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Christopher K. Wikle

Abstract (from http://sp.lyellcollection.org/content/early/2015/10/09/SP408.11.abstract): We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, climate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation...
Many real-world scientific processes are governed by complex non-linear dynamic systems that can be represented by differential equations. Recently, there has been an increased interest in learning, or discovering, the forms of the equations driving these complex non-linear dynamic systems using data-driven approaches. In this paper, we review the current literature on data-driven discovery for dynamic systems. We provide a categorisation to the different approaches for data-driven discovery and a unified mathematical framework to show the relationship between the approaches. Importantly, we discuss the role of statistics in the data-driven discovery field, describe a possible approach by which the problem can be...
Categories: Publication; Types: Citation
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Projecting Future Impacts to River Systems and Large River Fish: Missouri River Sturgeon Example
In collaboration with the University of Missouri and Iowa State University, this project advanced efforts to understand and accommodate uncertainty by applying to Missouri River sturgeon population dynamics the tools of multi-scale climate models and hierarchical Bayesian modeling frameworks, linking models for system components together by formal rules of probability. While a complete climate prediction may be intractable at this time -- for instance, the climate projections may not incorporate land use changes and solar fluctuations into the boundary conditions -- we proposed a framework to quantify known uncertainty that is also flexible enough to adapt to advances in climate predictions. A key advantage of the...
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