全球气候变化条件下新疆天山云杉林生长的分析与模拟

气候变化对人类赖以生存的陆地生态系统尤其是森林会产生很大的影响。本论文选择新疆天山东部的伊吾、中部的天池和小渠子、西部的昭苏四个代表性样点，利用BIOME-BGC模型和树木年轮分析方法探讨1961 ~ 2000年间气候变化和大气CO2浓度增高对天山北坡地带性植被天山云杉林（Picea schrenkiana）生长的影响，并利用BIOME-BGC模型预测未来气候变化条件下天山云杉林生产力的可能变化。 利用BIOME-BGC模型模拟了当前气候和CO2浓度条件下四个研究样点净初级生产力（NPP）特征。比较BIOME-BGC模型模拟值与实测NPP、树木年轮指数，结果表明该模型适用于天山北坡天山云杉林的模拟研究。 以BIOME-BGC模型模拟的NPP和树木年轮宽度指数作为生长指标，分析了天山云杉林过去40年的生长特点和趋势。结果表明近40年来天山云杉林生长总体上呈现上升趋势，尤其是自1987年以后，变化幅度更大。天山云杉林的生长对气候变化的反应很敏感，年降水量与当年的NPP呈现显著正相关关系（R=0.774 ~ 0.882，P < 0.001）。年降水量与树木年轮宽度指数也呈现出相似的相关关系，但相关系数相对较小（0.305 ~ 0.544），其中只有昭苏和小渠子样点达到显著水平。在昭苏和伊吾，年平均温度与对应年份的NPP相关关系微弱，相关系数仅分别为0.036和0.159。而天山中部的小渠子和天池年平均温度与对应年份的NPP呈显著负相关关系（相关系数分别为-0.324和-0.322;P <0.05）,这可能是由于温度的升高加剧水分胁迫，导致NPP下降。年平均温度与树木年轮宽度指数的相关关系与NPP的基本一致。同时，年平均温度也表现出比较强的滞后效应,尤其是滞后两年的效应，这可能是由于温度的升高，加速养分循环产生施肥效应，从而间接促进天山云杉林的生长。近40年来，大气CO2浓度的增高对天山云杉林生长具有一定促进作用，NPP升高的幅度为1.85 ~ 4.51%,根据树木年轮估算大气CO2施肥效应β相对比较小,仅为0.133。进一步分析表明大气 CO2浓度主要是通过提高水分利用效率的途径促进天山云杉林生长。 利用RegCM2区域气候模式模拟的大气CO2倍增时（大约2070年）的气候变化情形作为输入参数，应用BIOME-BGC模型预测了在未来气候状况发生改变，而大气CO2浓度没有变化的情况下（C0T1P1），天山云杉林的NPP增长幅度为13.33 ~ 29.11%,其中对东部伊吾NPP的促进作用最大，其次是中部的小渠子和天池，而对西部昭苏NPP的影响最小;结合当前气候条件和大气CO2浓度加倍情形（C1T0P0），模拟结果表明NPP在比较温暖的天山中部和西部将会有所增加，增加幅度为1.17 ~ 8.62%，而在寒冷的东部伊吾，NPP则会下降2.50%, CO2的施肥效应表现出很大的温度依赖性;结合气候变化和大气CO2浓度加倍情形（C1T1P1），模拟结果表明NPP的增加幅度将会上升为26.43 ~ 37.24%，温度、降水和大气CO2浓度对NPP的影响存在较强的交互作用。 研究表明树木年轮真实记录了树木在自然条件下长期的生长特征，是验证生态系统模型比较理想的材料之一。生态系统模型可以从机理上对生态系统的生物物理过程以及影响因子进行分析和模拟。本研究利用生态系统模型与树木年轮方法相结合很好地揭示天山云杉林的生长与全球气候变化之间的相互关系。同时，研究表明未来气候变化有利于天山云杉林的生长，天山云杉林可能会成为一个重要的碳汇而在碳循环研究中倍受关注。

