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Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies. However, crop yield is influenced by multiple factors within complex growth environments. Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat. Therefore, there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield, making precise yield prediction increasingly important. This study was based on four type of indicators including meteorological, crop growth status, environmental, and drought index, from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield. Using the sparrow search algorithm combined with random forest (SSA-RF) under different input indicators, accuracy of winter wheat yield estimation was calculated. The estimation accuracy of SSA-RF was compared with partial least squares regression (PLSR), extreme gradient boosting (XG-Boost), and random forest (RF) models. Finally, the determined optimal yield estimation method was used to predict winter wheat yield in three typical years. Following are the findings: 1) the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms. The best yield estimation method is achieved by four types indicators' composition with SSA-RF) (R2 = 0.805, RRMSE = 9.9%. 2) Crops growth status and environmental indicators play significant roles in wheat yield estimation, accounting for 46% and 22% of the yield importance among all indicators, respectively. 3) Selecting indicators from October to April of the following year yielded the highest accuracy in winter wheat yield estimation, with an R2 of 0.826 and an RAISE of 9.0%. Yield estimates can be completed two months before the winter wheat harvest in June. 4) The predicted performance will be slightly affected by severe drought. Compared with severe drought year (2011) (R2 = 0.680) and normal year (2017) (R2 = 0.790), the SSA-RF model has higher prediction accuracy for wet year (2018) (R2 = 0.820). This study could provide an innovative approach for remote sensing estimation of winter wheat yield, yield. [ABSTRACT FROM AUTHOR]

Forest ecological benefit compensation protects the ecological environment, increases enthusiasm among forest ecological builders, protects the legitimate economic interests of forest landowners, and maintains environmental security. In this study, a systematic analysis was conducted on 4062 publications in the field of international forest ecological benefit compensation identified using the Web of Science core collection Science Citation Index Expanded (SCI-E) and Social Science Citation Index (SSCI) databases alongside CiteSpace optical measurement software. The research status and influence of countries were tracked, scientific research institutions and important authors were identified, and interdisciplinary and scientific hotspots were analyzed. The results show that the number of studies in this field has significantly increased over time and has strong development potential. The journals and articles presenting cutting-edge research in this field are all considered highly professional. The selected research is highly interdisciplinary but primarily involves environmental science and ecology. Despite the publication volume of China ranking second among the top 10 countries, its average citation volume was the lowest, indicating the urgent need to increase the international influence of China. Forest biodiversity, ecosystem services, and climate change are current research hotspots in this field. Dynamic changes in forest ecological benefit compensation and the driving forces behind its evolution are of great concern to researchers. [ABSTRACT FROM AUTHOR]

Neurotrophic tyrosine kinase (NTRK) fusions involving NTRK1, NTRK2, and NTRK3 were found in a broad range of solid tumors as driver gene variants. However, the prevalence of NTRK fusions in Chinese solid tumor patients is rarely reported. Based on the next-generation sequencing data from 10,194 Chinese solid tumor patients, we identified approximately 0.4% (40/10,194) of Chinese solid tumor patients with NTRK fusion. NTRK fusions were most frequently detected in soft tissue sarcoma (3.0%), especially in the fibrosarcoma subtype (12.7%). A total of 29 NTRK fusion patterns were identified, of which 11 were rarely reported. NTRK fusion mostly co-occurred with TP53 (38%), CDKN2A (23%), and ACVR2A (18%) and rarely with NTRK amplification (5.0%) and single nucleotide variants (2.5%). DNA-based NTRK fusion sequencing exhibited a higher detection rate than pan-TRK immunohistochemistry (100% vs. 87.5%). Two patients with NTRK fusions showed clinical responses to larotrectinib, supporting the effective response of NTRK fusion patients to TRK inhibitors. [ABSTRACT FROM AUTHOR]

The increasing impact of drought stress on ecosystems with regard to climate change has received considerable attention, which has been demonstrated to have a time‐lag effect on ecosystems. However, the time‐lag effect on different types of droughts and gross primary production (GPP) at large regional scales remains unclear. Thus, using the GOSIF GPP product data of solar‐induced chlorophyll fluorescence, the meteorological drought index (standardized precipitation evapotranspiration index [SPEI]), and the agricultural drought index (soil moisture deficit index [SMDI]) based on the soil moisture data obtained from the Global Land Data Assimilation System, the time‐lag effect of regional drought and GPP and the contribution of drought to GPP variation were analysed in China from 2000 to 2018. Results showed that (1) China's annual GPP increased at an average rate of 9.26 g C m−2 y−1. With regard to the average rate for each climate zone, the largest increase of 30.44 g C m−2 y−1 was observed in the southern subtropical region, and the smallest increase (4.01 g C m−2 y−1) was observed in the Qinghai–Tibetan plateau, with about 53.11% of the regions showing a significant upward trend. In addition, the significantly declining regions were primarily concentrated in urban areas, accounting for about 2.26% of China. (2) SPEI and GPP had an average lag time of 6.28 months, whereas SMDI and GPP had an average lag time of 7.17 months. The comparison demonstrated that SMDI had a greater influence on GPP than SPEI. (3) The average contribution rate of meteorological drought and agricultural drought to the decrease of GPP was 79.37% and 87.06%, and their average contribution rate to the increase of GPP was 39.11% and 50.57%, respectively. This study will provide comprehensive understanding of the effects of drought on carbon and water cycles in terrestrial ecosystems with regard to climate change. [ABSTRACT FROM AUTHOR]

