中国东北样带植被净初级生产力时空动态遥感模拟

 中国东北样带(Northeast China Transect, NECT)是中纬度半干旱区的国际地圈-生物圈计划(IGBP)陆地样带之一, 是全球变化研究的 重要手段与热点。该研究应用生态系统碳循环过程CASA(Carnegie-Ames-Stanford Approach)模型分析了NECT从1982~1999年植被净初级生产力 (Net primary productivity, NPP)的时空变异及其影响因子。结果表明, 1) 1982~1999年NECT植被NPP为58 ~ 811 g C·m^–2·a^–1, 平均为426 g C·m^–2·a^–1, 大体上呈现由东向西逐渐递减的趋势; 2)研究时段内NECT的总NPP变异范围是0.218 ~ 0.325 Pg C, 平均为0.270 Pg C (1 Pg = 10¹⁵ g); 3) NECT的总NPP在过去18年内整体呈显著性增加趋势, 其中从1982~1990年样带NPP呈显著性增加趋势, 而后期1991~1999样带NPP没 有显著性变化趋势; 4)沿NECT不同植被类型对气候变化的响应特征是不同的, 在研究时段内, 农田、典型草原和草甸草原表现出最大的NPP增加 量, 而典型草原、荒漠草原对气候变化表现出高的敏感性; 5) NECT植被NPP的空间分布格局是由年降水量的分布格局所决定, 而NPP的时间变异 则由年降水量、年太阳总辐射的变化所影响驱动。     

利用CASA模型估算我国植被净第一性生产力

基于地理信息系统和卫星遥感应用技术,利用CASA模型估算了我国1997年植被净第一性生产力及其分布。结果表明：1997年我国植被净第一性生产力为1．95PgC,约是世界陆地植被年净第一性生产力的4．0％;我国植被净第一性生产力的主要分布趋势是从东南沿海向西北逐渐减小,其中海南岛南部、云南西南部、青藏高原东南部的热带雨林和季雨林地区植被年净第一性生产力最大,达900gC.m^2.a^-1以上,而西部塔克拉玛干沙漠地区植被年净第一性生产力最小,不足10gC.m^-2.a^-1。     

Response of terrestrial carbon uptake to climate interannual variability in China

The interest in national terrestrial ecosystem carbon budgets has been increasing because the Kyoto Protocol has included some terrestrial carbon sinks in a legally binding framework for controlling greenhouse gases emissions. Accurate quantification of the terrestrial carbon sink must account the interannual variations associated with climate variability and change. This study used a process‐based biogeochemical model and a remote sensing‐based production efficiency model to estimate the variations in net primary production (NPP), soil heterotrophic respiration (HR), and net ecosystem production (NEP) caused by climate variability and atmospheric CO₂ increases in China during the period 1981–2000. The results show that China's terrestrial NPP varied between 2.86 and 3.37 Gt C yr^?1 with a growth rate of 0.32% year^?1 and HR varied between 2.89 and 3.21 Gt C yr^?1 with a growth rate of 0.40% year^?1 in the period 1981–1998. Whereas the increases in HR were related mainly to warming, the increases in NPP were attributed to increases in precipitation and atmospheric CO₂. Net ecosystem production (NEP) varied between ?0.32 and 0.25 Gt C yr^?1 with a mean value of 0.07 Gt C yr^?1, leading to carbon accumulation of 0.79 Gt in vegetation and 0.43 Gt in soils during the period. To the interannual variations in NEP changes in NPP contributed more than HR in arid northern China but less in moist southern China. NEP had no a statistically significant trend, but the mean annual NEP for the 1990s was lower than for the 1980s as the increases in NEP in southern China were offset by the decreases in northern China. These estimates indicate that China's terrestrial ecosystems were taking up carbon but the capacity was undermined by the ongoing climate change. The estimated NEP related to climate variation and atmospheric CO₂ increases may account for from 40 to 80% to the total terrestrial carbon sink in China.     

