Accurately estimating forest net primary productivity (NPP) plays an important role in study of global carbon budget. A NPP model reflecting the synthetic effects of both biotic (forest stand age, A and stem volume, V...Accurately estimating forest net primary productivity (NPP) plays an important role in study of global carbon budget. A NPP model reflecting the synthetic effects of both biotic (forest stand age, A and stem volume, V) and climatic factors (mean annual actual evapotranspiration, E) was developed for Chinese pine (Pinus tabulaeformis) forest by making full use of Forest Inventory Data (FID) and dynamically assessing forest productivity. The NPP of Chinese pine forest was estimated by using this model and the fourth FID (1989–1993), and the spatial pattern of NPP of Chinese pine forest was given by Geography Information System (GIS) software. The results indicated that mean NPP value, of Chinese pine forest was 7.82 t m?2·a?1 and varied at the range of 3.32–11.87 t hm?2·a?1. NPP distribution of Chinese pine forests was significantly different in different regions, higher in the south and lower in the north of China. In terms of the main distribution regions of Chinese pine, the NPPs of Chinese pine forest in Shanxi and Shaanxi provinces were in middle level, with an average NPP of 7.4 t hm?2·a?1, that in the southern and the eastern parts (e.g. Shichuang Hunan, Henan, and Liaoning provinces) was higher (over 7.7 t hm?2·a?1), and that in the northern part and western part (e.g. Neimenggu and Ningxia provinces) was lower (below 5 t hm?2·a?1). This study provides an efficient way for using FID to understand the dynamics of foest NPP and evaluate its effects on global climate change. Keywords Forest NPP - Forest inventory data - Chinese pine forest - Climatic and biotic NPP model - Spatial distribution pattern CLC number S727.22 - S757.2 Document code A Foundation item: This study was supported by the National Natural Science Foundation of China (Nos. 30028001, 49905005), National Key Basic Research Specific Foundation (G1999043407); the Chinese Academy of Sciences (KSC2-1-07).Biography: ZHAO Min (1973-), female, Ph. D. in Laboratory of Quantitative Vegetation Ecology, Institute of Botany, the Chinese Academy of Sciences, Beijing 100093, P. R. China.Responsible editor: Zhu Hong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
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
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
文摘Accurately estimating forest net primary productivity (NPP) plays an important role in study of global carbon budget. A NPP model reflecting the synthetic effects of both biotic (forest stand age, A and stem volume, V) and climatic factors (mean annual actual evapotranspiration, E) was developed for Chinese pine (Pinus tabulaeformis) forest by making full use of Forest Inventory Data (FID) and dynamically assessing forest productivity. The NPP of Chinese pine forest was estimated by using this model and the fourth FID (1989–1993), and the spatial pattern of NPP of Chinese pine forest was given by Geography Information System (GIS) software. The results indicated that mean NPP value, of Chinese pine forest was 7.82 t m?2·a?1 and varied at the range of 3.32–11.87 t hm?2·a?1. NPP distribution of Chinese pine forests was significantly different in different regions, higher in the south and lower in the north of China. In terms of the main distribution regions of Chinese pine, the NPPs of Chinese pine forest in Shanxi and Shaanxi provinces were in middle level, with an average NPP of 7.4 t hm?2·a?1, that in the southern and the eastern parts (e.g. Shichuang Hunan, Henan, and Liaoning provinces) was higher (over 7.7 t hm?2·a?1), and that in the northern part and western part (e.g. Neimenggu and Ningxia provinces) was lower (below 5 t hm?2·a?1). This study provides an efficient way for using FID to understand the dynamics of foest NPP and evaluate its effects on global climate change. Keywords Forest NPP - Forest inventory data - Chinese pine forest - Climatic and biotic NPP model - Spatial distribution pattern CLC number S727.22 - S757.2 Document code A Foundation item: This study was supported by the National Natural Science Foundation of China (Nos. 30028001, 49905005), National Key Basic Research Specific Foundation (G1999043407); the Chinese Academy of Sciences (KSC2-1-07).Biography: ZHAO Min (1973-), female, Ph. D. in Laboratory of Quantitative Vegetation Ecology, Institute of Botany, the Chinese Academy of Sciences, Beijing 100093, P. R. China.Responsible editor: Zhu Hong
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.
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。