Drought is one of the most destructive natural disasters in China and can cause serious environmental and socio-economic impacts. Based on monthly precipitation and temperature data from 571 meteorological stations, the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated on a 12-month scale (SPEI-12) from 1985 to 2018 in mainland China, and it was compared with the records of the Bulletin of Flood and Drought Disasters in China to verify its drought monitoring accuracy. Then, run theory was used to explore in depth the spatiotemporal distribution of drought characteristics and trends in various climatic sub-regions. The results showed that: (1) the comparison with the Bulletin of Flood and Drought Disasters in China indicated that the results of SPEI-12 monitoring drought had high accuracy and could identify drought events in mainland China. (2) About 70% of the regions in mainland China experienced droughts more than 50 times, and about 43% of the regions had drought durations of between 100 and 110 months. Nearly 11% of the regions had drought severities of more than 130, which were mainly located in the Northwest Desert (NWC), the southern part of Northeast China (NEC), and the western part of North China (NC). (3) In the past 34 years, the droughts in the Northwest Desert (NWC), the western part of Inner Mongolia (IM), and the Qinghai-Tibet Plateau (TP) showed an aridity trend, while the droughts in South China (SC) and eastern Central and South China (CSC) presented a mitigation tendency. (4) Specifically, the droughts in South China (SC) were more influenced by precipitation, while those in the Northwest Desert (NWC) and Northeast China (NEC) were influenced by temperature and potential evapotranspiration, and the evolution of drought in North China (NC) and the Qinghai-Tibet Plateau (TP) was mainly influenced by soil moisture. The study could provide scientific guidance and a reference for drought response and sustainable development in China. [ABSTRACT FROM AUTHOR]

As the primary source of carbon dioxide fixation, vegetation is critical to the carbon sink process. In this paper, the Net Primary Productivity (NPP) and the Gross Primary Productivity (GPP) were simulated using the Carnegie-Ames-Stanford Approach (CASA) model and the Vegetation Photosynthesis Model (VPM), respectively, and then the Potential Gross Primary Productivity (PGPP) and the GPP affected by human activities (AGPP) were simulated by combining Potential Net Primary Productivity (PNPP), and then the impact of climate change and human activities on GPP was assessed in the Heihe River Basin (HRB). The results showed that the GPP of grassland and Bare or Sparse Vegetation (BSV) exhibited a fluctuation rise, with increases of 0.709 gCm−2 a−1 and 0.115 gCm−2 a−1, respectively, whereas the GPP of cropland showed a fluctuation reduction, with a decline rate of −0.465 gCm−2 a−1. Climate change and human activity are both positive for vegetation growth, and human activity being the primary factor influencing GPP change. Human-dominated vegetation restoration accounted for 56.1% of the overall restoration area, with grassland GPP being the most visible response to human activities. The GPP changes in crop and grassland had a positive correlation with precipitation but a negative correlation with temperature among climate change factors, whereas the GPP changes in BSV had a negative correlation with both precipitation and temperature. Quantitative analyses of climate change and human activities' dynamic contributions to vegetation can give scientific and theoretical insight for dealing with global climate change. [ABSTRACT FROM AUTHOR]

Under the background of climate warming, the increase in the frequency and severity of drought leads to vegetation facing severe challenges. A comprehensive and systematic assessment of the stability of vegetation under drought stress in the middle reaches of Yellow River basin (MRYRB) will help to grasp the characteristics of vegetation response to drought. In this study, the normalized difference vegetation index (NDVI) was used to achieve quantitative and qualitative assessments of vegetation stability to drought, and the smoothed monthly standardized precipitation evapotranspiration index (SPEI) was used to describe the characteristics of drought events in 2005/2006 and identified vegetation stability parameters using a standardized anomaly of NDVI across space, which included the resistance duration, resilience duration, drought threshold, and lag time. Vegetation was dominated by less resistance and less resilience. The 2005/2006 drought event affected most of the study area, and vegetation growth was inhibited. The duration of vegetation resistance over 100 days accounted for 65.7%, and vegetation in 89.4% of the regions could return to normal within 100 days. The drought threshold of vegetation gradually decreased from northwest to southeast, and the lag time was mainly concentrated from 1 to 3 months. These findings contribute to a better understanding of the effects of drought on the environment, as well as scientific references for reducing ecological, economic, and social losses in future droughts, and promoting ecological environmental governance and high-quality development in the MRYRB. [ABSTRACT FROM AUTHOR]

