The Bonneville Basin is a continental lacustrine system accommodating extensive microbial carbonate deposits corresponding to two distinct phases: the deep Lake Bonneville (30 000 to 11 500 14C bp ) and the shallow Great Salt Lake (since 11 500 14C bp ). A characterization of these microbial deposits and their associated sediments provides insights into their spatio‐temporal distribution patterns. The Bonneville phase preferentially displays vertical distribution of the microbial deposits resulting from high‐amplitude lake level variations. Due to the basin physiography, the microbial deposits were restricted to a narrow shoreline belt following Bonneville lake level variations. Carbonate production was more efficient during intervals of relative lake level stability as recorded by the formation of successive terraces. In contrast, the Great Salt Lake microbial deposits showed a great lateral distribution, linked to the modern flat bottom configuration. A low vertical distribution of the microbial deposits was the result of the shallow water depth combined with a low amplitude of lake level fluctuations. These younger microbial deposits display a higher diversity of fabrics and sizes. They are distributed along an extensive ‘shore to lake’ transect on a flat platform in relation to local and progressive accommodation space changes. Microbial deposits are temporally discontinuous throughout the lake history showing longer hiatuses during the Bonneville phase. The main parameters controlling the rate of carbonate production are related to the interaction between physical (kinetics of the mineral precipitation, lake water temperature and runoff), chemical (Ca2+, Mg2+ and HCO3? concentrations, Mg/Ca ratio, dilution and depletion) and/or biological (trophic) factors. The contrast in evolution of Lake Bonneville and Great Salt Lake microbial deposits during their lacustrine history leads to discussions on major chemical and climatic changes during this interval as well as the role of physiography. Furthermore, it provides novel insights into the composition, structure and formation of microbialite‐rich carbonate deposits under freshwater and hypersaline conditions. 相似文献
This work presents new 87Sr/86Sr and δ88/86SrSRM987 isotopic values of thirteen mineral, vegetal and animal reference materials. Except for UB‐N, all our results are consistent with previously published data. Our results highlight intermediate precisions among the best presently published and a non‐significant systematic shift with the calculated δ88/86SrSRM987 mean values for the three most analysed reference materials in the literature (i.e., IAPSO, BCR‐2 and JCp‐1). By comparison with the literature and between two distinct digestions, a significant bias of δ88/86SrSRM987 values was highlighted for two reference materials (UB‐N and GS‐N). It has also been shown that digestion protocols (nitric and multi‐acid) have a moderate impact on the δ88/86SrSRM987 isotopic values for the Jls‐1 reference materials suggesting that a nitric acid digestion of carbonate can be used without significant bias from partial digestion of non‐carbonate impurities. Different δ88/86SrSRM987 values were measured after two independent Sr/matrix separations, according to the same protocol, for a fat‐rich organic reference material (BCR‐380R) and have been related to a potential post‐digestion heterogeneity. Finally, the δ88/86SrSRM987 value differences measured between animal‐vegetal and between coral‐seawater reference materials agree with the previously published results, highlighting an Sr isotopic fractionation along the trophic chain and during carbonate precipitation. 相似文献
Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based on their contribution to the predictive model. To generate potential and uncertainty maps, compositional data are simulated at unsampled locations via a chain of transformations (isometric log-ratio transformation followed by the flow anamorphosis) and geostatistical simulation. The simulated results are subsequently back-transformed to the original compositional space. The trained predictive model is used to estimate the probability of classes for simulated compositions. The proposed approach is illustrated through two case studies. In the first case study, the major crustal blocks of the Australian continent are predicted from the surface regolith geochemistry of the National Geochemical Survey of Australia project. The aim of the second case study is to discover the superficial deposits (peat) from the regional-scale soil geochemical data of the Tellus Project. The accuracy of the results in these two case studies confirms the usefulness of the proposed method for geological class prediction and geological process discovery.
