Section on Environmental Sciences (EnviBayes)
Environmental sciences address a broad variety of problems requiring an interdisciplinary approach. Such problems include ecosystem changes, extreme events, earth processes, pollution, effects of global climate change. These issues are characterized by great process complexity with associated large datasets, typically in space and time, resulting in high dimensionality for models.
Multilevel modelling facilitates the understanding of complex; environmental phenomena; in particular, hierarchical Bayesian models constitute an efficient tool to exploit diverse sources of information, to accomodate influences that are unknown, and to draw inference on large numbers of latent variables and parameters that describe complex relationships. Furthermore, such analyses offer the possibility of providing a consequential societal impact in terms of environment regulation and public policy. Examples include assessment of the effects of climate change, interpolating and predicting exposure to environmental contaminants, and mitigation of damages and the risk reduction using probabilistic forecast of the natural catastrophes.
For this we propose an ISBA section on Environmental Sciences. This section will:
- facilitate the exchanges between Bayesian statisticians operating in different environmental sciences
- enable a connection point for the field experts who recognize the potential of Bayesian approach but are not still skilled in this discipline.
The Section will:
- promote research in Bayesian methods in environmental sciences, by organising conferences, workshops, and sessions in other meetings;
- promote education in Bayesian methods in environmental sciences by developing shortcourses for students and practitioners; and
- promote interactions among academic and environmental and public health organizations.
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Lawrence Berkeley National Laboratory
Berkeley, California, USA.
April 28, 2019
March 31 – April 2, 2016
Columbus, OH USA
May 30, 2017
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