基于功能平衡假说的玉米光合产物分配动态模拟

基于中国气象局沈阳大气环境研究所锦州农田生态系统定位观测站2004-2008年玉米各器官（根、茎和叶）生物量及相应环境因子的连续动态观测资料,检验了Friedlingstein模型在站点与日尺度上的适用性,并发展了基于施肥、土壤温度和土壤有效水分系数的玉米农田土壤有效养分系数模型,建立了基于功能平衡假说的日尺度的玉米光合产物的分配模型结果表明：与Friedlingstein模型相比,本文所建的玉米光合产物分配模型能更好地模拟玉米光合产物分配动态,为准确模拟日尺度的玉米农田生态系统生产力提供了技术支持.     

WOFOST模型在内蒙古河套灌区模拟玉米生长全程的适应性

在河套灌区引入成熟的作物模型并进行适应性验证,可为进一步开展玉米生长监测及估产提供依据和基础。本文利用河套灌区巴彦淖尔农业气象试验站2012年玉米观测数据,结合当地气象、土壤资料对荷兰瓦赫宁根大学开发的WOFOST模型进行参数校准,并利用2013年玉米观测数据和2001—2011年农业气象观测资料对模型的区域适用性进行验证,获得了玉米的基本作物参数,包括各发育阶段比叶面积、最大CO2同化率、单叶光能利用率等。结果表明:通过校准作物参数,WOFOST模型可以较好地模拟LAI扩展、生物量的动态积累过程,LAI、各器官生物量及最终产量的模拟值与实测值吻合较好;独立样本检验中,模型模拟LAI的绝对偏差平均值为0.75,叶生物量、茎生物量、贮存器官生物量、地上部总生物量、产量的归一化均方根误差分别为33%、26%、17%、18%和13%;模拟2001—2011年玉米产量的归一化均方根误差为7.5%。参数校准后的模型对LAI、各器官生物量、产量的模拟结果较为符合实际,WOFOST模型能够适用于河套地区玉米生产过程生理、生态因子诊断、评估等。     

基于植株拓扑结构的生物量分配的玉米虚拟模型

依据植物结构—功能相互作用机理,建立了能模拟玉米生长发育与形态结构建成的虚拟模型。该模型的重要部分为基于植株拓扑结构的生物量分配模块。叙述了该模块的构建原理,以2000年田间试验数据提取了玉米的发育、生物量生产和生物量分配参数。模型模拟了2001年的玉米生长发育与生物量分配过程,模拟结果与田间试验结果比较吻合。应用该模型模拟了2001年玉米不同生育阶段植株的生物量分配和各器官生物量积累动态。     

基于器官生物量构建植株形态的玉米虚拟模型

探讨了基于玉米器官生物量模拟其形态的方法,并应用2000年田间试验数据提取了玉米节间、叶鞘和叶片的形态构建参数。基于玉米虚拟模型生物量分配模块模拟的器官生物量积累和建立的形态构建方法与提取的参数,模拟了2001年玉米不同生长阶段的器官形态,模拟结果与田间试验数据吻合较好。应用本模型实现了玉米生长过程中植株各个器官形态变化以及植株高度、叶面积动态的模拟,并实现了植株形态的可视化。     

腾格里沙漠人工固沙植被中油蒿的生长及生物量分配动态

植物的资源分配模式反映了对环境的生态适应对策。2007年整个生长季, 采用生物量法对腾格里沙漠东南缘固沙植被区半灌木油蒿(Artemisia ordosica)地上部分各器官的生长及资源分配格局动态进行了研究。结果表明: 不同时期各器官的生长速率不同, 光合产物在各器官中的分配也不是等量的, 而是按一定的顺序在不同时期有不同的分配中心; 2007年油蒿的营养生长、繁殖输出、生殖枝大小都显著大于年降水量不足其一半的年份, 而繁殖分配和头状花序大小没有差异; 营养器官生物量大的油蒿总的繁殖输出也大, 但生殖期内营养生长和生殖生长既不同时也不等速, 表明资源分配的权衡(Trade-off)是存在的; 固沙植被建立以后, 随着时间延长, 油蒿的当年总生物量、繁殖输出、繁殖器官生物量分配有减小的趋势, 但不显著。     

