4 resultados para Aortic stenosis, valvuloplasty, results, mortality, survival.

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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The main purpose of this paper is to provide the core description of the modelling exercise within the Shelf Edge Advection Mortality And Recruitment (SEAMAR) programme. An individual-based model (IBM) was developed for the prediction of year-to-year survival of the early life-history stages of mackerel (Scomber scombrus) in the eastern North Atlantic. The IBM is one of two components of the model system. The first component is a circulation model to provide physical input data for the IBM. The circulation model is a geographical variant of the HAMburg Shelf Ocean Model (HAMSOM). The second component is the IBM, which is an i-space configuration model in which large numbers of individuals are followed as discrete entities to simulate the transport, growth and mortality of mackerel eggs, larvae and post-larvae. Larval and post-larval growth is modelled as a function of length, temperature and food distribution; mortality is modelled as a function of length and absolute growth rate. Each particle is considered as a super-individual representing 10 super(6) eggs at the outset of the simulation, and then declining according to the mortality function. Simulations were carried out for the years 1998-2000. Results showed concentrations of particles at Porcupine Bank and the adjacent Irish shelf, along the Celtic Sea shelf-edge, and in the southern Bay of Biscay. High survival was observed only at Porcupine and the adjacent shelf areas, and, more patchily, around the coastal margin of Biscay. The low survival along the shelf-edge of the Celtic Sea was due to the consistently low estimates of food availability in that area.

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A modelling scheme is described which uses satellite retrieved sea-surface temperature and chlorophyll-a to derive monthly zooplankton biomass estimates in the eastern North Atlantic; this forms part of a bio-physical model of inter-annual variations in the growth and survival of larvae and post-larvae of mackerel (Scomber scombrus). The temperature and chlorophyll data are incorporated first to model copepod (Calanus) egg production rates. Egg production is then converted to available food using distribution data from the Continuous Plankton Recorder (CPR) Survey, observed population biomass per unit daily egg production and the proportion of the larval mackerel diet comprising Calanus. Results are validated in comparison with field observations of zooplankton biomass. The principal benefit of the modelling scheme is the ability to use the combination of broad scale coverage and fine scale temporal and spatial variability of satellite data as driving forces in the model; weaknesses are the simplicity of the egg production model and the broad-scale generalizations assumed in the raising factors to convert egg production to biomass.

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A study was carried out in June/July 1996 in the River Po outflow in the northern Adriatic to investigate spawning of anchovy Engraulis encrasicolus and survival of larvae in relation to food availability and wind mixing. Hydrographic- and bongo net sampling was carried out on 2 grid surveys; one after a period of low winds and settled weather, and the other after an intervening period of strong winds, which resulted in a decrease in water column stratification. The spawning areas of anchovy and the larval distributions were associated with the river outflow plume (most clearly on the second survey grid, after the period of higher winds). Potential food particles for anchovy larvae, primarily copepod nauplii and copepodite stages, were also concentrated in the area influenced by the river outflow. Although there was a nearly 50% reduction in the mean water column abundance of potential food particles between the 2 survey grids, mostly due to a decline in abundance outside the immediate river plume area, there was no significant change in mortality of anchovy larvae between the 2 grids; the exponential decline in numbers of eggs and larvae to 10 mm in length being equivalent to overall mortality rates of 43.2%/d on the first survey and 44.7%/d on the second. The resilience of larval survival under potentially less favourable feeding conditions, following the period of wind mixing, was ascribed, in part, to the maintenance of local water column stratification by the superficial low salinity input from the River Po. This stratification in the immediate outflow area was associated with the presence of concentrated layers of potential food particles (typically >50 particles/L and 1.5 to 2.8 times the mean water column abundance) in the upper 10 m of the water column, coincident with peak numbers of anchovy larvae. However, since there was no evidence for lower larval survival in areas, less influenced by the immediate river outflow plume, a simple direct relationship between enhanced water column stability, improved feeding conditions and larval survival was not supported.

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The abundance of wild salmon (Salmo salar) in the North Atlantic has declined markedly since the late 1980s as a result of increased marine mortality that coincided with a marked rise in sea temperature in oceanic foraging areas. There is substantial evidence to show that temperature governs the growth, survival, and maturation of salmon during their marine migrations through either direct or indirect effects. In an earlier study (2003), long-term changes in three trophic levels (salmon, zooplankton, and phytoplankton) were shown to be correlated significantly with sea surface temperature (SST) and northern hemisphere temperature (NHT). A sequence of trophic changes ending with a stepwise decline in the total nominal catch of North Atlantic salmon (regime shift in ∼1986/1987) was superimposed on a trend to a warmer dynamic regime. Here, the earlier study is updated with catch and abundance data to 2010, confirming earlier results and detecting a new abrupt shift in ∼1996/1997. Although correlations between changes in salmon, plankton, and temperature are reinforced, the significance of the correlations is reduced because the temporal autocorrelation of time-series substantially increased due to a monotonic trend in the time-series, probably related to global warming. This effect may complicate future detection of effects of climate change on natural systems.