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.

Royle & Dorazio, 2008

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:

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:

Discussion groups/help forums:


Relevant R packages available on the CRAN repository

GitHub repositories with commented code

Currently under development

Other important resources on hierarchical modeling in ecology

page last updated: 26-Oct-2020