Relationships between soil respiration and hyperspectral vegetation indexes and crop characteristics under different warming and straw application modes.

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.