Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, and Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press.
This is based in part on the in-person tutorials that they and the other authors have been giving on statistical modeling for ecology.
The book starts at the beginning with an introduction to R, regression and ANOVA, discusses maximum likelihood estimation, then generalized linear models including “mixed effects” models, and then proceeds to Bayesian modeling with MCMC computation for inference, and winds up with some case studies involving BUGS and Stan. Everything works up from simple “hello world” type programs through real examples, which I really appreciate myself in computational examples.
Stan’s primarily showcased in three fully worked out examples (which I also really appreciate as a reader), all of which appear in Chapter 14, “Advanced Ecological Models”:
(14.2) zero-inflated Poisson mixed model for analyzing breeding success,
(14.3) occupancy model to measure species distribution, and
(14.5) analyzing survival based on mark-recapture data.