Site index for Chinese fir plantations varies with climatic and soil factors in southern China

Chinese fir[Cunninghamia lanceolata(Lamb.)Hook.]has a large native distribution range in southern China.Here,we tested differences in productivity of Chinese fir plantations in different climatic regions and screened the main environmental factors affecting site productivity in each region.Relationships of a Chinese fir site index with climatic factors and the soil physiochemical properties of five soil layers were examined in a long-term positioning observation trial comprising a total of 45 permanent plots in Fujian(eastern region in the middle subtropics),Guangxi(south subtropics)and Sichuan(central region in the middle subtropics)in southern China.Linear mixed effects models were developed to predict the site index for Chinese fir,which was found to vary significantly among different climatic regions.Available P,total N,bulk density and total K were dominant predictors of site index in three climatic regions.The regional linear mixed models built using these predictors in the three climatic regions fit well(R~2=0.86–0.97).For the whole study area,the available P in the 0–20-cm soil layer and total N in the 80–100-cm soil layer were the most indicative soil factors.MAP was the most important climatic variable influencing the site index.The model evaluation results showed that the fitting performance and prediction accuracy of the global site index model using the climatic region as the dummy variable and random parameters and the most important soil factors of the three climatic regions as predictors was higher than that of global site index model using the climatic variable and the most indicative soil variables of the whole study area.Our results will help with further evaluation of site quality of Chinese fir plantations and the selection of its appropriate sites in southern China as the climatic changes.

Impacts of climate change on the potential forest productivity based on a climate-driven biophysical model in northeastern China

Climate warming is expected to influence forest growth,composition and distribution.However,accurately estimating and predicting forest biomass,potential productivity or forest growth is still a challenge for forest managers dealing with land-use at the stand to regional levels.In the present study,we predicted the potential productivity(PP)of forest under current and future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5)in Jilin province,northeastern China by using Paterson’s Climate Vegetation and Productivity(CVP)index model.The PP was validated by comparing it with the mean and maximum net primary production calculated from light energy utilization(GLM_PEM).Our results indicated that using the CVP index model is partially valid for predicting the potential forest productivity in northeastern China.PP exhibited obvious spatial heterogeneity varying from 4.6 to 8.9 m3 ha-1 year-1 with an increasing tendency from northwest to southeast driven by the precipitation across the region.The number of vegetation-active months,precipitation and insolation coefficient were identified as the primary factors affecting PP,but no significant relationship was found for warmest temperature or temperature fluctuation.Under future climate scenarios,PP across the Jilin Province is expected to increase from 1.38%(RCP2.6 in 2050)to 15.30%(RCP8.5 in 2070),especially in the eastern Songnen Plain(SE)for the RCP8.5 scenarios.

Financial Innovation Way of Avoiding Risk of Climate Disasters in Food Production:Weather Index Insurance

Climate change will lead to a variety of climate disasters, and climate disasters have a greater impact on China＇s food production. Weather index insurance is a new financial way to avoid risk of climate disasters effectively in China＇s food production. Firstly, the relationship between weather index insurance and food production in China was elaborated, and then the development status, advantages and disadvantages of weather index insurance in China at present were analyzed. Finally, some countermeasures against the problems of weather index insurance in China were put forward.

Seasonal Dynamics of Terrestrial Net Primary Production in Response to Climate Changes in China

