Fisheries

Nonstationarity in Spatiotemporal Fisheries Models

Many fish species occur in areas with complicated geography. Natural barriers such as islands and coastlines mean that the spatial structure of the population is unlikely to be stationary. Here I develop and fit a spatiotemporal model that accounts …

A spatiotemporal model for combining survey and fishery data

Sustainable fisheries management requires the best stock assessments available in order to determine the current state of a stock and its trend over time. These estimates are typically based on fishery-independent surveys conducted specifically to …

Fishery-dependent data in a spatio-temporal context

Spatially-explicit catch and effort data is increasingly available, and may provide an important source of information for estimating abundance. There is potential to improve abundance estimates by combining fishery-independent and fishery-dependent …

Combining fishery-dependent and -independent CPUE data

Spatially varying catchability for fishery-dependent CPUE standardization.

Preferential sampling in fishery-dependent catch and effort data

Accounting for preferential sampling in spatial models of catch and effort data

Nonstationary spatial processes for fisheries

Incorporating nonstationary spatial processes by allowing for spatially varying covariance parameters.

Best practices for fitting non-linear Bayesian state-space models

Eliminating HMC divergences when fitting Bayesian state-space models for fish populations.