沿水分梯度草原群落NPP动态及对气候变化响应的模拟分析

水分条件不仅影响半干旱区群落的组成，而且在一定程度上决定了群落的功能。处于不同水分条件生境下群落的优势物种在水分利用和同化物利用效率方面的功能特征会存在差异，这些差异将导致群落对于气候变化产生不同的响应，进而影响到景观和区域尺度上对于全球变化下碳动态和格局的分析。本研究选取了锡林河流域典型草原区沿水分梯度的四个代表群落，在野外实验测定并结合长期定位研究成果基础上，利用BIOME-BGC模型对代表群落的长期净初级生产力(NPP)动态进行了模拟和模型验证。通过分析该地区1953~2005年气候变化趋势，推测了未来可能的气候变化情景，进而模拟了气候变化下四个群落长期NPP动态的响应。 野外实验分析表明，在四个群落中，净光合速率与光合有效辐射呈单峰曲线关系，与温度和蒸气压亏损(VPD)成反比，叶片氮含量和比叶面积也会影响到光合能力。四个群落由于水分与土壤条件的差别，净光合速率随VPD与温度的变化表现出不同的增减幅度。将日变化分为四个阶段，分别为大致在6:00~8:00左右的低温高湿阶段，10:00~16:00的高温低湿阶段，16:00以后的低温低湿阶段和低温高湿阶段变为高温低湿阶段过程中的适温适湿阶段。在每个阶段中，影响羊草光合速率的主导因子是不同的。在不同的水分与土壤状况下，羊草的光合特性表现出明显差异，但总体说来水分仍是光合作用的主导因子。 模型模拟结果表明，当前气候条件下，羊草群落NPP平均值为197.76 gC m-2 (SE=7.11)，大针茅群落NPP平均值为198.95 gC m-2 (SE=6.41)，贝加尔针茅群落NPP平均值为210.41 gC m-2 (SE=7.87)，克氏针茅群落NPP平均值为144.92 gC m-2 (SE=4.64)，四个群落NPP平均值为188.01 gC m-2 (SE=3.72)。 日最高温度与最低温度在1953~2005年间都明显增加，而降水变化很大。温度增加下(P0T1)NPP平均下降14.2%，降水增加下(P1T0)NPP平均增加13.2%，温度与降水都增加情景下(P1T1)NPP平均下降2.7%。在半干旱区，降水是NPP变化的主要限制因子，而温度通过影响了植物的呼吸与蒸散作用对NPP产生影响。 由于生境水分条件差别和优势物种功能特征差异，四个群落在气候变化中表现出对温度与降水不同的敏感程度，这与水分胁迫系数WSI、碳胁迫系数CSI变化密切相关。克氏针茅群落由于所处生境水分条件差，水分胁迫系数高，对降水的依赖程度最大;贝加尔针茅群落一方面处于较好的水分生境，具有相对较小的水分胁迫系数，另一方面，由于具有高碳氮比，维持呼吸消耗的光合产物比例低，碳胁迫系数远低于其它三个群落，未来气候变化下NPP较其它三个群落仍较高。

不同类型生态系统水热碳通量的监测与研究

亚太地区环境革新战略项目(APEIS)在中国5种主要生态系统类型区(草地:海北、耕地:禹城、稻田:桃源、林地:千烟洲、荒漠:阜康)建立了一个以连续观测能量、水分和碳素通量为中心,包括气象、水文、土壤、植被等各项生态要素的监测网络系统,被称之为APEIS-FLUX系统.作者首先对APEIS-FLUX系统的观测数据进行了初步分析,表明该系统稳定可靠,它可以实时地提供高质量、高精度、长期而连续的通量及生态要素的观测数据.对数据的比较清楚地反映出了不同生态系统类型区的水热碳通量的差异性.其次,利用APEIS-FLUX数据对美国航空航天局(NASA)的MODIS数据产品进行比较验证后发现,除部分产品如地表面温度(MOD11)等与观测数据较吻合以外,大部分数据产品如土地覆盖(MOD12),叶面积指数(MOD15)和光合速率与净第一性生产力(MOD17)等都与观测数据相差深远,有必要对其处理程序和模式进行修正.为此,我们利用APEIS-FLUX的数据作为MOD15和MOD17的生成模型(BIOME-BGC)的输入数据,并对该模型的有关参数进行了修订.结果表明,该模式在通过修正后,可以很好地模拟植被的生长过程及其相应的水热碳循环过程.

Influência das condições ambientais no verdor da vegetação da caatinga frente às mudanças climáticas

