NPP是森林生态系统物质循环过程的关键参数,是表征生态系统碳收支的重要指标,对了解植被生长生物量积累和大气CO_(2)吸收具有重要意义。采用中国科学院资源环境科学数据中心遥感监测的NPP数据,通过趋势分析、多元回归等方法,系统分析广...NPP是森林生态系统物质循环过程的关键参数,是表征生态系统碳收支的重要指标,对了解植被生长生物量积累和大气CO_(2)吸收具有重要意义。采用中国科学院资源环境科学数据中心遥感监测的NPP数据,通过趋势分析、多元回归等方法,系统分析广东省国家级公益林NPP时空变化特征。结果表明,2004—2015年,NPP主要分布在400~800 g C/(m^(2)·a)区间内,所占比例超过70%;NPP在空间分布上较为离散,与高程联系紧密,东部地区及茂名市、阳江市的NPP相对较高;广东省国家级公益林的NPP呈波动增加趋势,年平均增加速率为4.9 g C/(m^(2)·a);不同年度NPP值总体处于较稳定状态,所占比例为99.25%,抗干扰能力强;广东省国家级公益林的NPP经异养呼吸后仍有60.6%保留在生态系统中,反映了国家级公益林良好的固碳能力,为我国“碳中和”目标贡献了林业力量。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 Carnegie-A...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 Inventory 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 regression model based on least squares 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 increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. 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 NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration 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 regions. In addition to climatic 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
The impacts of climate change in terms of forest vegetation shifts and Net Primary Productivity (NPP) changes are assessed for Brahmaputra, Koshi and Indus river basins for the mid (2021-2050) and long (2071-2100) ter...The impacts of climate change in terms of forest vegetation shifts and Net Primary Productivity (NPP) changes are assessed for Brahmaputra, Koshi and Indus river basins for the mid (2021-2050) and long (2071-2100) terms for RCP4.5 and RCP8.5 scenarios. Two Dynamical Global Vegetation Models (DGVMs), Integrated BIosphere Simulator (IBIS) and (Lund Postdam and Jena (LPJ), have been used for this purpose. The DGVMs are driven by the ensemble mean climate projections from 5 climate models that contributed to the CMIP5 data base. While both DGVMs project vegetation shifts in the forest areas of the basins, there are large differences in vegetation shifts projected by IBIS and LPJ. This may be attributed to differing representation of land surface processes and to differences in the number of vegetation types (Plant Functional Types) defined and simulated in the two models. However, there is some agreement in NPP changes as projected by both IBIS and LPJ, with IBIS mostly projecting a larger increase in NPP for the future scenarios. Despite the uncertainties with respect to climate change projections at river basin level and the differing impact assessments from different DGVMs, it is necessary to assess the “vulnerability” of the forest ecosystems and forest dependent communities to current climate risks and future climate change and to develop and implement resilience or adaptation measures. Assessment of the “vulnerability” and designing of the adaptation strategies could be undertaken for all the forested grids where both IBIS and LPJ project vegetation shifts.展开更多
文摘NPP是森林生态系统物质循环过程的关键参数,是表征生态系统碳收支的重要指标,对了解植被生长生物量积累和大气CO_(2)吸收具有重要意义。采用中国科学院资源环境科学数据中心遥感监测的NPP数据,通过趋势分析、多元回归等方法,系统分析广东省国家级公益林NPP时空变化特征。结果表明,2004—2015年,NPP主要分布在400~800 g C/(m^(2)·a)区间内,所占比例超过70%;NPP在空间分布上较为离散,与高程联系紧密,东部地区及茂名市、阳江市的NPP相对较高;广东省国家级公益林的NPP呈波动增加趋势,年平均增加速率为4.9 g C/(m^(2)·a);不同年度NPP值总体处于较稳定状态,所占比例为99.25%,抗干扰能力强;广东省国家级公益林的NPP经异养呼吸后仍有60.6%保留在生态系统中,反映了国家级公益林良好的固碳能力,为我国“碳中和”目标贡献了林业力量。
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 Inventory 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 regression model based on least squares 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 increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. 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 NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration 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 regions. In addition to climatic 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.
文摘The impacts of climate change in terms of forest vegetation shifts and Net Primary Productivity (NPP) changes are assessed for Brahmaputra, Koshi and Indus river basins for the mid (2021-2050) and long (2071-2100) terms for RCP4.5 and RCP8.5 scenarios. Two Dynamical Global Vegetation Models (DGVMs), Integrated BIosphere Simulator (IBIS) and (Lund Postdam and Jena (LPJ), have been used for this purpose. The DGVMs are driven by the ensemble mean climate projections from 5 climate models that contributed to the CMIP5 data base. While both DGVMs project vegetation shifts in the forest areas of the basins, there are large differences in vegetation shifts projected by IBIS and LPJ. This may be attributed to differing representation of land surface processes and to differences in the number of vegetation types (Plant Functional Types) defined and simulated in the two models. However, there is some agreement in NPP changes as projected by both IBIS and LPJ, with IBIS mostly projecting a larger increase in NPP for the future scenarios. Despite the uncertainties with respect to climate change projections at river basin level and the differing impact assessments from different DGVMs, it is necessary to assess the “vulnerability” of the forest ecosystems and forest dependent communities to current climate risks and future climate change and to develop and implement resilience or adaptation measures. Assessment of the “vulnerability” and designing of the adaptation strategies could be undertaken for all the forested grids where both IBIS and LPJ project vegetation shifts.
基金This study was supported by the National Natural Science Foundation of China (Nos. 30028001 49905005)+1 种基金 National Key Basic Re-search Specific Foundation (G1999043407) the Chinese Acade