水分驱动下茵陈蒿(Artemisia capillaris Thunb.)地上生物量模型与异速生长特征

构建生物量预估模型,探究生物量在各器官中的分配策略和异速生长关系及其对环境因子的响应,对理解植物群落结构、功能、碳储存和分配机制具有重要意义。本研究以内蒙古荒漠草原常见种茵陈蒿(Artemisia capillaris Thunb.)为对象,在不同水分处理下,利用易测指标,如株高、基径、分枝数、冠幅和生物量等参数建立生物量模型,采用标准化主轴分析法分析其异速生长关系。结果表明:在不同水分处理下,茵陈蒿的最佳生物量预估模型的变量选择不同;不同水分处理下茵陈蒿各器官间、各器官与地上生物量间的异速生长关系不同,但相对于自然降水量,增水和减水50%下均为等速生长,这说明在不同水分条件下茵陈蒿对各器官间的资源配置存在权衡策略,符合最优分配假说;而在极端气候条件下,各器官对资源的竞争会变弱;在荒漠草原中,对草本植物进行生物量模拟,选择预测变量和方程模型时,应考虑生长季降水量。本研究可为荒漠草原草本植物生物量预估模型的建立和异速生长关系对环境因子适应的理解等提供方法支持及理论依据。     

温室作物生物量积累率二阶差分模型

为了研究温室作物生物量积累的变化过程,本文构建了一类二阶差分模型,该模型具有有界性、单调性与全局渐近稳定性.对实验数据的模拟表明,该模型能很好解释温室黄瓜生物量轨迹运动趋势与干重积累率增长特性,比原有的生长模型拟合效果好.     

北京松山不同龄级天然油松林生物量分配格局及其影响因子

北京松山自然保护区拥有华北地区唯一的天然油松林,通过对松山8块不同林龄天然油松林样地生物量分配格局进行调查,利用RDA分析和方差分解的方法探究环境因子对各器官生物量分配格局的影响,研究发现:(1)乔木层生物量随着林龄增大而增加,40、55、70、95年生林分乔木层生物量分别为116.96、132.31、144.86、170.82 t·hm-2,各器官(根、叶、干材、枝条)生物量随着林龄的增大也呈现增长趋势,但各器官的生物量分配比在各个林龄无明显差异(P0.05);(2)林龄与乔木层各器官生物量之间两两呈显著线性正相关。(3)环境因子前两个主成分对乔木层、灌木层、草本层生物量分配格局方差解释程度分别为:96.79%、46.04%、86.80%。在乔木层、草本层生物量分配格局的方差解释上,土壤因子模型的独立作用要远大于地形模型,在灌木层生物量分配格局的方差解释上,地形因子模型的独立作用要远大于土壤因子模型。     

油菜地上部干物质分配与产量形成模拟模型

利用油菜器官生长与发育进程及环境因子之间的定量关系,构建了基于分配指数的油菜地上部器官干物质分配动态模拟模型.各器官干物质分配指数随着生理发育时间而变化,基因型、播期、氮素及水分水平影响各器官干物质在地上部分配的大小.其中,氮素营养水平对绿色叶片干物质分配影响最大,氮素营养水平越高,绿色叶片分配指数越大;播期影响角果分配指数,晚播的角果分配指数高于早播.模型引入氮素营养指数、水分及播期影响因子来定量油菜各器官在实际生产条件下的分配强度,同时考虑了品种遗传特性的影响.通过不同品种氮肥处理试验建立模型,利用不同品种播期试验资料对模型进行了初步检验,表明模型具有较好的预测性和适用性.     

APSIM模型对华北平原小麦-玉米连作系统的适用性

利用中国科学院禹城试验站1999—2001年大田试验及2002—2003年水分池处理数据进行APSIM模型参数的调试及验证,检验其对华北地区冬小麦-夏玉米连作系统的适用性.模型调试和验证结果表明:禹城1999—2000年大田试验的作物叶面积指数、生物量和土壤含水量模拟结果的平均误差分别为27.61%、24.59%和7.68%,2000—2001年分别为32.65%、35.95%和10.26%;2002—2003年高水分处理的作物叶面积指数和生物量模拟结果的平均误差分别为26.65%和14.52%,低水分处理分别为23.91%和27.93%.叶面积指数、生物量的模拟值和实测值拟合较好,除2000—2001年叶面积指数的决定系数为0.78外,其他处理均大于0.85.表明APSIM模型在模拟华北地区小麦-玉米连作系统的作物生物量和土壤水分方面具有较好的准确性,对叶面积指数模拟误差稍大.     

