Geology topics

Joan Thomas

Publications and source records attributed to Joan Thomas.

3 recordsLinked to original sources

USGS2013

Emergence of MD type infectious hematopoietic necrosis virus in Washington State coastal steelhead trout

Infectious hematopoietic necrosis virus (IHNV) occurs in North America as 3 major phylogenetic groups designated U, M, and L. In coastal Washington State, IHNV has historically consisted of U genogroup viruses found predominantly in sockeye salmon Oncorhynchus nerka . M genogroup IHNV, which has host-specific virulence for rainbow and steelhead trout O. mykiss , was detected only once in coastal Washington prior to 2007, in an epidemic among juvenile steelhead trout in 1997. Beginning in 2007 and continuing through 2011, there were 8 IHNV epidemics in juvenile steelhead trout, involving 7 different fish culture facilities in 4 separate watersheds. During the same time period, IHNV was also detected in asymptomatic adult steelhead trout from 6 coastal watersheds. Genetic typing of 283 recent virus isolates from coastal Washington revealed that the great majority were in the M genogroup of IHNV and that there were 2 distinct waves of viral emergence between the years 2007 and 2011. IHNV type mG110M was dominant in coastal steelhead trout during 2007 to 2009, and type mG139M was dominant between 2010 and 2011. Phylogenetic analysis of viral isolates indicated that all coastal M genogroup viruses detected in 1997 and 2007 to 2011 were part of the MD subgroup and that several novel genetic variants related to the dominant types arose in the coastal sites. Comparison of spatial and temporal incidence of coastal MD viruses with that of the rest of the Pacific Northwest indicated that the likely source of the emergent viruses was Columbia River Basin steelhead trout.

Washington↗

USGS2012

Priorities for IOOS ® Data Management and Communications (DMAC)

Dramatic increases in the volume of online data and rapid advances in information technology have transformed many aspects of our society. In the coastal ocean, the amount of data is also growing dramatically due to new sensor and modeling technologies. Lagging behind this deluge of ocean data, however, is an effective framework of standards, protocols, tools and culture needed to transform the way we generate knowledge and value from ocean data. The Data Management and Communications (DMAC) sub-system was envisioned to provide such an information management capability for IOOS®, promoting standards and policies to be implemented by data providers across the IOOS enterprise. DMAC needs to build upon the successes and lessons learned during development of web service standards and promote a set of end-to-end standards and procedures for the entire ocean-data life cycle, including documentation through metadata, quality control and quality assurance, effective data discovery, and stewardship through archiving. Because information technology is constantly changing, a multiyear, top-down design and implementation plan is not workable. DMAC should start by promoting a set of protocols that are functional for specific use cases, creating a modular framework in which modules can be replaced as technologies change. In addition to promoting protocols, DMAC needs to support training, flexible online documentation, support, and social networking that enable users to share code, techniques and experiences. Through this bottom-up approach, trust and understanding will foster adoption by the community. Finally, a compliance and certification process should be developed that allows IOOS to ensure that they meet the needs of customers and other stakeholders while complying with regulatory requirements related to the data. If this approach is followed, we will enable breakthroughs in ocean data–driven technology similar to those common elsewhere in our society, fulfilling the broader mission of IOOS.

Book↗

USGS2003

Characterization and statistical modeling of bacterial (Escherichia coli) outflows from watersheds that discharge into Southern Lake Michigan

Two watersheds in northwestern Indiana were selected for detailed monitoring of bacterially contaminated discharges (Escherichia coli) into Lake Michigan. A large watershed that drains an urbanized area with treatment plants that release raw sewage during storms discharges into Lake Michigan at the outlet of Burns Ditch. A small watershed drains part of the Great Marsh, a wetland complex that has been disrupted by ditching and limited residential development, at the outlet of Derby Ditch. Monitoring at the outlet of Burns Ditch in 1999 and 2000 indicated that E. coli concentrations vary over two orders of magnitude during storms. During one storm, sewage overflows caused concentrations to increase to more than 10,000 cfu/100 mL for several hours. Monitoring at Derby Ditch from 1997 to 2000 also indicated that E. coli concentrations increase during storms with the highest concentrations generally occurring during rising streamflow. Multiple regression analysis indicated that 60% of the variability in measured outflows of E. coli from Derby Ditch (n = 88) could be accounted for by a model that utilizes continuously measured rainfall, stream discharge, soil temperature and depth to water table in the Great Marsh. A similar analysis indicated that 90% of the variability in measured E. coli concentrations at the outlet of Burns Ditch (n = 43) during storms could be accounted for by a combination of continuously measured water-quality variables including nitrate and ammonium. These models, which utilize data that can be collected on a real-time basis, could form part of an Early Warning System for predicting beach closures.

Environmental Monitoring and Assessment↗