10 resultados para multiple linear regression

em Publishing Network for Geoscientific


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Sediment core logs from six sediment cores in the Labrador Sea show millennial-scale climate variability during the last glacial by recording all Heinrich events and several major Dansgaard-Oeschger cycles. The same millennial-scale climate change is documented for surface-water d18O records of Neogloboquadrina pachyderma (left coiled); hence the surface-water d18O record can be derived from sediment core logging by means of multiple linear regression, providing a paleoclimate proxy record at very high temporal resolution (70 yrs). For the Labrador Sea, sediment core logs contain important information about deep-water current velocities and also reflect the variable input of IRD from different sources as inferred from grain-size analysis, benthic d18O, the relation of density and p-wave velocity, and magnetic susceptibility. For the last glacial, faster deep-water currents which correspond to highs in sediment physical properties, occurred during iceberg discharge and lasted for a several centuries to a few millennia. Those enhanced currents might have contributed to increased production of intermediate waters during times of reduced production of North Atlantic Deep Water. Hudson Strait might have acted as a major supplier of detrital carbonate only during lowered sea level (greater ice extent). During coldest atmospheric temperatures over Greenland, deep-water currents increased during iceberg discharge in the Labrador Sea, then surface water freshened shortly after, while the abrupt atmospheric temperature rise happened after a larger time lag of >=1 kyr. The correlation implies a strong link and common forcing for atmosphere, sea surface, and deep water during the last glacial at millennial time scales but decoupling at orbital time scales.

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Euphausiids constitute major biomass component in shelf ecosystems and play a fundamental role in the rapid vertical transport of carbon from the ocean surface to the deeper layers during their daily vertical migration (DVM). DVM depth and migration patterns depend on oceanographic conditions with respect to temperature, light and oxygen availability at depth, factors that are highly dependent on season in most marine regions. Changes in the abiotic conditions also shape Euphausiid metabolism including aerobic and anaerobic energy production. Here we introduce a global krill respiration model which includes the effect of latitude (LAT), the day of the year of interest (DoY), and the number of daylight hours on the day of interest (DLh), in addition to the basal variables that determine ectothermal oxygen consumption (temperature, body mass and depth) in the ANN model (Artificial Neural Networks). The newly implemented parameters link space and time in terms of season and photoperiod to krill respiration. The ANN model showed a better fit (r**2=0.780) when DLh and LAT were included, indicating a decrease in respiration with increasing LAT and decreasing DLh. We therefore propose DLh as a potential variable to consider when building physiological models for both hemispheres. We also tested for seasonality the standard respiration rate of the most common species that were investigated until now in a large range of DLh and DoY with Multiple Linear Regression (MLR) or General Additive model (GAM). GAM successfully integrated DLh (r**2= 0.563) and DoY (r**2= 0.572) effects on respiration rates of the Antarctic krill, Euphausia superba, yielding the minimum metabolic activity in mid-June and the maximum at the end of December. Neither the MLR nor the GAM approach worked for the North Pacific krill Euphausia pacifica, and MLR for the North Atlantic krill Meganyctiphanes norvegica remained inconclusive because of insufficient seasonal data coverage. We strongly encourage comparative respiration measurements of worldwide Euphausiid key species at different seasons to improve accuracy in ecosystem modelling.

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Visual-domain diffuse reflectance data collected aboard the JOIDES Resolution with the Minolta spectrometer CM-2002 during Ocean Drilling Program Leg 172 have been used to estimate successfully the carbonate content of sediments. Calibration equations were developed for each site and for each lithostratigraphic unit (or subunit at Site 1063) using multiple linear regression on raw as well as pretreated reflectance spectra (i.e., first-order derivation and squaring of raw reflectance spectra) for a total of 4141 direct carbonate measurements. The root-mean-square errors of 4% to 7% are within the range of previous estimates using diffuse reflectance data and are acceptable for the general extensive range of carbonate contents (i.e., 0-70 wt%) that characterize sedimentation at Leg 172 sites.

