Displaying 10 of 413 results for "J Van Der Beek" clear search
My research focuses on pastoral systems. I examine how pastoralists adapt to changing ecological, political and institutional conditions that affect their lives and livelihoods. I have been conducting research with pastoralists in the Far North Region of Cameroon since 1993. The long-term research has allowed me to develop innovative, interdisciplinary research projects with colleagues at the Ohio State University and the University of Maroua in Cameroon. Check out my website for more information about my research, teaching, and other scholarly activities: http://mlab.osu.edu
Pastoral systems, management of common-pool resources, coupled human and natural systems, complex adaptive systems, regime shifts, resilience, ecology of infectious diseases, herder-farmer conflicts, pastoral development, political ecology.
I am a computational archaeologist and Professor of Anthropology at San Diego State University, where I direct the Computational Archaeology Laboratory. My research integrates geospatial analysis, agent-based and simulation modeling, and complex adaptive systems theory to investigate long-term human–environment interactions, with particular attention to socio-environmental change associated with early farming and herding in Mediterranean and other semi-arid landscapes. I have conducted field and modeling research in regions including Italy, Jordan, and Central Asia, and my work spans landscape archaeology, land-use dynamics, and environmental modeling. I have been a member of the CoMSES community for well over a decade and have contributed multiple models to the Computational Model Library, several of which have undergone formal peer review. In addition to research, I regularly teach with agent-based models at undergraduate and graduate levels and use CoMSES models as both research and pedagogical resources. I am committed to open, reproducible, and theoretically informed computational modeling and to strengthening the role of peer-reviewed models as durable scholarly contributions.
Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean
Evolutionary Dynamics, Public Good Games, Emergence of Cooperation.
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
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