Study on seasonal responses of terrestrial net primary production (NPP) to climate changes is to help understand feedback between climate systems and terrestrial ecosystems and mechanisms of increased NPP in the northern middle and high latitudes. In this study, time series dataset of normalized difference vegetation index (NDVI) and corresponding ground-based information on vegetation, climate, soil, and solar radiation, together with an ecological process model, were used to explore the seasonal trends of terrestrial NPP and their geographical differences in China from 1982 to 1999. As the results,. seasonal total NPP in China showed a significant increase for all four seasons (spring, summer, autumn and winter) during the past 18 years. The spring NPP indicated the largest increase rate, while the summer NPP was with the largest increase in magnitude. The response of NPP to climate changes varied with different vegetation types. The increased NPP was primarily led by an advanced growing season for broadleaf evergreen forest, needle-leaf evergreen forest, and needle-leaf deciduous forest, whilst that was mainly due to enhanced vegetation activity (amplitude of growth cycle) during growing season for broadleaf deciduous forest, broadleaf and needle-leaf mixed forest, broadleaf trees with groundcover, perennial grasslands, broadleaf shrubs with grasslands, tundra, desert, and cultivation. The regions with the largest increase in spring NPP appeared mainly in eastern China, while the areas with the largest increase in summer NPP occurred in most parts of Northwestern China, Qinghai-Xizang Plateau, Mts. Xiaoxinganling-Changbaishan, Sanjiang Plain, Songliao Plain, Sichuan Basin, Leizhou Peninsula, part of the middle and lower Yangtze River, and southeastern mountainous areas of China. In autumn, the largest NPP increase appeared in Yunnan Plateau-Eastern Xizang and the areas around Hulun Lake. Such different ways of the NPP responses depended on regional climate attributes and their changes.

Estimation of net primary productivity and its driving factors in the Ili River Valley,China

Net primary productivity（NPP）, as an important variable and ecological indicator in grassland ecosystems, can reflect environmental change and the carbon budget level. The Ili River Valley is a wetland nestled in the hinterland of the Eurasian continent, which responds sensitively to the global climate change. Understanding carbon budget and their responses to climate change in the ecosystem of Ili River Valley has a significant effect on the adaptability of future climate change and sustainable development. In this study, we calculated the NPP and analyzed its spatio-temporal pattern of the Ili River Valley during the period 2000–2014 using the normalized difference vegetation index（NDVI） and an improved Carnegie-Ames-Stanford（CASA） model. Results indicate that validation showed a good performance of CASA over the study region, with an overall coefficient of determination（R2） of 0.65 and root mean square error（RMSE） of 20.86 g C/（m^2·a）. Temporally, annual NPP of the Ili River Valley was 599.19 g C/（m^2·a） and showed a decreasing trend from 2000 to 2014, with an annual decrease rate of –3.51 g C/（m^2·a）. However, the spatial variation was not consistent, in which 55.69% of the areas showed a decreasing tendency, 12.60% of the areas remained relatively stable and 31.71% appeared an increasing tendency. In addition, the decreasing trends in NPP were not continuous throughout the 15-year period, which was likely being caused by a shift in climate conditions. Precipitation was found to be the dominant climatic factor that controlled the inter-annual variability in NPP. Furthermore, the correlations between NPP and climate factors differed along the vertical zonal. In the medium-high altitudes of the Ili River Valley, the NPP was positively correlated to precipitation and negatively correlated to temperature and net radiation. In the low-altitude valley and high-altitude mountain areas, the NPP showed a negative correlation with precipitation and a weakly positive correlation with temperature and net radiation. The results suggested that the vegetation of the Ili River Valley degraded in recent years, and there was a more complex mechanism of local hydrothermal redistribution that controlled the growth of vegetation in this valley ecosystem.

Seasonal Responses of Net Primary Productivity of Vegetation to Phenological Dynamics in the Loess Plateau, China

With global warming, the great changes in the patterns of plant growth have occurred. The conditions in early spring and late autumn have changed the process of vegetation photosynthesis, which are expected to have a significant impact on net primary productivity(NPP) and affect the global carbon cycle. Currently, the seasonal response characteristics of NPP to phenological changes in dryland ecosystems are still not well defined. This article calibrated and analyzed the normalized difference vegetation index(NDVI)time series of Advanced Very-High-Resolution Radiometer(AVHRR) data from 1982 to 2015 in the Loess Plateau, China. The spatial and temporal distributions of vegetation phenology and NPP in the Loess Plateau under semihumid and semiarid conditions were investigated. The seasonal variation in the NPP response to vegetation phenology under the climate change was also analyzed. The results showed that, different from the northern forest, there was distinct spatial heterogeneity in the effect of climate change on the dynamic change in vegetation growth in the Loess Plateau: 1) an advance of the start of the growing season(SOS) and a delay of the end of the growing season(EOS) significantly increased the NPP in spring and autumn, respectively, in the humid southeast;2) in the arid northwest, the NPP did not significantly increase in spring and autumn but significantly decreased in summer.