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As the length of marine cores increases and sampling intervals decrease, the need for rapid and inexpensive means of determining sediment composition has become apparent. In this study we examine one potentially useful technique for assessing compositional changes in marine cores, diffuse reflectance spectrophotometry. We examined near-ultraviolet, visible, and near-infrared reflectance spectra from five data sets. Each data set consists of calibration samples and test samples. The calibration samples' spectra were related to a sediment component using multiple linear regression. The resulting regression or calibration equations were then evaluated using the test samples. Calibration equations were written relating spectra to several sediment components incduding carbonate (Atlantic and east Pacific Rise ODP Site 847), organic carbon content (Atlantic and east Pacific Rise), and opal content (east Pacific Rise). The correlation coefficients for the regression equations ranged from a high of 0.99 for carbonate and opal at ODP Site 847 to a low of 0.97 for Atlantic carbonate indicating that spectral variations are highly correlated to sediment composition. All of the equations include a substantial number of variables from shorter visible and longer near ultraviolet wavelengths suggesting that these wavelengths are especially important for devices designed specifically to scan marine cores. Although equations for estimating organic and carbonate content appear independent of other sediment components, the opal equation is strongly dependent on carbonate content indicating that opal concentration is correlated to carbonate content. Tests of the calibration equations indicated that all our equations reasonably estimate the pattern of changes, either down core or in surface sediments. Where our spectral estimates have difficulty is with absolute values, frequently over or underestimating observed values by a substantial amount. Within these limitations diffuse reflectance spectrophotometry can be a useful tool for characterizing marine cores and as our understanding of the relationship between spectra and mineralogy improves so will estimates of absolute values.

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Long chain 1,13- and 1,15-alkyl diols form the base of a number of recently proposed proxies used for climate reconstruction. However, the sources of these lipids and environmental controls on their distribution are still poorly constrained. We have analyzed the long chain alkyl diol (LCD) composition of cultures of ten eustigmatophyte species, with three species from different families grown at various temperatures, to identify the effect of species composition and growth temperature on the LCD distribution. The results were compared with the LCD distribution of sixty-two lake surface sediments, and with previously reported LCD distributions from marine environments. The different families within the Eustigmatophyceae show distinct LCD patterns, with the freshwater family Eustigmataceae most closely resembling LCD distributions in both marine and lake environments. Unlike the other two eustigmatophyte families analyzed (Monodopsidaceae and Goniochloridaceae), C28 and C30 1,13-alkyl diols and C30 and C32 1,15-alkyl diols are all relatively abundant in the family Eustigmataceae, while the mono-unsaturated C32 1,15-alkyl diol was below detection limit. In contrast to the marine environment, LCD distributions in lakes did not show a clear relationship with temperature. The Long chain Diol Index (LDI), a proxy previously proposed for sea surface temperature reconstruction, showed a relatively weak correlation (R2 = 0.33) with mean annual air temperature used as an approximation for annual mean surface temperature of the lakes. A much-improved correlation (R2 = 0.74, p-value<0.001) was observed applying a multiple linear regression analysis between LCD distributions and lake temperatures reconstructed using branched tetraether lipid distributions. The obtained regression model provides good estimates of temperatures for cultures of the family Eustigmataceae, suggesting that algae belonging to this family have an important role as a source for LCDs in lacustrine environments, or, alternatively, that the main sources of LCDs are similarly affected by temperature as the Eustigmataceae. The results suggest that LCDs may have the potential to be applicable as a palaeotemperature proxy for lacustrine environments, although further calibration work is still required.