基于CASA模型的内蒙古典型草原植被净初级生产力动态模拟

 植被净初级生产力及其对气候变化的响应研究是全球变化的核心内容之一。在利用内蒙古典型草原连续13年的地上生物量资料对基于遥感信息的生态系统碳循环过程CASA(Carnegie-Ames-Stanford Approach)模型验证的基础上, 分析了内蒙古典型草原1982~2002年植被净初级生产力(Net primary productivity, NPP)的时间变异及其影响因子。结果表明: 1) 1982~2002年21年间内蒙古典型草原的平均年NPP为290.23 g C·m^–2·a^–1, 变化范围为 145.80~502.84 g C·m^–2·a^–1; 2)内蒙古典型草原NPP呈增加趋势, 但没有达到显著性水平, 其中1982~1999年的18年间NPP呈现非常显著的增加趋势(p<0.01), NPP增加的直接原因是由于生长旺季生长本身增强所致; 3)内蒙古典型草原NPP与年降水量呈极显著的相关关系, 年降水量显著影响NPP的变异, 而NPP与年均温无显著相关关系。     

Assessing the Spatiotemporal Variation in Distribution,Extent and NPP of Terrestrial Ecosystems in Response to Climate Change from 1911 to 2000

To assess the variation in distribution, extent, and NPP of global natural vegetation in response to climate change in the period 1911–2000 and to provide a feasible method for climate change research in regions where historical data is difficult to obtain. In this research, variations in spatiotemporal distributions of global potential natural vegetation (PNV) from 1911 to 2000 were analyzed with the comprehensive sequential classification system (CSCS) and net primary production (NPP) of different ecosystems was evaluated with the synthetic model to determine the effect of climate change on the terrestrial ecosystems. The results showed that consistently rising global temperature and altered precipitation patterns had exerted strong influence on spatiotemporal distribution and productivities of terrestrial ecosystems, especially in the mid/high latitudes. Ecosystems in temperate zones expanded and desert area decreased as a consequence of climate variations. The vegetation that decreased the most was cold desert (18.79%), while the maximum increase (10.31%) was recorded in savanna. Additionally, the area of tundra and alpine steppe reduced significantly (5.43%) and were forced northward due to significant ascending temperature in the northern hemisphere. The global terrestrial ecosystems productivities increased by 2.09%, most of which was attributed to savanna (6.04%), tropical forest (0.99%), and temperate forest (5.49%). Most NPP losses were found in cold desert (27.33%). NPP increases displayed a latitudinal distribution. The NPP of tropical zones amounted to more than a half of total NPP, with an estimated increase of 1.32%. The increase in northern temperate zone was the second highest with 3.55%. Global NPP showed a significant positive correlation with mean annual precipitation in comparison with mean annual temperature and biological temperature. In general, effects of climate change on terrestrial ecosystems were deep and profound in 1911–2000, especially in the latter half of the period.     

中国陆地植被净初级生产力遥感估算

该文在综合分析已有光能利用率模型的基础上,构建了一个净初级生产力(NPP)遥感估算模型,该模型体现了3方面的特色:1)将植被覆盖分类引入模型,并考虑植被覆盖分类精度对NPP估算的影响,由它们共同决定不同植被覆盖类型的归一化植被指数(NDVI)最大值;2)根据误差最小的原则,利用中国的NPP实测数据,模拟出各植被类型的最大光能利用率,使之更符合中国的实际情况;3)根据区域蒸散模型来模拟水分胁迫因子,与土壤水分子模型相比,这在一定程度上对有关参数实行了简化,使其实际的可操作性得到加强。模拟结果表明,1989~1993年中国陆地植被NPP平均值为3.12 Pg C (1 Pg=10¹⁵ g),NPP模拟值与观测值比较接近,690个实测点的平均相对误差为4.5%;进一步与其它模型模拟结果以及前人研究结果的比较表明,该文所构建的NPP遥感估算模型具有一定的可靠性,说明在区域及全球尺度上,利用地理信息系统技术将遥感数据和各种观测数据集成在一起,并对NPP模型进行参数校正,基本上可以实现全球范围不同生态系统NPP的动态监测。     

