Strong Heterogeneity Research Articles

Investigating the spatial heterogeneity of drunk-driving events in Beijing based on a hybrid method with LISA and GeoDetector

Drunk-driving events can be divided into drunk-driving crashes (DDCs) and non-crash drunk-driving events (NDDEs). Strong spatial heterogeneity, which consists of spatial local heterogeneity and spatial stratified heterogeneity, exists in drunk-driving events. Therefore, this article proposed a hybrid method with LISA and GeoDetector to investigate the spatial heterogeneity of drunk-driving events. First, an integrated method of Getis-Ord Gi* and Anselin Local Moran’s I, which belong to LISA, was applied for the analysis of spatial local heterogeneity. Then, based on the improved GeoDetector with a highest q value, this article explored the main factors contributing to spatial stratified heterogeneity. Results show that DDCs are concentrated in the urban areas and the sub-centres located in the east of suburban, while NDDEs are predominantly found in the urban areas and the sub-centres located in the northwest and southwest of suburban. The spatial stratified heterogeneity analysis, conducted using the Factor Detector, reveals the pivotal factors influencing the spatial distribution of DDCs. Entertainment venues, alcohol outlets, and population density exhibit significant impacts, with q-values of 0.233, 0.227, and 0.203, respectively. Similarly, for NDDEs, the most influential factor is the density of entertainment venues, with a q-value of 0.243. When exploring the interaction effects between factors, the study emphasises that the interaction between population density and alcohol outlet density shows the highest q-value of 0.787. This highlights a substantial impact on the spatial formation of drunk-driving events. These findings offer valuable insights for implementing targeted measures to improve road safety and reduce the occurrence of drunk-driving events in Beijing.

Enhancing seismic porosity estimation through 3D sequence-to-sequence deep learning with data augmentation, spatial constraints, and geologic constraints

Estimating porosity from seismic data is critical for studying underground rock properties, assessing energy reserves, and subsequent reservoir exploration and development. For reservoirs with strong heterogeneity, the endeavor to accurately and stably characterize spatial variations in porosity often encounters considerable challenges due to the rapid lateral changes in formations. In view of this, establishing a robust mapping relationship from seismic data to reservoir properties in 3D space is important in addressing this challenge. We transform the conventional 1D sequence-to-point (STP) prediction paradigm into a 3D sequence-to-sequence (STS) prediction paradigm to enable machine learning to extract 3D seismic data features. The 3D STS prediction presents valuable potential for enhancing the geologic continuity and vertical characterization ability of porosity compared to STP. Building upon the 3D STS prediction model, three strategies from different perspectives are introduced to further enhance the performance of seismic porosity estimation. First, we apply a translation-based data augmentation (DA) strategy to mitigate the problem of sparsely labeled data. Second, we develop spatial constraints (SCs) considering absolute coordinates and relative time to boost the spatial delineation of porosity. Third, to incorporate geologic insights into machine learning, we impose geologic constraints (GCs) by measuring the data distribution similarity between around-the-well predictions and well labels. Compared with DA strategies, incorporating SCs and GCs to STS yields more substantial improvements, which illustrates the importance of prior knowledge for physical parameter inversion. Finally, the combined application of these three strategies and the 3D STS method gives better generalization performance and geologic plausibility in the porosity prediction for investigated carbonate reservoirs, outperforming other methods and decreasing error by an average of 8% across 48 wells compared to STP.

Research on spatial carving method of glutenite reservoir based on opacity voxel imaging

