土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响。改进后的模型被用地研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应。模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响。与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布。土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信。对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明：落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降。未来气候条件下NSTEC样带的净第一性生产力总量将增加。预测样带北部的净第一性生产力的变化范围大于样带南部。温度变化比降水变化对样带的生产力具有更强的控制。     

土地利用约束下中国东部南北样带生产力和植被分布对全球变化的响应

对现有的区域植被动态模拟模型进行了改进,使之包含了土地利用分布格局对植被和生态系统相关过程的影响.改进后的模型被用于研究中国东部南北样带(NSTEC)植被和净第一性生产力对未来气候变化的响应.模拟结果显示土地利用格局对未来气候条件下植被分布的变迁和生产力形成过程有非常显著的影响.与没有土地利用约束的情形相比较,土地利用作为限制条件缓减了植被类型之间的竞争,从而减少了模拟的样带区域内常绿阔叶林,但增加了模拟灌木和草地的分布.土地利用约束使得模拟得到的当前条件下的净第一性生产力更为接近实际情况,且未来气候条件下的生产力改变量更为可信.对未来CO2倍增条件下7个大气环流模型预测的气候情景的模拟结果表明:落叶阔叶林将显著增加,但针叶林、灌木和草原的分布将下降.未来气候条件下NSTEC样带的净第一性生产力总量将增加.预测样带北部的净第一性生产力的变化范围大于样带南部.温度变化比降水变化对样带的生产力具有更强的控制.     

Implications of future climate and atmospheric CO2 content for regional biogeochemistry,biogeography and ecosystem services across East Africa

We model future changes in land biogeochemistry and biogeography across East Africa. East Africa is one of few tropical regions where general circulation model (GCM) future climate projections exhibit a robust response of strong future warming and general annual‐mean rainfall increases. Eighteen future climate projections from nine GCMs participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment were used as input to the LPJ dynamic global vegetation model (DGVM), which predicted vegetation patterns and carbon storage in agreement with satellite observations and forest inventory data under the present‐day climate. All simulations showed future increases in tropical woody vegetation over the region at the expense of grasslands. Regional increases in net primary productivity (NPP) (18–36%) and total carbon storage (3–13%) by 2080–2099 compared with the present‐day were common to all simulations. Despite decreases in soil carbon after 2050, seven out of nine simulations continued to show an annual net land carbon sink in the final decades of the 21st century because vegetation biomass continued to increase. The seasonal cycles of rainfall and soil moisture show future increases in wet season rainfall across the GCMs with generally little change in dry season rainfall. Based on the simulated present‐day climate and its future trends, the GCMs can be grouped into four broad categories. Overall, our model results suggest that East Africa, a populous and economically poor region, is likely to experience some ecosystem service benefits through increased precipitation, river runoff and fresh water availability. Resulting enhancements in NPP may lead to improved crop yields in some areas. Our results stand in partial contradiction to other studies that suggest possible negative consequences for agriculture, biodiversity and other ecosystem services caused by temperature increases.     

Effect of global atmospheric carbon dioxide on glacial–interglacial vegetation change

Global vegetation changes at the time‐scale of the Earth's orbital variations (10⁴–10⁵ years) have been interpreted as a direct effect of consequential climatic changes, especially temperature. At mid‐ and high latitudes, the evidence from fossil data and general circulation models (GCMs) supporting this hypothesis is strong, but at low latitudes there is a major discrepancy. GCMs predict temperature changes that are less than those inferred from palaeoclimatic data, including the plant fossil record. However, changes in atmospheric CO₂ concentrations can account for a high proportion of the low‐latitude vegetation change hitherto attributed to temperature change, and may thus explain the discrepancy. The implications of this finding are considerable for understanding patterns of macroevolution and ecosystem development throughout the geological record.     

Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Developing higher resolution climate change scenarios for agricultural risk assessment: progress,challenges and prospects

Climate change presents perhaps the greatest economic and environmental challenge we have ever faced. Climate change and its associated impacts, adaptation and vulnerability have become the focus of current policy, business and research. This paper provides invaluable information for those interested in climate change and its impacts. This paper comprehensively reviews the advances made in the development of regional climate change scenarios and their application in agricultural impact, adaptation and vulnerability assessment. Construction of regional climate change scenarios evolved from the application of arbitrary scenarios to the application of scenarios based on general circulation models (GCMs). GCM-based climate change scenarios progressed from equilibrium climate change scenarios to transient climate change scenarios; from the use of direct GCM outputs to the use of downscaled GCM outputs; from the use of single scenarios to the use of probabilistic climate change scenarios; and from the application of mean climate change scenarios to the application of integrated climate change scenarios considering changes in both mean climate and climate variability.     

