Hierarchical Modeling in Ecology

Welcome to the landing page for a cluster of books on this very broad topic at the interface of applied statistics, population ecology, wildlife management, conservation biology and biodiversity monitoring.

Quick links:

We hope you find these books useful for your work and especially the additional resources that are available here.

Hierarchical statistical models break apart a complex statistical model into a series of linked, less complex submodels by factorizing the likelihood into a series of conditional probability statements. Hierarchical models have many advantages, but the biggest two are arguably:

• They often make the fitting of a complex model easier.
• They represent a principled approach to statistical modeling where, instead of doing relatively brain-free curve-fitting exercises, you think about the processes that likely gave rise to your data set and then represent them in your model. The result is often a more science-based model. And the act of hierarchical modeling almost enforces a clearer thinking about a scientific problem than does the application of some out-of-the-box statistical procedure.

Our books apply the principles of hierarchical modeling to a large range of problems and provide countless worked example analyses using both likelihood and Bayesian inference, and for the latter using the highly popular Bayesian BUGS modeling software (originally WinBUGS and now JAGS).

Hierarchical modeling in ecology publications:

• Royle & Dorazio, 2008, Hierarchical Modeling and Inference in Ecology
• Kéry, 2010, Introduction to WinBUGS for Ecologists
• Kéry & Schaub, 2012 (BPA), Bayesian Population Analysis using WinBUGS
• Royle et al., 2014 (SCR), Spatial Capture Recapture
• Kéry & Royle, 2016 (AHM1), Applied Hierarchical Modeling in Ecology, Vol 1
• Kéry & Royle, 2021 (AHM2), Applied Hierarchical Modeling in Ecology, Vol 2
• Schaub & Kéry, 2022 (IPM), Integrated Population Models

Web tutorials:

• Bayes with JAGS – a tutorial for wildlife researchers

Discussion groups/help forums:

• unmarked - Unmarked package help forum
• HMecology - Hierarchical Modeling in Ecology
• secr - M. Efford's Spatially explicit capure-recapture(SECR) forum
• phidot.org - Wildlife ecology software help forum
• JAGS - JAGS: Just Another Gibbs Sampler forum
• Nimble - Latest and very actively developed BUGS-language software

Workshops

• phidot.org

Relevant R packages available on (or off) the CRAN repository

• unmarked - Models for Data from Unmarked Animals
• AHMbook - Functions and Data for the Book "Applied Hierarchical Modeling in Ecology" Vols 1 and 2
• IPMbook - Functions and Data for the Book "Integrated Population Models"
• jagsUI - A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses
• ubms - Similar to unmarked,but fits models with Stan and allows estimation of additional random effects (of site, year, etc.)
• wiqid - Quick and Dirty Estimates for Wildlife Populations
• spOccupancy - A package to fit spatial and nonspatial occupancy models to BIG data sets
• RPresence - A package to fit a wide variety of occupancy models

GitHub repositories with commented code

• AHM_code - up-to-date code for both AHM1 and AHM2
• AHMbook - commented code for the AHMbook package
• IPM_code - up-to-date code for the IPMbook package
• IPMbook - commented code for the IPMbook package
• jagsUI - R package to Run JAGS (Just Another Gibbs Sampler) analyses from within R
• ubms - code for the ubms package
• unmarked - code for the unmarked package

Hierarchical models in action … and at a large spatial scale

• Knaus et al. (2018): latest Swiss breeding bird atlas (FREE English version, direct download of pdf)

Other important resources on hierarchical modeling in ecology

• Occupancy estimation and modeling, 2nd edition (MacKenzie et al., 2017)
• Distance sampling
• Mevin Hooten's page
• oSCR- an R package for fitting spatial capture-recapture models
• Mike Meredith's blog
• RPresence - A package to fit a wide variety of occupancy models