Based on the GIMMS AVHRR NDVI data （8 km spatial resolution） for 1982-2000, the SPOT VEGETATION NDVI data （1 km spatial resolution） for 1998-2009, and observa- tional plant biomass data, the CASA model was used to...Based on the GIMMS AVHRR NDVI data （8 km spatial resolution） for 1982-2000, the SPOT VEGETATION NDVI data （1 km spatial resolution） for 1998-2009, and observa- tional plant biomass data, the CASA model was used to model changes in alpine grassland net primary production （NPP） on the Tibetan Plateau （TP）. This study will help to evaluate the health conditions of the alpine grassland ecosystem, and is of great importance to the pro- motion of sustainable development of plateau pasture and to the understanding of the func- tion of the national ecological security shelter on the TP. The spatio-temporal characteristics of NPP change were investigated using spatial statistical analysis, separately on the basis of physico-geographical factors （natural zone, altitude, latitude and longitude）, river basin, and county-level administrative area. Data processing was carried out using an ENVI 4.8 platform, while an ArcGIS 9.3 and ANUSPLIN platform was used to conduct the spatial analysis and mapping. The primary results are as follows： （1） The NPP of alpine grassland on the TP gradually decreases from the southeast to the northwest, which corresponds to gradients in precipitation and temperature. From 1982 to 2009, the average annual total NPP in the TP alpine grassland was 177.2x1012 gC yrl（yr represents year）, while the average annual NPP was 120.8 gC m^-2 yr^-1. （2） The annual NPP in alpine grassland on the TP fluctuates from year to year but shows an overall positive trend ranging from 114.7 gC m^-2 yr^-1 in 1982 to 129.9 gC m^-2 yr^-1 in 2009, with an overall increase of 13.3%; 32.56% of the total alpine grassland on the TP showed a significant increase in NPP, while only 5.55% showed a significant decrease over this 28-year period. （3） Spatio-temporal characteristics are an important control on an- nual NPP in alpine grassland： a） NPP increased in most of the natural zones on the TP, only showing a slight decrease in the Ngari montane desert-steppe and desert zone. The positive 展开更多
草地是宁夏陆地生态系统的重要组成部分,估算其净初级生产力(NPP)对宁夏草地可持续利用与管理至关重要。采用MODIS数据和CASA模型对2000—2015年间宁夏草地生态系统NPP进行了估算,通过一元线性回归趋势分析、Hurst指数等方法研究草地NP...草地是宁夏陆地生态系统的重要组成部分,估算其净初级生产力(NPP)对宁夏草地可持续利用与管理至关重要。采用MODIS数据和CASA模型对2000—2015年间宁夏草地生态系统NPP进行了估算,通过一元线性回归趋势分析、Hurst指数等方法研究草地NPP的时空变化规律及未来演变趋势,并分析草地NPP与气象因子的相关性。结果表明:(1)基于CASA模型的宁夏草地NPP模拟精度高,其估算值与实测多年草地NPP均值具有良好的线性关系(R=0.93,P<0.01),与MOD17产品的草地NPP空间分布基本一致。(2)近16 a宁夏草地年均NPP为148.28 g C m^(-2)a^(-1),且存在波动上升的趋势,其线性增长率为3.84 g C m^(-2)a^(-1)(P<0.01)。(3)宁夏草地NPP整体处于上升趋势,草地NPP增长的草地面积达98%,且其增率自南向北递减;宁夏草地NPP的Hurst指数在0.27—0.81之间,均值为0.53,大部分草地的NPP变化趋势具有较强同向持续性。(4)在年时间尺度上,宁夏草地NPP主要受降水量的影响,与气温的相关性较弱;在月时间尺度上,生长季草地NPP与月总降水量的相关性高,且不存在时间滞后响应现象,而与月均温的响应则存在1个月的时间滞后性,宁夏大面积分布的干草原与荒漠草原NPP对气温响应滞后是导致这一现象发生的主要原因。展开更多
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 north...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.展开更多
Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial a...Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.展开更多
Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegi...Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.展开更多
基金National Basic Research Program of China,No.2010CB951704Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB03030501No.XDA05060704
