中文关键词培肥模式环境因子土壤呼吸温度敏感性高粱作物 英文关键词fertilization treatmentenvironmental factorssoil respirationtemperature sensitivitysorghum

作者	单位	E-mail
严俊霞	山西大学黄土高原研究所, 太原 030006	yjx422@sxu.edu.cn
张媛	山西大学黄土高原研究所, 太原 030006
焦晓燕	山西省农业科学院农业环境与资源研究所, 太原 030031	xiaoyan_jiao@126.com

中文摘要 基于对高粱地进行的5种培肥模式的长期定位试验，研究了不同培肥模式下土壤呼吸速率（R_s）及其温度敏感性（Q₁₀）与环境因子以及光谱特征参数的关系.试验共设5个处理：不施肥（CK）、无机肥（INF）、无机肥+有机肥（INF+M）、无机肥+有机肥+秸秆（INF+M+S）和有机肥+秸秆（M+S）.结果表明，施肥处理没有改变R_s的时间动态变化趋势.INF与CK的R_s没有明显差异，测定期间的平均值分别为3.68 μmol·（m²·s）^-1和3.51 μmol·（m²·s）^-1.与INF或CK相比，INF+M、M+S和INF+M+S的R_s分别增加了28.2%~39.1%、47.9%~76.0%和46.2%~50.8%，有机肥和秸秆还田处理后R_s增加.土壤温度和土壤水分分别能解释R_s季节变化的14%~96%和6%~37%，施肥处理显著提高了土壤温度的解释能力，而土壤水分的解释能力没有明显差异；R_s与差值植被指数、比值植被指数、增强植被指数的相关系数高于归一化植被指数；与红边斜率和红边面积的相关系数高于红边位置.有机肥和秸秆的施用降低了R_s与光谱特征参数的相关性.以光谱特征参数、T₁₀、W_s为自变量的3因子模型的决定系数R²都高于双因子和单因子模型.与CK相比，INF、INF+M、INF+M+S和M+S的Q₁₀分别提高了26%、39%、21%和37%，表明施肥可以提高土壤呼吸的温度敏感性.造成不同处理R_s/Q₁₀/R₁₀差异的主要因子分别为Shannon多样性指数/容重/土壤有机质，可以解释其97.6%/78.2%/92.8%的变异. 英文摘要 The characteristics of soil respiration under the condition of fertilization have not been fully understood,especially for a long-term fertilization condition. In this study we measured both soil respiration using an LI-COR-6400-09 soil chamber attached to LI-COR-6400 portable photosynthesis system, and the vegetation spectrum using an ASD FieldSpec HandHeld2, in five different fertilization treatment fields. The soil respiration (R_s) and vegetation spectrum were simultaneously measured with two samples per month in the growing season in 2016 and 2017. The soil temperature at 10 cm depth (T₁₀) and moisture (W_s) for the surface of 10 cm were also measured simultaneously. The five different fertilization treatments included no fertilization (CK), inorganic fertilizer (INF), inorganic fertilizer+organic fertilizer (INF+M), inorganic fertilizer+organic fertilizer+straw turnover (INF+M+S) and organic fertilizer+straw turnover (M+S), and all treatments had been conducted since 2011. Based on those observation data, we made an analysis of R_s and its temperature sensitivity (Q₁₀) in the five different fertilization treatments. The results showed that no significant temporal change in R_s among the five treatments was found. No significant difference was found in R_s between the CK and INF treatments. Compared with the values of R_s in CK and INF, the R_s values in INF+M, M+S, and INF+M+S treatments increased by 28.2%-39.1%, 47.9%-76.0%, and 46.2%-50.8%, respectively. This indicated that use of organic fertilization and straw application increased R_s. Both the T_s and W_s showed 14%-96% and 6%-37% in R_s seasonal variations, respectively. Among the treatments, the correlation coefficient of the fitted equations between R_sand T_s was higher in the INF+M, INF+M+S and M+S treatment than in CK and INF, but was not between R_sand W_s. For the relationship between R_s and vegetation indexes we found that the correlation coefficients between R_s and the difference vegetation index (DVI), ratio vegetation index (RVI), and enhanced vegetation index (EVI), respectively, were higher than that of R_s and the normalized differential vegetation index (NDVI); and that the correlation coefficients between R_sand the red edge slope (D_red) and red edge area (S_red) were higher than between R_s and the red edge position (λ_red). This indicated that the treatments in INF+M+S increased the correlation coefficient between R_s and the spectrum characteristics index. The determination coefficient of the fitted equations including the feature spectral parameters, T₁₀, and W_svariables was higher than that of the equations only including both T₁₀ and W_s variables, or a single variable of T₁₀ or W_s. Compared with CK, the Q₁₀ value increased by 26%, 39%, 21%, and 37% for the INF, INF+M, INF+M+S, and M+S treatments, respectively. This indicated that temperature sensitivity Q₁₀ increased under the condition of fertilization treatments. The Shannon diversity index, bulk density, and soil organic matter were the main factors causing the difference in R_s, Q₁₀, and R₁₀, i.e., R_s at a temperature of 10℃, in the different treatments, which could explain the 97.6%, 78.2%, and 92.8% variations in R_s, Q₁₀, and R₁₀, respectively.

PDF全文下载地址:

https://www.hjkx.ac.cn/hjkx/ch/reader/create_pdf.aspx?file_no=20191236&flag=1&journal_id=hjkx&year_id=2019