动态植被模型模拟的植被季节变化及其评估

利用MODIS卫星观测资料,对一个考虑了生态系统碳氮循环过程的动态植被模型ICM的模拟性能进行了评估.重点对反映植被动力学的关键参数--叶面积指数(LAI)的模拟结果与观测进行了对比分析,评估了ICM对LAI季节变化特征的模拟能力.结果表明,ICM基本能够模拟出植被的季节变化特征.总体而言,模拟值在低纬度和高纬度地区大...     

全球植被年际尺度动态过程的数值模拟及其评估

动态植被模型（Interactive Canopy Model,ICM）中考虑了生态系统碳氮循环过程,能够描述较短时间尺度上的植被与大气之间相互作用过程。利用21 a的GIMMS卫星观测LAI资料,与ICM模拟结果进行年际变率对比分析,评估模型对植被年际变化的模拟性能。结果表明,ICM能在一定程度上反映植被年际变率的空间分布特征,但模拟的热带部分地区植被的年际变率偏小,除此之外大部分地区模拟的年际变率偏大;模拟能够反映出全球植被年际变化的主要空间分布型,同时低纬度地区植被的时间演变特征要好于高纬度地区;ICM对寒带灌丛、北非稀树大草原、落叶针叶林的年际变化模拟较好,但对中国东部农作物的模拟表现出了明显的周期振荡现象,与实际情况差距较大。     

棉花阴、阳叶的气孔导度和光合作用观测对比及模型应用

以实验观测数据为基础,对棉花阳叶和阴叶光合速率、气孔导度的变化进行比较,通过双叶模型和大叶模型对冠层光合作用进行对比分析,结果表明,大叶模型的计算结果普遍高于双叶模型,总体高出13％。由此可见,过去在研究植被一大气碳交换中使用大叶模型估算植物光合作用会夸大碳汇的作用。     

干旱和复水对羊草碳氮分配的影响

植物的碳氮营养及其相互关系是最重要的基本生物过程之一,阶段性干旱对植物碳氮分配的影响研究甚少。实验以中国北方草原的典型植物羊草为材料,研究不同干旱持续期复水对羊草碳氮含量、分配及其相互关系的影响。结果表明:短期和中期干旱使植株生物量、氮素水平和单株总氮量增加,但长期干旱使之降低。水分处理对碳含量的影响不显著。干旱后复水降低了各器官特别是绿叶的碳氮比。中度持续干旱的氮素利用率(NUE)最高、短期干旱最低。羊草各器官氮素绝对量占整株的百分比从大到小依次为:绿叶、根茎、根、枯叶和茎鞘,其中叶片的氮素总量占植株的一半以上;随着干旱持续期的增加,氮素对根部的投资亦加大。羊草受到适当干旱驯化后复水引发的超补偿作用可促进羊草植株生长、提高氮素水平,并在一定程度上通过碳氮分配的调节作用来适应于阶段性的干旱胁迫。     

动态植被模型对青藏高原植被的模拟检验

动态植被模型是研究植被变化对气候反馈和影响的重要模型工具。本文对耦合了动态植被（Dynamic Vegetation, DV）和碳氮（Carbon and Nitrogen, CN）模型的NCAR陆面过程模式CLM4.5(Community Land Model version 4.5)对青藏高原（以下简称高原）植被的模拟性能进行了评估,获得了定量化的偏差信息,并对高原植被和气候变化因子的关系进行了初步探讨。结果表明：模型能大致再现叶面积指数（Leaf area index, LAI）在历史时期的季节循环、长期变化趋势和空间分布,但空间变率较遥感资料大。模拟的乔木覆盖度偏大,草地覆盖度偏小,因此严重高估了植被高原南部和东部的LAI。与遥感观测相比,模拟的LAI呈现了1～2个月的滞后,这与模式本身的植被动力机制不完善和模式的降水驱动偏差有关。高原植被变化趋势的时空分布与表层土壤水和降水等气象因子的趋势变化显示出较好的一致性,表明在该研究时段,地表水循环的变化（主要是降水和土壤水含量）对高原植被生长可能起主导作用。     

