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2021-present: Postdoctoral Researcher, Environmental Geography Department, Vrije Universiteit Amsterdam
2016-2021: PhD candidate, Department of Industrial and Operations Engineering, University of Michigan
agriculture & food systems | resilience & transformation & equity
The Global Resource Observatory (GRO)
The Global Resource Observatory is largest single research project being undertaken at the GSI, it investigates how the scarcity of finite resources will impact global social and political fragility in the short term. The ambitious three year project, funded by the Dawe Charitable Trust, will enable short term decision making to account for ecological and financial constraints of a finite planet.
GRO will include an open source multidimensional model able to quantify the likely short term interactions of the human economy with the carrying capacity of the planet and key scarce resources. The model will enable exploration of the complex interconnections between the resource availability and human development, and provides projections over the next 5 years.
Data and scenarios will be geographically mapped to show the current and future balance and distribution of resources across and within countries. The GRO tool will, for the first time, enable the widespread integration of the implications of depleting key resource into all levels of policy and business decision-making.
I am a senior lecturer teaching integrated water resources management and leadership courses at the department of Agricultural Engineering of University of Dschang and University of Ebolowa,Cameroon as well; holding a PhD in Applied development Sciences.
I am interested in network theory of change and agent-based. modeling.
My research interests stand between natural resource management and ecological economics. The aim of my PhD project responds to the increasing demand for cross-disciplinary agent-based models that examine the disjunction between economic growth and more sustainable use of natural resources.
My research attempts to test the effectiveness of different governance and economic frameworks on managing natural resources sustainably at both regional and national levels. The goal is to simulate how communities and institutions manage the commons in complex socio-ecological systems through several case-studies, e.g. rainforest management in Australia. It is hoped that the models will highlight which combination of variables lead to positive trends in both economic and environmental indicators, which could stimulate more sustainable practices by governments, private sectors and civil society.
My research focuses on the productivity of harvesting systems in Maine. This research generally includes on the ground observation and the conducting of time and motion studies. I recently started using agent based modelling as a tool to simulate the interaction of various machines and the change in productivity based on specific input variables.
I study human dimensions of natural resource management and resource use by under-represented populations—often in developing nations—to enhance our understanding of conflicts involving land use, natural resources, and conservation from an interdisciplinary, systematic lens. My research spans subjects such as common pool resource management and policy, decentralization, and land use/land cover change drivers and trends relating to population rise and environmental change.
Christophe Le Page currently works at the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD). Christophe does research on participatory modelling of the interactions between agriculture and the environment, focusing more specifically on the relationships among stakeholders about the management of natural renewable resources. Christophe is designing and using interactive agent-based simulation and role-playing games. He is an active member of the Companion Modelling research group.
Agent-based simulations and role-playing games in the field of renewable resource management.
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.
B.S. in Fish and Wildlife from Michigan State University in 1996. M.S. in Wildlife Ecology from the University of Maine - Orono in 2001. Employed by the Michigan Department of Natural Resources since 2003, first as a field biologist (2003-2008), then statewide endangered species coordinator (2008-2012), and currently as the statewide (climate) adaptation program lead (2012-present). Also currently a graduate student in the Boone and Crockett Quantitative Wildlife Center at Michigan State University (2015-present). Father, gardener, hiker, and amateur myxomycologist.
Human-wildlife social-ecological systems, resilience and learning in complex adaptive systems, climate change, disturbance ecology, and historical ecology
I am interested in questions of method, and in the application of computational social models to a wide variety of national security questions (such as counterterrorism and counterinsurgency) as well as decision-making around complex natural resources such as water. My methods interest center on the use of qualitative social theory to inform the structure of computational social models, and the ways in which such models handle qualitative data. This raises questions around the nature of data and the ways in which computational social models convey information to decision-makers.
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