中国陆地生态系统土壤有机碳变化研究进展

通过文献资料, 对中国陆地生态系统土壤有机碳变化研究进行评述. 20世纪80年代初至21世纪初, 中国森林、草地、灌丛和农田土壤有机碳库合计年均增加(71±19) Tg/a, 三江平原沼泽湿地垦殖导致土壤有机碳损失(6±2) Tg/a. 该结果存在极大的不确定性, 尤其是对森林、灌丛和草地碳库变化的估计. 未来研究需重点关注土地利用变化及其碳源、碳汇效应, 放牧管理对草地土壤有机碳库的影响, 灌丛和非森林树木(经济林、防护林及四旁绿化造林)土壤有机碳变化估算, 深层土壤有机碳变化的测定和估算, 中国土壤的固碳潜力及陆地生态系统碳收支模型开发.     

陆地生态系统类型转变与碳循环

 土地利用变化引起的陆地生态系统类型转变对于全球碳循环有着极其重要的作用。　通过总结国内外有关森林砍伐以及森林、草地转变成农田对于碳循环的影响,阐述了可能引起全球“未知汇”现象的重要原因,强调未来中国陆地生态系统碳循环研究应充分重视陆地生态系统类型转变对于全球碳循环的影响研究,包括研究陆地生态系统的不同发展阶段(自然与退化生态系统)、利用方式的改变(森林转化为人工林或农田,草地转化为农田、退耕还林草等)所引起的碳库类型转换的增汇机理及其对全球变化响应,并指出了建立统一观测方法与规范的陆地生态系统碳通量观测网     

辽宁中部城镇密集区土地利用变化的碳排放及低碳调控对策

土地利用变化引起的碳排放对全球气候变化有重要影响,调整区域的土地利用方式对适应全球气候变化具有重要的科学意义.本研究利用辽宁省碳排放/吸收参数,估算了辽宁中部城镇密集区土地利用变化的碳排放量.结果表明： 1997—2010年,碳排放量为308.51 Tg C,碳吸收量为11.64 Tg C,碳吸收量可抵消
3.8%的碳排放量.土地利用变化的净碳排放为296.87 Tg C,其中,保持用地类型不变的土地上净碳排放量是182.24 Tg C,对总排放量的贡献为61.4%;发生用地类型转换的土地上净碳排放量是114.63 Tg C,对总碳排放量的贡献为38.6%.通过量化土地利用变化和碳排放之间的映射关系可知,1997—2004年,保持建设用地不变（40.9%）和农田转为建设用地（40.6%）类型对碳源的贡献最大,农田转林地（38.6%）和保持林地不变（37.5%）类型对碳汇的贡献最大;2004—2010年,土地利用类型对碳源和碳汇的贡献类型与前一时段相同,但保持建设用地类型对碳源的贡献提高到80.6%,保持林地类型对碳汇的贡献提高到71.7%.基于不同景观变化类型的碳排放强度,我们从两方面提出低碳土地利用的调控对策：从碳减排方面,严格控制土地利用向建设用地转变,提高建设用地能源利用效率,避免对林地和水域过度开发利用;从碳增汇方面,增加森林覆盖率,实施农田、草地还林,加强对森林、水域的保护,调整农用地内部结构和科学实施农田管理.     