Responses of vegetation structure and primary production of a forest transect in eastern China to global change

Aim A regional model of vegetation dynamics was enhanced to include biogeochemical cycling of nitrogen and was then applied to a forest transect in east China (FTEC) in order to investigate the responses of the transect to possible global change. Location Eastern China. Methods Biomass and nitrogen concentration of green and nongreen portions of vegetation, moisture contents of three soil layers, and total and available soil nitrogen are included as state variables in the enhanced model. The model was parameterized and validated against field observations of biomass, productivity, plant and soil nitrogen concentration, nitrogen uptake, a vegetation index derived from satellite remote sensing and digital maps of vegetation and soil distributions along a forest transect in eastern China (FTEC). The model was applied to FTEC in order to investigate the responsive characteristics of the ecosystems to global climatic change. Scenarios of climate change under doubled CO₂ produced by seven general circulation models (GCM) were used to drive the model. Results The simulations indicated that the model is capable of simulating accurately potential vegetation distribution and net primary productivity under contemporary climatic conditions. The simulations for GCM‐projected future climate scenarios with doubled atmospheric CO₂ concentration predicted that broadleaf forests would increase, but conifer forests, shrubs and grasses would decrease; and that deciduous forests would have the largest relative increase, but evergreen shrubs would have the largest decrease. Conclusions The overall effects of doubling CO₂ and climatic changes on FTEC were to produce an increased net primary productivity (NPP) at equilibrium for all seven GCM scenarios. The inclusion of nitrogen dynamics in the model imposes more constraint on the responses of FTEC to climatic change than the previous version of the model without nitrogen dynamics. Temperature exerts a stronger control on NPP than precipitation, as indicated by the negative correlations between NPP and temperature. The southern portion of FTEC, at latitudes less than 33 °N, show much larger increases in annual NPP than in the north. However, the predicted range of NPP increases is much larger in the north than in the south.     

未来气候变化对黄土高原黑河流域水资源的影响

气候变化对黄土高原的水资源有重要影响,对其影响进行评估可以为区域发展提供重要的决策依据.基于分布式水文模型SWAT和4种全球环流模式的各3种排放情景,评估了2010～2039年黄土高塬沟壑区黑河流域水资源对气候变化的潜在响应.结果表明,黑河流域2010～2039年的年均降水变化-2.3%～7.8%,年均最高和最低温度分别升高0.7～2.2 ℃和1.2～2.8 ℃,年均径流量变化-19.8%～37.0%,1.2 m剖面年均土壤水分含量变化-5.5%～17.2%,年均蒸散量普遍增长0.1%～5.9%;水文气象变量变化趋势复杂,但T检验表明年降水、径流、土壤水分和蒸散增长的概率较大.对于季节变化,降水可能在12～7月份和9月份增长,8月份和10～11月份减少;径流在4～7月份和9～10月份增加,11～3月份和8月份减少;土壤水分在各月都增长;蒸散11～6月份普遍增长,7～10月份减少的可能性较大.未来气候将发生显著变化并对水资源有重要影响,需采取必要的措施来减缓其不利影响.     

Leaf area index and net primary productivity along subtropical to alpine gradients in the Tibetan Plateau

