22 resultados para artificial neutral network

em Publishing Network for Geoscientific


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Early and Mid-Pleistocene climate, ocean hydrography and ice sheet dynamics have been reconstructed using a high-resolution data set (planktonic and benthic d18O time series, faunal-based sea surface temperature (SST) reconstructions and ice-rafted debris (IRD)) record from a high-deposition-rate sedimentary succession recovered at the Gardar Drift formation in the subpolar North Atlantic (Integrated Ocean Drilling Program Leg 306, Site U1314). Our sedimentary record spans from late in Marine Isotope Stage (MIS) 31 to MIS 19 (1069-779 ka). Different trends of the benthic and planktonic oxygen isotopes, SST and IRD records before and after MIS 25 (~940 ka) evidence the large increase in Northern Hemisphere ice-volume, linked to the cyclicity change from the 41-kyr to the 100-kyr that occurred during the Mid-Pleistocene Transition (MPT). Beside longer glacial-interglacial (G-IG) variability, millennial-scale fluctuations were a pervasive feature across our study. Negative excursions in the benthic d18O time series observed at the times of IRD events may be related to glacio-eustatic changes due to ice sheets retreats and/or to changes in deep hydrography. Time series analysis on surface water proxies (IRD, SST and planktonic d18O) of the interval between MIS 31 to MIS 26 shows that the timing of these millennial-scale climate changes are related to half-precessional (10 kyr) components of the insolation forcing, which are interpreted as cross-equatorial heat transport toward high latitudes during both equinox insolation maxima at the equator.

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In this paper we present a paleoceanographic reconstruction of the southwestern South Atlantic for the past 13 kyr based on faunal and isotopic analysis of planktonic foraminifera from a high-resolution core retrieved at the South Brazil Bight continental slope. Our record indicates that oceanographic changes in the southwestern South Atlantic during the onset of the Holocene were comparable in strength to those that occurred during the Younger Dryas. Full interglacial conditions started abruptly after 8.2 kyr BP with a sharp change in faunal composition and surface hydrography (SST and SSS). Part of the observed events may be explained in terms of changes in thermohaline circulation while the other part suggests a dominant role of winds. Our data indicate that during the Early Holocene upwelling was significantly strengthened in the South Brazil Bight promoting high productivity and preventing the establishment of the typically interglacial menardiiform species. In general terms, oceanographic changes recorded by core KF02 occurred in synchrony with Antarctica's climate.

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Planktonic foraminiferal assemblages and artificial neural network estimates of sea-surface temperature (SST) at ODP Site 1123 (41°47.2'S, 171°29.9'W; 3290 m deep), east of New Zealand, reveal a high-resolution history of glacial-interglacial (G-I) variability at the Subtropical Front (STF) for the last 1.2 million years, including the Mid-Pleistocene climate transition (MPT). Most G-I cycles of ~100 kyr duration have short periods of cold glacial and warm deglacial climate centred on glacial terminations, followed by long temperate interglacial periods. During glacial-deglacial transitions, maximum abundances of subantarctic and subtropical taxa coincide with SST minima and maxima, and lead ice volume by up to 8 kyrs. Such relationships reflect the competing influence of subantarctic and subtropical surface inflows during glacial and deglacial periods, respectively, suggesting alternate polar and tropical forcing of southern mid-latitude ocean climate. The lead of SSTs and subtropical inflow over ice volume points to tropical forcing of southern mid-latitude ocean-climate during deglacial warming. This contrasts with the established hypothesis that southern hemisphere ocean climate is driven by the influence of continental glaciations. Based on wholesale changes in subantarctic and subtropical faunas, the last 1.2 million years are subdivided into 4-distinct periods of ocean climate. 1) The pre-MPT (1185-870 ka) has high amplitude 41-kyr fluctuations in SST, superimposed on a general cooling trend and heightened productivity, reflecting long-term strengthening of subantarctic inflow under an invigorated Antarctic Circumpolar Current. 2) The early MPT (870-620 ka) is marked by abrupt warming during MIS 21, followed by a period of unstable periodicities within the 40-100 kyr orbital bands, decreasing SST amplitudes, and long intervals of temperate interglacial climate punctuated by short glacial and deglacial phases, reflecting lower meridional temperature gradients. 3) The late MPT (620-435 ka) encompasses an abrupt decrease in the subantarctic inflow during MIS 15, followed by a period of warm equable climate. Poorly defined, low amplitude G-I variations in SSTs during this interval are consistent with a relatively stable STF and evenly balanced subantarctic and subtropical inflows, possibly in response to smaller, less dynamic polar icesheets. 4) The post-MPT (435-0 ka) is marked by a major climatic deterioration during MIS 12, and a return to higher amplitude 100 kyr-frequency SST variations, superimposed on a long term trend towards cooler SSTs and increased mixed-layer productivity as the subantarctic inflow strengthened and polar icesheets expanded.

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I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

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