土地利用/覆盖变化对陆地生态系统碳循环的影响

土地利用/覆盖变化是学术界最为关注的环境变化问题之一,它能够影响陆地生态系统的生物多样性、水、碳和养分循环、能量平衡,引起温室气体释放增加等其它环境问题。不同类型的土地利用/覆盖变化对生态系统碳循环的作用不同,由高生物量的森林转化为低生物量的草地、农田或城市后,大量的CO₂将释放到大气中。全球土地利用/覆盖变化具有很强的空间变异性,对生态系统碳循环的影响同样具有明显的空间差异:热带地区的土地利用/覆盖变化造成大量的碳释放,而中高纬度地区土地利用/覆盖变化则表现为碳汇。目前,土地利用/覆盖变化引起的生态系统碳循环变化主要是通过模型模拟来估算的。尽管土地利用/覆盖变化及其相关过程与生态系统碳循环的关系已经比较清楚,但是,由于土地利用/覆盖变化过程复杂且影响广泛,对于如何量化两者之间的关系还存在很多不确定性。目前的量化过程主要是利用经验数据来实现的,机理性不强,使得对土地利用/覆盖变化造成的陆地生态系统CO₂释放量的估测差异很大。除了进一步加强长期定位研究以获得土地利用/覆盖变化与生态系统碳循环过程的定量关系外,土地利用/覆盖变化模型与植被动态模型、生态系统过程模型的耦合也是今后模型发展的主要方向之一。采用合理的管理措施能够大量增加土地利用/覆盖变化过程中的碳储存量,降低碳释放量,因此在模型中耦合管理措施来研究土地利用/覆盖变化过程对生态系统碳循环的影响是未来几年的工作重点。     

陆地生态系统碳源与碳汇及其影响机制研究进展

全球碳循环研究中发现,目前已知碳源与碳汇不能达到平衡。存在一个很大的碳失汇。大气、海洋和陆地生态系统是人工源CO2的3个可能的容纳汇,其中陆地生态系统最复杂、最具不确定性,因此陆地生态系统碳源与碳汇研究是全球碳循环研究的核心问题之一。大气成分监测、CO2通量测定、森林资源清查以及模型模拟等方面的研究都表明,CO2施肥效应、氮沉降增加、污染、全球气候变化以及土地利用变化,是影响陆地生态系统碳储量的主要生态机制,但不确定在过去的10～100年以及未来哪一种机制起最主要的作用。     

东亚地区碳循环研究新进展

近百年来,温室效应的日益加剧,引发了全球温暖化、海平面上升等一系列重大环境问题,碳循环研究因此而受到全球范围的普遍关注和重视.东亚地区因其独特的气候特征,多样化的物种和生态系统,以及活跃的人类活动而成为世界碳循环研究中不可或缺的一部分.在中、日、韩三国联合启动东亚碳循环前沿研究计划(A3 Foresight Program)三周年之际,《中国科学生命科学》(Science China Life Sciences)2010年第7期发表了东亚地区碳循环研究专题,包括14篇述评和研究论文,从区域碳储量及其变化特征,不同地带森林生态系统的碳源汇变化,草地和农田生态系统的碳储量和碳循环研究中的新方法等多个方面系统展示了东亚地区碳循环研究的最新进展.     

农田生态系统碳汇研究进展

农田生态系统碳汇包括农作物生物量碳汇和农田土壤碳汇两个方面，中国农田生态系统面积大，碳储量高，是全球生态系统碳循环的重要组成部分。厘清中国农作物生物量和土壤有机碳含量、变化率和影响因素对于解析全球碳循环和维系粮食安全具有重要意义。梳理农田生态系统碳汇相关概念的基础上，比较农田生态系统碳汇研究方法的适用性及存在问题，通过以往研究和SoilGrids250数据研究中国农田生态系统碳库时空分布，并分析农田生态系统碳汇的影响因素及固碳方法。结果表明，中国近30年来农作物生物量呈现增加趋势，农田土壤有机碳含量普遍较低且空间分布不均，0-5cm土壤有机碳含量平均值在16.7 g/kg到86.5 g/kg之间，增加农田土壤有机碳含量是未来中国农田生态系统碳汇的重要方向。肥料和有机残留管理、保护性耕作、种植模式、灌溉等管理措施是增加土壤有机碳汇的主要措施，但农田生态系统碳汇潜力估算仍存在不确定性。最后，从农田生态系统碳汇潜力估算、影响因素厘定和增汇技术研发3个方面提出未来研究方向。研究结果有助于推动农田生态系统碳汇科学研究和技术推广，为实现农田生态系统助力"碳中和"寻求重要路径。     

