Modeling Complex Interactions of Overlapping River and Road Networks in a Changing Landscape

The goal of this research is to develop and test the analytical tools needed to understand and predict the interactions and feedbacks among humans and aquatic species across complex landscapes. The central organizing principle is that landscape patterns and changes in river and road network structure and function are explained by energy and time optimizations of water flows, biota, and humans. The importance of road and river network intersections in determining dynamic changes to landscapes will be tested using individual/agent-based simulation modeling that integrates field-based physical, biological, and social models. The investigators will focus on the road-river linkages because river ecosystems are vulnerable to human-related perturbations that are related to road access, such as invasion by non-native species and over-harvesting of fish and shellfish. The main overarching hypothesis is that an integrated, individual-based model will more accurately predict environmental effects than any single physical, biotic, or social model by reducing unexplained variation. The mechanism generating this reduction in variance results from including cross-disciplinary connections and corresponding agent feedbacks that otherwise would be missing in the individual disciplinary models. In order to test this hypothesis, the investigators will develop an integrated individual-based model of physical, biotic, and social networks. Through analyses of a case study in Puerto Rico, the investigators expect to demonstrate that river and road intersections bring about interaction of aquatic species and visitors with mutual feedbacks. Dynamic interactions are captured by interdependent functions of each individual agent on each other and each subsystem. The approach therefore will integrate multidisciplinary field studies in geomorphology, engineering, aquatic ecology, and social science into a unified, individual-based model that will evaluate different dimensions of interacting human and natural systems. The experimental design and modeling will rely on an existing natural continuum of land use, road densities, and road types within a network structure that reflects a hierarchy of land uses as well as geomorphic and riverine features. The project will make theoretical, policy, and educational contributions to societal understanding of biocomplexity. In terms of education, two high school teacher workshops will demonstrate the use of web-based GIS models to actively engage high school seniors (and their teachers) in Puerto Rico and Colorado. The project will involve extensive participation by undergraduate and graduate research assistants and multi-institution graduate seminars in biocomplexity that will directly engage students, faculty investigators, and managers in the implementation and integration of interdisciplinary research. Graduate students at University of Puerto Rico will obtain field data on ecological and economic values of rivers in Puerto Rico. The results will also provide information about the consequences of building new roads and closing existing roads in tropical rainforest settings. The findings regarding how individual/agent-based models are effective in integrating and visualizing feedback from physical, biological, and social network interactions will be disseminated. Results of this research should increase understanding of the natural variability of large tropical drainage systems, and the methods to be developed should have broader applicability for coastal-montane ecosystems ranging from North America to New Zealand. Furthermore, we will develop a deeper understanding of how network theory enhances communication and insight across multiple disciplines. This project is supported by an award resulting from the FY 2003 special competition in Biocomplexity in the Environment focusing on the Dynamics of Coupled Natural and Human Systems.