基于区域剖分算法的土壤碳通量空间采样策略

由于土壤碳通量在空间分布上具有很强的异质性,传统的采样方法难以对区域土壤碳通量进行精确估算,因此确定适当的采样策略对区域土壤碳通量的估算具有重要意义.本文提出一种逐点递增式采样的区域剖分部署策略(RDPG):设定初始采样点,使用改进的凸包插值算法构造Delaunay三角网,根据邻近已知采样点插值计算三角形各边垂直平分线的交点的离散度,选择离散度最大的点作为新增采样点.采用该方法对变异系数为0.42～0.59的仿真试验区域进行多次试验,结果表明:在相同试验条件下,RDPG布局策略能够获得比随机采样和均匀采样策略更高的区域土壤碳通量估算准确度.RDPG方法考虑了区域土壤碳通量的空间异质性,提高了区域土壤碳通量拟合精度.     

基于湿度分布特征的小尺度土壤碳通量空间采样策略

由于土壤碳通量的空间异质性很强,传统的随机抽样方法无法对区域土壤碳通量进行准确估算,而多点采样需耗费大量的人力及设备成本,因此确定适当的采样点数量及分布策略对于区域土壤碳通量的测算非常重要。提出一种基于湿度空间分布特征的小尺度土壤碳通量空间采样策略:首先利用无线传感网密集测量区域的土壤湿度,根据湿度数据的空间分布特征划分监测区域,通过Hammond Mc Cullagh方程计算各子区域内的最优采样点数量,最终确定整个监测区域的空间采样点部署策略。提出的方法考虑了各子区域间土壤碳通量空间分布的差异,使得采样点的部署位置与土壤碳通量的分布具有较好的相关性。研究结果证明:土壤碳通量部署策略能够获得比均匀部署策略、随机部署策略更高的区域土壤碳通量估算准确度。     

青藏高原土壤碳储量及其影响因素研究进展

青藏高原是全球变化的敏感区,也是泛第三极地区气候变化的启动区。青藏高原土壤碳作为生态系统碳库的重要组成部分,对生态系统碳循环过程具有非常重要的作用。目前,对青藏高原土壤碳储量的估算仍存在很大的不确定性。为此,本文综述了近30年来关于青藏高原土壤碳储量研究,比较不同研究的土壤碳储量估算结果,以固有因子和变化因子两类影响因素作为切入点,分析了土壤碳储量时空分异规律。从估算模型和方法看,CENTURY和TEM模型综合考虑了影响土壤碳储量的多种机理过程,结果可信度高于EVI、NDVI模型以及插值估算法。青藏高原草地土壤表层(0～20 cm)有机碳储量约10 Pg C(1 Pg=10~(15)g)。高原冻土区土壤有机碳储量(0～200 cm)约16.5 Pg C,土壤无机碳储量(0～100 cm)约14 Pg C。青藏高原土壤碳储量沿东南向西北方向逐渐降低,而关于变化因子对青藏高原土壤碳储量的作用规律还没有一致的认识。此外,采样点选择、数据源选择、估算深度以及估算方法等影响了青藏高原土壤碳储量估算结果的精确性。未来青藏高原土壤碳储量研究应建立土壤碳储量估算标准来提高结果的可比性;同时增大采样区、采样量以及采样深度并保障采样周期的时间连贯性等,有效减少土壤碳储量估算不确定性。以期更好地理解和预测未来青藏高原生态系统对气候变化的响应。     

土壤有机碳库的关键影响因素及其不确定性

土壤是陆地生态系统最大的有机碳库,比植被碳库或大气碳库的两倍还多。准确评估土壤有机碳库是预测全球变化与土壤有机碳之间反馈关系的关键。但目前对土壤有机碳库的估算还存在很大不确定性。该文综述了土壤有机碳库估算及其影响因素和土壤有机碳库估算不确定性的来源和常用的采样方法,以及计算土壤碳汇的最新研究进展。未来技术进步以及模型的不断完善可能会降低土壤有机碳库估算的不确定性,提高其估算的精度     

地形和采样数量对浙江省森林凋落物碳密度插值精度的影响

将浙江省分成平原沿海地区、丘陵-盆地和山地3个地形单元,研究地形和采样数量对浙江省森林凋落物碳密度克里格插值精度的影响.结果表明:浙江省平原沿海地区、丘陵-盆地和山地的森林凋落物碳密度半变异函数基台效应在28.3％～72.4％之间,具有中等空间相关性;不同地形的克里格插值精度高低顺序为平原沿海地区＞丘陵-盆地＞山地,随着地形复杂程度增加,其插值精度降低;同一地形单元内的克里格插值精度随采样数量增加而提高,以山地的插值精度提高最为明显.在地形复杂区域有必要设置较多的采样点以提高插值的精度.     