湿地碳循环过程与计算机模拟研究

湿地是地球4大陆地生态系统之一,全球湿地碳储量(450Pg C)约占陆地生态圈总碳量的20％。湿地系统因兼有“碳源”与“碳汇”的双重角色,其碳循环对大气全球碳收支以及与之有关的全球气候变化可能有重要影响。本文概述了湿地生态系统变化与碳排放的关系、湿地碳循环基本过程及其主要影响因子和湿地碳循环计算机模拟研究进展,提出了拟进一步研究的重要问题。     

森林碳计量方法研究进展

森林是陆地生态系统的主体,不仅是巨大的碳库而且对减缓气候变暖具有积极作用。科学有效的森林碳计量方法,有助于加深对全球碳循环过程的理解。然而,由于森林生态系统结构复杂,对森林碳计量的估算结果普遍存在精度低、不确定性高的问题。近年来,国内外发展了大量对森林碳计量进行估算的方法,主要有基于样地清查的森林植被和土壤碳估算、基于生长收获的经验模型估算、基于定量遥感雷达观测的遥感估测、基于多尺度森林生态系统网络的通量观测和陆地生态系统过程模型模拟等方法。在实际的森林碳计量中,根据不同的森林类型特征和数据获取情况,往往采取不同的碳计量方法,甚至不止一种。以生态过程模型模拟、遥感反演和数据同化技术为主要手段,基于碳通量观测数据、控制实验数据和遥感影像数据,发展多学科、多过程、多尺度的综合联网观测,充分认识森林碳循环过程中碳源/汇的时空分布特征,开展区域、洲际乃至全球尺度碳循环及其对全球变化和人类活动响应的系统性、集成性研究,以便建立高效、可靠的碳计量体系是未来林业碳计量的发展趋势。随着世界各国温室气体排放清单的编制,中国迫切需要科学的方法体系计量森林碳源/汇,提升我国在生态环境问题上的国际发言权和主导权,同时对我国森林可持续经营、生态环境保护以及美丽中国建设提供建议与支持。分析了各类森林碳计量方法的主要特征、优缺点,同时探讨了目前的森林碳计量方法存在的问题和未来的发展趋势,为不同时空尺度下森林碳计量提供参考。     

中国陆地生态系统碳源/汇整合分析

国家尺度陆地生态系统碳收支及其循环过程的研究对于提升地球系统科学与全球变化科学的科技创新能力、提高我国参与应对全球气候变化国际行动和维护国家利益的话语权、保障国家生态安全和改进生态系统管理都具有重要意义。近年来,我国已经在气候变化与陆地生态系统碳循环领域开展了大量的研究工作,主要包括国家清查、生态系统模型模拟、大气反演等手段。然而,由于大尺度陆地生态系统碳源/汇的估算存在很大的不确定性,目前尚未形成国家尺度的陆地生态系统碳源/汇的整合分析。通过搜集已发表的关于中国陆地生态系统及其组分碳源/汇的59篇文献,整合国家清查、生态系统模型模拟、大气反演3种研究手段,分析中国陆地生态系统碳源/汇大小以及时间尺度上的动态变化。结果表明,在1960s-2010s期间中国陆地生态系统碳汇整体呈上升趋势,平均为（0.213±0.030）Pg C/a,其中森林、草地、农田和灌木生态系统碳汇分别为（0.101±0.023）Pg C/a、（0.032±0.007）Pg C/a、（0.043±0.010）Pg C/a和（0.028±0.010）Pg C/a。森林生态系统中的植被碳汇远大于土壤碳汇,然而这种格局在草地和农田生态系统却相反,而且1960s-2010s期间中国主要植被类型的生态系统碳汇总体上随时间呈增加趋势。融合多源数据（地面观测、激光雷达、卫星遥感等）、多尺度数据（样地尺度、站点尺度、区域尺度）以及多手段数据（联网观测、森林清查、模型模拟）,有助于全面准确地评估中国陆地生态系统碳源/汇及其对气候变化的响应。     

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate‐change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process‐oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large‐scale remote‐sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate‐change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.     

