Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019

Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound changes.It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods.Therefore,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle.Based on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model.The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest.During 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing trend.The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to 2019.During 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest.During the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human activities.These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.

A Study of the Effects of Employee Engagement on Job Satisfaction:Mediating Effect of Labor Relations Climate

With the rapid advancement of new technologies and the transformation of the economic model on a global scale,enterprises are facing unprecedented changes in the external environment and more diversified demands from employees.Therefore,it is essential for enterprises to bolster employee engagement by enhancing employees’job satisfaction,building a stable and harmonious internal climate,and adapting to the dynamic,complex external environment.This study analyzes the positive effects of employee engagement on job satisfaction,explores the mediating effect of labor relations climate in the relationship between the two,and proposes corresponding practical countermeasures and suggestions.

Competition gives way to cooperation:rethinking Sino-Indian relations in climate change negotiations

In global climate change politics,China and India have worked closely with each other,representing two big emitters from the developing world.This article reviews Sino-Indian cooperation during four UN climate change negotiations from 2009 to 2012.Their collaboration echoed the perception of neorealism in international relations(IR) studies that states will seek "external balancing" for maximizing national "relative gains".China and India are expected to continue their cooperation on climate change issues when sharing the same structural position as big economies and big emitters,the same pressure in carbon emission reductions,and the same goal of improving living standards for their citizens.Encountering the devastating impacts of climate change and the deadlock in responsibility division in current global climate change governance,this work seeks to shed light on the evolving multilateral governance environment and its complex implications for Sino-Indian relations from an IR perspective.

Climate Change and Heavy Rainfall-Related Water Damage Insurance Claims and Losses in Ontario, Canada

The objective of this paper was to project possible impacts of climate change on heavy rainfall-related water damage insurance claims and incurred losses for four selected cites (Kitchener-Waterloo, London, Ottawa, and Toronto) located at Ontario, Canada. To achieve this goal, the future climate change scenarios and rainfall simulations, at local scale, were needed. A statistical downscaling method was used to downscale five global climate model (GCM) scenarios to selected weather stations. The downscaled meteorological variables included surface and upper-air hourly temperature, dew point, west-east and south-north winds, air pressure, and total cloud cover. These variables are necessary to project future daily rainfall quantities using within-weather-type rainfall simulation models. A model result verification process has been built into the whole exercise, including rainfall simulation modeling and the development of downscaling transfer functions. The results of the verification, based on historical observations of the outcome variables simulated by the models, showed a very good agreement. To effectively evaluate heavy rainfall-related water damage insurance claims and incurred losses, a rainfall index was developed considering rainfall intensity and duration. The index was evaluated to link with insurance data as to determination of a critical threshold of the rainfall index for triggering high numbers of rainfall-related water damage insurance claims and incurred losses. The relationship between rainfall index and insurance data was used with future rainfall simulations to project changes in future heavy rainfall-related sewer flood risks in terms of water damage insurance claims and incurred losses. The modeled results showed that, averaged over the five GCM scenarios and across the study area, both the monthly total number of rainfall-related water damage claims and incurred losses could increase by about 13%, 20% and 30% for the periods 2016-2035, 2046-2065, and 2081-2100, respectively (from the four-city seasonal average of 12 ± 1.7 thousand claims and $88 ± $21 million during April-September 1992-2002). Within the context of this study, increases in the future number of insurance claims and incurred losses in the study area are driven by only increases in future heavy rainfall events.

Variation in Expression of <i>Sub</i>1 Gene and Association with Submergence Stress Related Traits in Advance Rice (<i>Oryza sativa</i>L.) Genotypes as a Tool of Climate Change Adaptation

