Soil nutrients, elemental stoichiometry, and their associated environmental control play important roles in nutrient cycling. The objectives of this study were (1) to investigate soil nutrients and elemental stoichiometry, especially potassium and its associative elemental stoichiometry with other nutrients under different land uses in terrestrial ecosystems; (2) to discuss the impacts of climate factors, soil texture, and soil physicochemical properties; and (3) to identify the key factors on soil nutrient levels and elemental stoichiometry.
Materials and methods
Soil data, including pH, bulk density (BD), cation exchange capacity (CEC), volumetric water content (VMC), clay, silt and sand contents, total carbon (TC), nitrogen (TN), phosphorous (TP) and potassium (TK), available nitrogen (AN), phosphorus (AP), potassium (AK), and soil organic matter (SOM) under different land-use types, were collected, and their elemental stoichiometry ratios were calculated. Climate data including temperature, precipitation, relative humidity, wind speed, and evapotranspiration were collected. The least significant difference test and one-way analysis of variance were applied to investigate the variability of soil nutrients and elemental stoichiometry among land-use types; the ordinary least squares method and the general linear model were used to illustrate the correlations between soil nutrients, elemental stoichiometry, and soil properties or climate factors and to identify the key influencing factors.
Results and discussion
Woodlands had the highest SOM, TN, AN, and AK contents, followed by grasslands, croplands, and shrublands, while the TP and TK contents only varied slightly among land-use types. SOM, TN, AN, N/P, and N/K were strongly negatively correlated to soil pH (p <?0.05) and were strongly positively correlated to soil CEC (p <?0.05). For soil texture, only C/N was moderately negatively correlated to silt content but moderately positively correlated to sand content (p <?0.05). For climate factors, SOM, TN, AN, N/P, and N/K were significantly negatively correlated to evapotranspiration and temperature (p <?0.05), and the correlations were usually moderate. Soil pH explained most of the total variation in soil nutrients, and climate factors explained 5.64–28.16% of soil nutrients and elemental stoichiometry (except for AP (0.0%) and TK (68.35%)).
Conclusions
The results suggest that climate factors and soil properties both affect soil nutrients and elemental stoichiometry, and soil properties generally contribute more than climate factors to soil nutrient levels. The findings will help to improve our knowledge of nutrient flux responses to climate change while also assisting in developing management measures related to soil nutrients under conditions of climate change.
Journal of Soils and Sediments - Nitrogen (N) fertilizer placement in bands is a widely accepted agricultural practice to increase N use efficiency. An excessive ammonium concentration in a... 相似文献
The contribution of N remobilization is crucial for new shoots growth and quality formation during spring tea shoots development. However, the translocation mechanism of N from source leaves to sink young shoots is not well understood. In the present study, 15N urea was applied to mature tea leaves one week before bud break to track N remobilization in a field experiment. The dynamic changes in plant 15N abundance, contents of amino acids, and the expression levels of genes related to N metabolism and translocation were followed during the 18‐d development of new spring shoots until three expanding young leaves. The results showed that during the growth of new shoots the amount of 15N in the shoots increased, whereas the Ndff (N derived from 15N‐urea) in mature leaves decreased, showing that the foliar‐applied N in mature leaves was readily exported to new shoots. This process was found to be accompanied by decline of chlorophylls. In the mature leaves, expression CsATG18a and CsSAG12 involved in autophagy was dramatically induced (> 4‐fold) at approximately nine days after the bud breaking. The genes involved in the transformation of amino acids, including primarily CsGDH2, CsGDH4, CsGLT3, CsGS1;3, and CsASN2 were upregulated by > 3‐fold after bud breaking. The expression levels of CsATG8A, CsATG9, CsSAG12, CsGS1;1, CsGDH1, and CsAAP6 correlated negatively with the Ndff in mature leaves, but positively with 15N amount and total N amount in new shoots, suggesting these genes played important roles in N export from mature leaves. In the new shoots, the expression of most genes showed two defined peaks, one on six days and one on 12 days after bud breaking. The expression of CsGS2, CsASN3, CsGLT1, and CsAAP4 positively correlated with the 15N amount and total N amount in new shoots. These genes might be involved in the transport and re‐assimilation of N from mature leaves. The overall results demonstrated that the translocation of 15N from mature leaves to new spring shoots was regulated by the genes involved in autophagy, protein degradation, amino acid transformation and transport. 相似文献
为了解决联合收割机作业故障的非线性特征信号难以提取的问题,该研究提出了一种基于堆叠去噪自动编码器(Stack Denoising Auto Encoder, SDAE)和BP神经网络(Back Propagation,BP)融合的联合收割机作业故障监测及诊断的方法(SDAE-BP)。以转速传感器采集联合收割机脱粒滚筒转速、籽粒搅龙转速、喂入搅龙转速、杂余搅龙转速、风机转速、输送链耙转速、割刀频率以及逐稿器振动频率,并将采集的数据集作为系统的输入。利用SDAE提取输入信号的深层次特征,并由BP神经网络辨识收割机作业状态,实现联合收割机故障监测。在SDAE-BP模型训练过程中,去噪自动编码器(Denoising Auto Encode, DAE)依次经带有不同分布中心噪声的原始数据进行训练,然后将其堆叠,并通过误差反向传播算法对模型参数进行优化,以提升模型识别故障性能和泛化能力。试验结果表明,对于2018年联合收割机田间试验数据,模型的故障诊断准确率达到99.00%,与SDAE和BP神经网络相比,分别提高了1.5和4.5个百分点。将SDAE-BP故障诊断模型用2019年的试验数据进行更新,并用2018年和2019年试验数据进行测试,结果表明,更新后的模型对2018年试验数据的故障识别准确率为99.25%,对2019年试验数据的故障识别准确率为98.74%,更新后模型在2019试验数据集上的故障识别准确率较未更新模型提高了6.52个百分点。该文所建模型能够准确识别联合收割机的故障类型,且具有较好的鲁棒性,对旋转型机械故障监测及预警具有参考价值。 相似文献