The glutenite reservoir in an exploration area in eastern China is well-developed and holds significant exploration potential as an important oil and gas alternative layer. However, due to the influence of sedimentary characteristics, the glutenite reservoir exhibits strong lateral heterogeneity, significant vertical thickness variations, and low accuracy in reservoir space characterization, which affects the reasonable and effective deployment of development wells. Seismic data contains the three-dimensional spatial characteristics of geological bodies, but how to design a suitable transfer function to extract the nonlinear relationship between seismic data and reservoirs is crucial. At present, the transfer functions are concentrated in low-dimensional or high-dimensional fixed mathematical models, which cannot accurately describe the nonlinear relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of complex reservoirs. In this regard, this paper first utilizes a fusion method based on probability kernel to fuse seismic attributes such as wave impedance, effective bandwidth, and composite envelope difference. This provide a more intuitive reflection of the distribution characteristics of glutenite reservoirs. Moreover, a hybrid nonlinear transfer function is established to transform the fused attribute cube into an opaque attribute cube. Finally, the illumination model and ray casting method are used to perform voxel imaging of the glutenite reservoirs, brighten the detailed characteristics of reservoir space, and then form a set of methods for ' brightening reservoirs and darkening non-reservoirs ', which improves the spatial engraving accuracy of glutenite reservoirs.

Pore Structure and Heterogeneity Characteristics of Coal-Bearing Marine–Continental Transitional Shales from the Longtan Formation in the South Sichuan Basin, China

Marine–continental transitional shale has become a new field for shale gas exploration and development in recent years. Its reservoir characteristics analysis lags significantly behind that of marine shale, which restricts the theoretical research on the accumulation of marine–continental transitional shale and the progress of exploration and development. The shale pore system is complex and has strong heterogeneity, which restricts the fine evaluation and optimization of the reservoir. Based on nitrogen adsorption–desorption experiments, the morphology and structural characteristics of coal-bearing shale pores were analyzed, and then the micro-pore structure heterogeneity was quantitatively characterized based on fractal theory and nitrogen adsorption–desorption data, and the relationship between pore structure parameters and their influence on fractal characteristics were discussed. The hysteresis loop of nitrogen desorption isotherm mainly belongs to type B, indicating ink bottle, flat plate, and slit are the main pore shapes. The pore size distribution curves are left unimodal or multimodal, with the main peak around 4 nm and 20–60 nm. Smaller pores develop a larger specific surface area, resulting in a high value of fractal dimension (2.564 to 2.677). The rougher the pore surface and the larger the specific surface area provide an adequate adsorption site for shale gas adsorption and aggregation. Thus, fractal characteristics conduced to understand the pore structure, heterogeneity, and gas-bearing property of coal-bearing shale.

Mutation spectrum of hearing loss patients in Northwest China: Identification of 20 novel variants.

Hearing loss (HL) is the most frequent sensory deficit in humans, with strong genetic heterogeneity. The genetic diagnosis of HL is very important to aid treatment decisions and to provide prognostic information and genetic counselling for the patient's family. We detected and analysed 362 Chinese non-syndromic HL patients by screening of variants in 15 hot spot mutations. Subsequently, 40 patients underwent further whole-exome sequencing (WES) to determine genetic aetiology. The candidate variants were verified using Sanger sequencing. Twenty-three carrier couples with pathogenic variants or likely pathogenic variants chose to proceed with prenatal diagnosis using Sanger sequencing. Among the 362 HL patients, 102 were assigned a molecular diagnosis with 52 different variants in 22 deafness genes. A total of 41 (11.33%) cases with the biallelic GJB2 (OMIM # 220290) gene mutations were detected, and 21 (5.80%) had biallelic SLC26A4 (OMIM # 605646) mutations. Mitochondrial gene (OMIM # 561000) mutations were detected in seven (1.93%) patients. Twenty of the variants in 15 deafness genes were novel. SOX10 (OMIM # 602229), MYO15A (OMIM # 602666) and WFS1 (OMIM # 606201) were each detected in two patients. Meanwhile, OSBPL2 (OMIM # 606731), RRM2B (OMIM # 604712), OTOG (OMIM # 604487), STRC (OMIM # 606440), PCDH15 (OMIM # 605514), LOXHD1 (OMIM # 613072), CDH23 (OMIM # 605516), TMC1 (OMIM # 606706), CHD7 (OMIM # 608892), DIAPH3 (OMIM # 614567), TBC1D24 (OMIM # 613577), TIMM8A (OMIM # 300356), PTPRQ (OMIM # 603317), SALL1 (OMIM # 602218), and GSDME (OMIM # 608798) were each detected in one patient. In addition, as regards one couple with a heterozygous variant of CDH23 and PCDH15, respectively, prenatal diagnosis results suggest that the foetus had double heterozygous (DH) variants of CDH23 and PCDH15, which has a high risk to cause ID/F type Usher syndrome. Our study expanded the spectrum of deafness gene variation, which will contribute to the genetic diagnosis, prenatal diagnosis and the procreation guidance of deaf couple. In addition, the deafness caused by two genes should be paid attention to in the prenatal diagnosis of families with both deaf patients.