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Recent efforts to link the isotopic composition of snow in Greenland with meteorological and climatic parameters have indicated that relatively local information such as observed annual temperatures from coastal Greenland sites, as well as more synoptic scale features such as the North Atlantic Oscillation (NAO) and the temperature seesaw between Jakobshaven, Greenland, and Oslo, Norway, are significantly correlated with d18O and dD values from the past few hundred years measured in ice cores. In this study we review those efforts and then use a new record of isotope values from the Greenland Ice Sheet Project 2 and Greenland Ice Core Project sites at Summit, Greenland, to compare with meteorological and climatic parameters. This new record consists of six individual annually resolved isotopic records which have been average to produce a Summit stacked isotope record. The stacked record is significantly correlated with local Greenland temperatures over the past century (r=0.471), as well as a number of other records including temperatures and pressures from specific locations as well as temperature and pressure patterns such as the temperature seesaw and the North Atlantic Oscillation. A multiple linear regression of the stacked isotope record with a number of meteorological and climatic parameters in the North Atlantic region reveals that five variables contribute significantly to the variance in the isotope record: winter NAO, solar irradiance (as recorded by sunspot numbers), average Greenland coastal temperature, sea surface temperature in the moisture source region for Summit (30°-20°N), and the annual temperature seesaw between Jakobshaven and Oslo. Combined, these variables yield a correlation coefficient of r=0.71, explaining half of the variance in the stacked isotope record.

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A global sea surface temperature calibration based on the relative abundance of different morphotypes within the coccolithophore genus Gephyrocapsa in Holocene deep-sea sediments is presented. There is evidence suggesting that absolute sea surface temperature for a given location can be calculated from the relative abundance of Gephyrocapsa morphotypes in sediment samples, with a standard error comparable to temperature estimates derived from other temperature proxies such as planktic foraminifera transfer functions. A total of 110 Holocene sediment samples were selected from the Pacific, Indian, and Atlantic Oceans covering a mean sea surface temperature gradient from 13.6° to 29.3°C. Standard multiple linear regression analyses were applied to this data set, linking the relative abundance of Gephyrocapsa morphotypes to sea surface temperature. The best model revealed an r**2 of 0.83 with a standard residual error of 1.78°C for the estimation of mean sea surface temperature. This new proxy provides a unique opportunity for the reconstruction of paleotemperatures with a very small amount of sample material due to the minute size of coccoliths, permitting examination of thinly laminated sediments (e.g., a pinhead of material from laminated sediments for the reconstruction of annual sea surface temperature variations). Such fine-scale resolution is currently not possible with any other proxy. Application of this new paleotemperature proxy may allow new paleoenvironmental interpretations in the late Quaternary period and discrepancies between the different currently used paleotemperature proxies might be resolved.

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The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

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Aim: To investigate shell size variation among gastropod faunas of fossil and recent long-lived European lakes and discuss potential underlying processes. Location: 23 long-lived lakes of the Miocene to Recent of Europe. Methods: Based on a dataset of 1412 species of both fossil and extant lacustrine gastropods, we assessed differences in shell size in terms of characteristics of the faunas (species richness, degree of endemism, differences in family composition) and the lakes (surface area, latitude and longitude of lake centroid, distance to closest neighbouring lake) using multiple and linear regression models. Because of a strong species-area relationship, we used resampling to determine whether any observed correlation is driven by that relationship. Results: The regression models indicated size range expansion rather than unidirectional increase or decrease as the dominant pattern of size evolution. The multiple regression models for size range and maximum and minimum size were statistically significant, while the model with mean size was not. Individual contributions and linear regressions indicated species richness and lake surface area as best predictors for size changes. Resampling analysis revealed no significant effects of species richness on the observed patterns. The correlations are comparable across families of different size classes, suggesting a general pattern. Main conclusions: Among the chosen variables, species richness and lake surface area are the most robust predictors of shell size in long-lived lake gastropods. Although the most outstanding and attractive examples for size evolution in lacustrine gastropods derive from lakes with extensive durations, shell size appears to be independent of the duration of the lake as well as longevity of a species. The analogue of long-lived lakes as 'evolutionary islands' does not hold for developments of shell size because different sets of parameters predict size changes.