Statistical analysis for marine resources
The fisheries sector represents one of Norway’s most important export industries. Norwegian fisheries policy and management are based on the principles of sustainable harvest of the marine living resources (Norwegian fisheries management, fisheries.no). Norwegian fisheries management is based on scientific advices. Much of the research within fisheries involve analysis of data collected both from the fishery industry and through separate research vessels.
Statisticians at Department of Mathematics are involved in a range of different projects within marine resources, in close cooperation with the Norwegian Computing Center, the Institute of Marine Reasearch and Centre for Ecological and Evolutionary Synthesis. We also have close relationships to
Many of these projects are related to estimation of abundance for different species. Such estimates are typically based on population dynamic models. Assuming Ny,a is the total number of a species in year y at age a, a simple dynamic model is
where My,a is the natural mortality rate and Cy,a is the number of fish caught by the fishery. The model is typically made stochastic by distributional assumptions about the mortality rate. The fishery industry report total weight of hauls, while a sample of individual fish are taken and measurements of weight, length and (sometimes) age are provided. In addition relative abundance indices based on catch per unit effort from separate research vessels provide information about abundance. Many of the subprojects involve sophisticated statistical modelling and computational tools for improving existing technology.
The aim in all projects is to provide the fishery managers with better tools for specification of relevant information for performing decisions, e.g. setting quotas, opening/closing areas for fisheries, constructing sampling design for data collection.
In addition to software useable for fishery management, important outcomes have been publications in high-ranked journals. See publication list on sub-projects.
Statisticians at Department of Mathematics are involved in a range of different projects within marine resources, in close cooperation with the Norwegian Computing Center (NR), the Institute of Marine Reasearch (IMR) and Centre for Ecological and Evolutionary Synthesis (CEES). Many of these projects are related to estimation of abundance for different species. Such estimates are typically based on population dynamic models. Assuming
- Dynamic abundance estimation: PhD project for Peter Maisha (finances by Statistics_for_Innovation) where posterior output from catch-at-age estimation is combined with abundance indices for a full Bayesian estimation procedure. Inference is based on importance sampling/sequential Monte Carlo methods.
- Catch-at-age: In this NR based and IMR financed project, a Bayesian hierarchical model is built up for estimating catch at age based on landings data from fishery catch. Markov Chain Monte Carlo methods are used for estimation.
- Hirst, Aanes, Storvik, Huseby, Tvete (2004): Estimating catch at age from market sampling data ny using a Bayesian hierarchical model
- Hirst, Storvik, Aldrin, Aanes, Huseby (2005): Estimating catch-at-age by combining data from different sources
- Hirst, Storvik, Rognebakke, Aldrin, Aanes, Vølstad (2013): A Bayesian modelling frame for the estimation of catch-at-age of commercially harvested fish species
- Bycatch: In this NR based and IMR financed project, geostatistical and GAM modelling are combined to perform prediction of bycatch.
Infectious diseases in aquaculture NR project that develop stochastic simulation models to describe how infectious diseases are transmitted between fish farms.