Recent Workshops and Webinars
Hierarchical spatial modelling for applied population and community ecology
Four-day workshop on applied hierarchical spatial modeling with the spOccupancy and spAbundance R packages.
Hierarchical models have been widely deployed for the modelling of species distribution and abundance, because they enable one to separately model the actual quantity of interest (e.g., presence/absence or abundance) from measurement errors commonly found in ecological data sets. When modelling species distributions/abundance across large spatial domains and/or using a large number of observed locations, accommodating spatial autocorrelation becomes increasingly important. In this workshop, we present highly scalable approaches for hierarchical Bayesian spatial modelling of species distributions and abundance, focusing on practical implementation using the spOccupancy and spAbundance R packages.
Scalable Bayesian models and estimation methods for the analysis of big spatial and spatio-temporal data
One day introduction to Bayesian models for analysis of big spatial and spatio-temporal data, part of the Conference on Applied Statistics in Agriculture and Natural Resources.
Bayesian hierarchical models have been widely deployed for analyzing spatial and spatio-temporal datasets commonly encountered in forestry, ecology, agriculture, and climate sciences. In this course, we present scalable Bayesian models and related estimation methods that provide fast analysis of big spatial and spatio-temporal data using modest computing resources and standard statistical software such as R, including the Nearest Neighbor Gaussian Process (NNGP) and its implementation in the spNNGP and spOccupancy R packages. The workshop closes with a focused session on occupancy modeling to assess wildlife species distributions while accounting for measurement errors common in detection-nondetection data.
Spatially-explicit occupancy modeling with the spOccupancy R package
Half-day introductory workshop on the use of spOccupancy for fitting a variety of spatial occupancy models.
We presented an accessible overview of single-species, multi-species, and integrated spatially-explicit occupancy modeling with a focus on implementing these models using the spOccupancy R package, emphasizing practical software tools rather than statistical details.
Introduction to Applied Bayesian Analysis in Wildlife Ecology
One day introduction to Bayesian analysis for graduate students and early professionals in the wildlife sciences.
Management and conservation of wildlife in the 21st century involves myriad data collection approaches, ranging from traditional field surveys to camera trapping, acoustic recording, GPS tags, genetic data, and public science data. These disparate data types require state-of-the-art statistical approaches. In this workshop, I provided a gentle introduction to Bayesian modeling and its application in wildlife ecology, then took a guided tour of implementing different types of statistical models in a Bayesian framework using the R package brms.
Spatial occupancy models with the spOccupancy R package
Short webinar introduction to the spOccupancy R package.
Occupancy modeling is a common approach to assess species distribution patterns across space and/or time while explicitly accounting for false absences in detection-nondetection data. This presentation introduces occupancy modeling as a robust form of species distribution model, then details how to fit single-species and multi-species spatial and non-spatial occupancy models with spOccupancy, including integrated, multi-season, and correlated multi-species models.