The Caatinga biome, a semi-arid climate ecosystem found in northeast Brazil, presents low rainfall regime and strong seasonality. It has the most alarming climate change projections within the country, with air temperature rising and rainfall reduction with stronger trends than the global average predictions. Climate change can present detrimental results in this biome, reducing vegetation cover and changing its distribution, as well as altering all ecosystem functioning and finally influencing species diversity. In this context, the purpose of this study is to model the environmental conditions (rainfall and temperature) that influence the Caatinga biome productivity and to predict the consequences of environmental conditions in the vegetation dynamics under future climate change scenarios. Enhanced Vegetation Index (EVI) was used to estimate vegetation greenness (presence and density) in the area. Considering the strong spatial and temporal autocorrelation as well as the heterogeneity of the data, various GLS models were developed and compared to obtain the best model that would reflect rainfall and temperature influence on vegetation greenness. Applying new climate change scenarios in the model, environmental determinants modification, rainfall and temperature, negatively influenced vegetation greenness in the Caatinga biome. This model was used to create potential vegetation maps for current and future of Caatinga cover considering 20% decrease in precipitation and 1 °C increase in temperature until 2040, 35% decrease in precipitation and 2.5 °C increase in temperature in the period 2041-2070 and 50% decrease in precipitation and 4.5 °C increase in temperature in the period 2071-2100. The results suggest that the ecosystem functioning will be affected on the future scenario of climate change with a decrease of 5.9% of the vegetation greenness until 2040, 14.2% until 2070 and 24.3% by the end of the century. The Caatinga vegetation in lower altitude areas (most of the biome) will be more affected by climatic changes.

Toward a rule-based biome model

EXTRACT (SEE PDF FOR FULL ABSTRACT): Current projections of the response of the biosphere to global climatic change indicate as much as 50 to 90% spatial displacement of extratropical biomes. The mechanism of spatial shift could be dominated either by competitive displacement of northern biomes by southern biomes or by drought-induced dieback of areas susceptible to change. The current suite of global biosphere models cannot distinguish between these two processes, hence the need for a mechanistically based biome model. The first steps have been taken toward development of a rule-based, mechanistic model of regional biomes at a continental scale. ... The model is in an early stage of development and will require several enhancements, including: explicit simulation of potential evapotranspiration, extension to boreal and tropical biomes, a shift from steady-state to transient dynamics, and validation on other continents.

Evaluation and histological examination of a Campylobacter fetus subsp. venerealis small animal infection model

Bovine genital campylobacteriosis (BGC), caused by Campylobacter fetus subsp. venerealis, is associated with production losses in cattle worldwide. This study aimed to develop a reliable BGC guinea pig model to facilitate future studies of pathogenicity, abortion mechanisms and vaccine efficacy. Seven groups of five pregnant guinea pigs (1 control per group) were inoculated with one of three strains via intra-peritoneal (IP) or intra-vaginal routes. Samples were examined using culture, PCR and histology. Abortions ranged from 0 to 100 and re-isolation of causative bacteria from sampled sites varied with strain, dose of bacteria and time to abortion. Histology indicated metritis and placentitis, suggesting that the bacteria induce inflammation, placental detachment and subsequent abortion. Variation of virulence between strains was observed and determined by culture and abortion rates. IP administration of C. fetus subsp. venerealis to pregnant guinea pigs is a promising small animal model for the investigation of BGC abortion.

Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

1. Quantitative reconstruction of past vegetation distribution and abundance from sedimentary pollen records provides an important baseline for understanding long term ecosystem dynamics and for the calibration of earth system process models such as regional-scale climate models, widely used to predict future environmental change. Most current approaches assume that the amount of pollen produced by each vegetation type, usually expressed as a relative pollen productivity term, is constant in space and time.
2. Estimates of relative pollen productivity can be extracted from extended R-value analysis (Parsons and Prentice, 1981) using comparisons between pollen assemblages deposited into sedimentary contexts, such as moss polsters, and measurements of the present day vegetation cover around the sampled location. Vegetation survey method has been shown to have a profound effect on estimates of model parameters (Bunting and Hjelle, 2010), therefore a standard method is an essential pre-requisite for testing some of the key assumptions of pollen-based reconstruction of past vegetation; such as the assumption that relative pollen productivity is effectively constant in space and time within a region or biome.
3. This paper systematically reviews the assumptions and methodology underlying current models of pollen dispersal and deposition, and thereby identifies the key characteristics of an effective vegetation survey method for estimating relative pollen productivity in a range of landscape contexts.
4. It then presents the methodology used in a current research project, developed during a practitioner workshop. The method selected is pragmatic, designed to be replicable by different research groups, usable in a wide range of habitats, and requiring minimum effort to collect adequate data for model calibration rather than representing some ideal or required approach. Using this common methodology will allow project members to collect multiple measurements of relative pollen productivity for major plant taxa from several northern European locations in order to test the assumption of uniformity of these values within the climatic range of the main taxa recorded in pollen records from the region.

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations.

