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 m...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.展开更多
China is one of the world’s major exporters of fruit and vegetable products,and the expansion of fruit and vegetable exports is important for increasing agricultural income.Based on time-varying stochastic frontier g...China is one of the world’s major exporters of fruit and vegetable products,and the expansion of fruit and vegetable exports is important for increasing agricultural income.Based on time-varying stochastic frontier gravity model and trade inefficiency model,this paper empirically analyzes the influencing factors and trade efficiency of China’s fruit and vegetable products export to RCEP partners from 2001 to 2019.The results show that China’s GDP per capita,the population of importing countries,and common language conditions have positive effects on China’s fruit and vegetable products export to RCEP partners.GDP per capita of importing countries,the population of China,and geographical distance between trading parties hinder trade in fruit and vegetable products.The presence of trade inefficiencies constrains China’s fruit and vegetable products export to RCEP partners,with liner shipping connectivity and trade freedom having a positive relationship with export efficiency of fruit and vegetable products.Variable trade costs and fixed trade costs have a negative relationship with export efficiency of fruit and vegetable products,which hinder trade in fruit and vegetable products,while financial freedom and free trade agreements have no significant impact on export efficiency of fruit and vegetable products.展开更多
Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for res...Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.展开更多
Using the Integrated Biosphere Simulator, a dynamic vegetation model, this study initially simulated the net primary productivity（NPP） dynamics of China＇s potential vegetation in the past 55 years（1961–2015） and...Using the Integrated Biosphere Simulator, a dynamic vegetation model, this study initially simulated the net primary productivity（NPP） dynamics of China＇s potential vegetation in the past 55 years（1961–2015） and in the future 35 years（2016–2050）. Then, taking the NPP of the potential vegetation in average climate conditions during 1986–2005 as the basis for evaluation, this study examined whether the potential vegetation adapts to climate change or not. Meanwhile, the degree of inadaptability was evaluated. Finally, the NPP vulnerability of the potential vegetation was evaluated by synthesizing the frequency and degrees of inadaptability to climate change. In the past 55 years, the NPP of desert ecosystems in the south of the Tianshan Mountains and grassland ecosystems in the north of China and in western Tibetan Plateau was prone to the effect of climate change. The NPP of most forest ecosystems was not prone to the influence of climate change. The low NPP vulnerability to climate change of the evergreen broad-leaved and coniferous forests was observed. Furthermore, the NPP of the desert ecosystems in the north of the Tianshan Mountains and grassland ecosystems in the central and eastern Tibetan Plateau also had low vulnerability to climate change. In the next 35 years, the NPP vulnerability to climate change would reduce the forest–steppe in the Songliao Plain, the deciduous broad-leaved forests in the warm temperate zone, and the alpine steppe in the central and western Tibetan Plateau. The NPP vulnerability would significantly increase of the temperate desert in the Junggar Basin and the alpine desert in the Kunlun Mountains. The NPP vulnerability of the subtropical evergreen broad-leaved forests would also increase. The area of the regions with increased vulnerability would account for 27.5% of China.展开更多
草地综合顺序分类法(comprehensive and sequential classification system of grassland,CSCS)经过60多年的不断探索和完善,已成为具有中国知识产权的唯一的可数量化的草地分类系统。特别是2008年任继周等在Rangeland Journal专门著文...草地综合顺序分类法(comprehensive and sequential classification system of grassland,CSCS)经过60多年的不断探索和完善,已成为具有中国知识产权的唯一的可数量化的草地分类系统。特别是2008年任继周等在Rangeland Journal专门著文推介CSCS,开启了CSCS在国内外研究的新高潮。本研究以CSCS作为关键词从Wed of Science及中国知网等科技论文数据库检索得2008-2020年发表的中英文文献分别为48和29篇。通过系统梳理,获得最新的研究成果如下:1)将CSCS与国际公认的Holdridge Life Zone、BIOME4分类体系在全球尺度上进行对比验证,论证了CSCS在草地类型划分方面的突出优势;2)使用数字高程模型数据的坡度、坡向和坡度变化率等因子修正传统空间插值法,引入海拔、坡度等变量的多元回归和残差分析插值法,有效解决高海拔和复杂地形所带来的气候数据插值误差,提高了CSCS的模拟精度,也为深入广泛的应用提供了方法论依据;3)基于CSCS发生学特征,研究草地对全球气候变化的响应。现已在区域、全国及全球尺度上研究草地生态系统对全球气候变化的响应,为进一步的草地精细化分类管理和相关政策制定提供了数据基础;4)热量状况和水分条件的组合是草原现象和过程的本质的因素,以CSCS为理论框架,用分类指标为参数构建草地第一性生产力(NPP)分类指数模型,该模型不仅揭示草地类型与其净第一性生产力的内在联系,也为进一步研究地带性草地类型的生产潜力、草地净第一性生产力的区域分布和全球分布提供了可能。在区域、全国和全球尺度上的比较验证可知,基于CSCS的草地NPP模型已发展成为草地生态系统第一性生产力评估及碳汇计算的新工具。未来CSCS研究亟待开展的工作主要有:1)完善CSCS亚类及型的定量分类体系;2)通过开发CSCS方法在草地营养载畜量和生态服务价值评估等方面的应用,完善基于CSCS框架的草地精细化管理。展开更多
文摘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.
