93 resultados para Incidental parameter bias

em Publishing Network for Geoscientific


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The operator effect is a well-known methodological bias already quantified in some taphonomic studies. However, the replicability effect, i.e., the use of taphonomic attributes as a replicable scientific method, has not been taken into account to the present. Here, we quantified for the first time this replicability bias using different multivariate statistical techniques, testing if the operator effect is related to the replicability effect. We analyzed the results reported by 15 operators working on the same dataset. Each operator analyzed 30 biological remains (bivalve shells) from five different sites, considering the attributes fragmentation, edge rounding, corrasion, bioerosion and secondary color. The operator effect followed the same pattern reported in previous studies, characterized by a worse correspondence for those attributes having more than two levels of damage categories. However, the effect did not appear to have relation with the replicability effect, because nearly all operators found differences among sites. Despite the binary attribute bioerosion exhibited 83% of correspondence among operators it was the taphonomic attributes that showed the highest dispersion among operators (28%). Therefore, we conclude that binary attributes (despite showing a reduction of the operator effect) diminish replicability, resulting in different interpretations of concordant data. We found that a variance value of nearly 8% among operators, was enough to generate a different taphonomic interpretation, in a Q-mode cluster analysis. The results reported here showed that the statistical method employed influences the level of replicability and comparability of a study and that the availability of results may be a valid alternative to reduce bias.

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Arctic permafrost may be adversely affected by climate change in a number of ways, so that establishing a world-wide monitoring program seems imperative. This thesis evaluates possibilities for permafrost monitoring at the example of a permafrost site on Svalbard, Norway. An energy balance model for permafrost temperatures is developed that evaluates the different components of the surface energy budget in analogy to climate models. The surface energy budget, consisting of radiation components, sensible and latent heat fluxes as well as the ground heat flux, is measured over the course of one year, which has not been accomplished for arctic land areas so far. A considerable small-scale heterogeneity of the summer surface temperature is observed in long-term measurements with a thermal imaging system, which can be reproduced in the energy balance model. The model can also simulate the impact of different snow depths on the soil temperature, that has been documented in field measurements. Furthermore, time series of terrestrial surface temperature measurements are compared to satellite-borne measurements, for which a significant cold-bias is observed during winter. Finally, different possibilities for a world-wide monitoring scheme are assessed. Energy budget models can incorporate different satellite data sets as training data sets for parameter estimation, so that they may constitute an alternative to purely satellite-based schemes.

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During Ocean Drilling Program Leg 188 to Prydz Bay, East Antarctica, several of the shipboard scientists formed the High-Resolution Integrated Stratigraphy Committee (HiRISC). The committee was established in order to furnish an integrated data set from the Pliocene portion of Site 1165 as a contribution to the ongoing debate about Pliocene climate and climate evolution in Antarctica. The proxies determined in our various laboratories were the following: magnetostratigraphy and magnetic properties, grain-size distributions (granulometry), near-ultraviolet, visible, and near-infrared spectrophotometry, calcium carbonate content, characteristics of foraminifer, diatom, and radiolarian content, clay mineral composition, and stable isotopes. In addition to the HiRISC samples, other data sets contained in this report are subsets of much larger data sets. We included these subsets in order to provide the reader with a convenient integrated data set of Pliocene-Pleistocene strata from the East Antarctic continental margin. The data are presented in the form of 14 graphs (in addition to the site map). Text and figure captions guide the reader to the original data sets. Some preliminary interpretations are given at the end of the manuscript.

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Interannual environmental variability in Peru is dominated by the El Niño Southern Oscillation (ENSO). The most dramatic changes are associated with the warm El Niño (EN) phase (opposite the cold La Niña phase), which disrupts the normal coastal upwelling and affects the dynamics of many coastal marine and terrestrial resources. This study presents a trophic model for Sechura Bay, located at the northern extension of the Peruvian upwelling system, where ENSO-induced environmental variability is most extreme. Using an initial steady-state model for the year 1996, we explore the dynamics of the ecosystem through the year 2003 (including the strong EN of 1997/98 and the weaker EN of 2002/03). Based on support from literature, we force biomass of several non-trophically-mediated 'drivers' (e.g. Scallops, Benthic detritivores, Octopus, and Littoral fish) to observe whether the fit between historical and simulated changes (by the trophic model) is improved. The results indicate that the Sechura Bay Ecosystem is a relatively inefficient system from a community energetics point of view, likely due to the periodic perturbations of ENSO. A combination of high system productivity and low trophic level target species of invertebrates (i.e. scallops) and fish (i.e. anchoveta) results in high catches and an efficient fishery. The importance of environmental drivers is suggested, given the relatively small improvements in the fit of the simulation with the addition of trophic drivers on remaining functional groups' dynamics. An additional multivariate regression model is presented for the scallop Argopecten purpuratus, which demonstrates a significant correlation between both spawning stock size and riverine discharge-mediated mortality on catch levels. These results are discussed in the context of the appropriateness of trophodynamic modeling in relatively open systems, and how management strategies may be focused given the highly environmentally influenced marine resources of the region.

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Analogous to West- and North Africa, East Africa experienced more humid conditions between approximately 12 to 5 kyr BP, relative to today. While timing and extension of wet phases in the North and West are well constrained, this is not the case for the East African Humid Period. Here we present a record of benthic foraminiferal assemblages and sediment elemental compositions of a sediment core from the East African continental slope, in order to provide insight into the regional shallow Indian Ocean paleoceanography and East African climate history of the last 40 kyr. During glacial times, the dominance of a benthic foraminiferal assemblage characterized by Bulimina aculeata, suggests enhanced surface productivity and sustained flux of organic carbon to the sea floor. During Heinrich Stadial 1 (H1), the Nuttallides rugosus Assemblage indicates oligotrophic bottom water conditions and therefore implies a stronger flow of southern-sourced AAIW to the study site. During the East African Humid Period, the Saidovina karreriana Assemblage in combination with sedimentary C/N and Fe/Ca ratios suggest higher river runoff to the Indian Ocean, and hence more humid conditions in East Africa. Between 8.5 and 8.1 kyr, contemporaneous to the globally documented 8.2 kyr Event, a severe reduction in river deposits implies more arid conditions on the continent. Comparison of our marine data with terrestrial studies suggests that additional moisture from the Atlantic Ocean, delivered by an eastward migration of the Congo Air Boundary during that time period, could have contributed to East African rainfall. Since approximately 9 kyr, the gaining influence of the Millettiana millettii Assemblage indicates a redevelopment of the East African fringe reefs.

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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.