Remotely Sensed Interannual Variations and Trends in Terrestrial Net Primary Productivity 1981–2000

Spatial and temporal variations in net primary production (NPP) are of great importance to ecological studies, natural resource management, and terrestrial carbon sink estimates. However, most of the existing estimates of interannual variation in NPP at regional and global scales were made at coarse resolutions with climate-driven process models. In this study, we quantified global NPP variation at an 8 km and 10-day resolution from 1981 to 2000 based on satellite observations. The high resolution was achieved using the GLObal Production Efficiency Model (GLO-PEM), which was driven with variables derived almost entirely from satellite remote sensing. The results show that there was an increasing trend toward enhanced terrestrial NPP that was superimposed on high seasonal and interannual variations associated with climate variability and that the increase was occurring in both northern and tropical latitudes. NPP generally decreased in El Niño season and increased in La Niña seasons, but the magnitude and spatial pattern of the response varied widely between individual events. Our estimates also indicate that the increases in NPP during the period were caused mainly by increases in atmospheric carbon dioxide and precipitation. The enhancement of NPP by warming was limited to northern high latitudes (above 50°N); in other regions, the interannual variations in NPP were correlated negatively with temperature and positively with precipitation.     

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux‐tower‐based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO₂ trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO₂ sensitivity of NPP is compared to the results from four Free‐Air CO₂ Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr^?1) than JU11 (118 ± 6 Pg C yr^?1). In response to rising atmospheric CO₂ concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO₂ than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr^?1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr^?1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is ?3.0 ± 1.5 Pg C yr^?1 °C^?1, within the uncertainty of what derived from RLS (?3.9 ± 1.1 Pg C yr^?1 °C^?1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO₂ and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO₂ concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.     

Carbon emissions from fires in tropical and subtropical ecosystems

Global carbon emissions from fires are difficult to quantify and have the potential to influence interannual variability and long‐term trends in atmospheric CO₂ concentrations. We used 4 years of Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) satellite data and a biogeochemical model to assess spatial and temporal variability of carbon emissions from tropical fires. The TRMM satellite data extended between 38°N and 38°S and covered the period from 1998 to 2001. A relationship between TRMM fire counts and burned area was derived using estimates of burned area from other satellite fire products in Africa and Australia and reported burned areas from the United States. We modified the Carnegie‐Ames‐Stanford‐Approach (CASA) biogeochemical model to account for both direct combustion losses and the decomposition from fire‐induced mortality, using both TRMM and Sea‐viewing Wide Field of view Sensor (SeaWiFS) satellite data as model drivers. Over the 1998–2001 period, we estimated that the sum of carbon emissions from tropical fires and fuel wood use was 2.6 Pg C yr^?1. An additional flux of 1.2 Pg C yr^?1 was released indirectly, as a result of decomposition of vegetation killed by fire but not combusted. The sum of direct and indirect carbon losses from fires represented 9% of tropical and subtropical net primary production (NPP). We found that including fire processes in the tropics substantially alters the seasonal cycle of net biome production by shifting carbon losses to months with low soil moisture and low rates of soil microbial respiration. Consequently, accounting for fires increases growing season net flux by ～12% between 38°N and 38°S, with the greatest effect occurring in highly productive savanna regions.     

Spatial and temporal variability in the net primary production of grassland in China and its relation to climate factors

