanding human population, the scale and pace of human impacts on Earth have intensified to the extent that new concepts such as "anthropocene" and "anthromes" have developed, and are increasingly accepted. Such concepts recognize not only the dominance of human influences in shaping landscapes, but also the intricate coupling between humans and Earth systems in their co-evolutions into the future. Guiding Earth systems toward sustainable futures, therefore, requires understanding of the two-way reciprocal interactions between human activity and landscape change. These interactions often involve impact and feedback loops that return attention to the original human system causing landscape change. In such interacting systems, human decisions represent critical junctures in the development of landscapes. Yet, they are difficult to record, understand, and incorporate in predictive models of landscape change. Despite many methodological advances in capturing human alterations of landscapes, "fingerprinting" decisions represents an outstanding challenge. This paper explores the significance of human decisions in the evolution of coupled human-landscape systems, using an example of landscape change following the 2012 Waldo Canyon wildfire of Colorado, in which human interactions were intense. First, the paper demonstrates how a series of human decisions set the course of post-fire recovery in the burned landscape. Instead of an expected return over time to pre-fire levels of runoff and sediment movement through river systems, the interacting human impacts and feedbacks transformed the landscape and made hydro-geomorphological recovery impossible. Second, the paper illustrates an application of an agent-based model that simulates these interacting impacts and feedbacks. Capable of integrating social and biophysical data, this tool offers much utility and promise for encoding decisions in geomorphic analysis of human-altered landscapes.