Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

Uncertainty and sensitivity analysis of in-vessel phenomena under severe accident mitigation strategy based on ISAA-SAUP program

The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.

Production optimization in a fractured carbonate reservoir with high producing GOR

The Gas-Oil Ratio(GOR)is a crucial production parameter in oil reservoirs.An increase in GOR results in higher gas production and lower oil production,potentially leading to well shut-ins due to economic infeasibility.This study focuses on a real fractured oil field that requires urgent production operations to reduce the producing GOR.In this study,the static model for the field was developed using commercial software,involving steps such as data collection,fault modeling,meshing,and statistical analysis to prepare for dynamic simulation.The dynamic model incorporates geometry,gridding,and rock properties from the static model,utilizing a dual-porosity approach for the naturally fractured reservoir and the Peng-Robinson equation for fluid phase behavior.Initial reservoir conditions,production history,and rock-fluid interactions were defined,with relative permeability curves indicating a water-wet reservoir and low critical gas saturation affecting the GOR.To better understand the relationship between reservoir and production parameters,a detailed sensitivity analysis was performed using the Response Surface Methodology(RSM).Following the sensitivity analysis,a history matching process was conducted using the Designed Exploration and Controlled Evolution(DECE)optimizer to validate the model for future forecasts.Six operational scenarios were defined to decrease the production GOR and enhance final recovery from the field.The results indicate that the water injection scenario is effective in preventing the GOR increase by maintaining reservoir pressure,thereby sustaining production over a longer period.This scenario also improves oil recovery by approximately 6%compared to the base case.Finally,optimization was carried out using the DECE optimizer for each scenario to fine-tune the operational parameters.The goal was to maximize oil revenue for each scenario during the optimization process.This study stands out as one of the few that provides a comprehensive analysis of production behavior and development planning for a real fractured reservoir with high producing GOR.

Productivity Prediction Model of Perforated Horizontal Well Based on Permeability Calculation in Near-Well High Permeability Reservoir Area

To improve the productivity of oil wells,perforation technology is usually used to improve the productivity of horizontal wells in oilfield exploitation.After the perforation operation,the perforation channel around the wellbore will form a near-well high-permeability reservoir area with the penetration depth as the radius,that is,the formation has different permeability characteristics with the perforation depth as the dividing line.Generally,the permeability is measured by the permeability tester,but this approach has a high workload and limited application.In this paper,according to the reservoir characteristics of perforated horizontal wells,the reservoir is divided into two areas:the original reservoir area and the near-well high permeability reservoir area.Based on the theory of seepage mechanics and the formula of open hole productivity,the permeability calculation formula of near-well high permeability reservoir area with perforation parameters is deduced.According to the principle of seepage continuity,the seepage is regarded as the synthesis of two directions:the horizontal plane elliptic seepage field and the vertical plane radial seepage field,and the oil well productivity prediction model of the perforated horizontal well is established by partition.The model comparison demonstrates that the model is reasonable and feasible.To calculate and analyze the effect of oil well production and the law of influencing factors,actual production data of the oilfield are substituted into the oil well productivity formula.It can effectively guide the technical process design and effect prediction of perforated horizontal wells.

Sensitivity analysis of Biome-BGCMuSo for gross and net primary productivity of typical forests in China