Floods have now become most detrimental natural catastrophe worldwide due to radical climatic fluxes. Therefore, there is a dire necessity to develop a high yielding rice lines to deal with this scenario. For this purpose, a large scale experiment was conducted including one hundred and fifteen (115) rice genotypes having SUB1 gene imported from International Rice Research Institute (IRRI) Philippines, six local cultivars/approved varieties and three high yielding rice varieties i.e. Sabitri, IR6 and NSICRC222 being used as potential varieties in different countries of Asia as susceptible check and IR64-SUB1 as tolerant check. The genotypic screening was performed using two PCR-based DNA markers i.e. ART5 and SC3. Phenotypic screening was conducted in a natural pond to assess the interaction of SUB1 gene in natural stagnant flood water as well as the suitability of introgression of SUB1 gene into approved varieties and elite rice lines. The genotypes were assessed in terms of plant survival percentage, submergence tolerance index, physical condition, stem elongation, number of grains per panicle, thousand grain weight, grain yields and deviations in these traits after submergence stress. The PCR results suggested that both the primers ART5 and SC3 may be used as potential PCR-based markers for molecular screening of rice genotypes for SUB1 QTL. Furthermore, it confirmed the presence of SUB1 gene in all the lines imported from IRRI, while it was absent in all the local cultivars studied. All the genotypes with submergence tolerant gene (SUB1) showed significantly greater tolerance level in submergence stress of 14 days, as compared to other local cultivars/varieties, authenticating the effectiveness of SUB1QTL in conferring submergence tolerance. Significantly different performances of all the SUB1 genotypes in terms of all the studied traits indicate high Genotypic and Genotypic Environment Interaction (GEI) of SUB1QTL. Employment of SUB1 lines such as R105479:149-18, IR64-SUB1 and Rl05469:81-22-3 in breeding programs for developing flood tolerant rice varieties might further upsurge rice yields in flash flood areas. Correlation analysis revealed that plant survival percentage after submergence, reduced stem elongation during submergence and submergence tolerance index are very important traits for developing submergence tolerant lines.

The impacts of climate change on wheat yield in the Huang-Huai-Hai Plain of China using DSSAT-CERES-Wheat model under different climate scenarios

Climate change has been documented as a major threat to current agricultural strategies.Progress in understanding the impact of climate change on crop yield is essential for agricultural climate adaptation,especially for the Huang-Huai-Hai Plain(3H Plain)of China which is an area known to be vulnerable to global warming.In this study,the impacts of climate change on winter wheat(Triticum aestivum L.)yield between the baseline period(1981–2010)and two Representative Concentration Pathways(RCP8.5 and RCP4.5)were simulated for the short-term(2010–2039),the medium-term(2040–2069)and the long-term(2070–2099)in the 3H Plain,by considering the relative contributions of changes in temperature,solar radiation and precipitation using the DSSAT-CERES-Wheat model.Results indicated that the maximum and minimum temperatures(TMAX and TMIN),solar radiation(SRAD),and precipitation(PREP)during the winter wheat season increased under these two RCPs.Yield analysis found that wheat yield increased with the increase in SRAD,PREP and CO2 concentration,but decreased with an increase in temperature.Increasing precipitation contributes the most to the total impact,increasing wheat yield by 9.53,6.62 and 23.73%for the three terms of future climate under RCP4.5 scenario,and 11.74,16.38 and 27.78%for the three terms of future climate under RCP8.5 scenario.However,as increases in temperature bring higher evapotranspiration,which further aggravated water deficits,the supposed negative effect of increasing thermal resources decreased wheat yield by 1.92,4.08 and 5.24%for the three terms of future climate under RCP4.5 scenario,and 3.64,5.87 and 5.81%for the three terms of future climate under RCP8.5 scenario with clearly larger decreases in RCP8.5.Counterintuitively,the impacts in southern sub-regions were positive,but they were all negative in the remaining sub-regions.Our analysis demonstrated that in the 3H Plain,which is a part of the mid-high latitude region,the effects of increasing thermal resources were counteracted by the aggravated water deficits caused by the increase in temperature.

Modeling Climate Change Impacts on the US Agricultural Exports

Climate change is expected to have substantial effects on agricultural productivity worldwide. However, these impacts will differ across commodities, locations and time periods. As a result, landowners will see changes in relative returns that are likely to induce modifications in production practices and land allocation. In addition, regional variations in impacts can alter relative competitiveness across countries and lead to adjustments in international trade patterns. Thus in climate change impact studies it is likely useful to account for worldwide productivity effects. In this study, we investigate the implications of considering rest of world climate impacts on projections of the US agricultural exports. We chose to focus on the US because it is one of the largest agricultural exporters. To conduct our analyses, we consider four alternative climate scenarios, both with and without rest of world climate change impacts. Our results show that considering/ignoring rest of world climate impacts causes significant changes in the US production and exports projections. Thus we feel climate change impact studies should account not only for climate impacts in the country of focus but also on productivity in the rest of the world in order to capture effects on commodity markets and trade potential.