土地利用转变与海拔高度协同作用黄土高原植被固碳变化特征

全球固碳释碳问题一直是近年来关乎民生的热点话题,区域碳源/碳汇对生态环境的重要性不言而喻。基于CASA模型估算黄土高原1990—2015年植被净初级生产力的年际变化,并分析土地利用变化、海拔高度及两者协同作用对其综合影响,结果表明：(1)黄土高原1990—2015年植被NPP与植被固碳总体呈增加趋势,年均NPP增速2.74 gC m^-2 a^-1,年均固碳增速1.13 TgC/a,研究区林地年均NPP(619.5 gC m^-2 a^-1)远超其他用地类型,固碳效果理想;(2)黄土高原年均NPP随高程的增加先降低后升高,年总NPP和固碳量随高程增加变化趋势相反;(3)研究区土地利用转变类型中退耕还林的植被固碳效果最好;而林地变为耕地或草地均不能达到固碳目的,此外,更推荐在研究区海拔低于1500 m变草为耕,海拔高于1500 m退耕还草,海拔高于3000 m变耕、草为林。以期为区域尺度的生态环境建设提供一定的参考和科学依据。     

Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO₂ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO₂ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr^?1 for CASA′ vs. 1.2 Pg C yr^?1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.     

基于InVEST模型估算富阳市森林生态系统碳储量

基于森林资源遥感影像数据资料和ArcGIS10.0软件,以属于典型亚热带气候的富阳市为案例,运用InVEST-Carbon模型对其森林生态系统碳储量进行估算,可视化定量富阳市森林生态系统碳储量并明确其空间分布规律。结果表明：富阳市森林生态系统碳储量分布具有明显的区域差异性,由东向西呈现高－低－高－低的分布带规律。富阳市森林生态系统总的碳储量为26.7437×106 t,其价值量为39.9042亿元;得出富阳市各类森林类型平均碳密度的高低分布为常绿阔叶林碳密度>针阔混交林碳密度>竹林碳密度>马尾松林碳密度>杉木林碳密度,这与浙江省生态公益林各主要林型的碳密度分布规律基本一致,得到其森林生态系统总的碳密度约为180.75 t.hm-2,高于浙江省生态公益林平均碳密度和全国森林平均碳密度。与基于森林二类清查资料,由生物量与蓄积量的关系式估算出的碳储量(28.3780×106 t)相差不大,InVEST模型可适用于森林生态系统碳储量的总体估算。通过研究可以得出,InVEST模型评估结果简明直观,导入较少的数据,将量化的森林碳储量以地图的形式表现出来。 InVEST模型还可用于对未来或多种模拟场景情况下的预测估算等,可为政府、非盈利组织和公司企业等自然资源的管理提供决策信息,其多功能和模块化的设计为权衡评估得失提供了有效的工具。     

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling

Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.     

Impact of tropical land‐use change on soil organic carbon stocks – a meta‐analysis

Land‐use changes are the second largest source of human‐induced greenhouse gas emission, mainly due to deforestation in the tropics and subtropics. CO₂ emissions result from biomass and soil organic carbon (SOC) losses and may be offset with afforestation programs. However, the effect of land‐use changes on SOC is poorly quantified due to insufficient data quality (only SOC concentrations and no SOC stocks, shallow sampling depth) and representativeness. In a global meta‐analysis, 385 studies on land‐use change in the tropics were explored to estimate the SOC stock changes for all major land‐use change types. The highest SOC losses were caused by conversion of primary forest into cropland (?25%) and perennial crops (?30%) but forest conversion into grassland also reduced SOC stocks by 12%. Secondary forests stored less SOC than primary forests (?9%) underlining the importance of primary forests for C stores. SOC losses are partly reversible if agricultural land is afforested (+29%) or under cropland fallow (+32%) and with cropland conversion into grassland (+26%). Data on soil bulk density are critical in order to estimate SOC stock changes because (i) the bulk density changes with land‐use and needs to be accounted for when calculating SOC stocks and (ii) soil sample mass has to be corrected for bulk density changes in order to compare land‐use types on the same basis of soil mass. Without soil mass correction, land‐use change effects would have been underestimated by 28%. Land‐use change impact on SOC was not restricted to the surface soil, but relative changes were equally high in the subsoil, stressing the importance of sufficiently deep sampling.     

