Spatio-temporal joint species distribution modeling – A community-level basis function approach
You are welcome to attend the following joint La Trobe statistics and stochastic and Probability Victoria zoom seminar.
- Thursday 21 October 2021 12:00 pm until Thursday 21 October 2021 01:00 pm (Add to calendar)
- Andriy Olenko
- Presented by:
- Dr Francis K.C. Hui, ANU
- Type of Event:
The last decade in ecology has seen the development and rising popularity of joint species distribution modeling
approaches for studying species assemblages, with by far the most common approach being based around
generalized linear latent variable models (LVMs). However, while methodological and computational advances
continue to be made with LVMs, their application to spatio-temporal multivariate abundance data i.e., observations
of multiple species recorded across space and/or time, remains computationally challenging and not necessarily
scalable when it comes to fitting and inference.
In this talk, we propose an alternative approach to spatio-temporal joint species distribution modeling which breaks
away from the LVM framework. Inspired by the concept of fixed rank kriging, we employ a set of fixed, communitylevel
spatial and/or temporal basis functions, with corresponding species-specific random slopes to account for
spatio-temporal correlations both within and between species. The resulting community-level basis function model
(CBFM) can be used for the same array of purposes as LVMs, but is designed to be computationally much more
efficient given they can be set up and thus fitted using the same machinery as for generalized additive models.
Simulations and an application to a demersals fish dataset collected off the Northeast US continental shelf illustrate
the potential of CBFMs for scalable spatio-temporal joint species distribution modeling.
Zoom meeting link: https://unimelb.zoom.us/j/86951431269?pwd=S1FPSFBHLzd5QkpGYlJIYS9wUGtLUT09
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Password: 422668 (just in case).
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