Origin of pyrite nodules at the top of the nantuo diamictites, Southern China

Pyrite nodules up to 20 cm in diameter are found at the top of the Marinoan (~ 635 Ma) Nantuo glacial diamictite as well as in the cap dolostones and shale/siltstones in the lower Doushantuo Formation in eastern Guizhou, southern China. Field occurrences, petrography, and stable sulfur isotopic compositions of pyrite nodules were studied from a section at Taoying, eastern Guizhou, China. Pyrite δ34S values from different nodules varied from 7.3 to 60.5‰ at different stratigraphic levels. No stratigraphic trend existed for the δ34S, supporting the scenario of pyrite formation in sediments before the precipitation of the cap dolostone. Pyrite δ34S values were also homogeneous within individual nodules at a 0.3 to 1 cm sampling scale, but were more heterogeneous at a 2 mm sampling scale. Homogeneity was not expected from the particular model for pyrite nodule formation in a largely closed or semi-closed environment. Thus, differential cementation and compaction of the pyrite-bearing sediments may have produced the nodular shape of the pyrite deposit.

Diversity partitioning and community structure of epiphytic bryophytes along an elevational gradient in the north-eastern Madagascar

Understanding spatial variation in species composition of different communities is key to understanding the processes that generate and maintain biodiversity. The partitioning of diversity into hierarchical scale-related components is an interesting approach to quantitatively defining the overall net biodiversity from hierarchically scaled studies and is a useful method in studies of conservation biology and restoration. This paper deals with the additive partitioning of the overall diversity and the partitioning of beta-diversity of epiphytic bryophytes along an elevational gradient in Madagascar. The aim is to describe the variation in species composition between sites and to elucidate why different species occur in different communities in the Marojejy National Park (250–2050 m). We looked at the contribution of α and β diversity to total diversity were calculated from four hierarchical scales: microhabitat (50 cm2), quadrat (4 m2), plot (100 m2) and elevation (every 200 m). Furthermore, we documented how the two components of beta-diversity (turnover and nestedness) are influenced by variation in elevation. Our result suggests that more variation in species richness was found within the elevational scales, than within microplot scales, confirming that beta diversity at the largest sampling scale is the largest contributor to the total diversity. It indicates that bryophyte species among sample within each level are a subsample of the same species pool. This study shows evidence that the beta-diversity of epiphytic bryophyte assemblages is dominated by high spatial turnover due to recruitment of new species along the Marojejy transect, a clear pattern for mountains.

Variability of agrophysical properties of hillslope soils in the Cis-Salair region (West Siberia)

The aim of the study. The aim of the study was to estimate heterogeneity of moisture-related soil physical properties in a sequence of degraded hillslope soils in the cis-Salair region. The main tasks were to examine spatial fluctuations and changes in morphological and agrophysical properties of soils, differing in erosion degree, and assess their variability. Location and time of the study. The study was conducted in the forest-steppe zone in the Bugotak Hills (Novosibirsk region, Russia). A sequence of arable soils located along the 411 m convex hillslope with south-eastern exposition was investigated since July 01 till August 15, 2016. Main results. The article describes the variation of soil density, moisture content and temperature in a sequence of hillslope soils. The variation in the ploughed layer was found to be quite high, depending on the sampling scale. Examination of the spatial variability of the soil hydrophysical properties showed that the non-eroded podzolised chernozem (Luvic Greyzemic Chernozem) and toeslope meadow soil (Gleyic Greyzemic Phaeozem, Colluvic)had the highest density. The lower temperatures were recorded in the slightly eroded dark-gray forest soil (Luvic Greyzemic Phaeozem) and in the toeslope meadow soil, accumulating soil material eroded from the topslope. The temperature difference range between the “cold” and “warm” soils was 1.8 °С. Conclusions. Such studies have important prospects in development and introduction of agricultural technologies that are landscape-adapted, especially in areas with diverse relief and eroded soils. The main focus of such research should be the anti-erosion landscaping. The problem needs to be further studied within the framework of targeting the anti-erosion measures to geographic regions and natural zones.

Sampling scale and season influence the observed relationship between the density of deer and questing Ixodes ricinus nymphs

Background The relationship between environmentally transmitted tick parasites, Ixodes spp., and their main reproductive host, deer, is generally thought to be positive. However, measuring host abundance and density directly can be challenging and indirect methods are often used. The observed relationship between the parasite and host may be affected by sampling scale and season, which could lead to different inferences being made. Here, we aimed to test the effect of sampling scale and season on the relationship between density of deer and the density of questing Ixodes ricinus nymphs. Methods The density of deer (primarily Dama dama) was estimated using line transect distance sampling of deer dung quantified in different seasons (winter and summer) and measured at three different nested scales (site, transect and observation level). Questing nymph density was measured using blanket drag methods and estimates were calculated at the same scales as deer density estimates. General linear models were used to evaluate the relationship between questing nymphs, deer density and other environmental variables at each sampling scale and each season deer density was measured at. Results While a positive relationship between deer density and questing nymph density was detected at the site and transect scale, no relationship was apparent at the observation level. This was likely due to increased variation and reduced precision of deer dung counts at the finest sampling scale. Seasonal changes in deer populations were observed likely reflecting seasonal shifts in habitat usage. The summer estimates of deer density explained questing nymph density whereas winter estimates did not. Conclusions Our results show that the scale of sampling can affect the detectability of the positive association between host and vector species. Furthermore, such associations can be obscured if hosts exhibit seasonal changes in habitat use. Thus, both sampling scale and season are important to consider when investigating the relationship between host and vector species.

Parallel Hydrological Model Parameter Uncertainty Analysis Based on Message-Passing Interface

Parameter uncertainty analysis is one of the hot issues in hydrology studies, and the Generalized Likelihood Uncertainty Estimation (GLUE) is one of the most widely used methods. However, the scale of the existing research is relatively small, which results from computational complexity and limited computing resources. In this study, a parallel GLUE method based on a Message-Passing Interface (MPI) was proposed and implemented on a supercomputer system. The research focused on the computational efficiency of the parallel algorithm and the parameter uncertainty of the Xinanjiang model affected by different threshold likelihood function values and sampling sizes. The results demonstrated that the parallel GLUE method showed high computational efficiency and scalability. Through the large-scale parameter uncertainty analysis, it was found that within an interval of less than 0.1%, the proportion of behavioral parameter sets and the threshold value had an exponential relationship. A large sampling scale is more likely than a small sampling scale to obtain behavioral parameter sets at high threshold values. High threshold values may derive more concentrated posterior distributions of the sensitivity parameters than low threshold values.

Deep Active Learning for Surface Defect Detection

Most of the current object detection approaches deliver competitive results with an assumption that a large number of labeled data are generally available and can be fed into a deep network at once. However, due to expensive labeling efforts, it is difficult to deploy the object detection systems into more complex and challenging real-world environments, especially for defect detection in real industries. In order to reduce the labeling efforts, this study proposes an active learning framework for defect detection. First, an Uncertainty Sampling is proposed to produce the candidate list for annotation. Uncertain images can provide more informative knowledge for the learning process. Then, an Average Margin method is designed to set the sampling scale for each defect category. In addition, an iterative pattern of training and selection is adopted to train an effective detection model. Extensive experiments demonstrate that the proposed method can render the required performance with fewer labeled data.