应用高频观测探讨不同森林经营方式下矿质土壤呼吸的昼夜动态特征

矿质土壤呼吸是森林生态系统土壤碳库损失的重要途径之一,也是森林生态系统碳(C)平衡估算中的关键因子。了解矿质土壤呼吸在不同时间尺度上的变化,对理解森林生态系统C循环应对全球变化的响应至关重要,而高频观测是探讨矿质土壤呼吸在不同时间尺度变化的重要手段之一。通过高频自动观测系统与Li-8100土壤CO2通量测量系统,对福建省三明市陈大镇国有林场的米槠(Castanopsis carlesii)次生林在不同森林经营方式下(CK对照,RR皆伐,RB火烧)的矿质土壤呼吸与土壤温度和含水量的昼夜动态进行分析,并比较2种采样策略下矿质土壤呼吸的年、日均通量差异。结果表明:1)不同森林经营方式的矿质土壤呼吸与土壤温度和土壤含水量均存在着明显的季节动态,矿质土壤呼吸速率年均值表现为CK(2.18μmol m~(-2)s~(-1))RB(1.93μmol m~(-2)s~(-1))RR(1.89μmol m~(-2)s~(-1))。2)在不同森林经营方式下,采用手动观测的矿质土壤呼吸年平均日通量显著低于高频观测结果,而采用高频观测09:00—11:00时间段内观测数据计算日通量与高频自动观测系统全天(24h)结果无显著差异;3)不同森林经营方式下的林地,土壤水热条件的变化是影响矿质土壤呼吸的重要因素之一。双因子模型拟合结果表明,土壤温度和含水量共同解释了CK、RR和RB矿质土壤呼吸速率的年变化的96.8%,62.8%,95.4%,拟合结果明显优于以温度为单因子的指数模型。因此,未来气候变化背景下,为准确评估和预测不同森林经营方式对土壤与大气间碳通量交换的影响,采用高频自动观测技术观测矿质土壤呼吸,将有利于提高碳通量估算精度。     

中国陆地土壤有机碳蓄积量估算误差分析

简要介绍了土壤碳蓄积量的计算方法,包括土壤类型法、植被类型法、生命地带法、相关关系法和模型方法,以及土壤有机碳蓄积量的误差分析方法．根据中国策二次土壤普查2473个典型土种剖面数据,采用土壤类型法和两种碳密度方法计算,估算的中国陆地土壤有机碳蓄积量处于615.19×10^14-1211.37×10^14g之间,平均碳密度为10．49-10．53kg·m^-2(土壤厚度为100cm)或11．52-12．04kg·m^-3(土壤平均厚度为88cm),土壤平均碳蓄积量为913．28±298．09×10^14g,估算的不确定性在20％～50％之间．其中,土壤碳计算和采样数量的差异是导致土壤碳蓄积量估算不确定性的重要因素。     

天目山常绿落叶阔叶混交林土壤温室气体排放特点

采用静态箱-气象色谱法, 将试验样地按照自上而下分为A、B、C、D 四个梯度的采样点。研究了浙江天目山常绿落叶阔叶混交林2013 年3 月-11 月期间土壤温室气体排放的时空变化特点, 并分析了不同梯度的土壤温湿度与气体排放通量的相关性。结果表明: (1)天目山常绿落叶阔叶混交林土壤CO₂ 和CH₄ 两种温室气体排放/吸收季节变化特征较一致, 即夏季>春季>秋季; N₂O 排放通量季节变化表现为夏季>秋季>春季。其中, CO₂ 和N₂O 表现为土壤的排放源, CH₄ 为大气的吸收汇。(2)空间上, CO₂ 通量大小表现为: D 采样点> A 采样点> C 采样点 > B 采样点; 土壤对CH4吸收速率表现为A 采样点 > C 采样点 > B 采样点 > D 采样点; 土壤N₂O 通量大小依次为: A 采样点 > C 采样点 > B采样点 > D 采样点。(3)温度是影响天目山常绿落叶阔叶混交林土壤CO₂ 通量重要因子; CH₄ 的吸收通量随温度的升高和湿度的降低而增大; 在海拔较低的地区, 温度是N₂O 通量的重要影响因子, 海拔较高地区, 湿度是N₂O 通量的重要限制因子。     

