CNH-SBE: The Emergence of Coupled Natural and Human Landscapes in the Western Mediterranean. Pi: C. Michael Barton, Arizona State University In spite of millennia of anthropogenic landscape change, the western Mediterranean has maintained productive rural landscapes and supported dense urban populations for millennia. maintained productive rural landscapes and supported dense urban populations for millennia. In many respects, the western Mediterranean is a success story that embodies fundamental questions of sustainability: How can the earth sustain a human population rapidly growing toward 10 billion and maintain not only human life but quality of life? We propose to contribute to answering such questions through research on the emergence and subsequent dynamics of coupled natural and human landscapes in the western Mediterranean, seekingaa better understanding of how social and biophysical systems became so closely coupled, and the cascade of consequences from this coupling. This research will integrate computational modeling of the recursive processes that drive human and natural landscape dynamics, validated through empirical studies in the earth, life, and social sciences. We will develop an integrated modeling laboratory that dynamically couples components for simulating land-use decisions and practices at the household level, vegetation change, and landscape evolution. The dynamic coupling ensures that human decisions will be affected by land-cover and terrain, vegetation will be affected by land-use and landscape change, and the land surface and underlying soils/sediments will be affected by land-cover and land-use. We will carry out a series of experiments in which we systematically study the socio-ecological consequences of 1) variation in decision-making strategies that guide land-use and response to social and biophysical context; 2) variation in human population, and in the number, size, and location of communities; 3) variation agricultural land-use practice (e.g., farming vs. herding, shifting vs. intensive cultivation); and 4) variation in biophysical conditions (e.g., climate and terrain) relevant for land-use practices. Simulated proxy data (geological, botanical, cultural) will be generated during model runs that can be statistically sampled and compared with real-world proxy records of historical processes derived from empirical data collection in a series of study areas. This will help to better validate model performance and guide improvements. Data on ancient (archaeology, paleoecology, and paleoclimate) and modern (ethnographic, plant requirements, terrain) conditions also will be used to parameterize the modeling experiments in order to obtain more realistic outcomes. The intellectual merit and broader impacts of this project are closely intertwined. The emergence of coupled natural and human landscapes marked a transformative interval in the human past that set our species on the road to the urbanized, industrial world in which we live, and enabled many of the technologies and social institutions responsible for human-natural couplings in other domains. The proposed work exemplifies a new form of 'experimental socio-ecology' that has been made possible by recent advances in cyberinfrastructure. The methodologies that we proposealong with parallel work of others in the NSF CNH and related programshelp to give social science a more central role in interdisciplinary research on the grand challenges (nearly all of which are human challenges) that we face today. Because we draw on data from the distant past to parameterize and validate our models, the work has the potential to offer new insights into human prehistory. This research also contributes to applied computation and informatics in social and ecological sciences. Particularly important is the proposed work to integrate different kinds of models into a dynamically coupled simulation laboratory. The plan to embed a validation instrument in the modeling has the potential to significantly advance our ability to evaluate multi-agent and cellular models of long-term SES dynamics against the empirical record of past human and natural systems. We plan to offer diverse learning opportunities for students in this research. We make special effort to involve undergraduates and groups underrepresented in STEM fields. Participation in this research will promote computational thinking and encourage students to develop a culture of collaborating across academic disciplines.
|Effective start/end date||9/1/13 → 8/31/18|