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This study aims to assess the relative importance of natural and anthropogenic variables on the change of the red-crowned crane habitat in the Yellow River Nature Reserve, East China using multitempopral remote sensing and geographic information system. Satellite images were used to detect the change in potential crane habitat, from which suitable crane habitat was determined by excluding fragmented habitat. In this study, a principal component analysis (PCA) with seven variables (channel flow, rainfall, temperature, sediment discharge, number of oil wells, total length of roads, and area of settlements) and linear regression analyses of potential and suitable habitat against the retained principal components were applied to explore the influences of natural and anthropogenic factors on the change of the red-crowned crane habitat. The experimental results indicate that suitable habitat decreased by 5,935 ha despite an increase of 1,409 ha in potential habitat from 1992 to 2008. The area of crane habitat changed caused by natural drivers such as progressive succession, retrogressive succession, and physical fragmentation is almost the same as that caused by anthropogenic forces such as land use change and behavioral fragmentation. The PCA and regression analyses revealed that natural factors (e.g., channel flow, rainfall, temperature, and sediment discharge) play an important role in the crane potential habitat change and human disturbances (e.g., oil wells, roads, and settlements) jointly explain 51.8 % of the variations in suitable habitat area, higher than 48.2 % contributed by natural factors. Thus, it is vital to reduce anthropogenic influences within the reserve in order to reverse the decline in the suitable crane habitat.
Subject(s)
Ecosystem , Environmental Monitoring , Environmental Pollutants/analysis , Animals , Birds/physiology , China , Environmental Pollution/statistics & numerical data , Geographic Information Systems , Rivers/chemistryABSTRACT
Ecological drought is a complex process in terrestrial ecosystems where vegetation's eco-physiological functions are impaired due to water stress. However, there is currently a lack of long-term assessment of ecological drought from an eco-physiological perspective. In this study, the standardized ecological drought index (SESNDI) was developed using actual evaporation, root soil moisture, and kernel normalized difference vegetation index via the Euclidean distance method, reflecting ecosystem physiology, water supply capacity, and vegetation status. Solar-induced chlorophyll fluorescence validated SESNDI by reflecting vegetation photosynthesis. Using China as an example, severely impacted by climate change and ecological restoration, ecological drought's spatio-temporal variation and propagation characteristics was evaluated using clustering algorithms. The results demonstrated that (1) SESNDI showed superior performance over several other drought indices. (2) During 1982-2020, ecological drought was prevalent from 1990 to 2010, especially in the central and northeastern regions. (3) Compared to 1982-2000, the median duration and affected area of ecological drought events during 2001-2020 reduced by four months and 1.51 × 105 km2, respectively, while the median intensity increased by 0.06. (4) Decreased precipitation and increased temperature were the primary factors contributing to the frequent occurrence of ecological drought in China from 1990 to 2010. This study offers a crucial methodology for evaluating ecological drought, serving as a reference for developing effective terrestrial restoration strategies.
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To discuss the value of dual-source CT dual-energy parameters combined with serum detection of vascular endothelial growth factor (VEGF) and carcinoembryonic antigen (CEA) in the diagnosis of early lung cancer (LC). In total, 100 patients with lung lesions in our hospital from January 2020 to January 2022 were selected for retrospective study, and were divided into the lung cancer group (group A) and benign lung disease group (group B) according to the final results of pathological diagnosis, using dual-source CT dual-energy scanning combined with serum detection of VEGF and CEA to analyze the diagnostic values of single detection and combined detection. Among the 100 patients with lung lesions, there were 58 patients with LC and 42 patients with benign lung diseases after pathological examination, with no statistical difference in normalized iodine concentration (NIC) and the increased value of iodine at arterial phase between the two groups (P > 0.05). The NIC value of group A was higher than group B at venous phase (P < 0.05). The serum levels of VEGF and CEA in group A were higher than group B (P < 0.05). The area under the curve, specificity, sensitivity, Youden index and 95% CI of combined diagnosis were higher than single detection of NIC, VEGF and CEA at venous phase. The combined application of dual-source CT dual-energy parameters and serum detection of VEGF and CEA has higher diagnostic value in patients with early LC, which can provide effective reference for clinical diagnosis and treatment, with higher application value in clinic.