As an important component of the terrestrial carbon (C) cycle, variability in net primary productivity (NPP) plays a crucial role in the C input and accumulation in grasslands system. In this study, the spatial and temporal variability of grassland NPP in China during 2001–2010 and its relation to climate factors were analyzed by using a modified model of Carnegie–Ames–Stanford Approach based on the Comprehensive and Sequential Classification System. The results show that monthly grassland NPP increases from January to July. While the seasonal variability of NPP indicates peak productivity in summer. Annual mean grassland NPP follows a significant increasing trend with fluctuation from 2001 to 2010. The spatial pattern of grassland NPP shows increasing gradients from the west to the east and from the north to the south of China. Annual NPP differs significantly among different grassland types, with the highest NPP in the grassland distributed in sub-tropical perhumid evergreen broad leaved forest and tropical-perhumid rain forest. Time-lag correlation analysis at the monthly scale shows that grassland NPP responded more rapidly to changes in temperature than to precipitation. Among the climate factors, grassland NPP shows the strongest correlation at 1-month lag with moisture index K. There is a significant positive correlation between seasonal NPP and K. The seasonal NPP is significantly correlated with >0 °C annual cumulative temperature. The highest and the lowest NPP sensitivity to precipitation, K, and temperature were observed in the grassland distributed in tropical forest and semi-desert. The results indicate a complex mechanism of climate factors that control grassland C sequestration in terrestrial ecosystems.     

A historical meta‐analysis of global terrestrial net primary productivity: are estimates converging?

Net primary productivity (NPP) is one of the most important ecosystem parameters, representing vegetation activity, biogeochemical cycling, and ecosystem services. To assess how well the scientific community understands the biospheric function, a historical meta‐analysis was conducted. By surveying the literature from 1862 to 2011, I extracted 251 estimates of total terrestrial NPP at the present time (NPP_T) and calculated their statistical metrics. For all the data, the mean±standard deviation and median were 56.2±14.3 and 56.4 Pg C yr^–1, respectively. Even for estimates published after 2000, a substantial level of uncertainty (coefficient of variation by ±15%) was inevitable. The estimates were categorized on the basis of methodology (i.e., inventory analysis, empirical model, biogeochemical model, dynamic global vegetation model, and remote sensing) to examine the consistency among the statistical metrics of each category. Chronological analysis revealed that the present NPP_T estimates were directed by extensive field surveys in the 1960s and 1970s (e.g., the International Biological Programme). A wide range of uncertainty remains in modern estimates based on advanced biogeochemical and dynamic vegetation models and remote‐sensing techniques. Several critical factors accounting for the estimation uncertainty are discussed. Ancillary analyses were performed to derive additional ecological and human‐related parameters related to NPP. For example, interannual variability, carbon‐use efficiency (a ratio of NPP to gross photosynthesis), human appropriation, and preindustrial NPP_T were assessed. Finally, I discuss the importance of improving NPP_T estimates in the context of current global change studies and integrated carbon cycle research.     

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.     

Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change

Evaluating the role of terrestrial ecosystems in the global carbon cycle requires a detailed understanding of carbon exchange between vegetation, soil, and the atmosphere. Global climatic change may modify the net carbon balance of terrestrial ecosystems, causing feedbacks on atmospheric CO₂ and climate. We describe a model for investigating terrestrial carbon exchange and its response to climatic variation based on the processes of plant photosynthesis, carbon allocation, litter production, and soil organic carbon decomposition. The model is used to produce geographical patterns of net primary production (NPP), carbon stocks in vegetation and soils, and the seasonal variations in net ecosystem production (NEP) under both contemporary and future climates. For contemporary climate, the estimated global NPP is 57.0 Gt C y^–1, carbon stocks in vegetation and soils are 640 Gt C and 1358 Gt C, respectively, and NEP varies from –0.5 Gt C in October to 1.6 Gt C in July. For a doubled atmospheric CO₂ concentration and the corresponding climate, we predict that global NPP will rise to 69.6 Gt C y^–1, carbon stocks in vegetation and soils will increase by, respectively, 133 Gt C and 160 Gt C, and the seasonal amplitude of NEP will increase by 76%. A doubling of atmospheric CO₂ without climate change may enhance NPP by 25% and result in a substantial increase in carbon stocks in vegetation and soils. Climate change without CO₂ elevation will reduce the global NPP and soil carbon stocks, but leads to an increase in vegetation carbon because of a forest extension and NPP enhancement in the north. By combining the effects of CO₂ doubling, climate change, and the consequent redistribution of vegetation, we predict a strong enhancement in NPP and carbon stocks of terrestrial ecosystems. This study simulates the possible variation in the carbon exchange at equilibrium state. We anticipate to investigate the dynamic responses in the carbon exchange to atmospheric CO₂ elevation and climate change in the past and future.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

As above,not so below: Long-term dynamics of net primary production across a dryland transition zone

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long-term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland–shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one-time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long-term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.     