A three-dimensional numerical study on the stability of layered rock spillway tunnels in alpine canyon areas

Rock masses in alpine canyon areas exhibit strong heterogeneity, discontinuity, and are subject to strong tectonic effects and stress unloading, leading to extremely complex distribution of in-situ stress. In addition, the occurrence of layered rock masses makes it more complex, with obvious anisotropic mechanical properties. This study proposes a comprehensive method for evaluating the stability of layered rock spillway tunnels in a hydropower station in an alpine canyon. First, the failure criterion and mechanical model of layered rock masses considering the anisotropy induced by the bedding plane and the true triaxial stress regime were established; an inversion theory and calculation procedure for in-situ stress in alpine canyon areas were then introduced. Finally, by using a self-developed numerical tool, i.e. CASRock, the stability of the layered rock spillway tunnel in a hydropower station was numerically analyzed. The results show that, affected by geological structure and stratigraphic lithology, there is significant differentiation in the in-situ stress in alpine canyons, with horizontal tectonic stress as the main factor. The occurrence of layered rock masses in the region has a significant impact on the stability of surrounding rock, and the angle between the bedding strike and the tunnel axis as well as the bedding dip both exert a significant influence on the failure characteristics of the surrounding rock.

Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming

Human activities affect the Earth’s climate through modifying the composition of the atmosphere, which then creates radiative forcing that drives climate change. The warming effect of anthropogenic greenhouse gases has been partially balanced by the cooling effect of anthropogenic aerosols. In 2020, fuel regulations abruptly reduced the emission of sulfur dioxide from international shipping by about 80% and created an inadvertent geoengineering termination shock with global impact. Here we estimate the regulation leads to a radiative forcing of +0.2±0.11\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+0.2\\pm 0.11$$\\end{document}Wm−2 averaged over the global ocean. The amount of radiative forcing could lead to a doubling (or more) of the warming rate in the 2020 s compared with the rate since 1980 with strong spatiotemporal heterogeneity. The warming effect is consistent with the recent observed strong warming in 2023 and expected to make the 2020 s anomalously warm. The forcing is equivalent in magnitude to 80% of the measured increase in planetary heat uptake since 2020. The radiative forcing also has strong hemispheric contrast, which has important implications for precipitation pattern changes. Our result suggests marine cloud brightening may be a viable geoengineering method in temporarily cooling the climate that has its unique challenges due to inherent spatiotemporal heterogeneity.

Single-Cell Landscape and a Macrophage Subset Enhancing Brown Adipocyte Function in Diabetes.

Metabolic dysregulation is a hallmark of type 2 diabetes mellitus (T2DM), in which the abnormalities in brown adipose tissue (BAT) play important roles. However, the cellular composition and function of BAT as well as its pathological significance in diabetes remain incompletely understood. Our objective is to delineate the single-cell landscape of BAT-derived stromal vascular fraction (SVF) and their characteristic alterations in T2DM rats. T2DM was induced in rats by intraperitoneal injection of low-dose streptozotocin and high-fat diet feeding. Single-cell mRNA sequencing was then performed on BAT samples and compared to normal rats to characterize changes in T2DM rats. Subsequently, the importance of key cell subsets in T2DM was elucidated using various functional studies. Almost all cell types in the BAT-derived SVF of T2DM rats exhibited enhanced inflammatory responses, increased angiogenesis, and disordered glucose and lipid metabolism. The multidirectional differentiation potential of adipose tissue-derived stem cells was also reduced. Moreover, macrophages played a pivotal role in intercellular crosstalk of BAT-derived SVF. A novel Rarres2+macrophage subset promoted the differentiation and metabolic function of brown adipocytes via adipose-immune crosstalk. BAT SVF exhibited strong heterogeneity in cellular composition and function and contributed to T2DM as a significant inflammation source, in which a novel macrophage subset was identified that can promote brown adipocyte function.

