Search
Now showing items 1-7 of 7
Designing and transferring environmental flows
Societal and environmental water needs are increasingly in conflict due to rising water demands from growing global human populations and climate-change-induced intensification of hydrologic drought. The last couple of decades have seen a blossoming of research in environmental flows – the provisioning of water within rivers ...
The statistical analysis of wildfire growth
Understanding and quantifying wildfire behavior is of interest to the scientific community, as well as public health and fire management professionals. To achieve this end, there is a demand for statistical descriptions of wildfire behavior and its relationship to the environment. However, wildfire behavior can be complex, ...
Advancing Bayesian methods in fisheries stock assessment
Inference is the process of drawing conclusions from data about unobserved quantities. Bayesian inference is one type of statistical inference and is widely applied in diverse fields. In fisheries, it has many advantages, notably a statistically rigorous way of including information from other studies (through prior distributions) ...
Modeling population dynamics and species interactions in a changing climate
Many species are expected to undergo significant distributional shifts in response to changes in climate. This adaptive response can impact population dynamics in many ways, including decreasing reproductive fitness, limiting dispersal, shrinking habitat, and exposing organisms to new competition from invasive species. What ...
Wildfire disturbance shapes the physical and biological condition of Pacific Northwest stream ecosystems
Wildfire constitutes one of the most influential processes affecting watershed conditions across the Pacific Northwest. Although the patterns and impacts of wildfire are well-described for terrestrial ecosystems, a comprehensive understanding of wildfire effects in aquatic ecosystems is still being developed. The occurrence ...
Adaptive Bayesian Nonparametric Smoothing with Markov Random Fields and Shrinkage Priors
The need to estimate unknown functions or surfaces arises in many disciplines in science and there are many statistical methods available to do this. Our interest lies in using Bayesian nonparametric approaches to estimate unknown functions. One such approach to nonparametric estimation is based on the Gaussian Markov random ...
Modeling individual lodgepole pine mortality from mountain pine beetle outbreak in a spatially explicit framework
Outbreaks of native bark beetles (Curculionidae: Scolytinae) are key natural disturbances that shape the structure and function of conifer forests across the northern hemisphere. While drivers of bark beetle outbreaks have been studied extensively at spatial scales ranging from stands to continents, within-stand processes ...