Aim Our aims were to quantify climatic and soil controls on net primary productivity (NPP) and leaf area index (LAI) along subtropical to alpine gradients where the vegetation remains relatively undisturbed, and investigate whether NPP and LAI converge towards threshold‐like logistic patterns associated with climatic and soil variables that would help us to verify and parameterize process models for predicting future ecosystem behaviour under global environmental change. Location Field data were collected from 22 sites along the Tibetan Alpine Vegetation Transects (TAVT) during 1999–2000. The TAVT included the altitudinal transect on the eastern slope of the Gongga Mountains in the Eastern Tibetan Plateau, with altitudes from 1900 m to 3700 m, and the longitudinal‐latitudinal transect in the Central Tibetan Plateau, of approximately 1000 km length and 40 km width. Methods LAI was measured as the product of foliage biomass multiplied by the ratio of specific leaf area. NPP in forests and shrub communities was estimated as the sum of increases in standing crops of live vegetation using recent stem growth rate and leaf lifespan. NPP in grasslands was estimated from the above‐ground maximum live biomass. We measured the soil organic carbon (C) and total and available nitrogen (N) contents and their pool sizes by conventional methods. Mean temperatures for the year, January and July and annual precipitation were estimated from available meteorological stations by interpolation or simulation. The threshold‐like logistic function was used to model the relationships of LAI and NPP with climatic and soil variables. Results Geographically, NPP and LAI both significantly decreased with increasing latitude (P < 0.02), but increased with increasing longitude (P < 0.01). Altitudinal trends in NPP and LAI showed different patterns. NPP generally decreased with increasing altitude in a linear relationship (r² = 0.73, P < 0.001), whereas LAI showed a negative quadratic relationship with altitude (r² = 0.58, P < 0.001). Temperature and precipitation, singly or in combination, explained 60–68% of the NPP variation with logistic relationships, while the soil organic C and total N variables explained only 21–46% of the variation with simple linear regressions of log‐transformed data. LAI showed significant logistic relationships with both climatic and soil variables, but the data from alpine spruce‐fir sites diverged greatly from the modelled patterns associated with temperature and precipitation. Soil organic C storage had the strongest correlation with LAI (r² = 0.68, P < 0.001). Main conclusions In response to climatic gradients along the TAVT, LAI and NPP across diverse vegetation types converged towards threshold‐like logistic patterns consistent with the general distribution patterns of live biomass both above‐ground and below‐ground found in our earlier studies. Our analysis further revealed that climatic factors strongly limited the NPP variations along the TAVT because the precipitation gradient characterized not only the vegetation distribution but also the soil N conditions of the natural ecosystems. LAI generally increased with increasing precipitation and was well correlated with soil organic C and total N variables. The interaction between LAI growth and soil N availability would appear to have important implications for ecosystem structure and function of alpine spruce‐fir forests. Convergence towards logistic patterns in dry matter production of plants in the TAVT suggests that alpine plant growth would increase in a nonlinear response to global warming.     

Climate-induced changes in the vegetation pattern of China in the 21st century

Quantifying climate-induced changes in vegetation patterns is essential to understanding land–climate interactions and ecosystem changes. In the present study, we estimated various distributional changes of vegetation under different climate-change scenarios in the 21st century. Both hypothetical scenarios and Hedley RCM scenarios show that the transitional vegetation types, such as shrubland and grassland, have higher sensitivity to climatic change compared to vegetation under extreme climatic conditions, such as the evergreen broadleaf forest or desert, barren lands. Mainly, the sensitive areas in China lie in the Tibetan Plateau, Yunnan-Guizhou Plateau, northeastern plain of China and eco-zones between different vegetations. As the temperature increases, mixed forests and deciduous broadleaf forests will shift towards northern China. Grassland, shrubland and wooded grassland will extend to southeastern China. The RCM-project climate changes generally have caused positive vegetation changes; vegetation cover will probably improve 19% relative to baseline, and the forest will expand to 8% relative to baseline, while the desert and bare ground will reduce by about 13%.     

Modelling potential impacts of climate change on the spatial distribution of zonal forest communities in Switzerland

Abstract. A spatially explicit, climate-sensitive vegetation model is presented to simulate both present and future distribution of potential natural vegetation types in Switzerland at the level of zonal forest communities. The model has two versions: (1) a ‘basic’ version using geographical region, aspect, bedrock (represented by soil pH), and elevation, and (2) a ‘climate-sensitive’ version obtained by replacing elevation (complex environmental gradient) with temperature (climatic factor). Version 2 is used to predict vegetation response under different (today's and projected) climatic conditions. Two regional climate scenarios are applied: (1) assuming an annual mean temperature increase of 1.1 — 1.4 °C, and (2) assuming an increase of 2.2 — 2.75 °C. Both scenarios result in significant changes of the spatial vegetation patterns as compared with today's climatic conditions. In scenario 1, ca. 33 % of the sample points remain unchanged in terms of the simulated zonal forest community; in scenario 2, virtually all sample points change. The most noticeable changes occur on the Swiss Plateau with Carpinion forests (zonal vegetation of present colline belt) expanding to areas that are occupied today by submontane and low-montane Fagus forests. To estimate the reliability of the simulation, quantitative (comparison with field mapping) and qualitative (comparison with climate types in the Alpine region) tests are performed and the main limitations of the approach are evaluated.     