Research on water-out mode and differential perforation in thick carbonate reservoir

The development of anti-rhythmic carbonate reservoirs in the Middle East often encounters challenges such as water hold-up and reverse coning during the water injection process, leading to premature water breakthrough and various water-out issues. The unclear understanding of these phenomena, attributed to strong reservoir heterogeneity, results in a relatively low recovery degree in water injection development. This paper investigates the mechanisms behind water hold-up and reverse coning phenomena, offering detailed solutions. Numerical models of the oil reservoirs were developed, and an extensive study of influencing factors, including reservoir types, Kv/Kh, water injection pressure differential, wettability, and perforation position, was conducted to unveil the underlying mechanisms. Key findings indicate that the water hold-up phenomenon is influenced by capillary force barriers due to wettability and high-perm streaks, while the reverse coning phenomenon depends on the combined forces of gravity, capillary force and downward production differential among which downward production differential is the dominant factor compared to capillary force and gravity. The study also proposes a differential perforation principle tailored to different water-out types to enhance vertical sweep efficiency. The differential perforation principle is as follows: the optimal perforation position is at top layer and the optimal perforation length approximately accounts for 1/4 of the total oil layer thickness for water-out in bottom; the avoidance perforation height in top accounts for 1/6 of the total oil layer thickness and the optimal perforation length approximately accounts for 1/2 of the total oil layer thickness for water-out in top; the avoidance perforation height in top and bottom accounts for 1/5 and 2/5 of the total oil layer thickness respectively for water-out in both top and bottom.

Laboratory investigation on physical and mechanical behaviors of granite after heating and different cooling rates

As an important formation of geothermal reservoirs, granite has very complex microstructure and strong heterogeneity which play an important role in the damage and failure mechanical behavior of granite under different temperatures and cooling rates. In order to better understand the influence of microstructure on the multiscale physical and mechanical properties of granite at evaluated temperatures and cooling rates, this paper conducted a series of macroscopic and microscopic experimental investigations on the granite samples after a heating with two cooling rates treatment. The results show that the failure mode changes from brittle to ductile at 400 °C which is the critical temperature for both macroscopic and microscopic properties. The physical and mechanical properties of specimen after air cooling treatment increase at 200 °C due to the transition of macropores into micropores. Transgranular cracks take place in feldspar at 400 °C and numbers of intergranular cracks develop inside all minerals at 500 °C. The number and width of microcracks in water-cooled samples are much greater than those of air-cooled simples. Based on these experimental investigations, a cross-scale characterization method of Young’s modulus is proposed by introducing a thermal damage factor into the Mori–Tanaka method to consider the thermal damage induced by the thermal treatment.

Spatiotemporal distributions of dissolved N2O concentration, diffusive N2O flux and relevant functional genes along a coastal creek in southeastern China

Increased anthropogenic input of nitrogen into coastal creeks make them potential hotspots for N2O production and emission, but they are often excluded from regional and global N2O budget, and high-resolution sampling is required to characterize the strong spatiotemporal heterogeneity within the creeks. In this study, we analyzed the N2O concentration and diffusive N2O flux within a coastal creek in the Shanyutan Wetland in southeastern China in high spatial resolution across four seasons. Ancillary hydrographical variables and N2O-related functional gene abundances were also measured. Results showed that the creek was consistently oversaturated in N2O, at a seasonal average of 5.6–14.2 nmol/L, relative to the overlying atmosphere. The spatial distribution of N2O followed the gradient of nitrogenous substrate but was inversely related to the salinity gradient, and the coefficient of spatial variation of N2O flux ranged from 66.3 % to 116.5 %. Nitrite reduction (based on nirK and nirS gene abundances) and ammonia oxidation (AOA amoA and AOB amoA) appeared to outpace N2O reduction (nosZ I and nosZ II), and these were the main microbial processes that determined N2O concentration and flux. Both N2O concentration and flux were substantially higher in autumn than those in the other seasons, but that did not appear to be related to precipitation. N2O diffusive flux from the creek averaged 322.2 nmol m−2 h−1, which was over 2 times higher than the global average for lakes and reservoirs. Our results highlight that coastal creeks are strong atmospheric N2O sources with high spatiotemporal variability.