Impacts of future climate change(2030-2059)on debris flow hazard:A case study in the Upper Minjiang River basin,China

An increase in extreme precipitation events due to future climate change will have a decisive influence on the formation of debris flows in earthquake-stricken areas. This paper aimed to describe the possible impacts of future climate change on debris flow hazards in the Upper Minjiang River basin in Northwest Sichuan of China, which was severely affected by the 2008 Wenchuan earthquake. The study area was divided into 1285 catchments, which were used as the basic assessment units for debris flow hazards. Based on the current understanding of the causes of debris flows, a binary logistic regression model was used to screen key factors based on local geologic, geomorphologic, soil,vegetation, and meteorological and climatic conditions. We used the weighted summation method to obtain a composite index for debris flow hazards, based on two weight allocation methods: Relative Degree Analysis and rough set theory. Our results showed that the assessment model using the rough set theory resulted in better accuracy. According to the bias corrected and downscaled daily climate model data, future annual precipitation(2030-2059) in the study area are expected to decrease, with an increasing number of heavy rainfall events. Under future climate change, areas with a high-level of debris flow hazard will be even more dangerous, and 5.9% more of the study area was categorized as having a high-level hazard. Future climate change will cause an increase in debris flow hazard levels for 128 catchments, accounting for 10.5% of the total area. In the coming few decades, attention should be paid not only to traditional areas with high-level of debris flow hazards, but also to those areas with an increased hazard level to improve their resilience to debris flow disasters.

Response of Lakes to Climate Change in Xainza Basin Tibetan Plateau Using Multi-Mission Satellite Data from 1976 to 2008

Changes in the lake areas of Xainza basin in the past 33 years(1976 to 2008) were studied using Landsat data from Multispectral Scanners(1973-1977), Thematic Mapper(1989-1992, 2007-2009), and Enhanced Thematic Mapper Plus(1999-2002). The results indicated that lakes in the study area evidently expanded from 1976 to 2008, with total expansion of 1512.64 km2. The mean annual air temperature presented an upward trend with certain fluctuations from 1966 to 2008. The air temperature rise rates in the cold season(0.31°C/10a) were higher than those in the hot season(0.24°C/10a), in the Xainza station example. Precipitation exhibited evident seasonal differences. Mean annual precipitation in hot season is 281.48 mm and cold season is 32.66 mm from 1966 to 2008 in study area. Precipitation in the hot season was the major contributor to the increase in annual precipitation. Grey relational analysis(GRA) was used to study the response of lake areas to climatic factors. The mean air temperature and precipitation were selected as compared series, and the lake areas were regarded asthe reference series. The grey relational grade(GRG) between compared series and reference series were calculated through GRA. The results indicated that changes in lake areas were mainly affected by climatic factors in the hot season. Lakes in this region were classified into three grades, namely, Grades I, II, and III according to the recharge source and elevation. The GRGs of each series varied for different grade lakes: the area of Grade III lakes were the most relevant to the hot season factors, the GRGs of precipitation and air temperature were 0.7570 and 0.6606; followed by the Grade II lakes; Grade I lakes were more sensitive to the air temperature.

Analysis of Relation between Variation Characteristics and Climatic Influencing Factors of Shallow Ground Temperature in Shijiazhuang

Based on the daily observation data of shallow ground temperature, total cloud cover, precipitation, evaporation capacity and frozen soil of 5 stations in Shijiazhuang from 1981 to 2010, using methods such as linear trend and complete correlation coefficient, relation between variation characteristics and climatic influencing factors of shallow ground temperature was analyzed to lay the foundation for studying impact factors of shallow ground temperature and provide references for daily maintenance of automatic observation business. The results showed that fluctuant variability and fluctuant range of mean shallow layer ground temperature in Shijiazhuang became smaller with soil layer being deeper for all years and seasons, and the fluctuant variability was maximal in spring and minimal in winter, while the fluctuant range was maximal in summer and minimal in winter; mean shallow layer ground temperature for all years had a warming trend with an obvious warming trend in winter, and warming range in winter was smaller and the extent was weaker with soil layer being deeper while a cooling trend occurred in summer; there was a coincident trend between total cloud cover at night and shallow ground temperature in winter, and between evaporation capacity and shallow ground temperature in summer, while there was an inconsistent trend between maximum depth of frozen soil, period of freezing weather and shallow ground temperature in winter, and between total cloud cover in the davtime, orecioitation and shallow around temperature in summer.