A study on the value accounting of forest carbon sink services can promote the rapid development of the carbon sink market and help better understand the impact of forest carbon sinks on climate change and economic development. However, few studies have evaluated the value of China's current forest carbon sink services. Based on research on carbon peak and carbon neutrality, according to the characteristics of China's forest ecosystems and forest resource inventory data, the stock volume method was used to measure the amount and value of forest carbon sinks in China in 2009–2013 and 2014–2018. The results showed that: (1) the physical amount of forest carbon aggregates in China increased from 2009 to 2013 and from 2014 to 2018. The carbon storage of natural and plantation forests both showed an upward trend. Among them, the growth rate of the carbon storage of plantation forests was higher than that of natural forests. (2) The state, adjoint, and coupling equations of forest carbon sinks were employed to ascertain the best price for China's forest carbon sinks in 2020. The results showed that the price of China's forest carbon sinks was slightly higher than the internationally accepted carbon sink price, reflecting that the changes in the value of China's forest carbon sinks and international carbon sinks were roughly the same. (3) We obtained an appropriate accounting model for China's forest carbon sinks. (4) The value of China's forest carbon sinks increased from 2009 to 2013 and from 2014 to 2018. Although the price of carbon sinks has declined, the overall forest resource stock has increased, especially in plantation forests. The increase in the value of carbon sinks was as high as 24.7%, resulting in an overall increase in the value of forest carbon sinks, which was also in line with the physical amount of forest carbon sinks. The measurement conclusions were consistent. Several key points to note based on these findings are as follows: (1) China's current forest carbon sink transactions are all project-level certified emission reduction transactions, and diversified non-market means should be constructed to comprehensively promote carbon sink transactions. (2) China's current carbon sink transactions are mainly clean development mechanism projects, with few transactions between enterprises, and the carbon trading market situation is not optimistic. (3) The key to effective forest carbon sequestration trading is the accurate accounting of forest carbon storage and carbon sequestration value. Thus, it is of great significance to establish a forest carbon sequestration measurement method that is economical, simple, and accurate. (4) The physical amount and value of carbon sequestration of China's forest resources are rising, and the contribution rate is increasing year by year. However, there is still a gap in per capita forest area and storage compared with those in other countries worldwide. Thus, China must be vigilant in times of peace and further strengthen the protection and construction of forest resources. [ABSTRACT FROM AUTHOR]

Purpose: Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer in China and the 5-year mortality rate is up to 70%. Studies on the ESCC genetic landscape are needed to further explore clinical therapeutic strategies. In this study, we evaluated the genetic landscape of ESCC to aid the search for clinical therapeutic strategies. Patients and Methods: A total of 225 ESCC patients were enrolled in this study. Deep sequencing of 450 cancer genes was performed on formalin-fixed paraffin-embedded tumor biopsies and matched blood samples from patients. Tumor mutational burden (TMB) was calculated using an algorithm developed in-house. Results: Our results showed that the most commonly mutated genes in ESCC were TP53 (96%), CCND1 (46%), FGF4 (44%), FGF19 (44%), FGF3 (44%), CDKN2A (31%), PIK3CA (26%), NOTCH1 (24%), KMT2D (18%), FAT1 (16%), and LRP1B (16%). We found that TMB correlated with patient drinking status. We identified mutations associated with sex, early ESCC, high TMB, and metastasis lymph nodes. KMT2D mutations associated with sex (P = 0.035), tumor stage (P = 0.016), high TMB (P = 0.0072), and overall survival of patients (P = 0.0026). SPEN mutations associated with high TMB (P = 0.0016) and metastasis-positive lymph nodes (P = 0.027). These results suggested that SPEN and KMT2D could be potential prognosis biomarkers for Chinese patients with ESCC. We also found that the number of positive lymph nodes was associated with disease-free survival. Clinical target gene analysis indicated that nearly half of Chinese ESCC patients might benefit from treatment with gene-specific target drugs. Conclusion: Our study revealed the ESCC mutational landscape in 225 Chinese patients and uncovered the potential prognosis biomarker for Chinese patients with ESCC. [ABSTRACT FROM AUTHOR]