我国不同季节陆地植被NPP对气候变化的响应

阐明不同季节陆地植被净第一性生产力（NPP）对全球变化的响应将有助于理解陆地生态系统和气候系统之间的相互作用以及NPP变化机制。本文使用1982－1999年间的AVHRR／NDVI、气温、降水以及太阳辐射等资料,结合植被分布图和土壤质地图,利用生态过程模型,研究不同季节我国陆地植被NPP的年际变化及其地理分异。结果表明,在1982－1999年的18年间,4个季节的NPP都呈显著增加趋势。其中,春季是NPP增加速率最快的季节,夏季是NPP增加量最大的季节,不同植被类型对全球变化的响应有很大差异。常绿阔叶林,常绿针叶林和落叶针叶林NPP的增加主要由生长季节的提前所致。而落叶阔叶林、针阔混交林、矮林灌丛,温带草原及草甸,稀树草原、高寒植被,荒漠以及人工植被NPP的增加主要来自生长季生长加速的贡献。从区域分布看,在四季中春季NPP增加量最大的地区主要集中在东部季风区域;夏季NPP增量最大的地区包括西北干旱区域和青藏高原的大部分地区,小兴安岭－长白山区,三江平原,松辽平原,四川盆地,雷州半岛,长江中下游部分地区以及江南山地东部;而秋季植被NPP增加量最大的地区主要有云南高原－西藏东部和呼伦湖的周围等地区。不同植被和地理区域NPP的这些响应方式与区域气候特征及其变化趋势有关。     

大气CO2升高及气候变化对中国陆地生态系统结构与功能的制约和影响（英文）

在本顶研究中,我们探讨了大气CO2加倍和气候变化条件下,中国陆地生态系统的结构与功能的变化。与多数研究不同的是,我们耦合了两个以地理空间为参照的生态系统模型,即生物地理模型（KBIOME）和生物地球化学模型（TEM）,用此研究现状和未来的环境下,中国的植被分布和年净初级生产力（NPP）的状况,我们采用3个大气环流模型,（GFDL－Q,GISS和OSU）预测的结果代表潜在气候变化。3个气候模型的预测都煌中国将变得更温暖并总体上更湿润。耦合的模型预测中国陆地生态系统的结构与功能都将产生十分显著的变化。植被的变迁表现为：1）中国东部森林带北移,温带常绿阔叶林面积扩大,较南的森林取代较北的类型;2）森林和草地的总面积增加,这是作为取代干旱藻木林、沙漠和高山苔原的结果。年净初级生产力在大气CO2加倍和气候变化条件下,增加30％左右,与其它研究不同的另一点是,我们可能进一步区分生产力变化的原因,在所增加的生产力中,12％－21％是源于生态系统的取代较低产的生态系统的结果。这项研究预测了未来中国植被和生产力潜在的变化并给出了变化的范围,为同类的研究以及有关的政策评估提供了有用的参考信息。     

