Besides its ecological services to China and even Asia,the Qingzang Plateau(QP)hosts a rich variety of wildlife species.During the last century,wildlife population decreased quickly on the QP,driven by human intervent...Besides its ecological services to China and even Asia,the Qingzang Plateau(QP)hosts a rich variety of wildlife species.During the last century,wildlife population decreased quickly on the QP,driven by human interventions.Recently,wildlife has witnessed rapid recovery mainly propelled by a series of wildlife conservation policies.However,some cautions merit attentions to sustain wildlife restoration and conservation on the QP.This paper casted an overview of environmental and social-economic changes on the QP affecting wildlife subsistence.Re-sults show that QP has been warming,which can benefit wildlife recovery by easing extreme low temperature stresses.The fast growing social economy across the QP lays a solid economic foundation for investing on wildlife protection.Measures such as establishing conservation areas,constructing wildlife pathway corridors,and en-couraging herdsman moving out from wildlife rich regions,have boosted wildlife recovery.However,wildlife recovery is constrained by the limited carrying capacity of the ecosystem,left by domestic livestock.Additionally,fences intended to delineate conservation areas or to separate each type of grassland use,have brought about profound side effects on wildlife through fragmentation of their habitats.It is recommended to set up the fence in a more ecological way,which can be achieved by bypassing the wildlife frequent pathway and using mate-rials devoid of steel barb.Only considering both opportunities and problems simultaneously,can the wildlife protection on the QP be sustained.展开更多
碳利用效率(carbon use efficiency,CUE)是指机体用于生长的碳量占其吸收总碳量的比例,是研究生态系统碳循环和碳分配模式的重要参数。对CUE的研究可利用多种方法从多尺度开展,然而CUE的高尺度敏感性导致不同方法之间的结果变异性较大,...碳利用效率(carbon use efficiency,CUE)是指机体用于生长的碳量占其吸收总碳量的比例,是研究生态系统碳循环和碳分配模式的重要参数。对CUE的研究可利用多种方法从多尺度开展,然而CUE的高尺度敏感性导致不同方法之间的结果变异性较大,难以整合并且扩展外推,成为制约CUE研究方法及应用的重要因素。本文将CUE常见的测定方法按照研究对象的应用尺度差异分为样地尺度、生态系统尺度、景观和区域尺度以及大陆和全球尺度,概述各方法的特点、优势及局限性。随后,分尺度综述CUE的研究进展,发现CUE受到包括生物和非生物等多种因素的影响,各影响因素及其交互作用在不同时空尺度上控制着CUE,CUE数值也随尺度和测定方法的不同而发生变异。建议今后对CUE的研究应该综合考量生物和环境等多要素交互影响效果,通过机理和技术研究提升数据测定的准确性,以及整合多尺度结果为模型优化提供新思路。展开更多
Aims Grassland is the most widely distributed vegetation type on the Xizang Plateau.Accurate remote sensing estimation of the grass-land aboveground biomass(AGB)in this region is influenced by the types of vegetation ...Aims Grassland is the most widely distributed vegetation type on the Xizang Plateau.Accurate remote sensing estimation of the grass-land aboveground biomass(AGB)in this region is influenced by the types of vegetation indexes(VIs)used,the grain size(resolution)of the remote sensing data and the targeted ecosystem features.This study attempts to answer the following questions:(i)Which VI can most accurately reflect the grassland AGB distribution on the Xizang Plateau?(ii)How does the grain size of remote sensing imagery affect AGB reflection?(iii)What is the spatial distribution pattern of the grassland AGB on the plateau and its relationship with the climate?Methods We investigated 90 sample sites and measured site-specific AGBs using the harvest method for three grassland types(alpine meadow,alpine steppe and desert steppe).For each sample site,four VIs,namely,Normalized Difference VI(NDVI),Enhanced VI,Normalized Difference Water Index(NDWI)and Modified Soil-Adjusted VI(MSAVI)were extracted from the Moderate Resolution Imaging Spectroradiometer(MODIS)products with grain sizes of 250 m and 1 km.Linear regression models were employed to iden-tify the best estimator of the AGB for the entire grassland and the three individual grassland types.Paired Wilcoxon tests were applied to assess the grain size effect on the AGB estimation.General linear models were used to quantify the relationships between the spatial distribution of the grassland AGB and climatic factors.Important Findings The results showed that the best estimator for the entire grass-land AGB on the Xizang Plateau was MSAVI at a 250 m grain size(MSAVI_(250 m)).For each individual grassland type,the best estimator was MSAVI at a grain size of 250 m for alpine meadow,NDWI at a grain size of 1 km for alpine steppe and NDVI at a grain size of 1 km for desert steppe.The explanation ability of each VI for the grassland AGB did not significantly differ for the two grain sizes.Based on the best fit model(AGB=−10.80+139.13 MSAVI_(250 m)),the spatial pattern of the grassland AGB on the plateau was characterized.The AGB varied from 1 to 136 g m^(−2).Approximately 59%of total spatial variation in the AGB for the entire grassland was explained by the combination of the mean annual precipitation(MAP)and mean annual temperature.The explanatory power of MAP was weaker for each individual grassland type than that for the entire grassland.This study illustrated the high efficiency of the VIs derived from MODIS data in the grassland AGB estimation on the Xizang Plateau due to the vegetation homogeneity within a 1×1 km pixel in this region.Furthermore,MAP is a primary driver on the spatial variation of AGB at a regional scale.展开更多
基金supported by the National Key Research&Development Program(Grant No.2019YFA0607302)CNSF(Grant No.41725003).