• A new drought index, i.e., the water storage deficit index was defined. • There is a large variation in the propagation time of drought in different regions. • The sensitivity of vegetation to drought is influenced by the type of vegetation. • There is a significant time lag effect of drought on vegetation. Due to climate change and human activities, drought has become one of the most complex natural disasters in the Huang-Huai-Hai River basin, China. The purpose of the current research is to analyze the response of vegetation to drought in the Huang-Huai-Hai River basin by calculating the lag time correlation coefficient between the enhanced vegetation index (EVI) and drought indices. First, the water storage deficit index (WSDI) calculated from the total water storage anomalies (TWSA) was used as the hydrological drought index. The meteorological drought index we used was the self-calibrating Palmer drought severity index (scPDSI) provided by the Climate Research Unit (CRU). Then, the relationship between hydrological and meteorological drought was obtained based on the wavelet coherent change. Finally, the response of different vegetation types to drought was analyzed based on the lag time correlation coefficient. The results showed that: the average time of hydrological drought lagged meteorological drought in the three first-level basins of the Huang-Huai-Hai River basin, respectively, was 50 days (Yellow River basin), 43 days (Huaihe River basin), and 35 days (Haihe River basin); the lag time correlation coefficient of the different time scales (1–12 months) can reflect the sensitivity of vegetation to drought in different vegetation types and regions. The forest was the least sensitive to drought in the Huang-Huai-Hai River basin, followed by cropland, while grassland was the most sensitive to drought. It was discovered that hydrological drought had a huge influence on vegetation rather than meteorological drought by comparing the maximum lag time correlation coefficients of EVI with drought indices (scPDSI and SPEI). This study stresses the importance of taking into account the effects of various types of drought on the vegetation in the Huang-Huai-Hai River basin. This will help us better understand how drought affects vegetation. [ABSTRACT FROM AUTHOR]

Based on observed data and data simulated by climate models, temporal variation and spatial distribution of precipitation in China from 1961 to 2050 were investigated. The slope of annual precipitation and Mann-Kendall statistical test were applied to quantify the trend magnitude and detect the significant trend, respectively. Besides, decadal and interannual variations of different rain belts were analyzed to reveal the spatial changing pattern of precipitation. Results indicated the following. (1) During 1961–2011, annual precipitation in Haihe River Basin decreased significantly while the annual precipitation in river basins in the northwest increased significantly. Although the annual precipitation of Yangtze River Basin has an indistinctive decreasing trend, that in the middle and lower reaches has increased and that in the upper reaches has decreased. Arid zone and humid zone are shrinking while semiarid and semihumid zone are expanding. Transformation between semiarid and arid zones, humid and semihumid zones is frequent. During 2011–2050, annual precipitation will not change much (−6~12%) except river basins in the southwest (more than 40%) compared with the baseline. Besides, the area of arid zone will decrease and humid zone area will increase. Transformation area between semiarid and arid zone and humid and semihumid zone is small. [ABSTRACT FROM AUTHOR]

Ansai oilfield is a typical low-permeability, low pressure, and low productivity reservoir. The new oil well only can be built by fracturing, and most of other wells still need multiple fracturing to improve its productivity. Therefore, the fracturing technology has being actively explored and improved since the 1980s in Ansai oilfield; and has been basically formed two technical systems as "water control" and "volume fracturing". This paper reviews the development of fracturing, analyses the existing technology adapted in Ansai oilfield, and points out developing direction of fracturing technology in order to provide the reference for the similar reservoir. [ABSTRACT FROM AUTHOR]

Accurate identification of sandy land plays an important role in sandy land prevention and control. It is difficult to identify the nature of sandy land due to vegetation covering the soil in the sandy area. Therefore, HJ-2A hyperspectral data and GF-3 Synthetic Aperture Radar (SAR) data were used as the main data sources in this article. The advantages of the spectral characteristics of a hyperspectral image and the penetration characteristics of SAR data were used synthetically to carry out mixed-pixel decomposition in the "horizontal" direction and polarization decomposition in the "vertical" direction. The results showed that in the study area of the Otingdag Sandy Land, in China, the accuracy of sandy land detection based on feature-level fusion and single GF-3 data was verified to be 92% in both cases by field data; the accuracy of sandy land detection based on feature-level fusion was verified to be 88.74% by the data collected from Google high-resolution imagery, which was higher than that based on single HJ-2A (74.17%) and single GF-3 data (88.08%). To further verify the universality of the feature-level fusion method for sandy land detection, Alxa sandy land was also used as a verification area and the accuracy of sandy land detection was verified to be as high as 88.74%. The method proposed in this paper made full use of the horizontal and vertical structural information of remote sensing data. The problem of mixed pixels in sparse-vegetation scenes in the horizontal direction and the problem of vegetation covering sandy soil in the vertical direction were both well solved. Accurate identification of sandy land can be realized effectively, which can provide technical support for sandy land prevention and control. [ABSTRACT FROM AUTHOR]

