Applied hierarchical modelling (AHM) for species dist&Abund

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Applied hierarchical modelling (AHM) for species dist&Abund

Postby jhines » Tue Jan 31, 2023 11:29 am

    Instructors: Marc Kéry, Ken Kellner & Andy Royle Swiss Ornithological Institute, Switzerland; Michigan State University, MI, USA; USGS Eastern Ecological Science Center, MD, USA

    Date: 17–21 July 2023

    Venue: USGS Eastern Ecological Science Center - Patuxent Research Refuge. Address: 12100 Beech
    Forest Road, Laurel, MD 20708.

    Computers: Bring your own laptop with R and JAGS and R packages NIMBLE, unmarked, and ubms

    Registration: 600 US$ (normal rate), 400 US$ (student rate)

    Intermediate-level workshop (in person)

Hierarchical models (HMs) are tremendously powerful in the modeling of species distribution and
abundance, because they enable one to separately model the actual quantity of interest (typically
presence/absence or abundance) from the measurement errors that contaminate all SDM data sets: false
negatives and false positives. When these ubiquitous sources of errors are not adequately modeled, serious
bias may result and jeopardize scientific conclusions and management decisions based on such data sets.

In this workshop we present some of the most useful HMs for species distribution and abundance
and for both static and dynamic (i.e., changing) populations. Specifically, we cover the following topics:

    • Occupancy models for binary detection/nondetection data
    • Binomial N-mixture models for replicated count data
    • Multinomial N-mixture models for replicated capture-recapture data
    • Distance sampling models for a variety of distance sampling protocols
    • Modeling of false positives
    • Integrating multiple data types and integrated models
The course will be based on the two successful books "Applied hierarchical modeling in Ecology" by Kéry &
Royle (Volume 1/2016, Volume 2/2021). Model fitting will be conducted by likelihood methods (i.e.,
through the R package \texttt{unmarked}) and by Bayesian MCMC methods through software JAGS, NIMBLE and
the R package \texttt{ubms}.

In this intermediate-level workshop about 90% of the time is spent on lecturing and 10% on solving
exercises. Some previous experience with BUGS software, or Bayesian statistics, is not assumed, but
helpful, as is some previous exposure to occupancy and Nmix models. However, a good working
knowledge of modern regression methods and of program R is required.


Please send your application to Andy Royle (aroyle@usgs.gov), with CC to
marc.kery@vogelwarte.ch and kellner7@msu.edu, and describe your background and knowledge in
statistical modelling, R and JAGS/Nimble, and occupancy/Nmix models, by 30 April 2023.

One or two course fee waivers will be available provided we get a sufficient number of paying signups. To apply, please send us a description (at most 0.5 page) of why the course woudl be important for your work and why you should get a waiver.
jhines
 
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Joined: Fri May 16, 2003 9:24 am
Location: Laurel, MD, USA

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