Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Environ Sci Pollut Res Int. 2021 Aug;28(30):40756-40770. doi: 10.1007/s11356-021-13612-3. Epub 2021 Mar 26.
Examining the relationship between seasonal variations in soil respiration and abiotic factors and vegetation indexes is crucial for modeling soil respiration using upscaled remote sensing satellite data. A field experiment including control (CK), warming (WA), straw application (SA), and warming and straw application (WASA) treatments was performed in a winter wheat-soybean rotation cropland on the north shore of the lower reaches of the Yangtze River. Soil respiration, abiotic factors, crop hyperspectral vegetation indexes, leaf area index (LAI), and chlorophyll content (represented as the SPAD value) were measured during the 2018-2020 rotation growing seasons. The results indicated that the mean annual soil respiration was 2.27 ± 0.04, 3.08 ± 0.06, 3.64 ± 0.08, and 3.95 ± 0.20 μmol m s in the CK, WA, SA, and WASA plots, respectively, during the 2-year experimental period. Soil respiration was significantly (P < 0.05) correlated with soil temperature, soil moisture, hyperspectral vegetation indexes, LAI, and SPAD value in all plots. Models that included temperature, moisture, hyperspectral vegetation indexes, LAI, and SPAD value explained 50.5-74.7% of the seasonal variation in soil respiration in the CK, WA, SA, and WASA plots during the 2-year experimental period. A model including the seasonal mean NDVI, DVI, EVI, PRI, and LAI explained 72.4% of the interseasonal and intertreatment variations in seasonal mean soil respiration in the different plots across the four different crop-growing seasons. Our study indicated the potential applicability of hyperspectral vegetation indexes, LAI, and SPAD value to the estimation of soil respiration at a regional scale.
研究土壤呼吸与非生物因子和植被指数之间的季节性变化关系对于利用放大的遥感卫星数据模拟土壤呼吸至关重要。在长江下游北岸的冬小麦-大豆轮作农田中进行了一项田间实验，包括对照（CK）、增温（WA）、秸秆施用（SA）和增温和秸秆施用（WASA）处理。在 2018-2020 轮作生长季节期间，测量了土壤呼吸、非生物因子、作物高光谱植被指数、叶面积指数（LAI）和叶绿素含量（以 SPAD 值表示）。结果表明，在 2 年的实验期间，CK、WA、SA 和 WASA 小区的年平均土壤呼吸分别为 2.27±0.04、3.08±0.06、3.64±0.08 和 3.95±0.20 μmol m s。在所有小区中，土壤呼吸与土壤温度、土壤水分、高光谱植被指数、LAI 和 SPAD 值显著相关（P<0.05）。在 CK、WA、SA 和 WASA 小区中，包含温度、水分、高光谱植被指数、LAI 和 SPAD 值的模型解释了 50.5-74.7%的土壤呼吸季节性变化，在 2 年的实验期间。包含季节性平均 NDVI、DVI、EVI、PRI 和 LAI 的模型解释了不同小区不同作物生长季节中季节性平均土壤呼吸的季节间和处理间变化的 72.4%。我们的研究表明，高光谱植被指数、LAI 和 SPAD 值在区域尺度上估算土壤呼吸具有潜在的适用性。
