COMPUTATIONAL SOCIAL SCIENCE

CSS SEMINAR - February 26 - Steve Scott

Friday, February 26, 3:00 p.m.
Center for Social Complexity
3rd Floor Research Hall

Steve Scott, PhD Candidate
Computational Social Science Program
Department of Computational and Social Sciences
George Mason University

COMPUTATIONAL MODELING FOR MARINE RESOURCE MANAGEMENT

ABSTRACT: Many of the world’s fisheries are experiencing significant declines in production due to excess harvesting, climate change, habitat loss, disease, and pollution. Developing effective policies to manage these marine resources is challenging, as estimates of resource growth and depletion are often uncertain, and socioeconomic and political factors often emphasize short-term gains over long-term outcomes. Policy makers need new techniques that account for the complex interactions among biological, social and behavioral, economic, and policy domains in fishery management.

Classical bioeconomic methods are still widely used for marine policy analysis. These methods employ mathematical models expressing resource growth and harvest as a series of equations, providing an overview of the expected long-term trajectory of a natural resource system over time. More recently, policy analysts have begun using Management Strategy Evaluation (MSE), a methodology that includes stakeholder analysis, explicit definition of management goals and timelines, and prominent use of computational modeling techniques to project a range of possible future outcomes under various policy scenarios. Much of contemporary MSE modeling, however, still relies on classical bioeconomic techniques which have well known limitations.

This research demonstrates the use agent-based models (ABMs) as an alternative to classical bioeconomic methods for MSE in marine environments. Abstract, spatially explicit ABMs are used to model the biology of stock dynamics, social and behavioral interactions among fishermen, economic market factors, and various fishery management policies in three case studies of US commercial fisheries from 1980 to 2010. The results show that ABMs can provide useful insights for policy analysts applying MSE techniques in the assessment of marine resource management policies.