Spatial distribution models, Switzerland, 24-27 June 2024

[Marc Kery]

Hierarchical spatial modelling for applied population and community ecology

Intermediate-level workshop (in person)

Instructors: Jeff Doser (Michigan State University), Marc Kéry (Swiss Ornithological Institute)
Teaching Assistant: Gesa von Hirschheydt (Swiss Federal Institute for Forest, Snow and Landscape Research WSL)
Venue: Swiss Ornithological Institute, Sempach, Switzerland
Dates: 24-27 June 2024
Computers: Bring your own laptop with recent version of R installed and R packages spOccupancy and spAbundance
Registration: 500 Swiss Francs (normal rate), 350 Francs (student rate)

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. Failing to account for measurement errors and/or residual spatial autocorrelation (i.e., remaining spatial autocorrelation after accounting for environmental covariates) can lead to biased and overly precise estimates, potentially jeopardizing scientific conclusions and management decisions based on such data sets.
In this workshop, we present highly scalable approaches for hierarchical Bayesian spatial modelling of species distributions and abundance. This course focuses on practical implementation of hierarchical spatial models using the spOccupancy and spAbundance R packages. Course topics include:
1. Introduction to hierarchical and spatial modelling
• Hierarchical Bayesian models in ecology
• Introduction to spatial statistics (e.g., kriging, Gaussian Processes)
• Spatial modelling of big data
2. Spatial modelling of binary detection-nondetection data with spOccupancy
• Single-species spatial occupancy models
• Multi-species spatial occupancy models
• Joint species distribution models with imperfect detection
• Spatially-varying coefficient occupancy models
3. Spatial modelling of count data with spAbundance
• Spatial GLMMs, N-mixture models, and hierarchical distance sampling models
This intermediate-level course offers lecture, discussion, and hands-on exercises, with approximately 70% of the time on lectures and 30% of the time on exercises. We do not assume previous experience with Bayesian statistics, spatial statistics, or spOccupancy/spAbundance, although participants with basic knowledge of these areas will experience a gentler learning curve. We do require a good working knowledge of modern regression methods (e.g., linear models, generalized linear models) and of program R.

Application instructions
Please send an email to Jeff Doser ([url]doserjef@msu.edu[/url]) and Marc Kéry ([url]marc.kery@vogelwarte.ch[/url]). In the email, briefly describe your background and knowledge in statistical modelling, R, and occupancy/N-mixture models by 29 March 2024. Workshop invitations will be sent out shortly thereafter.

One or two course fee waivers will be available provided we get a sufficient number of paying sign-ups. To apply, please send us a description (at most 0.5 page) of why the course would be important for your work and why you should get a waiver.