玉米叶面积指数动态模拟的最适野外观测资料

基于锦州农田生态系统野外观测站2005-2011年多个品种的玉米大田试验资料,结合已经建立的玉米叶面积指数动态普适模型,探讨了准确模拟玉米叶面积指数动态所需的最适野外观测资料.结果表明: 准确模拟玉米叶面积指数动态至少需要3年的野外观测数据,且每年在生育期内至少需要进行4次观测.玉米生育期内的理想观测应为在出苗后20 d左右进行第1次观测,此后每月观测1次.
     

Carbon and nitrogen dynamics in bioenergy ecosystems: 1. Model development,validation and sensitivity analysis

Biofuel made from conventional (e.g., maize (Zea mays L.)) and cellulosic crops (e.g., switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus × giganteus)) provides alternative energy to fossil fuels and has been considered to mitigate greenhouse gas emissions. To estimate the large‐scale carbon and nitrogen dynamics of these biofuel ecosystems, process‐based models are needed. Here, we developed an agroecosystem model (AgTEM) based on the Terrestrial Ecosystem Model for these ecosystems. The model was incorporated with biogeochemical and ecophysiological processes including crop phenology, biomass allocation, nitrification, and denitrification, as well as agronomic management of irrigation and fertilization. It was used to estimate crop yield, biomass, net carbon exchange, and nitrous oxide emissions at an ecosystem level. The model was first parameterized for maize, switchgrass, and Miscanthus ecosystems and then validated with field observation data. We found that AgTEM well reproduces the annual net primary production and nitrous oxide fluxes of most sites, with over 85% of total variation explained by the model. Local sensitivity analysis indicated that the model sensitivity varies among different ecosystems. Net primary production of maize is sensitive to temperature, precipitation, cloudiness, fertilizer, and irrigation and less sensitive to atmospheric CO₂ concentrations. In contrast, the net primary production of switchgrass and Miscanthus is most sensitive to temperature among all factors. Nitrous oxide fluxes are sensitive to management in maize ecosystems, and sensitive to climate factors in cellulosic ecosystems. The developed model should help advance our understanding of carbon and nitrogen dynamics of these biofuel ecosystems at both site and regional levels.     

Plastic responses in the metabolome and functional traits of maize plants to temperature variations

Environmentally inducible phenotypic plasticity is a major player in plant responses to climate change. However, metabolic responses and their role in determining the phenotypic plasticity of plants that are subjected to temperature variations remain poorly understood. The metabolomic profiles and metabolite levels in the leaves of three maize inbred lines grown in different temperature conditions were examined with a nuclear magnetic resonance metabolomic technique. The relationship of functional traits to metabolome profiles and the metabolic mechanism underlying temperature variations were then explored. A comparative analysis showed that during heat and cold stress, maize plants shared common plastic responses in biomass accumulation, carbon, nitrogen, sugars, some amino acids and compatible solutes. We also found that the plastic response of maize plants to heat stress was different from that under cold stress, mainly involving biomass allocation, shikimate and its aromatic amino acid derivatives, and other non‐polar metabolites. The plastic responsiveness of functional traits of maize lines to temperature variations was low, while the metabolic responsiveness in plasticity was high, indicating that functional and metabolic plasticity may play different roles in maize plant adaptation to temperature variations. A linear regression analysis revealed that the maize lines could adapt to growth temperature variations through the interrelation of plastic responses in the metabolomes and functional traits, such as biomass allocation and the status of carbon and nitrogen. We provide valuable insight into the plastic response strategy of maize plants to temperature variations that will permit the optimisation of crop cultivation in an increasingly variable environment.     

Root to shoot ratio of crops as influenced by CO2

Crops of tomorrow are likely to grow under higher levels of atmospheric CO₂. Fundamental crop growth processes will be affected and chief among these is carbon allocation. The root to shoot ratio (R:S, defined as dry weight of root biomass divided by dry weight of shoot biomass) depends upon the partitioning of photosynthate which may be influenced by environmental stimuli. Exposure of plant canopies to high CO₂ concentration often stimulates the growth of both shoot and root, but the question remains whether elevated atmospheric CO₂ concentration will affect roots and shoots of crop plants proportionally. Since elevated CO₂ can induce changes in plant structure and function, there may be differences in allocation between root and shoot, at least under some conditions. The effect of elevated atmospheric CO₂ on carbon allocation has yet to be fully elucidated, especially in the context of changing resource availability. Herein we review root to shoot allocation as affected by increased concentrations of atmospheric CO₂ and provide recommendations for further research. Review of the available literature shows substantial variation in R:S response for crop plants. In many cases (59.5%) R:S increased, in a very few (3.0%) remained unchanged, and in others (37.5%) decreased. The explanation for these differences probably resides in crop type, resource supply, and other experimental factors. Efforts to understand allocation under CO₂ enrichment will add substantially to the global change response data base.Abbreviations R:S root to shoot ratio, dry weight basis     