Background:Process-based models are widely used to simulate forest productivity,but complex parameterization and calibration challenge the application and development of these models.Sensitivity analysis of numerous parameters is an essential step in model calibration and carbon flux simulation.However,parameters are not dependent on each other,and the results of sensitivity analysis usually vary due to different forest types and regions.Hence,global and representative sensitivity analysis would provide reliable information for simple calibration.Methods:To determine the contributions of input parameters to gross primary productivity(GPP)and net primary productivity(NPP),regression analysis and extended Fourier amplitude sensitivity testing(EFAST)were conducted for Biome-BGCMuSo to calculate the sensitivity index of the parameters at four observation sites under climate gradient from ChinaFLUX.Results:Generally,GPP and NPP were highly sensitive to C:Nleaf(C:N of leaves),Wint(canopy water interception coefficient),k(canopy light extinction coefficient),FLNR(fraction of leaf N in Rubisco),MRpern(coefficient of linear relationship between tissue N and maintenance respiration),VPDf(vapor pressure deficit complete conductance reduction),and SLA1(canopy average specific leaf area in phenological phase 1)at all observation sites.Various sensitive parameters occurred at four observation sites within different climate zones.GPP and NPP were particularly sensitive to FLNR,SLA1 and Wint,and C:Nleaf in temperate,alpine and subtropical zones,respectively.Conclusions:The results indicated that sensitivity parameters of China's forest ecosystems change with climate gradient.We found that parameter calibration should be performed according to plant functional type(PFT),and more attention needs to be paid to the differences in climate and environment.These findings contribute to determining the target parameters in field experiments and model calibration.

Stress sensitivity of formation during multi-cycle gas injection and production in an underground gas storage rebuilt from gas reservoirs

Permeability sensitivity to stress experiments were conducted on standard core samples taken from Wen 23 Gas Storage at multi-cycle injection and production conditions of the gas storage to study the change pattern of stress sensitivity of permeability.A method for calculating permeability under overburden pressure in the multi-cycle injection and production process was proposed,and the effect of stress sensitivity of reservoir permeability on gas well injectivity and productivity in UGS was analyzed.Retention rate of permeability decreased sharply first and then slowly with the increase of the UGS cycles.The stress sensitivity index of permeability decreased with the increase of cycle number of net stress variations in the increase process of net stress.The stress sensitivity index of permeability hardly changed with the increase of cycle number of net stress variations in the decrease process of net stress.With the increase of cycle number of net stress variation,the stress sensitivity index of permeability in the increase process of net stress approached that in the decrease process of net stress.The lower the reservoir permeability,the greater the irreversible permeability loss rate,the stronger the cyclic stress sensitivity,and the higher the stress sensitivity index of the reservoir,the stronger the reservoir stress sensitivity.The gas zones with permeability lower than 0.3’10-3 mm2 are not suitable as gas storage regions.Stress sensitivity of reservoir permeability has strong impact on gas well injectivity and productivity and mainly in the first few cycles.

Responses of food production systems to climate change:sensitivity and vulnerability

Climate warming has prolonged the optimization of crop-growing seasons,shortened actual growth periods,and changed crop-planting boundaries.It also has boosted crop yields in certain regions while compromising crop quality and affected the occurrence of meteorological disasters and pest diseases damage,which has resulted in reduction in grain yield.Crop production systems will evidence more sensitivity to climate change in future;for example,with an increase of 1°C in temperature,the average growth period will be shortened by 17 days for winter wheat and 7-8 days for maize and rice.Of course regional differences will exist.Climate change will threaten crop yield stability and affect crop quality.Vulnerability will be addressed in regard to extreme climatic events,which include reducing exposure and improving adaptive capacity,because the exposure of rain-fed agriculture is greater than that of irrigated agriculture.Therefore,we propose three suggestions to reduce the vulnerability of crop production systems to climate change.First,strengthen the evaluation capacity construction of sensitivity,which includes(1)refining and improving all types of evaluation indicator systems and models;(2)innovating and developing evaluation methods and tools;and(3)combining field observation and case studies,so that(1)the impact of climate change and sensitivity can be assessed scientifically;(2)uncertainty in the study can be identified and reduced;and(3)improved understanding of climate systems and their changes,climate change impact,and sensitivity will be achieved.Second,strengthen adaptive capacity construction for crop production systems,which includes(1)rebuilding existing farmland infrastructure to improve meteorological disaster defences;(2)adjusting agriculture structure and adopting new crop varieties with enhanced resistance;(3)popularizing water-saving technology and dry farming technology;and(4)further researching interdisciplinary theories and methods.Third,strengthen function construction for natural and social systems,which includes(1)popularizing innovative technology;(2)progressing agricultural insurance;and(3)improving energy efficiency and increasing carbon sequestration and emission reduction ability to maintain a favorable ecological environment.