Study on Spatialization and Spatial Pattern of Population Based on Multi-Source Data—A Case Study of the Urban Agglomeration on the North Slope of Tianshan Mountain in Xinjiang, China

Study on Spatialization and Spatial Pattern of Population Based on Multi-Source Data—A Case Study of the Urban Agglomeration on the North Slope of Tianshan Mountain in Xinjiang, China

Estimating soil moisture content in citrus orchards using multi-temporal sentinel-1A data-based LSTM and PSO-LSTM models

Soil moisture content is a vital variable in agricultural, hydrological, ecological and climatological processes. However, susceptible to soil type, soil structure, topography, vegetation and human activities, soil moisture content exhibits strong spatial heterogeneity in spatial distribution, which makes it difficult to accurately estimate the soil moisture content distribution information at a large scale using conventional methods. To solve the problem, this study proposed a novel hybrid model (PSO-LSTM) based on the particle swarm optimization (PSO) and long short-term memory (LSTM) network model to accurately predict soil moisture content at a large scale. Five different input combinations were constructed based on the vertical polarization (VV) and cross-polarization (VH) of multi-phase Sentinel-1A data, and the soil moisture content at depths of 5 cm, 10 cm, 20 cm and 40 cm in citrus orchards were estimated using the standalone LSTM and hybrid PSO-LSTM models. The results showed that the estimation accuracy of the hybrid PSO-LSTM model was greater than that of the standalone LSTM model at different depths, with the normalized root mean square error (NRMSE) of 4.568–11.023 % and 18.056–30.156 %, respectively. With the VV polarization as the only inputs, the PSO-LSTM model obtained high prediction accuracy, with the normalized root mean square error (NRMSE) of 5.458–10.125 %, respectively. Therefore, the PSO-LSTM model with VV polarization input was recommended to estimate the soil moisture content at different depths in citrus orchards, which provides important data for decision-making on distributed precision irrigation at a large scale.

Societal preferences for granting orphan drugs special status in reimbursement decisions

BackgroundOrphan drugs, for patients with a rare disease, are increasingly available but often do not meet standard cost-effectiveness criteria for reimbursement. Consequently, policymakers regularly face the dilemma whether to relax these criteria for reimbursing orphan drugs. We examined whether—and why—there would be societal support for such differential treatment of orphan drugs. MethodsWe conducted a labelled discrete choice experiment in a sample of the adult population (n = 1,172) in the Netherlands. Respondents were presented with ten choices on whether to reimburse an orphan drug given that a non-orphan drug with similar characteristics would not be reimbursed, because it was not cost-effective, and asked to explain their choices. We used random-intercept logit regression models and inductive coding for analysing the quantitative and qualitative data. ResultsOf the respondents, 36.4% consistently chose for reimbursing the orphan drug, mostly because “everyone is entitled to live a healthy life and good quality healthcare”, and 17.3% consistently for not reimbursing the orphan drug, mostly because “[this] is unfair to patients with a common disease”. The remaining 46.3% made alternating choices and were more likely to choose for reimbursing orphan drugs when patients were aged between 1 and 70 years, had moderate disease severity, and considerable health gain from treatment. ConclusionsThis study finds considerable support but also strong preference heterogeneity amongst members of the public in the Netherlands for differential treatment of orphan drugs in reimbursement decisions, when these drugs do not meet common cost-effectiveness criteria. However, a substantial minority opposes differential treatment, mostly on moral grounds.

