Uncovering ecological state dynamics with hidden Markov models
Ecological systems can often be characterised by changes among a finite set of underlying
states pertaining to individuals, populations, communities or entire ecosystems through time …
states pertaining to individuals, populations, communities or entire ecosystems through time …
A guide to state–space modeling of ecological time series
State–space models (SSMs) are an important modeling framework for analyzing ecological
time series. These hierarchical models are commonly used to model population dynamics …
time series. These hierarchical models are commonly used to model population dynamics …
TMB: automatic differentiation and Laplace approximation
TMB is an open source R package that enables quick implementation of complex nonlinear
random effects (latent variable) models in a manner similar to the established AD Model …
random effects (latent variable) models in a manner similar to the established AD Model …
Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions
We discuss hidden Markov‐type models for fitting a variety of multistate random walks to
wildlife movement data. Discrete‐time hidden Markov models (HMMs) achieve considerable …
wildlife movement data. Discrete‐time hidden Markov models (HMMs) achieve considerable …
Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns
Increased availability of high-resolution movement data has led to the development of
numerous methods for studying changes in animal movement behavior. Path segmentation …
numerous methods for studying changes in animal movement behavior. Path segmentation …
A stochastic surplus production model in continuous time
Surplus production modelling has a long history as a method for managing data‐limited fish
stocks. Recent advancements have cast surplus production models as state‐space models …
stocks. Recent advancements have cast surplus production models as state‐space models …
Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges
With the influx of complex and detailed tracking data gathered from electronic tracking
devices, the analysis of animal movement data has recently emerged as a cottage industry …
devices, the analysis of animal movement data has recently emerged as a cottage industry …
Landscape-scale forest loss as a catalyst of population and biodiversity change
Global biodiversity assessments have highlighted land-use change as a key driver of
biodiversity change. However, there is little empirical evidence of how habitat …
biodiversity change. However, there is little empirical evidence of how habitat …
State-space models' dirty little secrets: even simple linear Gaussian models can have estimation problems
State-space models (SSMs) are increasingly used in ecology to model time-series such as
animal movement paths and population dynamics. This type of hierarchical model is often …
animal movement paths and population dynamics. This type of hierarchical model is often …
Comparative performance of data-poor CMSY and data-moderate SPiCT stock assessment methods when applied to data-rich, real-world stocks
All fish stocks should be managed sustainably, yet for the majority of stocks, data are often
limited and different stock assessment methods are required. Two popular and widely used …
limited and different stock assessment methods are required. Two popular and widely used …