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The global pattern of plant evolution through the Permian−Triassic mass extinction is uncertain, and the extent to which land plants were affected is debated. Detailed studies undertaken at a regional scale can help evaluate this floral transition, and thus we provide a detailed account of floral evolution from the Permian to Middle Triassic of North China based on new paleobotanical data and a refined biostratigraphy. Five floral transition events are identified from before, during, and after the Permian−Triassic crisis, including the disappearance of the gigantopterid flora (associated with loss of coal deposits), the end-Permian mass extinction of Paleophytic taxa, and gradual recovery in the Triassic with the stepwise appearance of the Mesophytic vegetation. The record begins with a Cisuralian gigantopterid-dominated rainforest community, and then a Lopingian walchian Voltziales conifer-ginkgophyte community that evolved into a voltzialean conifer-pteridosperm forest community. The last is associated with a change amongst terrestrial vertebrates from the Jiyuan fauna to a pareiasaur-dominated fauna, found in red beds that lack coal deposits due to arid conditions. The disappearance of the voltzialean conifer forest community may represents the end-Permian mass extinction of plants although it could also be a consequence of the non-preservation of plants in sedimentary red-beds. The first post-crisis plants are an Induan herbaceous lycopsid community, succeeded by the Pleuromeia-Neocalamites shrub marsh community. A pteridosperm shrub woodland community dominated for a short time in the late Early Triassic along with the reappearance of insect herbivory. Finally, in the Middle Triassic, gymnosperm forest communities gradually rose to dominance in both uplands and lowlands along with other diverse plant communities, indicating the establishment of the Mesophytic Flora.

The Wufeng and Longmaxi organic-rich shales host the largest shale gas plays in China. This study examined the petrography, rare earth element (REE) and other trace-element geochemistry, Sm-Nd geochronology, and isotope geochemistry (87Sr/86Sr, δ18O, δ13C) of fracture-cementing minerals within core samples of the Wufeng and Longmaxi Formations from the Jiaoshiba shale gas field in order to (1) characterize the mineral phases occurring in the veins (mineralized fractures); (2) determine the ages of the calcite by the Sm-Nd isochron dating method; (3) understand the sources of calcite-precipitating fluids; and (4) explore the possible mechanisms responsible for calcite vein formation in shale gas systems. The fractures hosted in the Longmaxi Formation are mineralized with quartz as the predominant fracture cement, and calcite as an intracementation phase postdating the earlier quartz cement. In contrast, the fractures hosted in the Wufeng Formation are dominantly mineralized by calcite, which occurs either as the only cement present or as a cement phase predating later quartz cement. Calcite veins within the Longmaxi Formation have a Sm-Nd isochron age of 160 ± 13 Ma and δ13C values of –4.71‰ to –3.11‰, δ18O values of 17.1‰–17.4‰, and 87Sr/86Sr values of 0.72437–0.72869. Calcite veins within the Wufeng Formation yielded a Sm-Nd isochron age of 133 ± 15 Ma and are characterized by δ13C values of –2.29‰ to –1.03‰, δ18O values of 17.3‰–17.7‰, and 87Sr/86Sr values of 0.72202–0.72648. The similarity between 87Sr/86Sr values of the calcite and those of their respective surrounding host rocks (0.72670–0.72875 of the Longmaxi shales; 0.72030–0.72648 of the Wufeng shales), combined with relatively depleted δ13C and uniform fluid δ18O isotopic features, indicates that the calcite-precipitating fluids within the Wufeng and Longmaxi Formations were derived largely from their respective surrounding host-rock sources. REE data equally indicate that the distinguishable Eu anomalies (6.20–19.35; 4.45–11.91), Y anomalies (1.03–1.50; 1.44–1.70), and Y/Ho ratios (28.80–39.16; 38.86–45.18) of calcite veins within the Longmaxi and Wufeng Formations were controlled by their respective surrounding host rocks. The Sm-Nd isochron ages and fluid inclusion data of fracture cements suggest that fracture opening and calcite precipitation in composite veins within the Wufeng and Longmaxi Formations were triggered by gas generation overpressurization.