植被动力学模式中物候方案的研究进展

植物物候是指植物生长过程中呈现出的季节性现象,一般与植物所处的气候与环境变化密切相关。植被动力学模式研究的物候主要表现为叶面积指数变化,直接影响陆气间的碳通量与水热交换,同时影响物种间的竞争,从而间接地影响生态系统的结构组成。按照建模方法的差别,目前模式中使用的物候方案可分为使用卫星观测资料的物候方案、基于物候——气候关系的统计模型和基于叶碳平衡(周转)的动力学模型三大类。将植物物候分为物候期的触发和物候期叶片的发育过程两部分,分别对国际上广泛使用的八种全球植被动力学模式进行分类描述,对比其优缺点。最后探讨了植被动力学模式中物候方案的进一步发展方向。     

陆地生态系统与全球变化相互作用的研究进展

全球变化及其对生态系统特别是陆地生态系统的影响已经严重地影响到人类生存环境与社会经济的可持续发展 ,引起了各国政府、科学家及公众的高度关注。文中从CO2 浓度倍增、温度变化、水分变化、水热与CO2 协同作用、辐射变化、臭氧变化以及人为干扰等气候环境变化对植物光合生理、生长发育、物质分配、水分利用、碳氮代谢等的影响方面阐述了全球变化影响生态系统的过程与机理 ;从地理分布范围、物候、结构与功能、生态系统的稳定性等方面分析了中国植被、森林生态系统、草原生态系统与农田生态系统对全球变化的响应 ;从植被变化引起的动力条件与热力条件的变化及植被固碳潜力的变化探讨了植被对于气候的反馈作用。在此基础上 ,基于当前全球变化研究前沿 ,提出了未来关于陆地生态系统与全球变化相互作用研究需要重视的方面 ,尤其是关于生态系统对全球变化响应的阈值研究应引起高度重视。     

紫金山不同海拔高度土壤的碳氮分布特征

有机碳氮是影响陆地生态系统的重要因子,保持并提高土壤碳氮储量,是稳定生态系统生产力的关键.以南京紫金山土壤为研究对象,依照海拔高度进行采样,对比分析了土壤有机碳氮的变化规律.研究结果表明:紫金山土壤有机碳氮受地表植被的影响比较大,混交林>林地>草地,土壤有机碳氮总量随海拔的升高呈现上升趋势,土壤碳氮比高达34~45,且随海拔升高呈下降趋势.相关分析表明,紫金山土壤有机碳与全氮质量分数呈显著正相关关系,由此说明氮素主要以有机氮的形式存在于有机质中.     

陆面模式中氮循环过程的引入Ⅰ:模式介绍及站点验证（英文）

陆地生态系统氮循环对碳循环过程及其对气候变化的反馈具有重要的影响,但当前陆面模式多数都没有考虑氮循环过程对碳循环过程的限制。本研究基于氮在土壤-植被-大气中的传输交换过程,将氮循环过程引入到陆面模式AVIM(Atmosphere-Vegetation Interaction Model)中,发展形成包含碳氮耦合过程的新版模式AVIM-CN。与2004-05年当雄生态系统定位站通量观测数据相对比,模式中引入氮循环过程后,高寒草甸的总初级生产力模拟值从1.1403 gC m^-2d^-1降到了0.7073 gC m^-2d^-1,前者更接近通量站的观测值0.5407 gC m^-2d^-1。生态系统呼吸的模拟值也从1.7695 gC m^-2d^-1降到了1.0572 gC m^-2d^-1,更接近对应的通量观测值0.8034 gC m^-2d^-1。整体而言,在模式中考虑氮的限制作用后,当雄站的热量通量和碳通量的模拟值更接近实测值。不考虑氮过程对碳过程的限制,模式高估了约40%的陆地生态系统碳通量。     

