50 resultados para medical information system


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The National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) initiated a coral reef research program in 1999 to map, assess, inventory, and monitor U.S. coral reef ecosystems (Monaco et al. 2001). These activities were implemented in response to requirements outlined in the Mapping Implementation Plan developed by the Mapping and Information Synthesis Working Group (MISWG) of the Coral Reef Task Force (CRTF) (MISWG 1999). As part of the MISWG of the CRTF, NOS' Biogeography Branch has been charged with the development and implementation of a plan to produce comprehensive digital coral-reef ecosystem maps for all U.S. States, Territories, and Commonwealths within five to seven years. Joint activities between Federal agencies are particularly important to map, research, monitor, manage, and restore coral reef ecosystems. In response to the Executive Order 13089 and the Coral Reef Conservation Act of 2000, NOS is conducting research to digitally map biotic resources and coordinate a long-term monitoring program that can detect and predict change in U.S. coral reefs, and their associated habitats and biological communities. Most U.S. coral reef resources have not been digitally mapped at a scale or resolution sufficient for assessment, monitoring, and/or research to support resource management. Thus, a large portion of NOS' coral reef research activities has focused on mapping of U.S. coral reef ecosystems. The map products will provide the fundamental spatial organizing framework to implement and integrate research programs and provide the capability to effectively communicate information and results to coral reef ecosystem managers. Although the NOS coral program is relatively young, it has had tremendous success in advancing towards the goal to protect, conserve, and enhance the health of U.S. coral reef ecosystems. One objective of the program was to create benthic habitat maps to support coral reef research to enable development of products that support management needs and questions. Therefore this product was developed in collaboration with many U.S. Pacific Territory partners. An initial step in producing benthic habitat maps was the development of a habitat classification scheme. The purpose of this document is to outline the benthic habitat classification scheme and protocols used to map American Samoa, Guam and the Commonwealth of the Northern Mariana Islands. Thirty-two distinct benthic habitat types (i.e., four major and 14 detailed geomorphological structure classes; eight major and 18 detailed biological cover types) within eleven zones were mapped directly into a geographic information system (GIS) using visual interpretation of orthorectified IKONOS satellite imagery. Benthic features were mapped that covered an area of 263 square kilometers. In all, 281 square kilometers of unconsolidated sediment, 122 square kilometers of submerged vegetation, and 82.3 square kilometers of coral reef and colonized hardbottom were mapped.

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A density prediction model for juvenile brown shrimp (Farfantepenaeus aztecus) was developed by using three bottom types, five salinity zones, and four seasons to quantify patterns of habitat use in Galveston Bay, Texas. Sixteen years of quantitative density data were used. Bottom types were vegetated marsh edge, submerged aquatic vegetation, and shallow nonvegetated bottom. Multiple regression was used to develop density estimates, and the resultant formula was then coupled with a geographical information system (GIS) to provide a spatial mosaic (map) of predicted habitat use. Results indicated that juvenile brown shrimp (<100 mm) selected vegetated habitats in salinities of 15−25 ppt and that seagrasses were selected over marsh edge where they co-occurred. Our results provide a spatially resolved estimate of high-density areas that will help designate essential fish habitat (EFH) in Galveston Bay. In addition, using this modeling technique, we were able to provide an estimate of the overall population of juvenile brown shrimp (<100 mm) in shallow water habitats within the bay of approximately 1.3 billion. Furthermore, the geographic range of the model was assessed by plotting observed (actual) versus expected (model) brown shrimp densities in three other Texas bays. Similar habitat-use patterns were observed in all three bays—each having a coefficient of determination >0.50. These results indicate that this model may have a broader geographic application and is a plausible approach in refining current EFH designations for all Gulf of Mexico estuaries with similar geomorphological and hydrological characteristics.

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Two halfbeak species, ballyhoo (Hemiramphus brasiliensis) and balao (H. balao), are harvested as bait in south Florida waters, and recent changes in fishing effort and regulations prompted this investigation of the overlap of halfbeak fishing grounds and spawning grounds. Halfbeaks were sampled aboard commercial fishing vessels, and during fishery-independent trips, to determine spatial and temporal spawning patterns of both species. Cyclic patterns of gonadosomatic indices (GSIs) indicated that both species spawned during spring and summer months. Histological analysis demonstrated that specific stages of oocyte development can be predicted from GSI values; for example, female ballyhoo with GSIs >6.0 had hydrated oocytes that were 2.0−3.5 mm diameter. Diel changes in oocyte diameters and histological criteria demonstrated that final oocyte maturation occurred over a 30- to 36-hour period and that ballyhoo spawned at dusk. Hydration of oocytes began in the morning, and ovulation occurred at sunset of that same day; therefore females with hydrated oocytes were ready to spawn within hours. We compared maps of all locations where fish were collected to maps of locations where spawning females (i.e. females with GSIs >6.0) were collected to determine the degree of overlap of halfbeak fishing and spawning grounds. We also used geographic information system (GIS) data to describe the depth and bottom type of halfbeak spawning grounds. Ballyhoo spawned all along the coral reef tract of the Atlantic Ocean, inshore of the reef tract, and in association with bank habitats within Florida Bay. In the Atlantic Ocean, balao spawned along the reef tract and in deeper, more offshore waters than did ballyhoo; balao were not found inshore of the coral reef tract or in Florida Bay. Both halfbeak species, considered together, spawned throughout the fishing grounds of south Florida.

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In the face of dramatic declines in groundfish populations and a lack of sufficient stock assessment information, a need has arisen for new methods of assessing groundfish populations. We describe the integration of seafloor transect data gathered by a manned submersible with high-resolution sonar imagery to produce a habitat-based stock assessment system for groundfish. The data sets used in this study were collected from Heceta Bank, Oregon, and were derived from 42 submersible dives (1988–90) and a multibeam sonar survey (1998). The submersible habitat survey investigated seafloor topography and groundfish abundance along 30-minute transects over six predetermined stations and found a statistical relationship between habitat variability and groundfish distribution and abundance. These transects were analyzed in a geographic information system (GIS) by using dynamic segmentation to display changes in habitat along the transects. We used the submersible data to extrapolate fish abundance within uniform habitat patches over broad areas of the bank by means of a habitat classification based on the sonar imagery. After applying a navigation correction to the submersible-based habitat segments, a good correlation with major boundaries on the backscatter and topographic boundaries on the imagery were apparent. Extrapolation of the extent of uniform habitats was made in the vicinity of the dive stations and a preliminary stock assessment of several species of demersal fish was calculated. Such a habitat-based approach will allow researchers to characterize marine communities over large areas of the seafloor.

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Training included: Geographic Information System (GIS)concept and software; Global Positioning System (GPS); Ecological Gap Analysis and Marine Protected Area (MPA) design using Marine Reserve Design using Spatially Explicit Annealing (MARXAN); and cartography.