文摘Based on the GIMMS AVHRR NDVI data （8 km spatial resolution） for 1982-2000, the SPOT VEGETATION NDVI data （1 km spatial resolution） for 1998-2009, and observa- tional plant biomass data, the CASA model was used to model changes in alpine grassland net primary production （NPP） on the Tibetan Plateau （TP）. This study will help to evaluate the health conditions of the alpine grassland ecosystem, and is of great importance to the pro- motion of sustainable development of plateau pasture and to the understanding of the func- tion of the national ecological security shelter on the TP. The spatio-temporal characteristics of NPP change were investigated using spatial statistical analysis, separately on the basis of physico-geographical factors （natural zone, altitude, latitude and longitude）, river basin, and county-level administrative area. Data processing was carried out using an ENVI 4.8 platform, while an ArcGIS 9.3 and ANUSPLIN platform was used to conduct the spatial analysis and mapping. The primary results are as follows： （1） The NPP of alpine grassland on the TP gradually decreases from the southeast to the northwest, which corresponds to gradients in precipitation and temperature. From 1982 to 2009, the average annual total NPP in the TP alpine grassland was 177.2x1012 gC yrl（yr represents year）, while the average annual NPP was 120.8 gC m^-2 yr^-1. （2） The annual NPP in alpine grassland on the TP fluctuates from year to year but shows an overall positive trend ranging from 114.7 gC m^-2 yr^-1 in 1982 to 129.9 gC m^-2 yr^-1 in 2009, with an overall increase of 13.3%; 32.56% of the total alpine grassland on the TP showed a significant increase in NPP, while only 5.55% showed a significant decrease over this 28-year period. （3） Spatio-temporal characteristics are an important control on an- nual NPP in alpine grassland： a） NPP increased in most of the natural zones on the TP, only showing a slight decrease in the Ngari montane desert-steppe and desert zone. The positive
文摘草地是宁夏陆地生态系统的重要组成部分,估算其净初级生产力(NPP)对宁夏草地可持续利用与管理至关重要。采用MODIS数据和CASA模型对2000—2015年间宁夏草地生态系统NPP进行了估算,通过一元线性回归趋势分析、Hurst指数等方法研究草地NPP的时空变化规律及未来演变趋势,并分析草地NPP与气象因子的相关性。结果表明:(1)基于CASA模型的宁夏草地NPP模拟精度高,其估算值与实测多年草地NPP均值具有良好的线性关系(R=0.93,P<0.01),与MOD17产品的草地NPP空间分布基本一致。(2)近16 a宁夏草地年均NPP为148.28 g C m^(-2)a^(-1),且存在波动上升的趋势,其线性增长率为3.84 g C m^(-2)a^(-1)(P<0.01)。(3)宁夏草地NPP整体处于上升趋势,草地NPP增长的草地面积达98%,且其增率自南向北递减;宁夏草地NPP的Hurst指数在0.27—0.81之间,均值为0.53,大部分草地的NPP变化趋势具有较强同向持续性。(4)在年时间尺度上,宁夏草地NPP主要受降水量的影响,与气温的相关性较弱;在月时间尺度上,生长季草地NPP与月总降水量的相关性高,且不存在时间滞后响应现象,而与月均温的响应则存在1个月的时间滞后性,宁夏大面积分布的干草原与荒漠草原NPP对气温响应滞后是导致这一现象发生的主要原因。
文摘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.
基金Under the auspices of the National Natural Science Foundation of China (No. 40571117), the Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX3-SW-338), Research foundation of the State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences (KQ060006)
文摘Net Primary Productivity （NPP） is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer （MODIS） data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach （CASA） model. The spatial distribution of Absorbed Photosynthetically Active Radiation （APAR） of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation （FPAR） product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subreglons were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 10^6gC/（m^2.a）, and NPP in 2001 ranged from 2 to 608gC/（m^2-a）, with an average of 337.516gC/（m^2.a）. NPP of the study area in 2001 accumulated mainly from May to September （DOY 129-272）, high NIP values appeared from June to August （DOY 177-204）, and the maximum NPP appeared from late July to mid-August （DOY 209-224）.
基金Under the auspices of Key Program of Chinese Academy of Sciences(No.KZZD-EW-08-02)CAS/SAFEA(Chinese Academy of Science/State Administration of Foreign Experts Affairs)International Partnership Program for Creative Research Teams(No.KZZD-EW-TZ-07)Strategic Frontier Program of Chinese Academy of Sciences-Climate Change:Carbon Budget and Relevant Issues(No.XDA05050101)
文摘Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.