陆面模式的植物叶光合生理的数值模拟试验及分析

根据C3、C4植物生态生理过程中植物叶水平的光合同化机制过程和植物叶片尺度的光合作用限制函数方程。采用单叶光合作用模式进行C3、C4植物光合模拟试验,模拟不同环境影响因子对C3、C4植物光合作用的影响。结果表明,植物叶尺度光合作用模型能较好地模拟不同环境影响因子下的C3、C4植物光合作用状况。本文依据C3、C4植物光合生理特性进一步分析植物光合作用的三个限制函数方程在C3、C4植物光合的不同作用,揭示吸收光合有效辐射(PAR)、叶内温度(Tc)和CO2浓度(Ci)的敏感性。结果可用于植被—大气相互作用的能量和碳同化过程的物质交换研究。     

Climate and Vegetation Drivers of Terrestrial Carbon Fluxes:A Global Data Synthesis

The terrestrial carbon(C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity(GPP), ecosystem respiration(ER), net ecosystem productivity(NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers.The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature(MAT)for all biomes. Besides MAT, annual precipitation(AP) had a strong correlation with GPP(or ER) for non-wetland biomes.Maximum leaf area index(LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53%of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem–atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation(e.g.,LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions.     

An Updated Coupled Model for Land-Atmosphere Interaction. Part II： Simulations of Biological Processes

In Part I, the authors succeeded in coupling the spectral atmospheric model （SAMIL_R42L9） developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences （LASG/IAP/CAS） with the land surface model, Atmosphere-Vegetation-Interaction-Model （AVIM） and analyzed the climate basic state and land surface physical fluxes simulated by R42_AVIM. In this Part Ⅱ, we further evaluate the simulated results of the biological processes, including leaf area index （LAI）, biomass and net primary productivity （NPP） etc. Results indicate that R42_AVIM can simulate the global distribution of LAI and has good consistency with the monthly mean LAI provided by Max Planck Institute for Meteorology. The simulated biomass corresponds reasonably to the vegetation classifications. In addition, the simulated annual mean NPP has a consistent distribution with the data provided by IGBP and MODIS, and compares well with the work in literature. This land-atmosphere coupled model will offer a new experiment tool for the research on the two-way interaction between climate and biosphere, and the global terrestrial ecosystem carbon cycle.     

An Updated Coupled Model for Land-Atmosphere Interaction. Part Ⅱ: Simulations of Biological Processes

In Part Ⅰ, the authors succeeded in coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM) and analyzed the climate basic state and land surface physical fluxes simulated by R42_AVIM. In this Part Ⅱ, we further evaluate the simulated results of the biological processes, including leaf area index (LAI), biomass and net primary productivity (NPP) etc. Results indicate that R42_AVIM can simulate the global distribution of LAI and has good consistency with the monthly mean LAI provided by Max Planck Institute for Meteorology. The simulated biomass corresponds reasonably to the vegetation classifications. In addition, the simulated annual mean NPP has a consistent distribution with the data provided by IGBP and MODIS, and compares well with the work in literature. This land-atmosphere coupled model will offer a new experiment tool for the research on the two-way interaction between climate and biosphere, and the global terrestrial ecosystem carbon cycle.     

Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index?

The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terrestrial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O–CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AVHRR satellites over the period 1982–2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O–CN) or without (O–C) a dynamic nitrogen cycle coupled to the carbon–water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O–CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tropics, simulated LAI from the model without the dynamic N cycle (O–C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982–2002 by 0.0020 m² m^?2 y^?1. Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m² m^?2 y^?1 for O–C and 0.0057 m² m^?2 y^?1 for O–CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO₂ and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when the dynamic N cycle was included in the model (higher ranked fit for O–CN vs. O–C). Using the O–C configuration to estimate the direct effect of climate on LAI, we quantified the importance of climate-N cycle feedbacks in explaining the LAI response. We found that the warming-induced release of N from soil organic matter decomposition explains 17.5 % of the global trend in LAI over time, however, reaching up to 40.9 % explained variance in the boreal zone, which is a more important contribution than increasing anthropogenic nitrogen deposition. Our analysis supports a strong connection between warming, N cycling, and vegetation productivity. These findings underscore the importance of including N cycling in global-scale models of vegetation response to environmental change.     