• A new index, i.e., the soil water use efficiencies index was defined. • Significant differences in soil water use efficiency among vegetation. • Significant differences in the contributions of GPP and soil water to SUE. • Compared with PUE, SUE better reflects the water use efficiency of vegetation. Water is a prerequisite for the formation of earth-biochemical-ecological systems. Differences in the spatial and temporal distribution of water resources are important factors in the formation of differences in the distribution of vegetation in terrestrial ecosystems and are key to the differences in vegetation productivity. Vegetation water use efficiency is calculated by the total amount of fixed biogenic carbon per unit mass of water consumed in photosynthesis and can be used to assess the intensity and capacity of an ecosystem to use water biomass. Based on remote satellite sensing data, this study proposes a new water use efficiency assessment model. The model was validated using flux site data, and we analyzed the relative contribution of climate factors to soil moisture use efficiency using a first-difference method. The results revealed the following: (1) The soil moisture use efficiencies (SUE) of remote sensing data inversions that were evaluated using flux site data based on correlation coefficients and Nash coefficients showed high reliability, and only the NMG (Inner Mongolia) station showed low correlation among the nine sites. (2) Among the nine agricultural sub-regions in China, only the SUE of the Qinghai-Tibet Plateau region showed a decreasing trend (−1.08 g C/m−2 kg H 2 O yr), while all other regions showed an increasing trend. (3) The highest vegetation soil moisture use efficiency (1.83 g C/m−2 kg H 2 O) was found in ferralisols, while the lowest vegetation SUE (0.17 g C/m−2 kg H 2 O) was found in arid soils. The SUE of different vegetation types showed the characteristics of forest > scrub > cultivated vegetation > wetland > grassland. (4) The relative contribution of gross primary productivity (GPP) to the change in SUE was 37.53%, while the relative contribution of soil moisture content to the change in SUE was −26.71%. Among the five climatic factors, temperature was the most dominant factor affecting the change in SUE, followed by precipitation, net radiation, leaf area index, and potential evapotranspiration. Revealing the relationship between terrestrial ecosystem GPP, soil moisture content, and their responses to climate factors is a prerequisite for understanding the adaptation strategies of regional terrestrial ecosystems to global climate change, which can help to inform decision-making for the sustainable development of ecosystems. [ABSTRACT FROM AUTHOR]

Droughts resulting from global warming severely hamper the healthy development of terrestrial vegetation ecosystems. This paper defines a terrestrial vegetation ecological drought index, i.e., the Standardized Water Supply–Demand Index (SSDI), based on the water balance method using the same calculation model as the SPEI. The theory of run is used to analyze the spatial and temporal distribution of the drought characteristics in the Yangtze River Basin (YRB). The results show that (1) the drought events monitored by the SSDI were in good agreement with historical drought events, and the correlation coefficient between SSDI and NDVI (0.94) was significantly higher than that between SPEI and NDVI (0.88). (2) About 55.4% of the regions in the YRB experienced more than 13 droughts, and about 41.4% of the regions had an average drought duration of more than 3.1 months. In the northern part of the YRB, droughts tend to develop in a short-term high frequency, while in the southern part of the YRB, there is a long-term low-frequency development trend. Nearly 24.5% of the regions have an average drought intensity of more than 1.4, and most of them are located in the lower reaches of the Yangtze River. (3) Over the last 18 years, about 79.5% of the regions in the YRB showed an increasing trend in SSDI, of which 36.8% showed an increasing trend of more than 0.04/yr. In addition, 40.4% of the regions showed a significant upward trend. Precisely analyzing the spatiotemporal variation of drought characteristics in the YRB is critical for drought risk assessment and sustainable development of water resources and could provide a theoretical basis for effective water resource allocation and drought relief. • A new drought monitoring index, i.e., the Standardized Water Supply–Demand Index (SSDI) was defined. • SSDI can effectively monitor drought events. • SSDI is more suitable for monitoring ecological drought. • Drought of vegetation ecosystem in the Yangtze River Basin was assessed and analyzed with the SSDI. • It provides a theoretical basis for drought management and water allocation in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