On the Relationship between Climatic Variables and Pressure Systems over Saudi Arabia in the Winter Season

The synoptic circulation over Saudi Arabia is complicated and frequently governed by the effect of large-scale pressure systems. In this work, we used NCEP–NCAR global data to illustrate the relationship between climatic variables and the main pressure systems that affect the weather and climate of Saudi Arabia, and also to investigate the influence of these pressure systems on surface air temperature（SAT） and rainfall over the region in the winter season. It was found that there are two primary patterns of pressure that influence the weather and climate of Saudi Arabia. The first occurs in cases of a strengthening Subtropical High（Sub H）, a weakening Siberian High（Sib H）, a deepening of the Icelandic Low（Ice L）, or a weakening of the Sudanese Low（Sud L）. During this pattern, the Sub H combines with the Sib H and an obvious increase of sea level pressure（SLP） occurs over southern European, the Mediterranean, North Africa, and the Middle East. This belt of high pressure prevents interaction between midlatitude and extratropical systems, which leads to a decrease in the SAT,relative humidity（RH） and rainfall over Saudi Arabia. The second pattern occurs in association with a weakening of the Sub H, a strengthening of the Sib H, a weakening of the Ice L, or a deepening of the Sud L. The pattern arising in this case leads to an interaction between two different air masses： the first（cold moist） air mass is associated with the Mediterranean depression travelling from west to east, while the second（warm moist） air mass is associated with the northward oscillation of the Sud L and its inverted V-shape trough. The interaction between these two air masses increases the SAT, RH and the probability of rainfall over Saudi Arabia, especially over the northwest and northeast regions.

A technique for detecting and attributing changes in species distributions to climate change over time

The global climate has changed substantially over the last 100 years,and associated changes in species distribution limits have occurred in recent decades.Climate change presents a challenge for biodiversity conservation on a global scale.The ability to detect changes in species distributions and attribute them to past climate change is crucial for the accurate prediction of future species distributions and for biodiversity conservation.This study proposes a technique for the quantitative detection of species distribution changes and their attribution to past climate change.An attribution value was defined to describe the extent to which the distributional changes for observed species could be attributed to climate change.The calculation thereof involved the following steps:(1)construction of a time series of observed species distributions and climatic factors,(2)estimation of the correlations between changes in species distributions and climatic factors,(3)prediction of changes in species distributions as driven by climatic factors,(4)estimation of the consistency between observed and predicted changes in species distributions,and(5)estimation of the attribution value.Furthermore,using nine snake species found in China as examples,we demonstrated in detail the practical application of this technique.This technique can be used to identify,based on global species distribution and climate data,the effects of climate change on species distributions over the past years on a global scale.

Modelling the variation of demersal fi sh distribution in Yellow Sea under climate change

Climate change can aff ect fi sh individuals or schools,and consequently the fi sheries.Studying future changes of fi sh distribution and abundance helps the scientifi c management of fi sheries.The dynamic bioclimate envelope model(DBEM)was used to identify the“environmental preference profi les”of the studied species based on outputs from three Earth system models(ESMs).Changes in ocean conditions in climate change scenarios could be transformed by the model into those in relative abundance and distribution of species.Therefore,the distributional response of 17 demersal fi shes to climate change in the Yellow Sea could be projected from 1970 to 2060.Indices of latitudinal centroid(LC)and mean temperature of relative abundance(MTRA)were used to represent the results conducted by model.Results present that 17 demersal fi sh species in the Yellow Sea show a trend of anti-poleward shift under both low-emission scenario(RCP 2.6)and high-emission scenario(RCP 8.5)from 1970 to 2060,with the projected average LC in three ESMs shifting at a rate of-1.17±4.55 and-2.76±3.82 km/decade,respectively,which is contrary to the previous projecting studies of fi shes suggesting that fi shes tend to move toward higher latitudes under increased temperature scenarios.The Yellow Sea Cold Water Mass could be the major driver resulting in the shift,which shows a potential signifi cance to fi shery resources management and marine conservation,and provides a new perspective in fi sh migration under climate change.

China and the United States’ Critical Roles in Tackling Climate Change and Shaping the International Regimes

This paper argues that major powers can play critical roles in a complicated regime system,as evidenced by China and the U.S.which have had pivotal influence in the construction of the post-2020 climate regime.China and the U.S.have participated in multilateral consultations beyond the scope of the United Nations Framework Convention on Climate Change(UNFCCC)while making use of many political platforms,such as Asia-Pacific Economic Cooperation(APEC),G20,and informal meetings and dialogues to bridge the gap among various approaches to mitigating climate impacts.China-U.S.bilateral cooperation has incorporated energy and climate issues into the strategic and economic dialogue(S&ED)and launched other schemes,such as EcoPartnerships and wide-ranging dialogues and initiatives on clean energy/clean vehicles.These schemes support the reconciliation of ideas related to domestic abatement policies in the areas of energy,climate change,and environmental protection.Since the Trump administration came to power in 2017,the bilateral cooperation at national level has been retreated significantly and therefore slowdown the UN’s institutional response to climate change.At the stage,the U.S.may not be able to play a critical role in shaping the regime,yet China is regarded to be the most important player in negotiations under the Paris Agreement.

