A5068154952- Fish Ecology and Management Studies
- Marine Bivalve and Aquaculture Studies
- Marine and fisheries research
- Underwater Acoustics Research
- Bayesian Modeling and Causal Inference
- Oceanographic and Atmospheric Processes
- Arctic and Antarctic ice dynamics
- Genetic and phenotypic traits in livestock
- Survey Sampling and Estimation Techniques
Bedford Institute of Oceanography
2022-2024
Fisheries and Oceans Canada
2022
Dalhousie University
2018
Abstract To support ecosystem-based fisheries management, monitoring data from at-sea observer (ASO) programs should be leveraged to understand the impact of on discarded species (bycatch). Available techniques estimate fishery-scale quantities observations range simple mean estimators more complex spatiotemporal models, each making assumptions with differing degrees support. However, resulting implementation and analytical trade-offs are rarely discussed when applying these in practice....
Abstract State‐space models (SSMs) are now popular tools in fisheries science for providing management advice when faced with noisy survey and commercial fishery data. Such often fitted within a Bayesian framework requiring both the specification of prior distributions model parameters simulation‐based approaches inference. Here we present frequentist as viable alternative recommend using Laplace approximation automatic differentiation, implemented R package Template Model Builder, fast...
Length–weight relationships (LWRs) are an essential component of fishery stock assessments. They used to develop indices condition and convert length data into estimates biomass. Attempts capture variability in underlying ecological processes within statistical modeling frameworks for LWRs have typically relied on the inclusion environmental variables. Here, using a case study sea scallop ( Placopecten magellanicus), we demonstrate that introducing spatiotemporal random effects generalized...