藏香猪放牧对滇西北高原湿地土壤CO2通量的影响

高原湿地是生态系统中重要的碳汇。土壤CO_2通量作为高原湿地生态系统碳收支的重要组成部分,碳的释放对区域碳平衡发挥着重要的作用。藏香猪放牧是我国高海拔藏区一种特有的放牧方式,是导致高原湿地土壤退化的重要干扰因素之一,并影响着土壤CO_2通量的变化。采用土壤CO_2通量自动测量系统(LI-8100A,LI-COR,USA),分别在不同季节对滇西北布伦、哈木谷、伊拉草原上藏香猪干扰和对照(非干扰土壤)CO_2通量变化进行监测,研究发现,藏香猪干扰型放牧降低了土壤CO_2排放通量,且表现出明显的日波动变化特征。相比旱季,雨季不同放牧方式影响下的土壤CO_2通量差异性更为明显,其中布伦、哈木谷、伊拉草原较对照分别降低了70.4%、87.5%、60.7%。CO_2排放通量与土壤理化性状及植物生物量的回归分析表明,对照样地的土壤容重、孔隙度、pH、总活性碳、植物生物量与土壤CO_2通量具有显著的相关性(P0.01)。通过植物-土壤指数(plant-soil index,PSI)分析了藏香猪干扰型放牧对高原湿地的影响,总体来看,对照样地中土壤CO_2通量与PSI之间具有较好的线性关系,可以用来很好的预测未来高原湿地土壤CO_2通量的变化。该研究结果不仅有效估算了强干扰放牧影响下的高原湿地土壤碳排放量,而且为加强藏香猪放牧的科学管理,高原湿地生态系统的保护、恢复及重建提供了理论支持。     

黄土高原年均降水量空间插值及其方法比较

采用不同空间插值方法(普通克里格法OK、反距离权重法IDW和径向基函数法RBF),对黄土高原地区85个气象站点1957—2013年逐日降水数据进行年均降水量空间插值分析,采用平均绝对误差(MAE)、均方根误差(RMSE)、Pearson相关系数(R)以及准确度(AC)对插值结果进行对比,研究不同方法对该地区年均降水量插值结果的影响.结果表明:研究期间,黄土高原地区年均降水量的Moran I值为0.67,各站点年均降水量存在较强的空间自相关性.63个预测站点和22个检验站点的验证结果显示,3种方法的实测值和预测值均显著相关,但反距离权重法和径向基函数法的平均绝对误差(MAEIDW=38.98,MAERBF=34.61)和均方根误差(RMSEIDW=51.49,RMSERBF=43.79)均高于普通克里格法.通过普通克里格法的不同半变异函数模型(环形模型、球体模型、指数模型、高斯模型)对比发现,环形模型的平均绝对误差最小(MAE=32.34),准确度最高(AC=0.976),指数模型平均绝对误差最大(MAE=33.24).综合对比不同插值方法实测值与估算值的验证结果表明,采用半变异函数为环形模型的普通克里格法是进行黄土高原年均降水量插值较好的方法.     

Optimal sampling of a population to determine QTL location, variance, and allelic number

In a population intended for breeding and selection, questions of interest relative to a specific segregating QTL are the variance it generates in the population, and the number and effects of its alleles. One approach to address these questions is to extract several inbreds from the population and use them to generate multiple mapping families. Given random sampling of parents, sampling strategy may be an important factor determining the power of the analysis and its accuracy in estimating QTL variance and allelic number. We describe appropriate multiple-family QTL mapping methodology and apply it to simulated data sets to determine optimal sampling strategies in terms of family number versus family size. Genomes were simulated with seven chromosomes, on which 107 markers and six QTL were distributed. The total heritability was 0.60. Two to ten alleles were segregating at each QTL. Sampling strategies ranged from sampling two inbreds and generating a single family of 600 progeny to sampling 40 inbreds and generating 40 families of 15 progeny each. Strategies involving only one to five families were subject to variation due to the sampling of inbred parents. For QTL where more than two alleles were segregating, these strategies did not sample QTL alleles representative of the original population. Conversely, strategies involving 30 or more parents were subject to variation due to sampling of QTL genotypes within the small families obtained. Given these constraints, greatest QTL detection power was obtained for strategies involving five to ten mapping families. The most accurate estimation of the variance generated by the QTL, however, was obtained with strategies involving 20 or more families. Finally, strategies with an intermediate number of families best estimated the number of QTL alleles. We conclude that no overall optimal sampling strategy exists but that the strategy adopted must depend on the objective.Communicated by P. Langridge     