The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

The climate and biomes of Europe at 6000 yr BP: comparison of model simulations and pollen-based reconstructions

14C-dated pollen and lake-level data from Europe are used to assess the spatial patterns of climate change between 6000 yr BP and present, as simulated by the NCAR CCM1 (National Center for Atmospheric Research, Community Climate Model, version 1) in response to the change in the Earth’s orbital parameters during this perod. First, reconstructed 6000 yr BP values of bioclimate variables obtained from pollen and lake-level data with the constrained-analogue technique are compared with simulated values. Then a 6000 yr BP biome map obtained from pollen data with an objective biome reconstruction (biomization) technique is compared with BIOME model results derived from the same simulation. Data and simulations agree in some features: warmer-than-present growing seasons in N and C Europe allowed forests to extend further north and to higher elevations than today, and warmer winters in C and E Europe prevented boreal conifers from spreading west. More generally, however, the agreement is poor. Predominantly deciduous forest types in Fennoscandia imply warmer winters than the model allows. The model fails to simulate winters cold enough, or summers wet enough, to allow temperate deciduous forests their former extended distribution in S Europe, and it incorrectly simulates a much expanded area of steppe vegetation in SE Europe. Similar errors have also been noted in numerous 6000 yr BP simulations with prescribed modern sea surface temperatures. These errors are evidently not resolved by the inclusion of interactive sea-surface conditions in the CCM1. Accurate representation of mid-Holocene climates in Europe may require the inclusion of dynamical ocean–atmosphere and/or vegetation–atmosphere interactions that most palaeoclimate model simulations have so far disregarded.

Climate and biome simulations for the past 21,000 years

This paper reports on a set of paleoclimate simulations for 21, 16, 14, 11 and 6 ka (thousands of years ago) carried out with the Community Climate Model, Version 1 (CCM1) of the National Center for Atmospheric Research (NCAR). This climate model uses four interactive components that were not available in our previous simulations with the NCAR CCM0 (COHMAP, 1988Science, 241, 1043–1052; Wright et al., 1993Global Climate Since the Last Glocial Maximum, University of Minnesota Press, MN): soil moisture, snow hydrology, sea-ice, and mixed-layer ocean temperature. The new simulations also use new estimates of ice sheet height and size from ( Peltier 1994, Science, 265, 195–201), and synchronize the astronomically dated orbital forcing with the ice sheet and atmospheric CO2 levels corrected from radiocarbon years to calendar years. The CCM1 simulations agree with the previous simulations in their most general characteristics. The 21 ka climate is cold and dry, in response to the presence of the ice sheets and lowered CO2 levels. The period 14–6 ka has strengthened northern summer monsoons and warm mid-latitude continental interiors in response to orbital changes. Regional differences between the CCM1 and CCM0 simulations can be traced to the effects of either the new interactive model components or the new boundary conditions. CCM1 simulates climate processes more realistically, but has additional degrees of freedom that can allow the model to ‘drift’ toward less realistic solutions in some instances. The CCM1 simulations are expressed in terms of equilibrium vegetation using BIOME 1, and indicate large shifts in biomes. Northern tundra and forest biomes are displaced southward at glacial maximum and subtropical deserts contract in the mid-Holocene when monsoons strengthen. These vegetation changes could, if simulated interactively, introduce additional climate feedbacks. The total area of vegetated land remains nearly constant through time because the exposure of continental shelves with lowered sea level largely compensates for the land covered by the expanded ice sheets.

Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP

Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Inter-comparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981-2010) to the future (2070-2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.

SIMULATION OF USE AND MANAGEMENT EFFECTS ON THE SOIL ORGANIC MATTER POOLS OF THE ATLANTIC FOREST BIOME, BRAZIL

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Microcharcoal concentration and elongation, and age model of sediment core MD96-2098

Although grassland and savanna occupy only a quarter of the world's vegetation, burning in these ecosystems accounts for roughly half the global carbon emissions from fire. However, the processes that govern changes in grassland burning are poorly understood, particularly on time scales beyond satellite records. We analyzed microcharcoal, sediments, and geochemistry in a high-resolution marine sediment core off Namibia to identify the processes that have controlled biomass burning in southern African grassland ecosystems under large, multimillennial-scale climate changes. Six fire cycles occurred during the past 170,000 y in southern Africa that correspond both in timing and magnitude to the precessional forcing of north-south shifts in the Intertropical Convergence Zone. Contrary to the conventional expectation that fire increases with higher temperatures and increased drought, we found that wetter and cooler climates cause increased burning in the study region, owing to a shift in rainfall amount and seasonality (and thus vegetation flammability). We also show that charcoal morphology (i.e., the particle's length-to-width ratio) can be used to reconstruct changes in fire activity as well as biome shifts over time. Our results provide essential context for understanding current and future grassland-fire dynamics and their associated carbon emissions.

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.