Evaluation of the WRF Model with Different Land Surface Schemes： A Drought Event Simulation in Southwest China during 2009–10

The authors examined the performance of version 3.4.1 of the Weather Research and Forecasting Model（WRF） with various land surface schemes in simulating a severe drought event in Southwest China. Five numerical experiments were completed using the Noah land surface scheme, the Pleim-Xiu land surface scheme, the Noah-MP land surface schemes, the Noah- MP scheme with dynamic vegetation, and the Noah-MP scheme with dynamic vegetation and groundwater processes. In general, all the simulations reasonably reproduced the spatial and temporal variations in precipitation, but significant bias was also found, especially for the spatial pattern of simulated precipitation. The WRF simulations with the Noah-MP series land surface schemes performed slightly better than the WRF simulation with the Noah and Pleim-Xiu land surface schemes in reproducing the severe drought events in Southwest China. The leaf area index（LAI） simulated by the different land surface schemes showed significant deviations in Southwest China. The Pleim-Xiu scheme overestimated the value of LAI by a factor of two. The Noah-MP scheme with dynamical vegetation overestimated the magnitude of the annual cycle of the LAI, although the annual mean LAI was close to observations. The simulated LAI showed a long-term lower value from autumn 2009 to spring 2010 relative to normal years. This indicates that the LAI is a potential indictor to monitor drought events.     

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.     

NUMERICAL SIMULATIONS OF EFFECTS OF LAND SURFACE PROCESSES ON CLIMATE——IMPLEMENTING OF SSiB IN IAP/LASG AGCM AND ITS PERFORMANCE

This is an investigation of exchanges of energy and water between the atmosphere and thevegetated continents,and the impact of and mechanisms for land surface-atmosphere interactionson hydrological cycle and general circulation by implementing the Simplified Simple Biosphere(SSiB)model in a modified version of IAP/LASG global spectral general model(L9R15 AGCM).This study reveals that the SSiB model produces a better partitioning of the land surface heat andmoisture fluxes and its diurnal variations,and also gives the transport of energy and water amongatmosphere,vegetation and soil explicitly and realistically.Thus the coupled SSiB-AGCM runslead to the more conspicuous improvement in the simulated circulation,precipitation,mean watervapor content and its transport.particularly in the Asian monsoon region in the real world thanCTL-AGCM runs.It is also pointed out that both the implementation of land surfaceparameterizations and the variations in land surface into the GOALS model have greatly improvedhydrological balance over continents and have a significant impact on the simulated climate.particularly over the massive continents.Improved precipitation recycling model was employed to verify the mechanisms for landsurface hydrology parameterizations on hydrological cycle and precipitation climatology in AGCM.It can be argued that the recycling precipitation rate is significantly reduced,particularly in the aridand semi-arid region of the boreal summer hemisphere,coincident with remarkable reduction inevapotranspiration over the continental area.Therefore the coupled SSiB-AGCM runs reduce thebias of too much precipitation over land surface in most AGCMs,thereby bringing the simulatedprecipitation closer to observations in many continental regions of the world than CTL-AGCMruns.     

Coupling a Terrestrial Biogeochemical Model to the Common Land Model

A terrestrial biogeochemical model (CASACNP) was coupled to a land surface model (the Common Land Model,CoLM) to simulate the dynamics of carbon substrate in soil and its limitation on soil respiration.The combined model,CoLM CASACNP,was able to predict long-term carbon sources and sinks that CoLM alone could not.The coupled model was tested using measurements of belowground respiration and surface fluxes from two forest ecosystems.The combined model simulated reasonably well the diurnal and seasonal variations of net ecosystem carbon exchange,as well as seasonal variation in the soil respiration rate of both the forest sites chosen for this study.However,the agreement between model simulations and actual measurements was poorer under dry conditions.The model should be tested against more measurements before being applied globally to investigate the feedbacks between the carbon cycle and climate change.