Objectives Convolutional neural network (CNN) is a state-of-art deep learning (DL) method with superior performance in image classification. Here, a CNN-based workflow is proposed to discriminate hominid teeth. Our hope is that this method could help confirm otherwise questionable records of Homo from Pleistocene deposits where there is a standing risk of mis-attributing molars of Pongo to Homo. Methods and materials A two-step workflow was designed. The first step is converting the enamel-dentine junction (EDJ) into EDJ card, that is, a two-dimensional image conversion of the three-dimensional EDJ surface. In this step, researchers must carefully orient the teeth according to the cervical plane. The second step is training the CNN learner with labeled EDJ cards. A sample consisting of 53 fossil Pongo and 53 Homo (modern human and Neanderthal) was adopted to generate EDJ cards, which were then separated into training set (n = 84) and validation set (n = 22). To assess the feasibility of this workflow, a Pongo-Homo classifier was trained from the aforementioned EDJ card set, and then the classifier was used to predict the taxonomic affinities of six samples (test set) from von Koenigswald's Chinese Apothecary collection. Results Results show that EDJ cards in validation set are classified accurately by the CNN learner. More importantly, taxonomic predictions for six specimens in test set match well with the diagnosis results deduced from multiple lines of evidence, implying the great potential of CNN method. Discussion This workflow paves a way for future studies using CNN to address taxonomic complexity (e.g., distinguishing Pongo and Homo teeth from the Pleistocene of Asia). Further improvements include visual interpretation and extending the applicability to moderately worn teeth.

International audience; Objective: Three-dimensional relative enamel thickness (3DRET) is important for assessing hypotheses about taxonomy, phylogeny, and dietary reconstruction for primates. However, its weaknesses have not been thoroughly investigated. Here, we analyze its weaknesses and propose an index aiming at better taxonomic discrimination. Materials and Methods: The dimensionless 3D index, ratio of enamel-thickness to dentinethickness (3DRED), which is defined as the cubic root of the ratio of 3D average enamel thickness (3DAET) to 3D average dentine thickness (3DADT), is proposed here. To compare 3DRET and 3DRED and their sensitivity to voxel size, a fossil orangutan molar was scanned 14 times with different resolutions ranging from 10 to 50 μm. Enamel thickness analysis was carried out for each resultant digital model. In addition, enamel thickness measurements of 179 mandibular permanent molars (eight genera) were analyzed, followed by investigating the relationship between 3DRET and 3DAET and between 3DRED and 3DAET. Results: Regarding sensitivity, 3DRED is more robust than 3DRET. In addition, 3DRET is correlated with 3DAET by linear curve with regression coefficients approximating or larger than 0.8 in most cases, while 3DRED shows less correlation with 3DAET. Furthermore, there are clear separations between different taxa in the bivariate plot of 3DRED against 3DAET, indicative of the taxonomic value of 3DRED. Conclusion: Under certain conditions, 3DRED promises to be a robust and reliable alternative to 3DRET in taxonomic study. KEYWORDS enamel/dentine thickness ratio, hominid teeth, relative enamel thickness, taxonomic assessment, voxel size sensibility. Primate enamel thickness variation stems from an evolutionary interplay between functional/adaptive constraints (ecology) and strict control mechanisms of the morphogenetic program (

The destruction of both terrestrial and marine ecosystems generally shows a process of rapid extinction followed by the wipe out of the Permian-type relics in the Permian–Triassic mass extinction, but the relationship between the terrestrial and marine ecosystem collapses is not clear until now. The terrestrial input from the land to marine system is an important link between them. Previous study has demonstrated a substantial increase of terrestrial influx to the marine water most likely corresponding to the Permian–Triassic mass extinction. Our new geochemical data from the Laolongdong section in the shallow marine carbonate platform of South China, reveal that the elevated terrestrial input nearby the Permian–Triassic Boundary (PTB) is actually marked by a two-pulse scenario. The first pulse represents a ~ 3- to ~ 6-fold increase of the terrestrial flux. The onset of the increase took place in the extinction horizon at the basal part of microbialites at Laolongdong, basically corresponding to Bed 24a of Meishan section and prior to the end-Permian mass extinction zenith; then the increase continued and spanned the extinction zenith. The second pulse is characterized a ~ 21- to ~ 35-fold increase in the terrestrial flux, equivalent to the widespread, abundant presence of mudstones in the earliest Triassic and roughly corresponding to the stage where the Permian-type survivors were thoroughly wiped out. A two-pulse terrestrial input is also clearly recorded at Cili, Shangsi and Meishan of South China, western Australia and Arctic Canada. Two episodes of the enhanced terrestrial input provide strong evidence for the devastation of the terrestrial ecosystem and insights into the reasonable explanation for the relationship between terrestrial and marine ecosystem collapses nearby the PTB.

