磷高效利用野生大麦基因型筛选及其根际土壤无机磷组分特征

通过土培盆栽试验,研究了16份野生大麦种质资源在相同供磷水平下磷素吸收利用的基因型差异,探讨磷高效野生大麦根际土壤无机磷组分特征.结果表明：拔节期和扬花期磷素干物质生产效率（CV=11.6%、12.4%）、成熟期磷素籽粒生产效率（CV=13.7%）基因型间差异较大.不同生育时期磷高效基因型IS-22-30和IS-22-25生物量、磷积累量和磷素干物质生产效率均显著高于低效基因型IS-07-07,且高效基因型的籽粒产量分别是低效基因型的3.10和3.20倍.不施磷、施磷30 mg·kg^-1条件下,不同磷素利用效率野生大麦根际土壤有效磷和水溶性磷含量均显著低于非根际土壤,且高效基因型较低效基因型根际土壤水溶性磷亏缺量更大.根际与非根际土壤无机磷组分含量为Ca₁₀-P＞O-P＞Fe-P＞Al-P＞Ca₂-P＞Ca₈-P.在拔节期和扬花期,施磷30 mg·kg^-1条件下,磷高效基因型根际土壤Ca₈-P含量显著高于低效基因型,而Ca₂-P含量显著低于低效基因型;不施磷条件下,高效基因型根际土壤Ca₂-P和Ca₈-P含量均显著高于低效基因型,且根际土壤Ca₁₀-P均减少.施磷30 mg·kg^-1条件下,根际土壤Fe-P和O-P含量均表现为高效基因型显著高于低效基因型,Al-P含量则呈现相反的趋势;不施磷条件下,高效基因型根际土壤Al-P、Fe-P和O-P含量均显著低于低效基因型.低磷胁迫下,高效基因型活化吸收Ca₂-P、Al-P的能力强于低效基因型.     

基于小波变换的土壤有机质含量高光谱估测

利用统计分析方法选取了土壤N、P、K元素含量近似而有机质含量差异较大的样本60个,通过高光谱探测分析获得样本反射率对数的一阶导数光谱,采用Bior 1.3函数进行多层离散小波分解,剔除低频近似信号和高频噪声信号,得到反映土壤理化参数的特征光谱曲线;采用相关分析筛选土壤有机质含量的显著相关波段,基于显著相关波段和特征光谱曲线分别构建土壤有机质含量高光谱多元回归估测模型;通过比较分析,确定了提取土壤有机质特征光谱的最佳小波分解尺度并构建了最佳预测模型.结果表明： 提取土壤有机质特征光谱的最佳小波分解层数是9层,其次是8层和10层;基于小波9层分解特征光谱曲线的有机质含量估测模型最佳,其决定系数（R²）为0.89,比基于显著相关波段构建模型的R²增加了0.31,比基于原始光谱所构建模型的R²增加了0.10.     

基于小波变换的土壤有机质含量高光谱估测术

利用统计分析方法选取了土壤N、P、K元素含量近似而有机质含量差异较大的样本60个,通过高光谱探测分析获得样本反射率对数的一阶导数光谱,采用Bior 1.3函数进行多层离散小波分解,剔除低频近似信号和高频噪声信号,得到反映土壤理化参数的特征光谱曲线;采用相关分析筛选土壤有机质含量的显著相关波段,基于显著相关波段和特征光谱曲线分别构建土壤有机质含量高光谱多元回归估测模型;通过比较分析,确定了提取土壤有机质特征光谱的最佳小波分解尺度并构建了最佳预测模型.结果表明:提取土壤有机质特征光谱的最佳小波分解层数是9层,其次是8层和10层;基于小波9层分解特征光谱曲线的有机质含量估测模型最佳,其决定系数(R2)为0.89,比基于显著相关波段构建模型的R2增加了0.31,比基于原始光谱所构建模型的R2增加了0.10.     