Sensitivity of the Product System of Set-Valued Non-Autonomous Discrete Dynamical Systems

This paper is concerned with the sensitivity of set-valued discrete systems. Firstly, this paper obtained the equivalence between or and the product system in sensitivity, infinite sensitivity, F-sensitivity, (F1, F2)-sensitivity. Then, the relation between (X, f1,∞) or (Y, g1,∞) and in ergodic sensitivity is obtained. Where is the set-valued dynamical system induced by a non-autonomous discrete dynamical system (X, f1,∞).

油气田刺激响应性材料应用现状及前景展望

油田化学品在钻井完井、压裂酸化、调剖堵水、乳化降黏、油水分离等环节发挥关键作用,但低渗透、高温、高盐、极端pH及使用过程中温度、pH变化等苛刻油气藏环境,给应用于油田化学品的聚合物和表面活性剂的研发带来了严峻的挑战。引入磺酸基等抗温抗盐基团或增大驱油剂相对分子质量等传统方式已难以满足油田需求。该文介绍了温度敏感聚合物、pH敏感聚合物、磁响应聚合物、CO_(2)敏感聚合物及表面活性剂、盐度敏感聚合物响应环境变化的刺激响应原理和性能;综述了5种刺激响应性材料在钻井完井、提高采收率、乳化破乳、压裂酸化、调剖堵水、油水分离等方向的应用,展望了刺激响应性材料在油气开采中的发展前景。

连续重整装置混合二甲苯产量最大化策略分析与实践

介绍了某公司1.2 Mt/a连续重整装置的实际生产情况,探讨了影响混合二甲苯产品产量的原因,并提出对应优化措施。以混合二甲苯产量为优化目标时,分别在原料优化、反应过程和产品精馏3个环节探讨相关优化策略。优化措施:原料优化方面,按石脑油资源芳烃潜含量排序,将重整进料芳烃潜含量控制在45%左右;根据装置负荷能力和原料情况,重整进料初馏点从67℃提至74℃,反应进料中C_(8)组分油的质量分数提高了1.8百分点,混合二甲苯产量提高约2 t/h;反应过程方面,反应温度从524℃降至518℃,提高了芳烃的转化率;氯质量分数控制在0.5~0.7μg/g,确保催化剂酸性功能;产品精馏方面,以目标产品质量为目标,优化精馏部分灵敏板温度,优化混合二甲苯分离策略,避免二甲苯资源流入汽油,将C^(+)_(9)石脑油中对二甲苯含量控制至最低。调整结果:避免了混合二甲苯产品含量异常降低,同时混合二甲苯实现产量最大化。

中国制造业绿色发展韧性测度及演变趋势研究——来自制造企业的经验证据

提升绿色发展韧性是中国制造业面对动荡环境实现可持续发展的重要方向。本文采用敏感性指数法测算制造企业绿色发展韧性,利用核密度分布与马尔科夫链法评估中国制造业绿色发展韧性的动态趋势与收敛状态。结果发现:(1)中国制造业绿色转型处于“发展水平与发展韧性”双重下降时期。其中,绿色发展水平下降态势趋缓,绿色发展韧性则经历了“上升→下降”、“正向→负向”阶段转变;(2)高端装备制造业是绿色发展水平变化的主导力量,传统制造业在绿色发展韧性变化中发挥着关键作用;(3)根据绿色发展韧性的马尔科夫链结果,低水平和高水平的状态锁定概率较高,状态跃迁与状态退化主要发生在相邻状态间。制造业中收敛于高水平与较高水平类型企业占半数左右,其中,传统制造业为55%,高端装备制造业为45%。研究结论可为我国制造业促进绿色发展韧性提升和高效推进绿色发展提供一定的政策启示。