文摘China is one of the world’s major exporters of fruit and vegetable products,and the expansion of fruit and vegetable exports is important for increasing agricultural income.Based on time-varying stochastic frontier gravity model and trade inefficiency model,this paper empirically analyzes the influencing factors and trade efficiency of China’s fruit and vegetable products export to RCEP partners from 2001 to 2019.The results show that China’s GDP per capita,the population of importing countries,and common language conditions have positive effects on China’s fruit and vegetable products export to RCEP partners.GDP per capita of importing countries,the population of China,and geographical distance between trading parties hinder trade in fruit and vegetable products.The presence of trade inefficiencies constrains China’s fruit and vegetable products export to RCEP partners,with liner shipping connectivity and trade freedom having a positive relationship with export efficiency of fruit and vegetable products.Variable trade costs and fixed trade costs have a negative relationship with export efficiency of fruit and vegetable products,which hinder trade in fruit and vegetable products,while financial freedom and free trade agreements have no significant impact on export efficiency of fruit and vegetable products.
文摘Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.
基金Key Project of National Natural Science Foundation of China,No.41530749 Science and Technology Project of Sichuan Provincial Department of Education,No.15ZB0023+1 种基金 Youth Projects of National Natural Science Foundation of China,No.41301196,No.41501202 Chongqing Foundation and Advanced Research Project,No.cstc2014jcyj A0808
文摘Using the Integrated Biosphere Simulator, a dynamic vegetation model, this study initially simulated the net primary productivity（NPP） dynamics of China＇s potential vegetation in the past 55 years（1961–2015） and in the future 35 years（2016–2050）. Then, taking the NPP of the potential vegetation in average climate conditions during 1986–2005 as the basis for evaluation, this study examined whether the potential vegetation adapts to climate change or not. Meanwhile, the degree of inadaptability was evaluated. Finally, the NPP vulnerability of the potential vegetation was evaluated by synthesizing the frequency and degrees of inadaptability to climate change. In the past 55 years, the NPP of desert ecosystems in the south of the Tianshan Mountains and grassland ecosystems in the north of China and in western Tibetan Plateau was prone to the effect of climate change. The NPP of most forest ecosystems was not prone to the influence of climate change. The low NPP vulnerability to climate change of the evergreen broad-leaved and coniferous forests was observed. Furthermore, the NPP of the desert ecosystems in the north of the Tianshan Mountains and grassland ecosystems in the central and eastern Tibetan Plateau also had low vulnerability to climate change. In the next 35 years, the NPP vulnerability to climate change would reduce the forest–steppe in the Songliao Plain, the deciduous broad-leaved forests in the warm temperate zone, and the alpine steppe in the central and western Tibetan Plateau. The NPP vulnerability would significantly increase of the temperate desert in the Junggar Basin and the alpine desert in the Kunlun Mountains. The NPP vulnerability of the subtropical evergreen broad-leaved forests would also increase. The area of the regions with increased vulnerability would account for 27.5% of China.
文摘草地综合顺序分类法(comprehensive and sequential classification system of grassland,CSCS)经过60多年的不断探索和完善,已成为具有中国知识产权的唯一的可数量化的草地分类系统。特别是2008年任继周等在Rangeland Journal专门著文推介CSCS,开启了CSCS在国内外研究的新高潮。本研究以CSCS作为关键词从Wed of Science及中国知网等科技论文数据库检索得2008-2020年发表的中英文文献分别为48和29篇。通过系统梳理,获得最新的研究成果如下:1)将CSCS与国际公认的Holdridge Life Zone、BIOME4分类体系在全球尺度上进行对比验证,论证了CSCS在草地类型划分方面的突出优势;2)使用数字高程模型数据的坡度、坡向和坡度变化率等因子修正传统空间插值法,引入海拔、坡度等变量的多元回归和残差分析插值法,有效解决高海拔和复杂地形所带来的气候数据插值误差,提高了CSCS的模拟精度,也为深入广泛的应用提供了方法论依据;3)基于CSCS发生学特征,研究草地对全球气候变化的响应。现已在区域、全国及全球尺度上研究草地生态系统对全球气候变化的响应,为进一步的草地精细化分类管理和相关政策制定提供了数据基础;4)热量状况和水分条件的组合是草原现象和过程的本质的因素,以CSCS为理论框架,用分类指标为参数构建草地第一性生产力(NPP)分类指数模型,该模型不仅揭示草地类型与其净第一性生产力的内在联系,也为进一步研究地带性草地类型的生产潜力、草地净第一性生产力的区域分布和全球分布提供了可能。在区域、全国和全球尺度上的比较验证可知,基于CSCS的草地NPP模型已发展成为草地生态系统第一性生产力评估及碳汇计算的新工具。未来CSCS研究亟待开展的工作主要有:1)完善CSCS亚类及型的定量分类体系;2)通过开发CSCS方法在草地营养载畜量和生态服务价值评估等方面的应用,完善基于CSCS框架的草地精细化管理。
