Displaying 10 of 12 results conservation clear search
Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
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.
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
Aniruddha Belsare is a disease ecologist with a background in veterinary medicine, interspecific transmission, pathogen modeling and conservation research. Aniruddha received his Ph.D. in Wildlife Science (Focus: Disease Ecology) from the University of Missouri in 2013 and subsequently completed a postdoctoral fellowship there (University of Missouri, May 2014 – June 2017). He then was a postdoctoral fellow in the Center for Modeling Complex Interactions at the University of Idaho (June 2017 - March 2019) and later a Research Associate with the Boone and Crockett Quantitative Wildlife Center, Michigan State University (March 2019 - Jan 2021). He was a Research Scientist in the Civitello Disease Ecology Lab at Emory University from Jan 2021 to Jan 2023. Currently, Aniruddha is an Assistant Professor of Disease Ecology at the College of Forestry, Wildlife & Environment / College of Veterinary Medicine at Auburn University.
My research interests primarily lie at the interface of ecology and epidemiology, and include host-pathogen systems that are of public health or conservation concern. I use ecologic, epidemiologic and model-based investigations to understand how pathogens spread through, persist in, and impact host populations. Animal disease systems that I am currently working on include canine rabies, leptospirosis, chronic wasting disease, bighorn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), chytridiomycosis, and Lyme disease.
Lu Ping is a dedicated researcher in interdisciplinary fields including artificial intelligence (AI), digital economy, technological innovation, and industrial economics. Currently serving as an Associate Research Fellow at the China Academy of Information and Communications Technology (CAICT), Lu Ping focuses on examining the impacts of digital technologies (e.g., AI, big data, and IoT) on economic growth, industrial ecosystems, policy formulation, and societal ethics through multidimensional data modeling and empirical research.
Representative Academic Contributions:
1. AI Development and Societal Implications
A Brief History of Artificial Intelligence Development in China (2017): Explored the technological evolution and policy-driven pathways of China’s AI industry.
Ethical Dilemmas Faced by AI Algorithms (2018): Analyzed ethical challenges such as algorithmic bias and data privacy, proposing governance frameworks.
A Brief History of the Evolution of Smart Hardware in China (2018): Systematically reviewed the technological iterations and market dynamics of China’s smart hardware sector.
2.Technological Innovation and Industrial Economics
An Empirical Analysis of Technological Innovation Driving Growth in Internet Companies: Evidence from A-Share Listed Internet Firms in Shanghai and Shenzhen (2019).
Research on Competitiveness Measurement of Frontier Emerging Industries Based on Data Envelopment Analysis (DEA) Models (2019).
3.Digital Economy and Market Behavior
Correlation Analysis of Crowdfunding Behavior and Funding Performance for Internet Products: A Bayesian Approach Based on JD.com Crowdfunding Data (2018): Uncovered nonlinear relationships between user participation and project success rates using crowdfunding platform data.
Analyzing the Effects of Developer and User Behavior on Mobile App Downloads (2019): Built predictive models for app market performance based on user behavior data.
4.Policy Simulation
General Equilibrium Analysis of Beijing’s Water Supply and Consumption Policies: A Computable General Equilibrium (CGE) Model-Based Approach (2015).
Impact Analysis of EU Food Safety Standards on China’s Food Industry: A Dynamic Global Trade Analysis Project (GTAP) Model-Based Study (2015).
Academic Contributions:
Pioneered interdisciplinary paradigms in industrial economics research by integrating perspectives from econometrics, data science, and sociology. Published high-impact research in AI ethics, digital economy policies, and resource-environmental economics, providing decision-making references for academia and policymakers.
My research focuses on the interdisciplinary nexus of artificial intelligence (AI), digital economy, technological innovation, and industrial economics, with an emphasis on understanding how digital technologies reshape economic structures, policy frameworks, and societal norms. Key areas of interest include:
Prof. Christian E. Vincenot is by nature an interdisciplinary researcher with broad scientific interests. He majored in Computer Science / Embedded Systems (i.e. IoT) at the Université Louis Pasteur (Strasbourg, France) while working professionally in the field of Computer Networking and Security. He then switched the focus of his work towards Computational Modelling, writing his doctoral dissertation on Hybrid Modelling in Ecology, and was awarded a PhD in Social Informatics by Kyoto University in 2011 under a scholarship by the Japanese Ministry of Research. He subsequently started a parallel line of research in Conservation Biology (esp. human-bat conflicts) under a postdoctoral fellowship of the Japanese Society for the Promotion of Science (JSPS) (2012-2014). This led him to create the Island Bat Research Group (www.batresearch.net), which he is still coordinating to this date. In 2014, he was appointed as the tenured Assistant Professor of the Biosphere Informatics Laboratory at Kyoto University. He also been occupying editorial roles for the journals PLOS ONE, Frontiers in Environmental Science, and Biology. In 2020, he created Ariana Technologies (www.ariana-tech.com), a start-up operating in the field of Data Science/Simulation and IoT for crisis management.
Prof. Vincenot’s main research interests lie in the theoretical development of Hybrid Mechanistic Simulation approaches based on Individual/Agent-Based Modeling and System Dynamics, and in their applications to a broad range of systems, with particular focus on Ecology.
Displaying 10 of 12 results conservation clear search