黄河流域生态保护迈向高质量发展的特征——植被绿度、生产力和降水利用效率的差异性变化

Globally,vegetation has been changing dramatically.The vegetation-water dynamic is key to understanding ecosystem structure and functioning in water-limited ecosystems.Continual satellite monitoring has detected global vegetation greening.However,a vegetation greenness increase does not mean that ecosystem functions increase.The intricate interplays resulting from the relationships between vegetation and precipitation must be more adequately comprehended.In this study,satellite data,for example,leaf area index(LAI),net primary production(NPP),and rainfall use efficiency(RUE),were used to quantify vegetation dynamics and their relationship with rainfall in different reaches of the Yellow River Basin(YRB).A sequential regression method was used to detect trends of NPP sensitivity to rainfall.The results showed that 34.53%of the YRB exhibited a significant greening trend since 2000.Among them,20.54%,53.37%,and 16.73%of upper,middle,and lower reach areas showed a significant positive trend,respectively.NPP showed a similar trend to LAI in the YRB upper,middle,and lower reaches.A notable difference was noted in the distributions and trends of RUE across the upper,middle,and lower reaches.Moreover,there were significant trends in vegetation-rainfall sensitivity in 16.86%of the YRB’s middle reaches—14.08%showed negative trends and 2.78%positive trends.A total of 8.41%of the YRB exhibited a marked increase in LAI,NPP,and RUE.Subsequently,strategic locations reliant on the correlation between vegetation and rainfall were identified and designated for restoration planning purposes to propose future ecological restoration efforts.Our analysis indicates that the middle reach of the YRB exhibited the most significant variation in vegetation greenness and productivity.The present study underscores the significance of examining the correlation between vegetation and rainfall within the context of the high-quality development strategy of the YRB.The outcomes of our analysis and the proposed ecological restoration framework can provide decision-makers with valuable insights for executing rational basin pattern optimization and sustainable management.

超深层碳酸盐岩气藏产能预测模型及影响因素研究

超深层碳酸盐岩气藏具有储集介质多样、非均质性强和高温高压等典型特征,且普遍采用斜井开发,导致气井产能评价难度大。考虑该类气藏的多重储集介质、应力敏感性、非线性渗流、阈压效应和井斜等因素,基于Forchheimer气相微分方程、应力敏感和气相渗流物理模拟实验数据建立三项式产能预测模型,对不同区域、不同类型碳酸盐岩储层的气井产能进行预测,并分析上述因素对产能的影响规律。结果表明:孔隙型和低渗透孔洞型储层受阈压效应的影响,缝洞型和高渗透孔洞型储层受非线性渗流的影响,因此三项式产能预测模型更适合储层类型多样的超深层碳酸盐岩气藏;不同类型储层表现出不同程度的应力敏感性和非线性渗流特征,需进行各类储层岩心的物理模拟实验确定产能方程所需的各项参数;井斜会产生负表皮因子影响气井产能,当井斜角大于55°时,各类储层的气井产能开始快速提升,且对缝洞型储层的改善效果最明显;阈压效应的产能抑制作用在低压差阶段很强,而应力敏感性和非线性渗流的影响主要体现在高压差阶段;启动压力梯度和非线性渗流系数分别为0.01~0.048MPa/m和10^(9)~10^(12)m^(-1)时显著抑制气井产能,而应力敏感造成的产能损失较稳定;影响气井产能的主控因素是表皮系数和地层系数,而开发阶段的非线性渗流效应对高渗透储层以及阈压效应对低渗透储层的影响也较为显著。

风电制氢系统阻抗建模及振荡特性分析

由于风电机组与主网呈现远距离逆向分布特点,高度电力电子化的风电就地制氢系统与电网互联时将存在振荡失稳的风险。对此,通过建立风电制氢系统的阻抗模型分析了其与电网互联时的振荡特性。首先,建立了考虑电解槽动静态电气特性的阻抗模型,并在此基础上采用双傅里叶变换,建立了包含电力电子变换器在内的电解水制氢设备阻抗模型;随后,结合风电机组的阻抗特性,分析了电网短路比以及制氢设备运行工况对风电制氢系统稳定性的影响。接着,对制氢设备控制参数进行了灵敏度分析,为提升系统稳定性的参数优化方案提供了指导;最后,构建了时域仿真模型,对所得结论进行验证。