Comparing the closed static versus the closed dynamic chamber flux methodology: Implications for soil respiration studies

Soil respiration is the largest C-flux component in the terrestrial carbon (C) cycle, yet in many biomes this flux and its environmental responses are still poorly understood. Several methodological techniques exist to measure this flux, but mostly there remain comparability uncertainties. For example, the closed static chamber (CSC) and the closed dynamic chamber (CDC) systems are widely used, but still require a rigorous comparison. A major issue with the CSC approach is the generally long manual gas sampling periods causing a potential underestimation of the calculated fluxes due to an asymptotic increase in headspace CO₂ concentrations. However, shortening the sampling periods of the static chamber approach might provide comparable results to the closed dynamic chamber system. We compared these two different chamber systems using replicated CSC cover boxes and a Li-Cor 8100 CDC system under field conditions, and performed tests on both, mineral and peat soil. Whereas the automated CDC system calculated fluxes during the first two minutes, the CSC approach considered either all seven manual sampling points taken over 75?min, or only the first three sampling points over 15?min. Although flux variation was fairly large, there were considerable and statistically significant differences between the calculated fluxes considering the two chamber systems, yet this depended on soil type and the number of CSC sampling time points. The cover-box approach underestimated the chamber-based fluxes by 30% for combined samples, 21% for mineral and 39% for peat soils when calculated over 75?min but was comparable over the first 15?min. The chamber flux comparison demonstrates that the CSC approach can provide CO₂ flux measurements comparable to the CDC system when sampling at an appropriate initial frequency, preventing flux underestimation due to a build up of CO₂ headspace concentrations.     

Seasonal and spatial variability of soil respiration in four Sitka spruce stands

We investigated the causes for the seasonal and spatial variation of soil respiration in a first rotation Sitka spruce chronosequence composed of four age classes (10, 15, 31, and 47 year old) in Central Ireland. The study aimed at identifying easily determinable environmental parameters that explained the variation in soil respiration rates. The variation in temperature and soil water content influenced the seasonal trend observed in the spatial variability of soil respiration. The highest coefficients of variation in soil respiration were observed during autumn drought, while lower coefficients were generally observed during periods with highest soil respiration rates. On average, the sampling strategy of 30 sampling points per stand was adequate to obtain an average rate of soil respiration within 20% of its actual value at the 95% confidence level. Significantly higher soil respiration rates were observed at locations with high accumulation of organic matter and in collars established in close vicinity to tree stems. The organic layer thickness was the only variable that yielded significant regressions for explaining spatial variation in soil respiration in all the stands. Correlation analyses between the studied variables and soil respiration suggested the relative importance of heterotrophic and autotrophic components differed in their annual contribution to total soil respiration at each forest stand. Multiple regression analyses were used to assess the relative importance of primary temporal and spatial controls over soil respiration. Soil temperature and organic layer thickness explained most of the variance of soil respiration for the different sampling periods, while soil water content had a weaker effect as well as a different influence on soil respiration depending on the time of the year. The strong linear correlation between forest floor carbon and soil carbon stock further confirmed organic layer thickness as an integrative factor encompassing the effect of soil carbon pools on soil respiration. Moreover, its inclusion in the multiple regression analyses overrode the influence of both distance and fine root biomass. Overall, a multiple linear regression model driven by easily determinable environmental variables such as soil temperature, organic thickness, soil water content, soil bulk density, and soil organic carbon concentration allowed us to explain 54% of total variance of soil respiration over the different stand ages for the entire year (P < 0.05). Our results show that the adoption of an adequate sampling strategy, and the determination of some key environmental variables may help to explain a large proportion of total variation of soil respiration over the entire rotation length of afforested ecosystems.     

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442–887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30‐year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios.     

Error propagation in constraint-based modeling of Chinese hamster ovary cells

Chinese hamster ovary (CHO) cells are the most popular mammalian cell factories for the production of glycosylated biopharmaceuticals. To further increase titer and productivity and ensure product quality, rational system-level engineering strategies based on constraint-based metabolic modeling, such as flux balance analysis (FBA), have gained strong interest. However, the quality of FBA predictions depends on the accuracy of the experimental input data, especially on the exchange rates of extracellular metabolites. Yet, it is not standard practice to devote sufficient attention to the accurate determination of these rates. In this work, we investigated to what degree the sampling frequency during a batch culture and the measurement errors of metabolite concentrations influence the accuracy of the calculated exchange rates and further, how this error then propagates into FBA predictions of growth rates. We determined that accurate measurements of essential amino acids with low uptake rates are crucial for the accuracy of FBA predictions, followed by a sufficient number of analyzed time points. We observed that the measured difference in growth rates of two cell lines can only be reliably predicted when both high measurement accuracy and sampling frequency are ensured.     

