Modelling of socio-ecological systems and management of common property resources in artisanal fisheries. Population dynamics of coastal marine invertebrates exploited by artisanal fisheries.
Researcher in social simulation or Computational social scientists
in LISC (Irstea), and associate researcher in LAPSCO (UCA) https://www.lapsco.fr/HUET-Sylvie.html
Eric is a Research Fellow in the Complexity programme at the MRC/CSO Social and Public Health Unit at the University of Glasgow, working on agent-based simulation approaches to complex public health issues. Prior to this he was a Research Lecturer/Senior Lecturer in Artificial Intelligence and Interactive Systems in the School of Computing at Teesside University. Before working at Teesside, he worked on the CLC Project at the University of Southampton, a multidisciplinary project which focuses on the application of complexity science approaches to the social science domain.
Eric received a BA with Honours in Psychology from Pennsylvania State University, and a PhD from the School of Computing at the University of Leeds. After his PhD, he worked as a JSPS Postdoctoral Research Fellow at the University of Tokyo, conducting research in computer simulation and robotics.
I am interested in the dynamics of cultural transmission, especially in diffusion of religious innovations (concepts and practices) across a population. In my dissertation, I am targeting this issue while studying and modelling the development of Christian meal practices in the first four centuries CE across the Roman Mediterranean.
Ecology and population dynamics of fish and wildlife populations, epidemiology, biometry
Primate evolutionary biologist and geneticist at the University of Texas at Austin
I conduct long-term behavioral and ecological field research on several species in the primate community of Amazonian Ecuador to investigate the ways in which ecological conditions (such as the abundance and distribution of food resources) and the strategies of conspecifics together shape primate behavior and social relationships and ultimately determine the kinds of societies we see primates living in. This is a crucial and central focus in evolutionary anthropology, as understanding the ways in which behavior and social systems are shaped by environmental pressures is a fundamental part of the discipline.
I complement my field studies with molecular genetic laboratory work and agent-based simulation modeling in order to address issues that are typically difficult to explore through observational studies alone, including questions about dispersal behavior, gene flow, mating patterns, population structure, and the fitness consequences of individual behavior. In collaboration with colleagues, I have also started using molecular techniques to investigate a number of broader questions concerning the evolutionary history, social systems, and ecological roles of various New World primates.
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 is currently a Computational Ecologist in the Civitello Lab at Emory 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, big horn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), and Lyme disease.
Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.
How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.
Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.
Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour
Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.
Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.
Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.
neural computation, population dynamics
STDs, HIV, Hepatitis C in prison populations