Threats posed by global climate change have heightened the urgency for economies to transition to sustainability. However, quantitative metrics that measure sustainability status remain under development, hampered in part by the difficulty of identifying clear relationships between economic growth and sustainability. The Environmental Kuznets Curve hypothesis provides a framework for describing sustainability status relative to socioeconomic development. In this study, the Environmental Kuznets Curve hypothesis was adopted to investigate statistical relationships between the carbon intensity of human well-being (as an indicator of sustainability) and economic development in eight economic zones of China during 1997–2015. The results provide new evidence that seven of eight Chinese economic zones began advances to sustainability (defined here as downward turning points marked by inverted "N" shapes in the Environmental Kuznets Curve) between 2012 and 2015. The lone exception was the Northwestern economic zone, in which an approach to sustainability had not yet occurred by 2015. This study thus supports the contention that environmental policies and technologies have contributed to improving sustainability in terms of carbon intensity. The results suggest two strategic options for further increasing sustainability in China: 1) "first help the weakest"; and 2) "first help the latest to sustainability". • Advance to sustainability defined in terms of carbon intensity of human well-being. • Almost all economic zones in China began advances to sustainability around 2013. • Only the Northwestern economic zone had yet to reach a turning point by 2015. • Assessment shows progress toward international obligations and national objectives. • Both environmental policies and technological advances have contributed. [ABSTRACT FROM AUTHOR]

• Ecological effects under land use changes were explored in alpine area in winter. • Land use changed by human activities reduced the soil fertility and grass biomass. • Land use changed by human activities had weak impacts on NFB and PSB in winter. • Human activities disturbed ecosystem stability compared to natural succession. As one of the critical factors affecting the ecological systems, the effects of land use change should be concerned. However, few studies revealed the ecological effects especially the resilience under different land us changes, especially in alpine areas and in winter. To response the above question, this study conducted the field experiments in the Huangshui River Basin in winter, to compare the different ecological indicators for land use conversion under natural succession (perennial grassland, perennial forest, grassland transformed into forest) and land use conversion influenced by anthropogenic activities (returning farmland to forest, anthropogenic using land transformed into grassland anthropogenic activity zones). The results reveal that land use changed by human activities reduced the stability of ecosystems compared with natural succession. The concentrations or contents of most physicochemical properties in topsoil and grass decreased as well. While the relative abundance of NFB and PSB was slightly higher in the ecosystems with land use conversion influenced by anthropogenic activities. The results could provide references for evaluating the effects of land use changes from the ecological perspective, which could further guide the adaptation facing to climate change. [ABSTRACT FROM AUTHOR]

• A new method for ecosystem stability assessment. • The resistance and resilience of terrestrial ecosystems were quantified. • The vegetation resilience under different disturbance patterns was assessed. With the ongoing impacts of global climate change, the cumulative stress effects of external disturbances on ecosystems are gradually strengthening. Therefore, it is very important to scientifically evaluate the stability of ecosystems. In the terrestrial ecosystems, vegetation serves as a link between the water, energy, and carbon cycles, and is an important index which allows for the measurement of ecosystem stability. In this study, two vegetation indices (normalized difference vegetation index and enhanced vegetation index), along with solar-induced chlorophyll fluorescence data from 2001 to 2021, were used to determine the external disturbance events in the Minjiang river basin using a dynamic time warping (DTW) algorithm. Analyses of the disturbance characteristics during this period, and quantification of the vegetation resistance, resilience, and vegetation regime shift rate were conducted. The results indicated the following. (1) The disturbance results monitored by the DTW algorithm were highly consistent with typical events, and it was feasible to monitor the disturbance of the Minjiang river basin using the DTW algorithm. (2) Disturbance intensity in the river basin increased slightly, while in urban areas it decreased. (3) The resistance of different types of vegetation varied greatly, with the resistance strongest in forests, next in croplands, and weakest in grasslands. In contrast, resilience was the strongest in croplands, next in grasslands, and weakest in forests. (4) The vegetation growth state of the river basin was more significantly affected by external disturbance in 2001–2021, with 58.75% of forest, 54.37% of grassland, and 37.21% of cropland having regime shift rates < 1. Lastly, (5) the response of vegetation to external disturbance was diverse under different disturbance scenarios, with the vegetation recovery rate under gradual disturbance being greater than the rate under abrupt disturbance. [ABSTRACT FROM AUTHOR]

