Statement of Purpose

CNH-Style Snippet

Amalgamated Fisheries Modeling: A cross-scale approach to environmental dilemmas

This project aims to better understand systemic environmental problems, focused on fisheries management, by developing new cross-scale perspectives. Researchers will investigate how social and ecological systems at diverse scales interact, and how these insights can be integrated into a general modeling framework for coupled multi-scale dynamics.

Longer Statement

The Open World project aims to better understand systemic problems in social-ecological systems by developing new multi-scale perspectives. As an application and context, we focus on fisheries management. Fisheries collapse is a global concern, affecting world food supply and economic prospects for fishing communities, and impacting marine environments and endangered species. Management structures have struggled to manage the perverse economic incentives, multiple scales of uncertainty, and unintended feedbacks in this highly variable and spatially complex system. Policies and dynamics at regional scales, including climate, trade, and migration networks, have a complicated relationship with local choices and behaviors. By improving our understand of how scales and systems interact, we hope to reveal opportunities for more sustainable management.

To study these interactions, the Open World project explores a powerful intersection between new theoretical grounds and modeling technology. Theoretically, we seek a stronger foundation for multi-scale systems and new forms of coupling. This foundation supports the development of new frameworks for "amalgamated" modeling, which allows models at diverse scales and contexts to interact. However, such a composite model needs new theoretical and technological work to elucidate the driving principles behind the resulting dynamics.

The interactions between natural and human systems at different scales are central to many environment and resource management issues. For example, global and regional policies place constraints on local behaviors, but the collective impact of these local decisions enters the large-scale systems that define those policies. A combination of coupling across scales using downscaling and aggregation, and the interplay between large-scale networks and diffusion offers a way to understand these connections. Economic and scientific models are most effective at a given scale and context, but the boundaries between social institutions, between ecosystems, and between scales are rarely clear. Moreover, direct coupling of these models can both distort their accuracy and obfuscate the drivers behind their results. This project investigates how we can move beyond coupling, by looking at how systems and their constituent components can overlap and mutually inform each other.

To support this research, the project will build a general framework for integrating an unlimited collection of models of social-ecological systems. This framework would provide an interface between models operating at different scales and contexts and according to different techniques and assumptions. The amalgamated approach allows different policy scenarios and ecological models to be easily substituted and compared. The composite system aims to be transparent in its operation, available as a rich foundation for other researchers, and open to new contributions.

Making this modeling framework useful requires integrated cross-scale metrics and validation. The framework would also incorporate computational tools for more insightful communication. These include finding ways to identify critical feedback loops and the most salient interconnections to help construct higher level conceptual models. Another key need for environmental problems is the ability to identify leverage points, such as parameters or structures where small changes can result in pervasive differences in dynamics.