区域气候变化统计降尺度研究进展

统计降尺度方法(the Statistical Downscaling Methods, SDM)是为合理预测区域尺度的气候变化情景而提出的新型研究方法。统计降尺度法利用多年大气环流的观测资料建立大尺度气候要素和区域气候要素之间的统计关系,并用独立的观测资料检验这种关系的合理性。把这种关系应用于大气环流模式(Global atmospheric general circulation models, GCMs)中输出大尺度气候信息,来预估区域未来的气候变化情景(如气温和降水)。同时,10a来降尺度方法在生态过程模拟以及气候变化与生态预报关系拟合研究方面也取得一定进展。对统计降尺度方法概念的内涵和外延、基本原理和操作步骤的创新研究方面进行了综述,归纳了该方法在模拟区域气候变化中的应用进展、研究热点及发展趋势,介绍了降尺度在生态预报中的相关应用,为相关研究提供参考。     

Regional variation in SE Fennoscandian mire vegetation

The distribution in bogs is outlined for all species occurring in bogs only in part of their SE Fennoscandian area. The patterns displayed by these species are diverse, and different explanations are applicable to different patterns. Regional variation in SE Fennoscandian bog and extremely poor fen vegetation is described, based on all available published material. Carpets, lawns, and hummocks are considered separately. Four regional vegetational gradients are identified: (1) W-E, (2) S-N, (3) SW-NE, and (4) NW-SE. These are related to different underlying climatic gradients: (1) humidity (precipitation surplus), (2) temperature, (3) and (4) combinations of humidity and temperature. Effects of climatic gradients on the ground water regime are outlined. The decisive factor for the SW-NE gradient is probably frequency of ground water table fluctuations, the NW-SE gradient is likely to be caused by differences in water supply and ground water flow rates. The main gradient of carpets is S-N (SE-NW), of lawns SW-NE (W-E), and of hummocks partly SW-NE, partly S-N. The effects of the underlying ecological factors on the different plant groups are discussed in order to explain the patterns of regional variation in vegetation.     

Climate change‐induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands

Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change‐induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change‐induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water‐limited ecosystems.     

Is vegetation in equilibrium with climate? How to interpret late-Quaternary pollen data

Current methods for estimating past climatic patterns from pollen data require that the vegetation be in dynamic equilibrium with the climate. Because climate varies continuously on all time scales, judgement about equilibrium conditions must be made separately for each frequency band (i.e. time scale) of climatic change. For equilibrium conditions to exist between vegetation and climatic changes at a particular time scale, the climatic response time of the vegetation must be small compared to the time scale of climatic variation to which it is responding. The time required for vegetation to respond completely to climatic forcing at a time scale of 10⁴ yr is still unknown, but records of the vegetational response to climatic events of 500-to 1000-yr duration provide evidence for relatively short response times. Independent estimates for the possible patterns and timing of late-Quaternary climate changes suggest that much of the vegetational evidence previously interpreted as resulting from disequilibrium conditions can instead be interpreted as resulting from the individualistic response of plant taxa to the different regional patterns of temperature and precipitation change. The differences among taxa in their response to climate can lead a) to rates and direction of plant-population movements that differ among taxa and b) to fossil assemblages that differ from any modern assemblage. An example of late-Holocene vegetational change in southern Quebec illustrates how separate changes in summer and winter climates may explain the simultaneous expansion of spruce (Picea) populations southward and beech (Fagus) populations northward.     

Patterns and Variability of Projected Bioclimatic Habitat for Pinus albicaulis in the Greater Yellowstone Area

Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980–2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2–29% and 0.04–10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010–2099 time period related to consistent warming above the 1910–2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios.     