• A rainfall interception experiment was completed for Pinus sylvestris var. mongolica. • Analyses were conducted in semi humid, northeastern China. • The derived throughfall accounted for high proportion compared to other pine forests. • A revised Gash analytical model was able to accurately simulate canopy interception. • Hydrological, ecological, and policy implications were further discussed. Rainfall loss by canopy interception comprises a substantial portion of the water budget in forested ecosystems, and accurately measuring and simulating this process is critical for the effective management of forest water resources. Pinus sylvestris var. mongolica is a main afforested species in northeastern China; however, little work has been carried out assessing the canopy interception loss of this plant species in semi-humid areas. Accordingly, a rainfall interception experiment was conducted for P. sylvestris plots in a semi-humid area of northeastern China from June to September 2019. The revised Gash analytical model was then applied to the canopy interception values, and its regional applicability was tested. During the experimental process, incident rainfall (P), throughfall (T f), and stemflow events (S f) were collected and measured, while meteorological data were simultaneously obtained on-site. The Penman (PM) equation and the Gash regression method were used to estimate evaporation rates (E) from the saturated canopy, and the Leyton constraint method was applied to obtain canopy storage capacity (S). Parameters such as E , S , stemflow partitioning coefficient (p t), and trunk storage capacity (S t) were scaled to the canopy cover fraction per unit area (producing E c , S c , p tc , and S tc in the revised Gash analytical model, respectively) for use in the simulated rainfall interception. The proportions of measured canopy interception (I), S f , and T f accounted for 17.2 %, 6.0 %, and 76.8 % of P , respectively; whereas the S c , p tc , and S tc were calculated as 1.60 mm, 0.067, and 0.21 mm, respectively, over the experimental period. The revised Gash analytical model with E c varied from 0.37 to 0.93, and E c / R varied from 0.62 to 1.55 (acquired via the PM equation), thus indicating its ability to accurately simulate P. sylvestris canopy interception. These findings can provide a theoretical foundation for understanding correlated ecological and hydrological processes, allowing land managers to predict the impacts of afforestation on water inputs for current and future rainfall scenarios in typical coniferous forests of semi-humid regions. [ABSTRACT FROM AUTHOR]

Drought is a complex and dynamic natural phenomenon. A single drought index can hardly reflect the multi-type characteristics of drought, and comprehensive drought indices that incorporate data from multiple sources have been proposed recently. In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by taking into account the lag time of meteorological drought, agricultural drought and hydrological drought. The Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Water Storage Deficit Index (WSDI) represented the three types of droughts, respectively. Specifically, we used the Solar-induced Chlorophyll Fluorescence (SIF) to characterize the vegetation condition instead of the Normalized Difference Vegetation Index (NDVI). The application results of the proposed drought index in the middle reaches of Yellow River basin (MRYRB) showed that the lag time of different types of drought indices had seasonal differences, with a shorter lag time in summer (0-4 months) and a longer lag time in winter and spring (> 4 months). For typical drought events, the drought intensity and duration identified by OCDI were compatible with the drought evolution characteristics and consistent with the historical records, therefore, OCDI is more suitable for drought monitoring in the study area. Based on the monitoring results of the OCDI, the average number of droughts in the MRYRB was 16 times, with a duration of 2.8 months and an average drought intensity of 0.28 (at moderate drought grade). Drought times and intensity were higher in the northwestern part of the study area, and spring was a high-frequency period for drought occurrences., Competing Interests: Declaration of competing interest No conflict of interest exists in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere. All the authors listed have approved the manuscript that is enclosed., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Droughts are the most expensive natural disasters on the planet. As a result of climate change and human activities, the incidence and impact of drought have grown in China. Timely and effective monitoring of drought is crucial for water resource management, drought mitigation, and national food security. In this study, we constructed a comprehensive drought index (YCDI) suitable for the Yellow River Basin using principal component analysis and the entropy weight-AHP method, which integrated a standardized precipitation evapotranspiration index (SPEI), self-calibrating Palmer drought severity index (scPDSI), vegetation condition index (VCI), and standardized water storage index (SWSI). SWSI is calculated by the terrestrial water storage anomaly (TWSA), which can more comprehensively reflect the impact of surface water resources on drought (as compared with soil moisture-based indexes). The study results showed that: (1) compared with single drought index, YCDI has stronger ability to monitor drought process. In terms of time scale and drought degree, the monitoring results based on YCDI were similar with data presented in the China Flood and Drought Bulletin and Meteorological Drought Yearbook, reaching ~87% and ~69%, respectively. The correlation between drought intensity and crop harvest area was 0.56. (2) By the combined analysis of the Mann-Kendall test and Moving T test, it was found that the abrupt change of YCDI index at the time of 2009, mainly due to the precipitation in 2009 reached the lowest value in the past 30 years in northern China and extreme high temperature weather. (3) The YCDI of Henan and Shandong provinces in the middle and lower reaches of the basin decreased more significantly, with the maximum value reaching 0.097/yr, while the index in the upper reaches showed an increasing trend with the maximum rate of 0.096/yr. (4) The frequency of mild drought, moderate drought, severe drought and extreme drought in the Yellow River basin during the study period was 15.84%, 12.52%, 4.03% and 0.97%, respectively. Among them, the highest frequency of droughts occurred in Ningxia, Inner Mongolia and central Shaanxi provinces. Drought causation in the Yellow River basin is more influenced by human activities than climate change in the middle and lower reaches, while climate change is the main factor in the upper reaches. Overall, YCDI is a reliable indicator for monitoring the spatial and temporal evolution of drought in the Yellow River basin, and it can be used for monitoring soil moisture changes and vegetation dynamics, which can provide scientific guidance for regional drought governance., Competing Interests: The authors declare that they have no competing interests., (© 2022 Shi et al.)