Microstructure-based quantitative computation of the shale permeability is challenging due to the presence of organic matter with nanoporous features. In this study, a new three-dimensional (3D) coupled model is proposed to investigate the micro-scale permeability of organic-rich-shale matrix. The coupled model consists of two subdomains, organic matter and inorganic matrix. They are described by the pore network model (PNM) and continuum model to capture the non-Darcy and Darcy flow, respectively, and the gas flow in the two subdomains are coupled by finite element mortars (Mortar). The convergence error, grid discretization and parallel scheme are also investigated to get the optimal computing parameters for this model. Then, the effects of the total organic content (TOC), kerogen distribution and pore-size distribution on the apparent permeability (AP) of shale matrix are studied using the coupled model with computer-generated PNMs. And on the basis of FIB-SEM images, a Longmaxi shale sample from the Sichuan Basin, China is introduced to build a real shale model. Results show that AP is more sensitive to TOC and pore-size distribution than kerogen distribution. Additionally, in order to analyze the necessity of 3D model, a comparison of 3D and two-dimensional (2D) model is made and the error of 2D model is pointed out. The 3D couple model affords a foundation for further upscaling of shale permeability to REV scale and reservoir scale. (C) 2017 Elsevier Ltd. All rights reserved.

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

Most of pore network models were originally designed for conventional porous media (e.g. sandstone), where pore size is at micron-scale and the dominant flow is Darcy-flow. However, those models could be inapplicable for shale (a typical unconventional porous media), since plenty of nanopores exist therein and therefore the non-Darcy effects can no longer be ignored. In this contribution, the details of shale gas flow were analyzed, and it was found that flow resistance could be misestimated by previous models. For this reason, we propose a pore network model that takes into account the influences of non-Darcy effects on pore structure. In the model, pore/throat radius and throat length are not constant but change with pressure, which is distinguishable from previous models where parameters are independent of pressure. The proposed model and previous models are defined as apparent pore network (APN) and intrinsic pore network (IPN), respectively. A shale sample, imaged by focused ion beam-scanning electron microscope, was used to extract APN and IPN, and then, their network structures were compared in the terms of throat length and throat radius. Under different pressure conditions (ranging from 0.1 MPa to 48 MPa) and image resolutions (5 nm, 10 nm, 20 nm, 50 nm, and 100 nm), shale gas flow was simulated through APN and IPN, respectively. Numerical results show that apparent permeability is likely to be erroneously predicted by IPN, while APN provides a relatively reasonable solution.

A large amount of nano-pores exists in pore clusters in shale gas reservoirs. In addition to the multiple transport regimes that occur on the nanoscale, the pore space is another major factor that significantly affects the shale gas recoverability. An investigation of the pore-scale shale gas flow is therefore important, and the results can be used to develop an effective cluster-scale pore network model for the convenient examination of the process efficiency. Focused ion beam scanning electron microscope imaging, which enables the acquisition of nanometre-resolution images that facilitate nano-pore identification, was used in conjunction with a high-precision pore network extraction algorithm to generate the equivalent pore network for the simulation of Darcy and shale gas flows through the pores. The characteristic parameters of the pores and the gas transport features were determined and analysed to obtain a deeper understanding of shale gas flow through nanoscale pore clusters, such as the importance of the throat flux–radius distribution and the variation of the tortuosity with pressure. The best parameter scheme for the proposed effective model of shale gas flow was selected out of three derived schemes based on the pore-scale prediction results. The model is applicable to pore-scale to cluster-scale shale gas flows and can be used to avoid the multiple-solution problems in the study of gas flows. It affords a foundation for further study to develop models for shale gas flows on larger scales.

Characterization of pore structure in reservoirs plays a significant role in predicting properties of rocks and classifying the reservoirs. The focus is on determining comprehensive geometric and topological parameters of pore structure. X-ray computerized tomography scanning provides a 3D image of the pore structure. However, these images cannot directly generate pore structure parameters without numerical characterization of the images. A new method is developed to determine comprehensive geometric and topological parameters of pore structure from images. These parameters were determined by utilizing common mathematical morphology operations to segment the entire pore space into a series of space blocks of different radii, subsequently identifying these blocks as pores and throats based on the proposed morphological features of pore and throat. The parallel scheme was also studied to obtain the highest efficiency. Thereafter, the characteristics of pore structures and the performance of the method were assessed for various samples. The results were compared to the results calculated by other methods. Results showed that the method produced reliable pore structure characteristics for a wide variety of rocks. Additionally, in order to discuss whether our results can be used as the basic input data for other researches, an example about two-phase flow simulation was made and a comparison of simulation results and experimental data was made. Our results were a competent choice for other studies. Also, after proposing the detection criteria of pore and throat, the subsequent detecting procedure is without artificial adjustable parameters, making the method convenient to use. This method can comprehensively, efficiently, accurately, and conveniently characterize the pore structure based only on images.