State–space models (SSMs) are an important modeling framework for analyzing ecological
time series. These hierarchical models are commonly used to model population dynamics …

Integrated population models (IPMs) represent the single, unified analysis of population
count data and demographic data. This modelling framework is quite novel and can be …

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines
the Bayesian and frequentist methods of conducting data analyses. The book provides the …

Binomial N‐mixture models have proven very useful in ecology, conservation, and
monitoring: they allow estimation and modeling of abundance separately from detection …

Abstract Changes in the abundance and distribution of wildlife populations are common
consequences of historic and contemporary climate change. Some Arctic marine mammals …

Emphasizing model choice and model averaging, this book presents up-to-date Bayesian
methods for analyzing complex ecological data. It provides a basic introduction to Bayesian …

The dynamics of many populations is strongly affected by immigrants. However, estimating
and modelling immigration is a real challenge. In the past, several methods have been …

In Borchers et al.(2002), a unifying framework was given for the plethora of methods for
estimating the abundance of closed populations of animals. In Chap. 13 of that book, the …

Structured population models are widely used in plant and animal demographic studies to
assess population dynamics. In matrix population models, populations are described with …

Statistical and mathematical models are defined by parameters that describe different
characteristics of those models. Ideally it would be possible to find parameter estimates for …