Modifications on the coastal atmospheric sulfur and cloud condensation nuclei along the Eastern China seas by shipping fuel transition

Marine fuel combustion from shipping releases SO2 and forms sulfate particles, which may alter low cloud characteristics. A series of strategies were implemented to control the sulfur content of ship fuel oil from 2018 to 2020, offering insights into the effects of the ship fuel oil transition on sulfur-related pollutants and the consequent cloud condensation nuclei (CCN) in the atmosphere. Compared to 2018 in the southeast China waters, shipping SO2 emission decreased by 78 % in 2020, resulting in a 76 % reduction in ship-related total sulfur concentration, and a decrease of 54 % in CCN number concentration under supersaturation 0.2 % (CCN0.2) contributed by shipping. The response of CCN0.2 to ship-related sulfate modification is more pronounced in relatively clean environments than polluted environments, highlighting the uneven changes in coastal CCN along the Eastern China Sea induced by the ship fuel policies. CCN can trigger the formation of cloud droplets, 2020 fuel regulation may have and will reduce the cooling radiative forcing effect with strong spatial heterogeneity. The study provides insights into the variations in coastal atmospheric sulfur-related pollutants and CCN in uneven response to changes in ship fuel oil, prompting the need for further comprehensive assessments of the climate effects resulting from potential shifts in ship fuel use in the future.

Prediction Technology of a Reservoir Development Model While Drilling Based on Machine Learning and Its Application

In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation methods that mainly rely on seismic, logging, and core data, which are difficult to meet the timeliness and accuracy of drilling operations. Firstly, the box method and normalization formula are used to process and normalize the abnormal data of element logging and engineering logging, and then the stepwise regression analysis method is used to optimize the sensitive parameters of element logging and engineering logging. The Light Gradient Boosting Machine (LightGBM) algorithm, deep neural network (DNN), and support vector machine (SVM) are used to establish a new method for predicting the development pattern of buried hill reservoirs. Lastly, a comprehensive evaluation index F1 score for the model is established to evaluate the prediction model for the development pattern of buried hill reservoirs. The F1 score value obtained from this model’s comprehensive evaluation index indicates that the LightGBM model achieves the highest accuracy, with 96.7% accuracy in identifying weathered zones and 95.8% accuracy in identifying interior zones. The practical application demonstrates that this method can rapidly and accurately predict the development mode of buried hill reservoirs while providing a new approach for efficient on-site exploration and decision-making in oil and gas field developments. Consequently, it effectively promotes exploration activities as well as enhances the overall process of oil and gas reservoir exploration.

Review of Shale Oil and Gas Refracturing: Techniques and Field Applications

Shale oil and gas wells usually experience a rapid decline in production due to their extremely low permeability and strong heterogeneity. As a crucial technique to harness potential and elevate extraction rates in aged wells (formations), refracturing is increasingly employed within oil and gas reservoirs globally. At present, the selection processes for refracturing, both of wells and layers, are somewhat subjective and necessitate considerable field data. However, the status of fracturing technology is difficult to control precisely, and the difference in construction effects is large. In this paper, well selection, formation selection, and the fracturing technology of shale oil and gas refracturing are deeply analyzed, and the technological status and main technical direction of refracturing technology at home and abroad are analyzed and summarized. The applicability, application potential, and main technical challenges of existing technology for different wells are discussed, combined with the field production dynamics. The results show that well and layer selection is the key to the successful application of refracturing technology, and the geological engineering parameters closely related to the remaining reservoir reserves and formation energy should be considered as the screening parameters. General temporary plugging refracturing technology has a low cost and a simple process, but it is difficult to accurately control the location of temporary plugging, and the construction effect is very different. Mechanical isolation refracturing technology permits the exact refurbishment of regions untouched by the initial fracturing. However, it is costly and complex in terms of construction. Consequently, cutting the costs of mechanical isolation refracturing technology stands as a pivotal research direction.