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Flash droughts are a recently recognised type of extreme drought defined by the rapid onset and strong intensification of drought conditions. Our understanding of flash drought processes under the influence of heat waves needs to be improved in the context of global warming. Here, we applied a physically based hydrological model, i.e., TRAnspiration and INterception (TRAIN) model to simulate root zone soil moisture (RZSM) and evapotranspiration (ET) with daily time steps and at a 1 × 1 km resolution to identify and assess flash droughts. Two states, Baden-Württemberg (BW) and Rhineland-Palatinate (RP), located in southwestern Germany, were selected as the study areas. Three datasets, the Global Land Evaporation Amsterdam Model (GLEAM) dataset, ERA5-Land (land component of the fifth generation of European ReAnalysis) dataset, and SMAP-L4 (Soil Moisture Active Passive Level-4) dataset, were selected to evaluate the TRAIN simulated RZSM and ET from 1961 to 2016. The results show that the simulated RZSM had the highest correlation with the ERA5-Land products, followed by SMAP-L4 and GLEAM, with regional average correlation coefficients (CC) of 0.765, 0.762, and 0.746, respectively. The CC of the TRAIN simulated ET with ERA5-Land and GLEAM ET were 0.828 and 0.803, respectively. The results of the trend analyses showed a significant increase (p < 0.05) in the number of flash droughts and heat waves in both the BW and RP states. A comparative analysis revealed that the mean duration and onset speed of flash droughts in BW (RP) without heat waves were 10.42 (10.67) pentads and 19.69th percentile/pentad (17.16th percentile/pentad), respectively, while associated with heat waves they were 8.95 (9.53) pentads and 21.77th percentile/pentad (19.91th percentile/pentad), respectively. This indicates that flash droughts under the influence of heat waves are generally shorter in duration but faster in occurrence. The findings of this study have important implications for flash drought assessment, monitoring, and mitigation under the impact of heat waves.
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Understanding of runoff response changes (RRC) is essential for water resource management decisions. However, there is a limited understanding of the effects of climate and landscape properties on RRC behavior. This study explored RRC behavior across controls and predictability in 1003 catchments in the contiguous United States (CONUS) using catchment classification and machine learning. Over 1000+ catchments are grouped into ten classes with similar hydrological behavior across CONUS. Indices quantifying RRC were constructed and then predicted within each class of the 10 classes and over the entire1000+ catchments using two machine learning models (random forest and CUBIST) based on 56 indicators of catchment attributes (CA) and 16 flow signatures (FS). This enabled the ranking of the important influential factors on RRC. We found that (i) CA/FS-based clusters followed the ecoregions over CONUS, and the impact of climate on RRC seemed to overlap with physiographic attributes; (ii) CUBIST outperforms the random forest model both within the cluster and over the whole domain, with a mean improvement of 39 % (depending on clusters) within clusters. Runoff sensitivity was better predicted than runoff changes; (iii) FS related to runoff ratio, average, and high flow are the most important for RRC, whereas climate (evaporation and aridity) is a secondary factor; and (iv) RRC patterns are substantial in the dominant factor space. High total changes and catchment characteristic-induced changes occurred mainly at 100°west longitude. The elasticity of climate and catchment characteristics was found to be high in spaces with high evaporation and low runoff ratios and low in spaces with low evaporation and high runoff ratios. Uncertainties existed in the number of catchments between clusters which was verified using a fuzzy clustering algorithm. We recommend that future research that clarifies the impact of uncertainty on hydrological or catchment behavior should be conducted.
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Introduction: Conductance-photosynthesis (Gs-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (Gs) and transpiration (Tc) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (gsu and gsh) and maximum LUE (ϵmsu and ϵmsh) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in Tc estimation errors, as it contradicts field observations. Methods: In this study, the measured flux data from three temperate deciduous broadleaved forests (DBF) FLUXNET sites were adopted, and the key parameters of LUE and Ball-Berry models for sunlit and shaded leaves were calibrated within the entire growing season and each season, respectively. Then, the estimations of gross primary production (GPP) and Tc were compared between the two schemes of parameterization: (1) entire growing season-based fixed parameters (EGS) and (2) season-specific dynamic parameters (SEA). Results: Our results show a cyclical variability of ϵmsu across the sites, with the highest value during the summer and the lowest during the spring. A similar pattern was found for gsu and gsh, which showed a decrease in summer and a slight increase in both spring and autumn. Furthermore, the SEA model (i.e., the dynamic parameterization) better simulated GPP, with a reduction in root mean square error (RMSE) of about 8.0 ± 1.1% and an improvement in correlation coefficient (r) of 3.7 ± 1.5%, relative to the EGS model. Meanwhile, the SEA scheme reduced Tc simulation errors in terms of RMSE by 3.7 ± 4.4%. Discussion: These findings provide a greater understanding of the seasonality of plant functional traits, and help to improve simulations of seasonal carbon and water fluxes in temperate forests.
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Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.