中国西北地区植被NPP多时间尺度变化及其对气候变化的响应

净初级生产力(NPP)是评估植被生长的重要参数,也是评价区域生态环境质量的重要指标。以"一带一路"枢纽地区西北六省为研究区,基于多年连续的GIMMS NDVI资料和气象数据,利用CASA模型,估算了西北六省34年NPP值,利用MK和EEMD方法,揭示了NPP变化的非线性特征,并探究不同时间尺度植被NPP变化对气候变化的响应。研究结果发现:(1)1982—2015年生长季植被NPP总体呈增加趋势,线性增长率为0.718 gCm~(-2) a~(-1);大多数研究区植被NPP短时间内将保持现有变化趋势,尤其是青藏高原、塔里木盆地边缘和内蒙古南部一带。(2)1982—2015年植被NPP以3年周期变化和长期增加趋势为主。其中陕西的南部,甘肃、新疆、宁夏和青海的北部以及内蒙古中部和北部以3年周期变化为主导,而陕西的北部,甘肃、新疆、宁夏的南部以及内蒙古东部以长期变化为主。不同植被类型NPP变化差异明显:针叶林、阔叶林以及混交林以3年周期波动为主,而灌木、草地和农田以3年周期波动和长期增长趋势为主。(3)NPP与气温和降水之间的相关性随着时间尺度的增大逐渐显著。在3年时间尺度上,大多数研究区NPP与气温和降水的相关性很小(P0.05)。6年时间尺度上,NPP与降水量呈正相关的区域向南略有扩散,其中青海南部高寒草甸NPP与降水的相关性由负相关转为正相关。在长期趋势上,NPP与气温和降水量具有非常显著的相关关系,且呈正相关的区域大于负相关的区域。本研究发现多时间尺度能够更好的分析NPP时空特征以及不同时间尺度NPP对气候变化的响应,有助于揭示全球气候变化背景下植被NPP对气候变化的非线性响应机制,评价气候变化的生态坏境风险,为西北六省区域可持续发展和生态环境保护提供理论依据。     

Is carbon within the global terrestrial biosphere becoming more oxidized? Implications for trends in atmospheric O2

Measurements of atmospheric O₂ and CO₂ concentrations serve as a widely used means to partition global land and ocean carbon sinks. Interpretation of these measurements has assumed that the terrestrial biosphere contributes to changing O₂ levels by either expanding or contracting in size, and thus serving as either a carbon sink or source (and conversely as either an oxygen source or sink). Here, we show how changes in atmospheric O₂ can also occur if carbon within the terrestrial biosphere becomes more reduced or more oxidized, even with a constant carbon pool. At a global scale, we hypothesize that increasing levels of disturbance within many biomes has favored plant functional types with lower oxidative ratios and that this has caused carbon within the terrestrial biosphere to become increasingly more oxidized over a period of decades. Accounting for this mechanism in the global atmospheric O₂ budget may require a small increase in the size of the land carbon sink. In a scenario based on the Carnegie–Ames–Stanford Approach model, a cumulative decrease in the oxidative ratio of net primary production (NPP) (moles of O₂ produced per mole of CO₂ fixed in NPP) by 0.01 over a period of 100 years would create an O₂ disequilibrium of 0.0017 and require an increased land carbon sink of 0.1 Pg C yr⁻¹ to balance global atmospheric O₂ and CO₂ budgets. At present, however, it is challenging to directly measure the oxidative ratio of terrestrial ecosystem exchange and even more difficult to detect a disequilibrium caused by a changing oxidative ratio of NPP. Information on plant and soil chemical composition complement gas exchange approaches for measuring the oxidative ratio, particularly for understanding how this quantity may respond to various global change processes over annual to decadal timescales.     

Estimation of Net Primary Productivity of Terrestrial Vegetation in China by Remote Sensing (in English)

Among the many approaches for studying the net primary productivity ( NPP ), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and thermal infrared band) of NOAA-AVHRR, we can get the relative index and parameters, which can be used for estimating NPP of terrestrial vegetation. By means of remote sensing, the estimation of biomass and NPP is mainly based on the models of light energy utilization. In other words, the biomass and NPP can be calculated from the relation among NPP , absorbed photosynthetical active radiation (APAR) and the rate (ε) of transformation of APAR to organic matter, thus：NPP=(FPAR×PAR)×［ε*×σT×σE×σS×(1-Ym)×（1-Yg）］ . Based upon remote sensing (RS) and geographic information system (GIS), the NPP of terrestrial vegetation in China in every ten days was calculated, and the annual NPP was integrated. The result showed that the total NPP of terrestrial vegetation in China was 6.13×109 t C·a-1in 1990 and the maximum NPP was 1 812.9 g C/m. According to this result, the spatio-temporal distribution of NPP was analyzed. Comparing to the statistical models, the RS model, using area object other than point one, can better reflect the distribution of NPP , and match the geographic distribution of vegetation in China.