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Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
General Question:
Without Central Control is self organization possible?
Specific Case:
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
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Hi. I’m Wolf. I’m the Argelander (Tenure-Track Assistant) Professor for Integrated System Modeling for Sustainability Transitions at the University of Bonn, Germany.
We reshape human-environment modeling to identify critical leverage points for sustainability transitions.
Cooperation at scale – in which large collectives of intelligent actors in complex environments seek ways to improve their joint well-being – is critical for a sustainable future, yet unresolved.
To move forward with this challenge, we develop a mathematical framework of collective learning, bridging ideas from complex systems science, multi-agent reinforcement learning, and social-ecological resilience.
My profound interest in networks convinced me to work in these subjects and start my master project on an application of social network analysis for detecting organized fraud in Automobile insurance, which helps to flag groups of fraudsters. The key point of this project is simply to find fraudulent rings, while the most of traditional methods have only taken opportunistic fraud into consideration. My duty in research is to design an algorithm for identifying cyclic components, then to be compared with theoretical ones. This project showed me how networks are used in the analysis of relations.
Andrew Bell (Ph.D. 2010, Michigan) was a Research Fellow in the Environment and Production Technology Division at the International Food Policy Research Institute (IFPRI) in Washington, DC. His current research portfolio focuses on the use of field instruments – such as discrete choice experiments, framed field experiments, randomized control trials – to inform behavior in agent-based models of coupled human-natural systems. Prior to this post, Andrew was a post-doctoral research fellow at The Earth Institute at Columbia University, where he focused on developing applications for paleo-climate histories.
Dr. Gravel-Miguel is currently looking for work. For the past 2.5 years, she worked as a Research Scientist at the New Mexico Consortium, training Machine Learning models to find archaeological sites in lidar-derived imagery. Before that, she worked as a Postdoctoral Research Scholar for the Institute of Human Origins at Arizona State University. She does research in Archaeology and focuses on the Upper Paleolithic of Southwest Europe.
Archaeology, GIS, ABM, social networks, portable art, ornaments, data science, machine learning, lidar
I’m a Research Associate in Computational Social Science at Durham University working on a project that intends to produce more realistic artificial social networks (RASN) for simulation by creating a taxonomy of existing generator papers, accessible as an interactive, open-access database, in addition to exploring the interdependencies of social network’s structural properties. I obtained my PhD from University of Glasgow in (2023) where I was working on modelling national identity polarisation on social media platforms using ABMs.
agent-based models, social networks, echo chambers, polarisation, social influence, protest mobilisation
NetLogo, R, Julia, and Python
I obtained my undergraduate degree in Mathematics at Worcester College, Oxford University. I then worked for 9 years for the UK government before returning to university to study for a MSc and PhD at UCL. On leaving UCL I started working in the insurance industry, where I develop models of cyber catastrophe events.
Key research interests are how to build models of complex human behaviour.
My PhD research project was focussed on building a model of the process by which people develop the propensity to commit acts of crime or terrorism, from which came a computer simulation of the radicalisation process.
My current research interest is on creating models of cyber threats.
Moscow City University, Professor: Institute of Digital Education - http://digida.mgpu.ru
National Research University Higher School of Economics, Professor: Institute of Education / Department of Educational Programmes. Leading Expert: Institute of Education / Laboratory for Digital Transformation of Education - 2019 – present
2016 – present Leading Researcher at Moscow City University, Educational policies & educational practices
2018 – 2020 World Bank, Consultant. Children Learning to Code: Essential for 21st Century Human Capital
2011 - 2019 - Co-founder, chief community officer at WikiVote!
Educational network - Letopisi.org 2006 – present, Co-founder, chief community officer
Scientific project “Mobile and ubi-learning”, 2009 - 2011
ABM, wiki, NetLogo, StarLogo Nova, R, Collaboration
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