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Coupled natural human systems (CNHs) are often distinguished by how they have evolved the right fit between their biophysical and social sub-systems when faced with known/anticipated disturbances. This project addresses what happens when CNHs are exposed to a new set of disturbances or novel changes likely to occur with increased globalization and climate change.
The portion of this project conducted at Arizona State University will focus on integrating research activities by developing a conceptual socio-ecological framework to address the implications for sustainability of current and alternative policy practices and scientific knowledge gaps.
Important challenges of scientific infrastructure have slowed the spread of computational modeling into research domains where it could be most profitably used. Building on a successful, National Science Foundation-funded pilot program, we propose to establish a scientific research collaboration network to confront and begin to mitigate these issues.
We believe a better understanding of the underlying social-ecological processes driving adaptation in coastal areas – particularly the feedbacks among risk from biophysical change, cognitive processes and adaptation – will reduce the incidence of maladaptations while increasing the frequency of win-win adaptations. Findings will directly inform and support adaptation decision making in coastal areas, add to current knowledge on vulnerability and adaptation and facilitate learning and appreciation of feedbacks in adaptation responses.
The bottom-up structure of ABMs enables simulation and investigation of complex systems and their emergent behavior with a high level of detail; however, such models create large non-linear multidimensional “big data,” which are difficult to analyze using traditional statistical methods. This international collaborative project addresses these challenges by developing algorithms and web-based analysis and visualization tools that provide automated means of discovering complex relationships among variables.
The central objective of this proposal is to improve understanding of the joint consequences of socio-economic development and regional climate change by developing and applying tools to better integrate human and earth system models. We will pursue this objective by focusing on impacts in three key systems – urban areas, agriculture and forests – in three regional case studies in rapidly developing countries – China, India and Brazil.
The core question addressed in this interdisciplinary research project is why some social-ecological systems are more successful in navigating disturbances and change in the environment than others. The project will generate a deeper understanding of how societies may become fragile as they attempt to cope with uncertainty and change in the environment.
This project allows for climate modeling that produces “hind-casts” of the South African Cape climate during a glacial phase in the deep human past. The effort supports attempts at long-term climate forecasting by providing the background and paleo-models against which to test future projections.
Using new technologies and collaborating with an international coalition of scholars, we seek to build an archaeological information infrastructure that will allow archaeologists to archive, access, integrate, and mine disparate datasets in order for archaeology to approach its potential to provide long term, scientific understandings of human history.
Although the project focuses on investments in archaeology and closely related fields, its explicit and fundamental objective is to propose investments that will directly and importantly enhance the infrastructure for scientific research. This includes addressing the needs of transdisciplinary researchers who are attacking fundamental questions about the long-term interactions of human societies and their environments.