山地城市高温热浪灾害空间识别与风险评估——以重庆市为例

【目的】以重庆市为代表的山地城市高温热浪问题突出,对高温热浪风险进行准确识别与科学评估是增强城市韧性和气候适应性的重要途径。【方法】采集社会经济、地理信息和人口数据,识别高温热浪风险要素,构建以“危险性—山地城市暴露度—脆弱性”为框架的山地城市高温热浪风险评估体系,并选择重庆市2018年7—9月典型高温热浪事件展开评估。【结果】极高和高风险区县都分布在中心城区以内,其高温热浪平均风险水平超出中等级风险区的2倍,由危险性和暴露度共同主导,越靠近中心,综合风险越高;危险性与暴露度都呈“近高远低”的空间分布特征,脆弱性空间分布特征则为“近低远高”;危险性较小的区县往往收入、医疗、教育水平有限,脆弱性明显高于中心城区;根据高温热浪风险主导因子的不同,以“局地优化、区域互补”为思路,提出山地城市热灾害风险应对策略与规划建议。【结论】完善了风景园林应对气候变化的策略体系,推动构建健康、安全、舒适的城市人居环境,为落实山地城市气候韧性发展规划提供理论支持与指导。

辛丑年运气方治疗皮肌炎相关间质性肺疾病所致难治性咳嗽

基于五运六气理论,从整体恒动的观念出发,分析辛丑年运用五味子汤合备化汤治疗皮肌炎相关间质性肺疾病(DM-ILD)所致难治性咳嗽的疗效。辛丑全年,岁水不及,太阴湿土司天,太阳寒水在泉,整年气化以寒湿为主。寒湿为阴邪,易伤阳气,尤伤肾阳,故辛丑年防治疾病应注重扶阳温中。五味子汤和备化汤是陈无择根据辛丑年运气特点所创的运气方,二者配伍具有温肾健脾散寒、温肺化痰滋阴之效,恰合辛丑年DMILD所致难治性咳嗽的病机特点,故辛丑年以其治疗该病具有良好疗效。

榆林市沙漠化演变及其驱动力分析

识别土地沙漠化的影响因素,对制定沙漠化防治对策、促进人与自然和谐发展具有重要意义。基于2000—2014年榆林市沙漠化监测数据和气象数据,采用灰色关联度分析、偏相关分析、主成分分析等方法,研究6种气候因素和8种人为因素对不同沙漠化等级土地面积变化的影响,识别主要驱动因子,并构建沙漠化面积预测模型。结果表明:1)除潜在沙漠化土地面积有所增加外,其余各类型沙漠化土地面积均显著减少;2)前5主成分中,人为因素的累积贡献率为52.98%,气候因素累积贡献率为38.17%,表明沙漠化主要受人类活动影响;3)构建的三次回归模型可较好模拟不同类型沙漠化面积变化,模型解释量达40%~66%。本成果可为评估未来气候变化对沙漠化的影响和制定沙漠化防治对策提供参考。

基于多元统计分析的茄衣烟叶生产气候资源配置

为探究茄衣烟叶生产中的气候资源配置情况,以“云雪1号”品种为试验材料,通过调整移栽期以改变烟株生育期内的气候指标,采用多元统计分析法研究茄衣烟叶的气候资源配置及其对烟株农艺性状及发酵后烟叶化学成分的影响。相关性分析结果显示,烟株大田期的积温、≥10℃有效积温、总降水量与总温差对烟株农艺性状各指标的影响较大,其相关系数分布范围为0.478~0.939,而积温、≥10℃有效积温、平均气温对烟叶总糖、烟碱、总氮、蛋白质含量影响较大,其相关系数分布范围为-0.955~-1.000。采用因子分析的方法在8项气候指标中提取出气候积累因子与湿度因子2个主因子,进一步通过灰色关联分析得出上述二者分别是影响烟株农艺性状和烟叶常规化学成分的主因子。以上结果表明,确定茄衣烟株移栽期的主要气候因子依据为大田生育期的气温、降水量和相对湿度的综合配置。

英国气候风险强制披露制度及对我国环境保护的启示

要求企业进行环境信息披露,为应对气候变化提供基础性信息,已成为实现“双碳目标”面临的重要环节。英国在气候风险强制披露领域进行了诸多探索。以气候风险与强制披露为研究起点,分析英国现行制度的框架内容和制度实践,探讨现行制度的优势与不足,提出对我国气候风险强制披露制度建设的启示建议。