Temporal response of soil organic carbon after grassland‐related land‐use change

The net flux of CO₂ exchanged with the atmosphere following grassland‐related land‐use change (LUC) depends on the subsequent temporal dynamics of soil organic carbon (SOC). Yet, the magnitude and timing of these dynamics are still unclear. We compiled a global data set of 836 paired‐sites to quantify temporal SOC changes after grassland‐related LUC. In order to discriminate between SOC losses from the initial ecosystem and gains from the secondary one, the post‐LUC time series of SOC data was combined with satellite‐based net primary production observations as a proxy of carbon input to the soil. Globally, land conversion from either cropland or forest into grassland leads to SOC accumulation; the reverse shows net SOC loss. The SOC response curves vary between different regions. Conversion of cropland to managed grassland results in more SOC accumulation than natural grassland recovery from abandoned cropland. We did not consider the biophysical variables (e.g., climate conditions and soil properties) when fitting the SOC turnover rate into the observation data but analyzed the relationships between the fitted turnover rate and these variables. The SOC turnover rate is significantly correlated with temperature and precipitation (p < 0.05), but not with the clay fraction of soils (p > 0.05). Comparing our results with predictions from bookkeeping models, we found that bookkeeping models overestimate by 56% of the long‐term (100 years horizon) cumulative SOC emissions for grassland‐related LUC types in tropical and temperate regions since 2000. We also tested the spatial representativeness of our data set and calculated SOC response curves using the representative subset of sites in each region. Our study provides new insight into the impact grassland‐related LUC on the global carbon budget and sheds light on the potential of grassland conservation for climate mitigation.     

六盘山林区几种土地利用方式下土壤活性有机碳的比较

 应用KMnO4氧化法测定分析了六盘山林区天然次生林（杂灌林、山杨（Populus davidanda）和辽东栎（Querces liaotungensis）林）、农田、草地和人工林（13、18和25年华北落叶松（Larix principis-rupprechtii））土壤活性有机碳含量及分配比例的差异。结果表明：农田和草地土壤活性有机碳含量比天然次生林分别低60%和36%,差异主要在0～70 cm土层;人工林比农田和草地分别高129%和29%,差异主要在0～50 cm土层。农田和草地土壤活性有机碳分配比例比天然次生林分别低11%和4%以上, 差异主要在0～20 cm与70～110 cm土层;人工林比农田和草地分别高13.3%和5.3%,差异主要在0～110 cm土层。土壤活性有机碳含量和分配比例随土层加深而递减,其中天然次生林和人工林土壤活性有机碳含量随土层加深而递减的幅度比农田和草地中大,农田土壤活性有机碳分配比例随土层加深而递减幅度较大。不同土地利用方式间土壤活性有机碳含量的差异比活性有机碳分配比例的差异大,土壤活性有机碳含量随土层加深而递减的幅度比分配比例随土层加深而递减的幅度大。这可能由土壤有机碳的输入、稳定性、质量和根系分布等差异所致。结果说明土壤活性有机碳含量和分配比例随天然次生林变成农田或草地而降低,随农田或草地中造林而增加,且土壤活性有机碳含量的变化幅度比分配比例大。另外,土壤活性有机碳含量和分配比例在土壤剖面的分布也随土地利用变化而改变,其中活性有机碳含量的变化幅度比分配比例大。