Defining plausible migration rates based on historical tagging data: a Bayesian mark-recapture model applied to English sole (Parophrys vetulus)

A generalized Bayesian population dynamics model was developed for analysis of historical mark-recapture studies. The Bayesian approach builds upon existing maximum likelihood methods and is useful when substantial uncertainties exist in the data or little information is available about auxiliary parameters such as tag loss and reporting rates. Movement rates are obtained through Markov-chain Monte-Carlo (MCMC) simulation, which are suitable for use as input in subsequent stock assessment analysis. The mark-recapture model was applied to English sole (Parophrys vetulus) off the west coast of the United States and Canada and migration rates were estimated to be 2% per month to the north and 4% per month to the south. These posterior parameter distributions and the Bayesian framework for comparing hypotheses can guide fishery scientists in structuring the spatial and temporal complexity of future analyses of this kind. This approach could be easily generalized for application to other species and more data-rich fishery analyses.

A Bayesian method for identification of stock mixtures from molecular marker data

Molecular markers have been demonstrated to be useful for the estimation of stock mixture proportions where the origin of individuals is determined from baseline samples. Bayesian statistical methods are widely recognized as providing a preferable strategy for such analyses. In general, Bayesian estimation is based on standard latent class models using data augmentation through Markov chain Monte Carlo techniques. In this study, we introduce a novel approach based on recent developments in the estimation of genetic population structure. Our strategy combines analytical integration with stochastic optimization to identify stock mixtures. An important enhancement over previous methods is the possibility of appropriately handling data where only partial baseline sample information is available. We address the potential use of nonmolecular, auxiliary biological information in our Bayesian model.

Interannual variability of siliceous phytoplankton fluxes and relationships with hydrography in the northeastern subarctic Pacific, 1982-1986 [abstract and figures]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Time-series flux variabilities of biogenic opal particles were measured during 1982-1986 at pelagic Station PAPA (50° N, 145° W) located just south of the Gulf of Alaska, eastern North Pacific. PARFLUX sediment traps with two week sampling increments were deployed at 1000 m and 3800 m in 4200 m deep water, yielding nearly continuous time-series flux records for four years. The flux data allowed us to examine interannual and seasonal variabilities of siliceous phytoplankton production as well as environmental signals retained within the siliceous shells, which can be used to reconstruct environments.

Changes in mass balance of South Cascade Glacier, North Cascades, 1959 to 1994

EXTRACT (SEE PDF FOR FULL ABSTRACT): Annual, winter, and summer mass balance measurements at South Cascade Glacier in the North Cascade Mountains of Washington State constitute a continuous time series 36 years long, from 1959 to 1994. ... The long-term trends at South Cascade Glacier are decreased winter accumulation and increased summer ablation, neither of which is conducive to glacier growth, so the trend in the Pacific Northwest is clearly away from an ice-age type of climate at the current time. The data also demonstrate that a glaciologically significant long-term change in snow precipitation can occur rapidly, in as short an interval as 1 year, much more rapidly than changes in temperature.