文摘Besides its ecological services to China and even Asia,the Qingzang Plateau(QP)hosts a rich variety of wildlife species.During the last century,wildlife population decreased quickly on the QP,driven by human interventions.Recently,wildlife has witnessed rapid recovery mainly propelled by a series of wildlife conservation policies.However,some cautions merit attentions to sustain wildlife restoration and conservation on the QP.This paper casted an overview of environmental and social-economic changes on the QP affecting wildlife subsistence.Re-sults show that QP has been warming,which can benefit wildlife recovery by easing extreme low temperature stresses.The fast growing social economy across the QP lays a solid economic foundation for investing on wildlife protection.Measures such as establishing conservation areas,constructing wildlife pathway corridors,and en-couraging herdsman moving out from wildlife rich regions,have boosted wildlife recovery.However,wildlife recovery is constrained by the limited carrying capacity of the ecosystem,left by domestic livestock.Additionally,fences intended to delineate conservation areas or to separate each type of grassland use,have brought about profound side effects on wildlife through fragmentation of their habitats.It is recommended to set up the fence in a more ecological way,which can be achieved by bypassing the wildlife frequent pathway and using mate-rials devoid of steel barb.Only considering both opportunities and problems simultaneously,can the wildlife protection on the QP be sustained.
文摘碳利用效率(carbon use efficiency,CUE)是指机体用于生长的碳量占其吸收总碳量的比例,是研究生态系统碳循环和碳分配模式的重要参数。对CUE的研究可利用多种方法从多尺度开展,然而CUE的高尺度敏感性导致不同方法之间的结果变异性较大,难以整合并且扩展外推,成为制约CUE研究方法及应用的重要因素。本文将CUE常见的测定方法按照研究对象的应用尺度差异分为样地尺度、生态系统尺度、景观和区域尺度以及大陆和全球尺度,概述各方法的特点、优势及局限性。随后,分尺度综述CUE的研究进展,发现CUE受到包括生物和非生物等多种因素的影响,各影响因素及其交互作用在不同时空尺度上控制着CUE,CUE数值也随尺度和测定方法的不同而发生变异。建议今后对CUE的研究应该综合考量生物和环境等多要素交互影响效果,通过机理和技术研究提升数据测定的准确性,以及整合多尺度结果为模型优化提供新思路。
基金National Natural Science Foundation of China(31300356)Chinese National Key Program for Developing Basic Science(2013CB956302)+1 种基金China Postdoctoral Science Foundation(2013M530717)Hundred Talents Program of Chinese Academy of Sciences(Y11S0400P5).
文摘Aims Grassland is the most widely distributed vegetation type on the Xizang Plateau.Accurate remote sensing estimation of the grass-land aboveground biomass(AGB)in this region is influenced by the types of vegetation indexes(VIs)used,the grain size(resolution)of the remote sensing data and the targeted ecosystem features.This study attempts to answer the following questions:(i)Which VI can most accurately reflect the grassland AGB distribution on the Xizang Plateau?(ii)How does the grain size of remote sensing imagery affect AGB reflection?(iii)What is the spatial distribution pattern of the grassland AGB on the plateau and its relationship with the climate?Methods We investigated 90 sample sites and measured site-specific AGBs using the harvest method for three grassland types(alpine meadow,alpine steppe and desert steppe).For each sample site,four VIs,namely,Normalized Difference VI(NDVI),Enhanced VI,Normalized Difference Water Index(NDWI)and Modified Soil-Adjusted VI(MSAVI)were extracted from the Moderate Resolution Imaging Spectroradiometer(MODIS)products with grain sizes of 250 m and 1 km.Linear regression models were employed to iden-tify the best estimator of the AGB for the entire grassland and the three individual grassland types.Paired Wilcoxon tests were applied to assess the grain size effect on the AGB estimation.General linear models were used to quantify the relationships between the spatial distribution of the grassland AGB and climatic factors.Important Findings The results showed that the best estimator for the entire grass-land AGB on the Xizang Plateau was MSAVI at a 250 m grain size(MSAVI_(250 m)).For each individual grassland type,the best estimator was MSAVI at a grain size of 250 m for alpine meadow,NDWI at a grain size of 1 km for alpine steppe and NDVI at a grain size of 1 km for desert steppe.The explanation ability of each VI for the grassland AGB did not significantly differ for the two grain sizes.Based on the best fit model(AGB=−10.80+139.13 MSAVI_(250 m)),the spatial pattern of the grassland AGB on the plateau was characterized.The AGB varied from 1 to 136 g m^(−2).Approximately 59%of total spatial variation in the AGB for the entire grassland was explained by the combination of the mean annual precipitation(MAP)and mean annual temperature.The explanatory power of MAP was weaker for each individual grassland type than that for the entire grassland.This study illustrated the high efficiency of the VIs derived from MODIS data in the grassland AGB estimation on the Xizang Plateau due to the vegetation homogeneity within a 1×1 km pixel in this region.Furthermore,MAP is a primary driver on the spatial variation of AGB at a regional scale.