经济预警指数、国房景气指数与CPI指数波动溢出实证分析——基于三元VAR-GARCH-BEKK模型

建立三元VAR-GARCH-BEKK模型对中国经济预警指数、国房景气指数和CPI指数间的ARCH型和GARCH型波动溢出进行了分析,发现经济预警指数和国房景气指数当期波动均受到了自身滞后残差平方与滞后波动的显著影响,但CPI指数波动不存在ARCH和GARCH效应。CPI指数对经济预警指数和国房景气指数有显著的波动溢出作用,经济预警指数对国房景气指数存在波动溢出作用。因此,国家制定宏观经济政策时应避免分割控制模式,积极建立动态制度框架和信息沟通机制以抵御风险。

居民物价感受与CPI的悖离——基于典型价格指数的模拟分析

文章以2016年1月至2020年11月国家统计局公布的月度环比CPI和农产品价格指数、国房景气指数以及清华iCPI项目组发布的网络CPI环比数据为样本,模拟分析在农产品金融化背景下,将农产品价格、住房价格以及线上商品价格纳入CPI核算体系对CPI的影响。研究表明,农产品价格变化对CPI的影响最大,是居民体验感与CPI实际变化不一致的主要原因,相对而言,房价变化对CPI的影响较小。采用当前CPI核算体系计算得到的CPI总指数的代表性偏误,会随着网购数量和规模的增加而增大,而不同类型线上商品的数量和规模变化对CPI的影响并不一致。其中,线上衣着类商品规模的增加会减少CPI波动,线上生活用品及服务类商品规模的增加会增加CPI波动。

论GDP、CPI与国民经济总价值TH及通货膨胀、紧缩率i

本文通过使用"全面价值论"的观点,找到了国民经济总价值、剩余价值的实时计算指标及度量方法,也就是具体找到了GDP的完善化指标。给出了全面价值的价值规律指导下的国民经济全面协调发展的指路明灯。此外,通过全面价值论观点,还找到了符合通货膨胀或通货紧缩定义的"全部商品"的通货膨胀率或通货紧缩率计算公式,通过全部商品的通货膨胀率或通货紧缩率的具体计算,可以还原纸币本身的时间价值,使纸币起到实物货币的功能,成为根本治理通货膨胀、通货紧缩及金融危机的基本实操。

气候变化背景下黑龙江省东南部水稻增产潜力评估分析

研究旨在评估黑龙江省东南部水稻气候生产潜力,并分析其增产空间,以便为该地区合理有效利用气候资源、提高水稻生产力提供科学依据。通过收集发育期观测数据,确定了水稻播种、移栽及成熟的临界温度指标,并采用联合国粮食和农业组织(FAO)推荐的逐步订正法计算了水稻的气候生产潜力。进而还分析了多年气候变化对水稻生产潜力的影响。研究结果显示,播种期、出苗期和成熟期的临界温度分别为5℃、12.5℃、10℃。在五常、宾县、宁安地区,无论是从播种到成熟期间,还是从移栽到成熟期间,水稻的气候生产潜力均呈现出增长趋势。特别是在气候变暖的情况下,宁安地区的水稻生产受到了积极影响。通过对1961-2020年的数据进行分析,发现黑龙江省东南部从播种到成熟期的水稻单产增产潜力呈现先下降后升高的趋势,该地区的水稻实际生产力逐渐提高,即实际单产有所增加。然而,与其气候生产潜力相比,仍存在较大的差距,表明该地区水稻的增产空间仍然巨大。本研究的结果不仅为水稻生产的合理布局提供了科学依据,还为充分有效利用气候资源提供了指导。

Influence of vapor pressure deficit on vegetation growth in China

Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.

