Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

Aim:Understanding temporal changes in aquatic communities is essential to address the freshwater biodiversity crisis. In particular, it is important to understand the patterns and drivers of spatial ...

Canada experiences a relatively large number of tornadoes, which can cause a significant amount of damage and fatalities. In this study, a preferred prediction model for the spatially varying tornado ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

We develop a spatial dynamic general equilibrium model of a small open agricultural economy to study the impact of global food, fuel and fertilizer price shocks on consumption patterns of ...

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