The frequency and intensity of droughts are increasing in many parts of the world as a result of global climate change and human activity, posing a serious threat to regional ecological security. The climate in the middle reaches of the Yellow River Basin (MRYRB) has been warm and dry in recent years, with frequent droughts. In order to investigate the temporal trend of drought, and reveal the resistance of vegetation to drought in the MRYRB, this study used remotely-sensed vegetation index products (MODIS-NDVI and SPOT-NDVI) and the standardized precipitation evapotranspiration index (SPEI). The results indicated that: (1) drought intensity showed a weak upward trend in the study area from 2000 to 2018, with linear growth rates of SPEI at temporal scales of 1, 3, 6, 9 and 12 months of -0.002, 0.0034, 0.0198, 0.0234, and 0.0249, respectively; (2) drought was positively correlated with vegetation in most areas (97.6%), and vegetation was most affected by drought on long-term time scales (9 and 12 months); (3) with the extension of drought, vegetation resistance index decreased, then gradually recovered after the end of the drought. Forest had the longest resistance duration of 260 days, while grassland and cultivated land had resistance durations of only 170 days. This study adds to the understanding of vegetation's ability to withstand drought, and these findings provide evidence to support drought response in the MRYRB.

Background: Cholangiocarcinoma (CCA) is a rare malignant tumor of the biliary system. The heterogeneity of CCA leads to the lack of effective targeted treatment for CCA subtypes. The molecular characteristic of hilar CCA (hCCA) is still unclear., Methods: A total of 63 hCCA patients were enrolled from Shanghai Eastern Hepatobiliary Surgery Hospital. Formalin-fixed, paraffin-embedded tumor tissues, and matched blood were collected and deep sequencing targeting 450 cancer genes were performed. Tumor mutation burden (TMB) was measured by an algorithm developed in-house. Correlation analysis was performed by Fisher's exact test., Results: The most commonly mutated genes were TP53 (51.7%), NF1 and KRAS (20%, for both), SMAD4 (16.7%), FAT3 and FRS2 (13.3%, for both), NF1 (11.7%), and KMT2C, MDM2, and ATM (10%, for each) in hCCA. ARID1A, GATA6, and PREX2 mutations commonly occurred in female and KMT2C mutations mainly occurred in patients under 60 years old. Statistical analysis showed the association between ARID1A mutation and tumor stage (P = 0.041) and between NF1 mutation and high TMB (P = 0.0095). Furthermore, ARID1B mutation was identified to associate with the poor prognosis of Chinese hCCA patients (P = 0.004)., Conclusion: The mutational characterization of hCCA is different from both extrahepatic CCA and intrahepatic CCA. ARID1B is a potential biomarker for prognosis prediction of Chinese hCCA patients.

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Lung cancer is the leading causes of cancer-related death worldwide. Precise treatment based on next-generation sequencing technology has shown advantages in the diagnosis and treatment of lung cancer. This cohort study included 371 lung cancer patients. The lung cancer subtype was related to the smoking status and sex of the patients. The most common mutated genes were TP53 (62%), EGFR (55%), and KRAS (11%). The mutation frequencies of EGFR, TP53, PIK3CA, NFE2L2, KMT2D, FGFR1, CCND1, and CDKN2A were significantly different between lung adenocarcinoma and lung squamous cell carcinoma. We identified the age-associated mutations in ALK, ERBB2, KMT2D, RBM10, NRAS, NF1, PIK3CA, MET, PBRM1, LRP2, and CDKN2B; smoking-associated mutations in CDKN2A, FAT1, FGFR1, NFE2L2, CCNE1, CCND1, SMARCA4, KEAP1, KMT2C, and STK11; tumor stage-associated mutations in ARFRP1, AURKA, and CBFB; and sex-associated mutations in EGFR. Tumor mutational burden (TMB) is associated with tumor subtype, age, sex, and smoking status. TMB-associated mutations included CDKN2A, LRP1B, LRP2, TP53, and EGFR. EGFR amplification was commonly detected in patients with acquired lcotinib/gefitinib resistance. DNMT3A and NOTCH4 mutations may be associated with the benefit of icotinib/gefitinib treatment.