气候风险对期货市场产品价格的影响研究

以农产类、粮食类、能源类、化工类4类期货产品为研究对象,在阐述气候风险影响期货市场产品价格基本理论的基础上,采用文本分析和GARCH类模型相结合的方法,同时考虑4种宏观经济因素,定量评估了气候风险对期货市场产品价格的影响。结果表明,气候风险指数与能源类和化工类期货产品的价格指数呈正相关,且气候风险对能源类和化工类期货市场均具有风险溢出效应。当期的气候风险指数对农产类、能源类和化工类期货产品价格指数的收益率具有显著正向影响,对粮食类期货产品价格指数的收益率具有显著负向影响。当期的气候风险指数对农产类期货产品价格指数的收益波动率具有显著正向影响,对粮食类、化工类和能源类期货产品价格指数的收益波动率具有显著负向影响。研究结果揭示了气候风险对期货市场的复杂影响,有助于为金融市场应对气候风险提供科学依据。

农用地分等中最大自然质量等指数可比性探讨

最大自然质量等指数综合反映区域间气候因子差异性,是农用地分等指数横向可比的关键。①对最大自然质量等指数可比性影响因素分析表明,β系数的产量比算法具有条件性,国家提供的光温潜力指数与重庆实际存在一定偏差,不同两熟标准耕作制度间作物生育期存在重叠长短差异,导致最大自然质量等指数偏差;②尝试对最大自然质量等指数模型进行改进,β系数采用同能量标准粮折算与光温潜力匹配;引入光温潜力协调系数γ,以调整作物间光温潜力偏差和协调不同耕作制度间最大自然质量等指数偏差;③以重庆市为例,通过改进的算法获得5种作物中稻、冬小麦、玉米、甘薯、油菜的β系数为1、0.99、1.04、0.23、1.66,γ系数为1、1.11、0.90、0.86、1.05;用改进的算法与《农用地分等规程》算法分别计算最大自然质量等指数,对比分析表明:改进的算法有效实现了4个2级区水田和旱地最大自然质量等指数的可比,有机整合了各作物光温潜力对不同区域农用地质量的贡献,验证了方法的合理性。

气候变化背景下安徽省冬小麦气候生产潜力和胁迫风险研究

从气候的资源和灾害双重属性出发,构建了冬小麦气候生产潜力和胁迫风险评价指标,以安徽省为例分析了二者对气候变化的响应特征,综合气候对高产和稳产的影响进行研究区冬小麦种植气候适宜性区划。结果表明:采用逐级订正法结合作物生长动态参数估算安徽省冬小麦气候生产潜力多年平均为12391kg?hm-2,以沿淮和江淮之间最高;1961-2015年淮北和沿淮东部地区为显著上升趋势,而淮河以南地区则以下降为主。通过考虑在冬小麦生长发育过程中气候条件偏离最适区间而导致的胁迫影响,建立了高温、低温、雨涝、干旱4种气候胁迫的评估指标,并基于气候胁迫的超越概率形成了冬小麦气候风险评价方法。气候变暖使研究区冬小麦高温胁迫显著上升,低温胁迫显著下降,水分胁迫无显著的变化趋势。安徽省冬小麦的气候风险呈现中间低,两头高的分布特征,以沿淮和江淮之间风险最低,淮北北部和江南南部风险较高;淮北地区主要以干旱和低温贡献为主,而淮河以南地区则以雨涝风险为主。融合气候生产潜力和气候胁迫风险形成冬小麦的气候适宜性区划,其空间格局呈南北低、中间高的特征,种植分布格局与气候适宜性的空间匹配程度较高,但有一定的优化调整空间。