Subject(s)
Ecosystem , Grassland , Humans , Tibet , Climate ChangeABSTRACT
Objective: To explore the effects of cyclophosphamide combined with vinorelbine in advanced small cell lung cancer (SCLC) and anteroposterior changes in MRI. Methods: The clinical data of 90 patients with advanced SCLC admitted to our hospital from April 2020 to April 2021 were retrospectively analyzed. They were divided into the control group and the study group according to the order of admission, with 45 cases in each group. The control group received the routine treatment, while the study group was treated with cyclophosphamide and vinorelbine to compare the indexes of imaging data and clinical indicators between the two groups before and after treatment. Results: There was no significant difference in the indexes of imaging data between the two groups before treatment (P > 0.05), and the indexes of imaging data in the study group were visibly lower than those in the control group after treatment (P < 0.001). The DCR in the study group was significantly higher than that in the control group after treatment (P < 0.05), while the QLQ-C30 scores and serum indices of the study group after treatment were significantly lower than those of the control group (P < 0.001). Conclusion: Patients with advanced SCLC were treated with cyclophosphamide and vinorelbine, which can effectively improve the quality of life and reduce the expression of inflammatory factors. This treatment model has a higher application value, and the treatment value is also reflected compared with the routine treatment. At the same time, the permeability parameters obtained by MRI can predict the therapeutic effects of cyclophosphamide and vinorelbine, and further studies are helpful to establish a better solution for patients.
Subject(s)
Lung Neoplasms , Small Cell Lung Carcinoma , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Cyclophosphamide/therapeutic use , Humans , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/drug therapy , Magnetic Resonance Imaging , Quality of Life , Retrospective Studies , Small Cell Lung Carcinoma/diagnostic imaging , Small Cell Lung Carcinoma/drug therapy , Vinblastine/therapeutic use , Vinorelbine/therapeutic useABSTRACT
Flash droughts, with rapid onset and strong intensity, have attracted much attention in recent literature due to their devastating socio-agricultural impacts. Based on the microwave remote sensing soil moisture data released by the European Space Agency Climate Change Initiative program (ESA CCI SM), flash droughts were identified by focusing on the attenuation rate of weekly soil moisture percentile. On this basis, the spatiotemporal patterns of flash drought frequency, their evolution process combined with meteorological conditions, and the relationship with seasonal droughts were analyzed. Results showed that the frequency of flash drought occurrence over China during 2000-2016 mainly varied between 6% and 20%. Spatially, such events were most likely to occur in the northern and southern region, and the Qinghai-Tibet Plateau showed the lowest frequency of occurrence. Influenced by the complex roles of negative anomalies of precipitation and relative humidity, along with positive anomalies of potential evapotranspiration (PET) and temperature, the southwest region suffered three severe drought attacks in summer 2006. In addition, a coexisting relationship was also observed between flash droughts and seasonal droughts. Initiated by the rapid reduction of soil moisture, the northern, northeastern, southern, and southwestern areas were more vulnerable to droughts with duration no more than 12 weeks. In contrast, the southern China were likely to suffer longer periods of droughts (more than 12 weeks) in spring (April to May), while for southwestern regions such type of droughts were mainly concentrated in summer (June and July).
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Droughts are comprehensive and complex issues that need to be characterized from a multivariate perspective. In recent years, a number of composite indices have been proposed for drought characterization. However, rare studies have systematically compared similarities and dissimilarities of these indices, and they have provided little insights into the combination mechanisms. To address this issue, two widely used combination approaches, namely the principal component analysis (PCA) and copula based joint probability distribution were employed, with the corresponding integrated product denoted as the Aggregate Drought Index (ADI) and Joint Drought Deficit Index (JDI). Five constituents for constructing ADI and JDI were derived from the variable infiltration capacity model (VIC) monthly simulations over the Yellow River basin (YRB), China, including precipitation (P), actual evapotranspiration (ET), soil moisture of top two layers, and runoff (during 1961-2012). Results showed that the behavioral patterns of ADI and JDI may not be easily influenced by the variation of one single element, and they represented comprehensive moisture status well. A further comparison between these two composite indices suggested that ADI and JDI behaved similarly in most areas of YRB, with some dissimilarities in the source region. The particular behavior of ET was responsible for the inconsistency. Comparing to other regions, an enhanced role of potential evapotranspiration (PET) was imposed on ET in the source region, leading to a poor relationship of ET with P and other hydrological variables. Accordingly, when constructing composite drought indices, the drought information indicated by ET was more easily abandoned by ADI but reserved in JDI. This study clearly demonstrates the mechanisms of two common integrated approaches in blending different drought information, which has significant implications for composite drought indices construction and application, and potentially provides some valuable references for the improvement of monitoring techniques in future drought related researches.