一种青海湖流域消除植被光谱对土壤光谱影响的土壤有机质含量遥感估算方法

基于遥感技术手段快速测定区域尺度土壤有机质含量(SOM), 对气候、陆地生态系统和农业等领域具有重要的作用和意义。但现有的多光谱遥感影像因其波段宽度较窄, 包含的土壤有机质信息有限, 导致其估算结果的可靠性与精度较低。为此, 以青海湖流域为实证试验区, 将2016 年9 月底(此时, 青海湖流域牧草等植被停止生长, 土壤有机质积累达到全年最高)地面采集并测定的土壤有机质含量数据与同时期MODIS 黑空BRDF/Albedo 产品的宽、窄波段进行了对比与检验。发现: BRDF/Albedo 宽波段的相关性(近红外、短波波段相关系数分别为0.704 和 0.670)高于窄波段相关性(第2, 5, 6 波段的相关系数分别是0.583、0.631 和0.625), 证实了宽波段含有更加丰富、完整的土壤有机质含量信息。为了进一步提高SOM 估算的精度, 基于梯形方法构建了宽波段近红外反照率/植被覆盖度梯形特征空间,从宽波段近红外反照率(包含植被、土壤混合光谱)中成功分离出裸土反照率, 并分别构建了SOM 遥感估算模型。经验证,消除了植被对土壤光谱影响的裸土反照率模型精度(均方根误差为16.87、平均绝对百分比误差为30.0%, 希尔不等系数为0.22)高于宽波段近红外反照率模型精度(均方根误差为20.12、平均绝对百分比误差为31.0%, 希尔不等系数为0.27)。该方法简单易操作, 不仅有助于提高表层土壤有机质含量遥感估算的精度, 也可为土壤其他属性如N, P等元素含量的遥感估算提供了新思路。     

Impact of elevated CO2 on soil organic matter dynamics as related to changes in aggregate turnover and residue quality

Increasing global atmospheric CO₂ concentration can potentially affect C cycling in terrestrial ecosystems. This study was conducted to assess the impact of elevated CO₂ concentration on soil organic matter and aggregate dynamics in Lolium perenne and Trifolium repens pastures. Soil samples from a 6 year old `free air CO₂ enrichment' (FACE) experiment were separated in four aggregate size classes (<53, 53–250, 250–2000, and > 2000 m). Free light fraction (i.e. particulate organic matter (POM) outside of aggregates; free LF) and intra-aggregate-POM (i.e. POM occluded within the aggregate structure; iPOM) were isolated. The distinct ¹³C-signature of the CO₂ used to raise the ambient CO₂ concentration in FACE allowed us to calculate proportions of recently incorporated C (< 6 yr) in the physically defined soil fractions. The proportion of new C increased with increasing aggregate size class, except the two largest aggregate size classes had a similar proportion of new C; this indicates a faster turnover of macroaggregates compared to microaggregates. In addition, higher proportions of new C in macroaggregates under T. repens compared to L. perenne indicate a faster macroaggregate turnover under T. repens. This faster macroaggregate turnover is hypothesized to be a result of the higher residue quality (C:N ratio) of T. repens compared to L. perenne and reduces the potential of sequestering C under elevated CO₂. In the L. perenne soil, elevated CO₂ did not significantly increase total C, but led to: (1) a 54% increase in aggregation and (2) a 40% increase in total iPOM-C. It is hypothesized that the sequestration of iPOM-C induced by elevated CO₂ in the low residue quality, L. perenne treatment, resulted from an increase in the proportion of large macroaggregates with a slow turnover.     

A new approach to estimating the pool of stable organic matter in soil using data from long-term field experiments

It is a necessity to have a successful method to separate, quantify and define the active and passive soil organic matter pools for appropriate verification of models. In this study, the organic carbon content of long-term bare fallow soils was used as an indicator of the size of the stable soil organic matter pool. Although soil texture and soil structure are widely accepted as having an influence on the stable pool, most soil organic models neglect the relationship between soil structure and carbon stabilization. Therefore, the aim of this presentation is to estimate the size of the stable carbon pool and to relate it to soil texture and structure properties. It was calculated that over 50 yr, under bare fallow conditions, the relative decrease in the amount of carbon (C) for the most stable pools ranged between 2 and 12%. In comparison, for the less stabilized pools the relative decrease was calculated from 50 to 100%. This indicates that the organic carbon content of long-term bare fallow soils should be very similar to the size of the most stable C pool. We also observed that the amounts of carbon associated with primary particles <20 μm for numerous soils with contrasting carbon content, soil texture, and management practices showed a lower and an upper limit. Both these limits and the carbon content of long-term bare fallow soils (which were assumed to be similar to the size of the stable pool) were related to the content of primary particles <20 μm in the soil. To calculate these relationships, an equation was used including one term to describe the influence of soil texture and another to describe that of soil structure. The calculated regression for the bare fallow soils corresponded very well to the lower limit of carbon content associated with primary particles <20 μm. The upper limit was estimated only by increasing the regression parameter which is related to the amount of C per unit primary particles <20 μm. Considering the many published results of the influence of soil texture and structure on carbon stabilization processes in soil, the stable pool may be defined as the capacity of soils to sorb C. The upper limit of carbon content associated with primary particles <20 μm may be interpreted as the capacity of soil to protect C. This revised version was published online in June 2006 with corrections to the Cover Date. This revised version was published online in June 2006 with corrections to the Cover Date. This revised version was published online in June 2006 with corrections to the Cover Date.     