考虑煤层割理的多分支水平井煤层气开发数值模拟研究

开发煤层气的多分支水平井形态多样且在对开发过程中割理的作用认识不清,有必要探究煤层中离散割理分布特征和多分支水平井形态对气井产能的影响。根据煤层中面割理和端割理的发育情况和正交特性,采用随机方法在煤层中分别构建了低密度、中密度和高密度的离散割理系统,并与等长型、纺锤型、交错型和哑铃型4种不同形态的多分支水平井结合,构建出多分支水平井开发煤层气的物理模型。在考虑开发过程中煤层有效应力变化和基质收缩效应的条件下建立了煤层基质和割理系统的应力敏感模型,并采用Langmuir定理计算煤层气的解吸附,建立了一种可压缩煤层气在煤层基质–割理系统–多分支水平井耦合中流动的开发模型,进而研究了多分支水平井形态和割理密度对煤层气开发的影响。结果表明:煤层中的离散割理可以极大地增加多分支水平井在短时间内对煤层的动用范围,但是仅限于与多分支水平井直接联通的割理及周围基质区域,未与多分支水平井联通的部分则需要较长的开发时间,这也是气井在较短的时间获得峰值产量并迅速减产的重要原因;等长型多分支水平井控制的储层范围最大,交错型、哑铃型和纺锤型的控制范围依次减小;在煤层中割理密度相同时,等长型多分支水平井的煤层气峰值日产量和20 a内的累积产量均高于其他3种类型的多分支水平井,可以取得更好的开发效果;增大多分支水平井主次井筒的夹角,等长型多分支水平井开发效果更好,同时纺锤型分支水平井的峰值日产量提高显著;交错型和哑铃型多分支水平井的峰值日产量对分支数量更加敏感,纺锤型多分支水平井的分支数量应不少于8条,而哑铃型多分支井的分支数量不多于6条。

Eosin Y敏化CQDs-Ni_(12)P_(5)光催化制氢研究

通过水热法和低温煅烧法分别合成了稳定的碳量子点(CQDs)和Ni_(12)P_(5),通过简单的机械研磨将两者复合成CQDs-Ni_(12)P_(5)。采用X射线衍射(XRD)、透射电镜(TEM)和电化学阻抗(EIS)等对催化剂进行了表征,并通过荧光光谱(FL)测试其电子转移行为。以染料Eosin Y(EY)为催化剂(敏化剂),Ni_(12)P_(5)为助催化剂,三甲胺(TMA)为牺牲剂,研究了CQDs修饰Ni_(12)P_(5)的染料敏化制氢性能。研究表明,CQDs负载量为15 wt%的Ni_(12)P_(5)(15CQDs-Ni_(12)P_(5))拥有最高的染料敏化制氢活性(3565μmol·h^(-1)·g^(-1)),是纯Ni_(12)P_(5)的3.36倍。活性的提高是因为EY、CQDs及Ni_(12)P_(5)之间有效的电子传递。此外,探讨了可能的析氢反应机理。

基于土地生态敏感性评价的生态产品价值分区实现研究——以阿勒泰市为例

良好的生态环境是维持人类生存与发展的基础,是国家生态文明建设的重要前提。利用GIS技术对阿勒泰市的生态环境进行敏感性评价。结果表明:(1)阿勒泰市生态环境敏感性影响程度由大到小排序为:土地利用类型>植被覆盖度>河流缓冲区>道路缓冲区>高程>坡度>坡向。(2)阿勒泰市生态敏感性总体偏高,极度敏感和高度敏感等级区域占研究区总面积的42.45%,在北部山区、中部丘陵区,以及南部额尔齐斯河两岸均有分布;不敏感等级和低度敏感等级区域主要分布在中部丘陵和山间冲积平原区。(3)基于生态敏感性评价结果将阿勒泰市分生态保护区、生态提升区以及生态防护治理区3个区域,并根据区域特点提出完善生态补偿、特色生态旅游、生态农业、开展生态治理与修复等生态产品价值实现模式,为阿勒泰市生态产品价值实现提供实践参考。