A simulation model of Bouteloua gracilis biomass dynamics on the North American shortgrass prairie

Summary A grassland primary producer model for simulating intraseasonal biomass dynamics as a function of temperature, moisture, light, and nitrogen was developed for Bouteloua gracilis (H.B.K.) Lag., the dominant C₄ grass of the North American shortgrass prairie. Plant state variables included young and mature leaves, crowns, and roots from three depth categories while simulated processes included spring regrowth, photosynthesis, respiration, photosynthate allocation, death, and litterfall. Sensitivity analyses revealed the model was most sensitive to changes in photosynthesis and photosynthate allocation and least sensitive to changes in initial values of state variables, leaf dark respiration rates, and rate of spring regrowth.An abiotic submodel driven by observed weather data was used in conjunction with the primary producer model to simulate plant biomass dynamics under a variety of conditions including untreated controls (C), nitrogen fertilization (F), irrigation (I), and irrigation plus fertilization (IF). Model predictions of life shoot biomass (B _s) and annual aboveground net primary production (NPP _A) followed the same trends as field measurements with B _sand NPP _Aof IF>I>F>C. Failure of the model to accurately predict measured declines in peak B _sand NPP _Aafter several years of irrigation may have been caused by failure to account for growth lags following water stress, inadequate simulation of interspecific competition, or failure to simulate response to some mineral nutrients which had become limiting after several years of this treatment. A simulated annual carbon budget for plants in the four treatments suggests that from 61% (IF) to 80% (C) of the net carbon fixed above ground is ultimately translocated and utilized below ground.     

不同促腐条件下秸秆还田对土壤微生物量碳氮磷动态变化的影响

通过2年田间定位试验,研究了冀东地区小麦 玉米轮作制度下,不同促腐条件下玉米秸秆配施化肥直接还田对土壤微生物量C、N、P动态变化的影响,并讨论了其与土壤养分和酶活性的关系.结果表明,秸秆配施化肥并调节其C/N条件下,施用促腐剂处理作物各生育期土壤微生物量C、N、P均表现出高于未施用处理的趋势,并使微生物量N、P达到高峰期的时间提前,对土壤养分调控效果较好.土壤微生物量C、N、P与土壤酶活性在作物各生育期均表现为显著和极显著正相关关系,但与土壤碱解氮、有效磷的相关性受到施肥制度和作物生长的强烈影响.     

Using a Crop Growth Model to Quantify Regional Biogas Potentials: an Example of the Model Region Biberach (South-West Germany)

Over the last decade, political framework conditions in the energy sector provoked a strong focus on biogas production in Germany. In this context, a sufficient and secure regional biomass supply is needed in order to run biogas plants economically. It is important to estimate which biomass amounts can be produced and are available for bioenergy production in a defined region. The present study focused on a model-based approach quantifying the biomass and, from this, the resulting biogas potential of the model region of Biberach (south-west Germany) using the process-oriented crop growth model DSSAT 4.0. Considering the regional soil and climate conditions of the model region, dry matter yields of maize, triticale, and a crop rotation system (CRS) of maize and triticale including different management systems (change in sowing and harvest date) were simulated. The results indicated an adequate model fit between simulated and measured yields. Dry matter yields of maize (14.7 t ha^?1), triticale (12.7 t ha^?1), and the CRS (18.1–19.2 t ha^?1) differed significantly, indicating that the chosen CRS provided the highest dry matter yields. The biomass potential of all crops was simulated considering different bioenergy scenarios depending on the available agricultural land used for bioenergy. The highest biomass potential was provided by the management system consisting of maize and triticale sown on 1 May and 15 October, respectively. Finally, an additional energy potential of 45,000 kW_el (bioenergy scenario 50/50 % of the agricultural land used for biogas production) and of 5,700 kW_el (bioenergy scenario 25/25 % of the agricultural land used for biogas production) was determined for the county of Biberach by implementing a CRS, which consisted of maize and triticale. It could be concluded that an additional biomass potential for biogas production exists in the county. Suitable areas for the location of biogas plants could be identified based on the available biomass potential.