Alexandrium catenella (group IV) and Alexandrium tamarense (group III) (Dinophyceae) are two cryptic invasive phytoplankton species belonging to the A. tamarense species complex. Their worldwide spread is favored by the human activities, transportation and climate change. In order to describe their diversity in the Mediterranean Sea and understand their settlements and maintenances in this area, new microsatellite markers were developed based on Thau lagoon (France) samples of A. catenella and A. tamarense strains. In this study twelve new microsatellite markers are proposed. Five of these microsatellite markers show amplifications on A. tamarense and ten on A. catenella. Three of these 12 microsatellite markers allowed amplifications on both cryptic species. Finally, the haplotypic diversity ranged from 0.000 to 0.791 and 0.000 to 0.942 for A. catenella and A. tamarense respectively. 相似文献
ABSTRACT Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis. 相似文献
Most source-to-sink studies typically focus on the dynamics of clastic sediments and consider erosion, transport and deposition of sediment particles as the sole contributors. Although often neglected, dissolved solids produced by weathering processes contribute significantly in the sedimentary dynamics of basins, supporting chemical and/or biological precipitation. Calcium ions are usually a major dissolved constituent of water drained through the watershed and may facilitate the precipitation of calcium carbonate when supersaturating conditions are reached. The high mobility of Ca2+ ions may cause outflow from an open system and consequently loss. In contrast, in closed basins, all dissolved (i.e. non-volatile) inputs converge at the lowest point of the basin. The endoreic Great Salt Lake basin constitutes an excellent natural laboratory to study the dynamics of calcium on a basin scale, from the erosion and transport through the watershed to the sink, including sedimentation in lake's waterbody. The current investigation focused on the Holocene epoch. Despite successive lake level fluctuations (amplitude around 10 m), the average water level seems to have not been affected by any significant long-term change (i.e. no increasing or decreasing trend, but fairly stable across the Holocene). Weathering of calcium-rich minerals in the watershed mobilizes Ca2+ ions that are transported by surface streams and subsurface flow to the Great Salt Lake (GSL). Monitoring data of these flows was corrected for recent anthropogenic activity (river management) and combined with direct precipitation (i.e. rain and snow) and atmospheric dust income into the lake, allowing estimating the amount of calcium delivered to the GSL. These values were then extrapolated through the Holocene period and compared to the estimated amount of calcium stored in GSL water column, porewater and sediments (using hydrochemical, mapping, coring and petrophysical estimates). The similar estimate of calcium delivered (4.88 Gt) and calcium stored (3.94 Gt) is consistent with the premise of the source-to-sink approach: a mass balance between eroded and transported compounds and the sinks. The amount of calcium deposited in the basin can therefore be predicted indirectly from the different inputs, which can be assessed with more confidence. When monitoring is unavailable (e.g. in the fossil record), the geodynamic context, the average lithology of the watershed and the bioclimatic classification of an endoreic basin are alternative properties that may be used to estimate the inputs. We show that this approach is sufficiently accurate to predict the amount of calcium captured in a basin and can be extended to the whole fossil record and inform on the storage of calcium. 相似文献
In June 2018, the European Parliament and Council of the European Union adopted a legislative regulation for incorporating greenhouse gas emissions and removals from Land Use, Land Use Change and Forestry (EU-LULUCF) under its 2030 Climate and Energy Framework. The LULUCF regulation aim to incentivise EU Member States to decrease greenhouse gas emissions and increase removals in the LULUCF sector. The regulation, however, does not set a target for increasing the LULUCF carbon sink, but rather includes a ‘no net debit’ target for LULUCF (Forests and Agricultural soils). For Managed Forest Land (MFL) an accounting framework with capped credits for additional mitigation against a set forest reference level (FRL) was agreed for 2021–2030. The FRL gives the projected future carbon sink in the two compliance periods 2021–2025 and 2026–2030 under “continuation of forest management practices as they were in the reference period 2000–2009”. This FRL was disputed by some Member States as it was perceived to put a limit on their future wood harvesting from MFL. Here we simulated with the EFISCEN European forest model the “continuation of forest management practices” and determined the corresponding wood harvest for 26 EU countries under progressing age classes.
Results
The simulations showed that under “continuation of forest management practices” the harvest (wood removals) in the 26 EU countries as a whole can increase from 420 million m3/year in 2000–2009 to 560 million m3/year in 2050 due to progressing age classes. This implies there is a possibility to increase absolute wood harvests without creating debits compared to the forest reference level. However, the manner in which ‘continuation of forest management’ developed with a progressing age class development over time, meant that in some countries the future harvesting exceeded 90% of the increment. Since this generally is considered to be unsustainable we additionally set a harvesting cut-off as max 90% of increment to be harvested for each individual country as a possible interpretation of sustainability criteria that are included in the regulation. Using this additional limit the projected harvest will only increase to 493 million m3/year.
Conclusions
The worry from Member States (MS) that the FRL will prevent any additional harvesting seems unwarranted. Due to differences between Member States concerning the state of their forest resources, the FRL as a baseline for harvesting works out very differently for the different Member States. The FRL may have other unforeseen consequences which we discuss. Under all scenarios the living forest biomass sink shows a decline. This can be counteracted through incentivising measures under Climate Smart Forestry.
A compositional multivariate approach was used to analyse regional-scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey of Northern Ireland. The multi-element total concentration data presented comprise X-ray fluorescence (XRF) analyses of 6862 rural soil samples collected at 20-cm depth on a non-aligned grid at one site per \(2\,\hbox {km}^{2}\). Censored data were imputed using published detection limits. Each soil sample site was assigned to the regional geology map, resulting in spatial data for one categorical variable and 35 continuous variables comprised of individual and amalgamated elements. This paper examines the extent to which soil geochemistry reflects the underlying geology or superficial deposits. Since the soil geochemistry is compositional, log-ratios were computed to adequately evaluate the data using multivariate statistical methods. Principal component analysis (PCA) and minimum/maximum autocorrelation factors (MAF) were used to carry out linear discriminant analysis (LDA) as a means to discover and validate processes related to the geologic assemblages coded as age bracket. Peat cover was introduced as an additional category to measure the ability to predict and monitor fragile ecosystems. Overall prediction accuracies for the age bracket categories were 68.4 % using PCA and 74.7 % using MAF. With inclusion of peat, the accuracy for LDA classification decreased to 65.0 and 69.9 %, respectively. The increase in misclassification due to the presence of peat may reflect degradation of peat-covered areas since the creation of superficial deposit classification. 相似文献