环境规制强度对纺织品出口竞争力的影响

为了量化各国环境规制对环境敏感型行业贸易竞争力的影响,以G20国家的纺织品贸易作为研究对象,采用横截面相关性检验、平稳性单位根检验、面板协整检验和面板FMOLS估计对1994—2020年G20国家的环境规制强度(EPSI)和纺织品出口显示比较优势指数(RCA)之间的关联性进行充分的计量验证。结果表明:二者间存在显著相关性,EPSI对纺织品出口RCA呈现出显著的负向影响;EPSI对纺织品出口RCA的影响程度在经济发展水平不同的国家之间表现出明显差异,环境规制对发展中国家纺织品出口的影响程度明显高于发达国家;日本和英国环境规制的加强对其纺织品出口竞争力的提升存在积极作用,证明了波特假说的有效性;环境规制对中国纺织品出口竞争力的负面影响弱于印度,显示出中国纺织品行业在国内环境规制的过程中形成了良好的行业应对策略,依然保证了持续性和较强的国际竞争力。最后提出建议:中国应密切关注国内环境规制对纺织品行业出口竞争力的动态变化,以确保中国纺织品出口竞争力的持续性;借鉴日本和英国的经验,将环境规制的负向影响转为正向影响;中国政府应大力提供应对国际环境规制的资金和技术等公共服务,降低行业应对环境规则的成本。

Private information and investment-q sensitivity:Evidence from new products

This study shows that a decline in investment efficiency due to information asymmetry may not necessarily devalue a firm but may enhance its value instead.Firms base their investment decisions on both public and private information.However,effectively transmitting private information to investors in a competitive market is quite challenging,as it leads to stock prices inadequately reflecting a firm’s true value.Simultaneously,firms must invest to achieve their business objectives,which results in a deviation between a firm’s actual investment level and the market’s expected investment level,thereby reducing investment-q sensitivity.However,this deviation does not imply a waste of societal resources;instead,it improves a firm’s core competitiveness in the product market.We consider the future launch of new products as a proxy for firm private information.We find that(1)private information is negatively associated with investment-q sensitivity,and that the greater the sales of the new product,the lower the investment-q sensitivity;(2)the negative effect is more pronounced for firms with higher revenue volatility and ownership concentration than for those with lower revenue volatility and ownership concentration.This study helps us to further understand how to evaluate firm investment efficiency from the perspective of private information and provides empirical evidence of the costs of the new product launch process.

全球旱地饱和水汽压差和根区土壤水分变化对植被生产力的影响及其成因

旱地约占全球陆地面积的40%,而水分是旱地植被生长的一大限制要素。尽管土壤水分与饱和水汽压差对植被生长的重要性已经得到了广泛证实,然而目前二者对植被生产力影响的空间异质性及其形成因素仍未得到深入研究,这对研究旱地生态系统对气候变化的响应带来了挑战。为了填补这一认知空白,研究收集了多源气象、根区土壤含水率和总初级生产力产品,基于随机森林算法量化了植被总初级生产力对根区土壤含水率和饱和水汽压差的敏感性,结合土地覆盖数据和分档平均方法分析了敏感性空间异质性的形成机制。结果表明:全球旱地饱和水汽压差与植被生产力总体呈显著上升趋势;根区土壤水分对植被生长的影响以正效应主导,饱和水汽压差对植被生长的影响以负效应主导;相较于森林和灌木,饱和水汽压差对植被生长的负效应及根区土壤含水率对植被生长的正效应在农田、草地和苔原及半干旱区更为强烈;植被生产力对饱和水汽压差和根区土壤水分的敏感性在数量上总体呈显著的线性负相关性。综上,植被种类和气候条件是导致全球旱地植被生产力对土壤水分和饱和水汽压差敏感性空间异质性的重要因素。