高寒草原对气候生产力模型的适用性分析

本研究利用中国科学院巴音布鲁克草原生态研究站1984-1990年、2004-2008年2个时间序列植物营养生长期的气候指标及净第一性生产力(NPP)实测值,结合北京模型、综合植被模型和林慧龙等建立的模型模拟研究区的NPP;根据3个模型NPP的模拟值与实测值对其进行了一元线性回归与相关分析,并基于NPP的模拟值探讨了研究区草地载畜量。结果表明,北京模型(R=0.857**)、综合植被模型(R=0.894**)和林慧龙建立的模型(R=0.894**)的NPP模拟值与实测值相关性及一元线性回归方程拟合较好,同时从线性回归的拟合度也揭示了降水是研究区NPP的主要限制因子,而温度对NPP的影响程度相对较小。在年均气温增加2和4℃,年降水量增加20%时,草地理论载畜量分别由目前的0.94个羊单位/hm2增加到1.49和1.62个羊单位/hm2。

长江上游典型区的耕地地力与农业结构调整——以川江流域及其周边地区为例

耕地地力的调查研究是对长江上游地区的生态环境整治建设、农业结构调整等有重要意义的工作。以川江流域及其周边的几个典型农业生态区的耕地为例进行研究,结果表明:采用土壤质量系数、土地生产潜力等对该区域耕地地力进行评价是适宜的。评价结果对该区生态环境建设、农业结构调整等有指导意义。同时,根据该区耕地地力特点和分布状况,提出了保护利用和农业结构调整的对策。

气候变化对陕南汉江流域植被净初级生产力的影响

根据陕南汉江流域及其周边34个气象站1959-2010年的逐日气温和降水资料,利用周广胜—张新时模型、Penman-Monteith公式、Mann-Kendall检验、相关分析和Spline插值等方法,分析了近52a水热条件的变化及其对净初级生产力(NPP)的影响,并对NPP的未来变化进行预估。结果表明:1)汉江流域年均温为13.7℃,整体呈升高趋势(0.14℃.(10a)-1)(p<0.001),北部快于南部,东部快于西部。多年平均降水为747.3mm,整体呈减少趋势,于1991年发生减少突变;2)NPP高值区位于大巴山区和米仓山部分地区,秦岭山地相对较小,表现出由南向北递减的空间格局。秦岭南麓部分地区NPP上升,汉江谷地除安康外均呈下降趋势,大巴山和米仓山一带除平利、镇坪外均呈现下降趋势。3)NPP与降水、相对湿度和湿润指数呈极显著的正相关关系(p<0.001),与潜在蒸散、日照时数和气温负相关,温度对于NPP积累起到的作用有限,水分是主要制约因素;4)a情景下NPP增幅15%以上,b情景下增加9%左右,c情景下NPP整体下降。

内蒙古1981-2010年干湿气候类型和净第一性生产力演变

为了更好服务于内蒙古地区生态建设,提供地区大气候背景的演变过程。运用徐文铎湿润指数划分了内蒙古地区的干湿气候类型,研究结果表明:1981—2010年内蒙古半干旱区、干旱区+极干旱区面积、亚湿润区+湿润区面积分别为343 090,388 035,411 819km^2;2001—2010年半干旱区+干旱区+极干旱区面积是20世纪90年代面积的1.3倍;半湿润区+湿润区面积减少了0.5倍,地区生态环境质量进一步下降。干湿气候类型与历年降水量分布图对比显示,干旱区和极干旱区面积与200mm降水量分布线对应;湿润区在东北地区与400 mm分布线接近;分布最广的半干旱区受温度和降水综合影响较多,与雨量带分布无明显关系。1981—2010年,温度呈显著增加趋势,降水量下降趋势属正常气候波动。地区净第一性生产力(NPP)与降水量的相关系数达到显著水平,相关系数为0.930 0,而与温度的相关系数只有-0.270 0。年代际NPP在2001—2010年下降明显,从西北到东南阶梯式降低,受影响较大的地区主要分布在呼伦贝尔市西部的典型草原和温性草甸草原,赤峰市和通辽市也下降明显;总趋势是东部区下降明显,西部区波动变化,整体下降明显。