低丘红壤区农田水热通量变化特征及气候学足迹

农田水热通量的变化特征以及气候学足迹分析对加强区域气候资源管理和提高红壤地区水热资源利用率有重要意义.利用低丘红壤区的大孔径闪烁仪和自动气象站数据,在保证数据质量的基础上,详细分析了低丘红壤区农田在非雨季、作物生长旺期不同时间尺度水热通量的变化特征和观测通量的源区分布特征.结果表明: 水热通量的日变化呈单峰型,但与晴天相比较,多云天的日变化曲线波动更为复杂;无论是旬尺度还是月尺度, 8月的水热通量整体上都大于9月,且净辐射通量都更多地用于潜热交换,但9月潜热通量所占净辐射比例相较于8月有所减少,感热通量则相反;受气象条件(尤其是风)、稳定度和下垫面状况影响,不同时间尺度的观测通量源区特征不同;结合下垫面作物来看,不同时间尺度源区的通量贡献来源也不同.     

旱改水型农田整治对土壤碳排放的短期影响

灌溉农业可提升粮食生产潜力,已成为全球农业重要的发展方向,但此类土地利用转换势必影响旱作农田土壤的稳定性,尤其是碳循环。然而,旱改水整治过程中土壤碳通量变化及其与环境因子间的互馈机制尚不清楚。为此,采用大田模拟实验,连续7 d监测土壤碳通量变化,评估旱改水整治对土壤碳库组成及环境驱动的短期效应。结果表明：①旱地、水田的土壤碳通量和温度均呈昼高夜低的单峰型曲线,且碳通量与温度峰值出现于每日13：00前后,但水田土壤碳通量稍高于旱地。②旱改水后短期内土壤可溶性有机碳（DOC）、微生物量碳（MBC）、易氧化有机碳（EOC）、惰性有机碳（ROC）、总有机碳（TOC）和土壤碳库管理指数均呈减少趋势,其中土壤微生物量碳、易氧化有机碳降幅分别达28.55%、29.09%。③土壤含水量、微生物OTU数、碳库含量是影响碳通量速率变化的关键因子（P<0.05）,土壤温度、理化性状是制约土壤碳库的主控因子（P<0.05）。农业活动是重要的碳源之一,深入研究大范围旱改水诱发的碳排放问题可为低碳农业、气候减缓及其应对策略制定提供科学依据。     

Carbon balance along the Northeast China Transect(NECT-IGBP)

The Northeast China Transect (NECT) along a precipitation gradient wasused to calculate the carbon balance of different vegetation types, land-use practices and temporal scales. NECT consists of mixed coniferous-broadleaved forest ecosystems, meadow steppe ecosystems and typical steppe ecosystems. Analyses of the C budget were carried out with field measurement based on dark enclosed chamber techniques and alkali absorption methods, and the application of the CENTURY model. Results indicated that: (1) soil CO2 flux had a strong diurnal and seasonal variation influenced by grassland type and land-use practices. However, the seasonal variation on soil CO2 fluxes did not show obvious changes between non-grazing and grazing Leymus chinensis dominated grasslands. (2) Hourly soil CO2 fluxes mainly depended on temperature, while daily CO2 fluxes were affected bothby temperature and moisture. (3) NPP of the three typical ecosystems showed linear relationships with inter-annual precipitation, but total soil carbon of those ecosystems did not. NPP and total soil carbon values decreased westward with decreasing precipitation. (4) Model simulation of NPP and total soil carbon showed that mean annual precipitation was the major limiting factor for ecosystem productivity along NECT. (5) Mean annual carbon budget is the largest for the mixedconiferous- broadleaved forest ecosystem (503.2 gC m-2 a-1), followed by the meadow steppe ecosystem (227.1 gC m-2 a-1), and the lowest being the typical steppe ecosystem (175.8 gC m-2 a-1). This study shows that concurrent field measurements of terrestrial ecosystems including the soil and plant systems with surface layer measurements along the water-driven IGBP-NECT are valuable in understanding the mechanisms driving the carbon cycle in different vegetation types under different land-use practices. Future transect research should be emphasized.