Influence of rhizodeposition under elevated CO2 on plant nutrition and soil organic matter

Atmospheric CO₂ concentrations can influence ecosystem carbon storage through net primary production (NPP), soil carbon storage, or both. In assessing the potential for carbon storage in terrestrial ecosystems under elevated CO₂, both NPP and processing of soil organic matter (SOM), as well as the multiple links between them, must be examined. Within this context, both the quantity and quality of carbon flux from roots to soil are important, since roots produce specialized compounds that enhance nutrient acquisition (affecting NPP), and since the flux of organic compounds from roots to soil fuels soil microbial activity (affecting processing of SOM).From the perspective of root physiology, a technique is described which uses genetically engineered bacteria to detect the distribution and amount of flux of particular compounds from single roots to non-sterile soils. Other experiments from several labs are noted which explore effects of elevated CO₂ on root acid phosphatase, phosphomonoesterase, and citrate production, all associated with phosphorus nutrition. From a soil perspective, effects of elevated CO₂ on the processing of SOM developed under a C4 grassland but planted with C3 California grassland species were examined under low (unamended) and high (amended with 20 g m^–2 NPK) nutrients; measurements of soil atmosphere 13C combined with soil respiration rates show that during vegetative growth in February, elevated CO₂ decreased respiration of carbon from C4 SOM in high nutrient soils but not in unamended soils.This emphasis on the impacts of carbon loss from roots on both NPP and SOM processing will be essential to understanding terrestrial ecosystem carbon storage under changing atmospheric CO₂ concentrations.Abbreviations SOM soil organic matter - NPP net primary productivity - NEP net ecosystem productivity - PNPP p-nitrophenyl phosphate     

Selenium uptake by plants as a function of soil type,organic matter content and pH

In pots containing sandy soils at two levels (pH 5 and 7) to which 0.5 mg Se L^-1 soil had been added, an increase in the proportion of clay soil or peat soil led to a decrease in the uptake of Se by spring wheat grain (Triticum aestivum L., var. Drabant) and winter rape plants (Brassica napus L., var. Emil). The effect was most pronounced for the smallest additions of clay and peat soils. Differences in Se uptake between the two pH levels were greatest in treatments where the additions of clay and peat soils were small. At the high pH, an increase in clay content from 7% to 39% resulted in a decrease in Se uptake of 79% for wheat and 70% for rape. At the low pH, the uptake decreased by 72% and 77%, respectively. At the higher pH, an increase in the content of organic matter from 1.4% to 39% resulted in decreases in Se uptake of 88% for wheat grain and 69% for rape. At the low pH, Se uptake decreased by 63% and 48%, respectively. Adding peat soil to clay soil had little effect on Se uptake. Among the limed, unmixed clay, sand and peat soils to which Se had not been added, uptake was highest from the sandy soil, i.e. 8.3 ng Se/g wheat grain and 42 ng Se/g rape. The lowest uptake rates were obtained in the clay soil, i.e. 3.0 ng Se/g for wheat grain and 9.0 ng Se/g for rape.     

Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index

Accurate estimates of the spatial variability of soil organic matter (SOM) are necessary to properly evaluate soil fertility and soil carbon sequestration potential. In plains and gently undulating terrains, soil spatial variability is not closely related to relief, and thus digital soil mapping (DSM) methods based on soil–landscape relationships often fail in these areas. Therefore, different predictors are needed for DSM in the plains. Time-series remotely sensed data, including thermal imagery and vegetation indices provide possibilities for mapping SOM in such areas. Two low-relief agricultural areas (Peixian County, 28 km × 28 km and Jiangyan County, 38 km × 50 km) in northwest and middle Jiangsu Province, east China, were chosen as case study areas. Land surface diurnal temperature difference (DTD) extracted from moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), and soil-adjusted vegetation index (SAVI) at the peak of growing season calculated from Landsat ETM+ image were used as predictors. Regression kriging (RK) with a mixed linear model fitted by residual maximum likelihood (REML) and residuals interpolated by simple kriging (SK) were used to model and map SOM spatial distribution; ordinary kriging (OK) was used as a baseline comparison. The root mean squared error, mean error and mean absolute error calculated from leave-one-out cross-validation were used to assess prediction accuracy. Results showed that the proposed covariates provided added value to the observations. SAVI aggregated to MODIS resolution was able to identify local highs and lows not apparent from the DTD imagery alone. Despite the apparent similarity of the two areas, the spatial structure of residuals from the linear mixed models were quite different; ranges on the order of 3 km in Jiangyan but 16 km in Peixian, and accuracy of best models differed by a factor of two (3.3 g/kg and 6.3 g/kg SOM, respectively). This suggests that time-series remotely sensed data can provide useful auxiliary variable for mapping SOM in low-relief agricultural areas, with three important cautions: (1) image dates must be carefully chosen; (2) vegetation indices should supplement diurnal temperature differences, (3) model structure must be calibrated for each area.     

Long-term effects of elevated atmospheric CO2 on below-ground biomass and transformations to soil organic matter in grassland

We determined the effects of elevated [CO₂] on the quantity and quality of below-ground biomass and several soil organic matter pools at the conclusion of an eight-year CO₂ enrichment experiment on native tallgrass prairie. Plots in open-top chambers were exposed continuously to ambient and twice-ambient [CO₂] from early April through late October of each year. Soil was sampled to a depth of 30 cm beneath and next to the crowns of C4 grasses in these plots and in unchambered plots. Elevated [CO₂] increased the standing crops of rhizomes (87%), coarse roots (46%), and fibrous roots (40%) but had no effect on root litter (mostly fine root fragments and sloughed cortex material >500 μm). Soil C and N stocks also increased under elevated [CO₂], with accumulations in the silt/clay fraction over twice that of particulate organic matter (POM; >53 μm). The mostly root-like, light POM (density ≤1.8 Mg m^-3) appeared to turn over more rapidly, while the more amorphous and rendered heavy POM (density >1.8 Mg m^-3) accumulated under elevated [CO₂]. Overall, rhizome and root C:N ratios were not greatly affected by CO₂ enrichment. However, elevated [CO₂] increased the C:N ratios of root litter and POM in the surface 5 cm and induced a small but significant increase in the C:N ratio of the silt/clay fraction to a depth of 15 cm. Our data suggest that 8 years of CO₂ enrichment may have affected elements of the N cycle (including mineralization, immobilization, and asymbiotic fixation) but that any changes in N dynamics were insufficient to prevent significant plant growth responses. This revised version was published online in June 2006 with corrections to the Cover Date.     

Estimating C inputs retained as soil organic matter from corn (Zea Mays L.)

In agroecosystems, the annual C inputs to soil are a major factor controlling soil organic matter (SOM) dynamics. However, the ability to predict soil C balance for agroecosystems is limited because of difficulties in estimating C inputs and in particular from the below-ground part. The objective of this paper was to estimate the proportion of corn residue retained as SOM. For that purpose, the results of a ¹³C long-term (15 yr) field study conducted on continuous silage corn and two silage corn rotations along with data from the existing literature were analyzed. The total amount of corn-derived C (0–30 cm) was about 2.5 to 3.0 times higher for the continuous corn treatment (445 g m^-2), compared to the two rotational treatments (175 and 133 g m^-2 for the corn-barley-barley-wheat and corn-underseeded barley hay-hay rotations, respectively). Assuming that the C inputs to the soil from silage-corn was mainly roots and would have been similar across treatments on an annual basis, the total amount of corn-derived C for the two rotational treatments was approximately proportional to the number of years the silage-corn was present in the rotation (4 yr). The results from the current study indicate that about 17% of root-derived C is retained as SOM. This value is higher than those reported in the literature for long-term studies on shoot-derived C (range of 7.7 to 20%, average of 12.2%), which is in agreement with previous studies showing that more C is retained as SOM from roots than from shoots. This revised version was published online in June 2006 with corrections to the Cover Date.     

Effect of soil organic matter on chickpea inoculated withAzospirillum brasilense andRhizobium leguminosarum bv.ciceri

Azosprillum inoculated withRhizobium improved the nodulation of chickpea-Cicer arietinum. This interaction was further enhanced by organic matter present in the growth medium.