BASiCS workflow: a step-by-step analysis of expression variability using single cell RNA sequencing data

Cell-to-cell gene expression variability is an inherent feature of complex biological systems, such as immunity and development. Single-cell RNA sequencing is a powerful tool to quantify this heterogeneity, but it is prone to strong technical noise. In this article, we describe a step-by-step computational workflow that uses the BASiCS Bioconductor package to robustly quantify expression variability within and between known groups of cells (such as experimental conditions or cell types). BASiCS uses an integrated framework for data normalisation, technical noise quantification and downstream analyses, propagating statistical uncertainty across these steps. Within a single seemingly homogeneous cell population, BASiCS can identify highly variable genes that exhibit strong heterogeneity as well as lowly variable genes with stable expression. BASiCS also uses a probabilistic decision rule to identify changes in expression variability between cell populations, whilst avoiding confounding effects related to differences in technical noise or in overall abundance. Using a publicly available dataset, we guide users through a complete pipeline that includes preliminary steps for quality control, as well as data exploration using the scater and scran Bioconductor packages. The workflow is accompanied by a Docker image that ensures the reproducibility of our results.

Carbon stock increase during post-agricultural succession in central France: no change of the superficial soil stock and high variability within forest stages

Forest development following agricultural abandonment concerns extensive areas including the Massif Central region of France where this study was undertaken. This land-use and land-cover change is expected to have effects on biodiversity and ecosystem services, including an increase of carbon sequestration—a major concern in the face of climate change. Nevertheless, uncertainties about carbon stock changes during successions are remaining, especially as to the total stock and the contribution of the different carbon pools. Our work contributes to this field by studying carbon stocks in multiple plots of different successional stages. We measured and estimated carbon stocks in aboveground and belowground vegetation, deadwood, litter and superficial soil, and surveyed plant communities and plot conditions (slope, aspect, soil characteristics). The average total carbon stock increased along the succession from 70.60 at stage 0 to 314.19 tC ha−1 at stage 5. However, the total carbon stocks at the young forest stage (abandoned for 74 years maximum) and the older forest stage (forested for at least 74 years) were not significantly different, and probably reflected strong local heterogeneity in the older forest stage. An increase of the carbon stock was found in all pools, except the soil pool that did not vary significantly between the successional stages. The aboveground carbon stock was found strongly related to the woody species cover, especially the macrophanerophyte cover. This case study supports the view that the succession dynamics of former agricultural plots participates in carbon sequestration, sometimes with great local variations.

Heterogeneity in breeding productivity is driven largely by factors affecting nestlings and young fledglings in an imperiled migratory passerine.

Identifying factors that drive variation in vital rates among populations is a prerequisite to understanding a species' population biology and, ultimately, to developing effective conservation strategies. This is especially true for imperiled species like the golden-winged warbler (Vermivora chrysoptera) that exhibit strong spatial heterogeneity in demography and responds variably to conservation interventions. Habitat management actions recommended for breeding grounds conservation include timber harvest, shrub shearing, and prescribed fire that maintain or create early successional woody communities. Herein, we assessed variation in the survival of nests [n = 145] and fledglings [n = 134] at 17 regenerating timber harvest sites within two isolated populations in Pennsylvania that differed in productivity and response to habitat management. Although the overall survival of nests and fledglings was higher in the eastern population than the central population, this was only true when the nest phases and fledgling phases were considered wholly. Indeed, survival rates of nestlings and recently fledged young (1-5 days post-fledging) were lower in the central population, whereas eggs and older fledglings (6-30 days post-fledging) survived at comparable rates in both populations. Fledglings in the central population were smaller (10% lower weight) and begged twice as much as those in the eastern population, suggesting food limitation may contribute to lower survival rates. Fledgling survival in the central population, but not the eastern, also was a function of habitat features (understory vegetation density [positive] and distance to mature forest [negative]) and individual factors (begging effort [negative]). Our findings illustrate how identifying how survival varies across specific life stages can elucidate potential underlying demographic drivers, such as food resources in this case. In this way, our work underscores the importance of studying and decomposing stage-specific demography in species of conservation concern.