沿水分梯度草原群落NPP动态及对气候变化响应的模拟分析

水分条件不仅影响半干旱区群落的组成,而且在一定程度上决定了群落的功能。处于不同水分条件生境下群落的优势物种在水分利用和同化物利用效率方面的功能特征会存在差异,这些差异将导致群落对于气候变化产生不同的响应,进而影响到景观和区域尺度上对于全球变化下碳动态和格局的分析。该文选取了锡林河流域典型草原区沿水分梯度的4个代表群落,在野外实验测定并结合长期定位研究成果基础上,利用BIOME-BGC模型对代表群落的长期净初级生产力（Net primary productivity,NPP）动态进行了模拟和模型验证。通过分析该地区1953~2005年气候变化趋势,推测了未来可能的气候变化情景,进而模拟了气候变化下4个群落长期NPP动态的响应。结果表明,当前气候条件下,羊草（Leymus chinensis）群落NPP平均值为197.76gC·m^-2（SE=7.11）,大针茅（Stipa grandis）群落NPP平均值为198.95gC·m^-2（SE=6.41）,贝加尔针茅（Stipa baicalensis）群落NPP平均值为210.41gC·m^-2（SE=7.87）,克氏针茅（Stipa krylovii）群落NPP平均值为144.92gC·m-2（SE=4.64）,4个群落NPP平均值为188.01gC·m^-2（SE=3.72）;气候变化情景下,温度增加下（P0T1）,NPP平均下降14.2%,降水增加下（P1T0）,NPP平均增加13.2%,温度与降水都增加情景下（P1T1）,NPP平均下降2.7%,但由于生境水分条件差别和优势物种功能特征差异,4个群落表现出了增减幅度不同的趋势。对气候因子的敏感性分析及回归分析表明,降水是该地区NPP最主要的决定因子,而温度决定作用相对较小,主要通过影响植物的呼吸和水分蒸散等过程影响NPP。在最有可能代表未来气候变化的温度增加的两种情景下（P0T1、P1T1）,NPP均呈下降趋势。群落NPP对气候变化的响应趋势与水分胁迫系数（Water stress index,WSI）、碳胁迫系数（Carbon stress index,CSI）变化密切相关。克氏针茅群落由于所处生境水分条件差,WSI高,对降水的依赖程度最大;贝加尔针茅群落一方面处于较好的水分生境,具有较小的WSI,另一方面,由于具有高碳氮比,维持呼吸消耗的光合产物比例低,CSI远低于其它3个群落,未来气候变化下,NPP较其它3个群落仍较高。

气候变化与生产经营活动对草地退化影响的实证研究——以锡林郭勒盟牧区为例

以锡林郭勒盟牧区为例，利用NOAA／HAVRRNDVI与MODISNDVI遥感数据，估计得到其1981—2013年的植被覆盖度，并根据草地退化国家标准，计算草地退化指数作为衡量草地质量状况的指标，实证研究气候变化与生产经营活动对草地退化的影响。结果表明：（1）1981—2013年，锡盟牧区草地退化指数呈先升后降的特征，总体呈上升态势，说明研究区草地退化水平呈先恶化、后期不断下降的变化趋势。（2）研究区草地退化主要受生产经营活动的影响。其中，非农生产经营活动是草地退化的主要驱动因素之一，尤其是矿产开采：农业生产经营活动中的畜牧业生产是草地退化的另一主要影响因素，草地载畜量越多，草地退化状况越严重。（3）除生产经营活外，气候因素对草地退化的影响主要表现为锡盟牧区夏季气候长期趋于干旱化的变化趋势，且生产经营活动对草地退化的影响小于夏季降水量的影响。