Regional changes in extravascular lung water detected by positron emission tomography

Regional measurements of extravascular lung water (rEVLW) were made with positron emission tomography (PET) and 15O-labeled radionuclides. The label used to measure the total lung water (TLW) content fully equilibrated with TLW prior to scanning in both dogs with normal and low cardiac outputs, and nearly so in areas of lung made edematous by oleic acid injury (the TLW values used were 97% of maximum values). Regional EVLW measurements made by PET (EVLW-PET) and gravimetric techniques in both normal and edematous lung were closely correlated (r = 0.93), and EVLW-PET increased from an average of 0.20 to 0.37 mlH2O/ml lung (P less than 0.05) after regional lung injury. PET measurements of regional blood volume always decreased [from an average of 0.12 to 0.09 ml blood/ml lung (P less than 0.05)] after cardiac output was lowered by hemorrhage in a separate set of animals. Total EVLW (by thermodye indicator dilution) did not change. Likewise, regional EVLW remained constant in areas below the left atrium but decreased in areas above the left atrium. We conclude that PET measurements are accurate, noninvasive, and reproducible and that regional changes may be detected even when measurements of total EVLW by other methods may fail to change significantly.     

1988-2013年基于BP神经网络的植被叶面积指数遥感定量反演

叶面积指数（Leaf Area Index,LAI）高度综合了植被水平覆盖状况和垂直结构,以及枯枝落叶层厚薄和地下生物量多少,是植被影响土壤侵蚀的主要方面。区域尺度的时间序列叶面积指数揭示了区域土壤侵蚀的演化过程。因此,及时准确地掌握区域尺度上长时间序列的植被LAI,对研究土壤侵蚀动态变化与植被的关系至关重要。选择南京市1988-2013年10期遥感影像,基于反向传播（Back Propagation,BP）神经网络构建LAI反演模型,进行了长时间序列的叶面积指数反演。结合2009和2010年LAI实测值,验证与探讨了该模型的评价精度与适应性。结果表明：（1）该模型拟合度较高,2009和2010年平均相对误差、均方根误差、相关系数分别是0.2395和0.2174,0.2962和0.2581,0.7713和0.6844,各项精度评价指标均较好;（2）统计分析去除耕地后全市LAI变化,低植被覆盖（LAI<2）面积不断增加,高植被覆盖区（LAI>3）面积先减少后增加,耕地面积不断减少,符合南京市的发展变化规律;（3）主城区LAI年际变化与其他学者得到的南京市植被盖度变化趋势一致,反演结果的时序性较高。本文提出的基于反向传播神经网络模型反演长时间序列LAI是可行的,为区域尺度土壤侵蚀定量遥感监测提供新途径。     

CLM3.0-DGVM中植物叶面积指数与气候因子的时空关系

作为陆面模型里植被的特征量,叶面积值数（LAI）和植被覆盖度在陆地-大气相互作用的相关研究里被广泛应用。LAI的模拟是动态植被模式（DVM）的核心任务之一,需要对模拟的LAI与气候因子间的时空关系进行评估以更好的了解模式性能以及理解植被-大气反馈过程。用1950—1999年的气象数据驱动通用陆面模式的动态植被模式（CLM3.0-DGVM）模拟得到的全球潜在植被的LAI和2001—2003年MODIS观测资料衍生出的LAI数据进行对比,并在此基础上研究当前气候条件下不同植物功能型（PFT）的LAI与不同气候因子在年际尺度上的时空关系,包括运用Moran系数理论分析空间自相关性、运用逐步回归算法构建空间最优一阶线性回归方程、分析模式LAI与气候因子间的滞后相关性。研究表明：1）以MODIS衍生数据作参照,改进后的CLM3.0-DGVM能较好地模拟不同PFTs的LAI年最大值的空间分布型,但是在物候模拟即LAI的季节循环上存在不足;2）植物LAI的分布具有正的空间自相关性。对潜在植物LAI和气候因子进行拟合时不同气候因子对不同PFTs的方差贡献不一样,一般降水最大、风速最小。这反映了陆地生态系统和气候间复杂的相互关系;3）模式模拟的LAI和气候因子有显著的1～2年的滞后相关,其中光照、降水和LAI的滞后相关性波动较大,而温度、比湿的较小,风速的不明显。这些基于CLM3.0-DGVM的结论在自然界的植物–气候相互作用系统中具有普遍意义：不同地区不同植物受不同气候因子的影响不一样;找出不同PFT的主要气候影响因子和理解其中最关键的生物物理和生物化学过程是至关重要的。进一步工作需要用更精确和更高分辨率的气候数据以及局地观测的LAI对DGVM做评估,同时DGVM本身也需要继续改进（例如加入农作物和灌溉过程的模拟）。     

Streamflow Impacts of Biofuel Policy-Driven Landscape Change

Likely changes in precipitation (P) and potential evapotranspiration (PET) resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979–2004 using the Weather Research Forecast (WRF) model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.