Calibration of Near-Infrared Spectra for Phosphorus Fractions in Grassland Soils on the Tibetan Plateau

Soil phosphorus (P) is essential for plant growth and influences biological processes. Determining the amounts of available P to plants has been challenging, and many different approaches exist. The traditional Hedley sequential extraction method and its subsequent modification are applied to determine different soil P forms, which is critical for understanding its dynamics and availability. However, quantifying organic and inorganic P (Po & Pi) in different extracts is labor-intensive and rarely used with large sample numbers. As an alternative, near-infrared spectroscopy (NIRS) has been employed to determine different P fractions at reasonable costs in a short time. This study aimed to test whether the analysis of P fractions with NIRS is an appropriate method to disentangle the effects of P limitation on high-altitude grassland ecosystems, particularly with fertilizer amendments. We explored NIRS in soils from the grassland soil samples on the northern Tibetan Plateau. First, we extracted the P fractions of 191 samples from the Haibei Alpine Meadow Ecosystem Research Station at four depth increments (0-10 cm, 10-20 cm, 20-40 cm, and 40-70 cm), including nutrient additions of nitrogen (N) and P. We compared the results of the Hedley extraction with the laboratory-based NIRS model. The fractionation data were correlated with the corresponding NIRS soil spectra; the coefficient of determination (R-2) of the NIRS calibrations to predict P in P fractions ranged between 0.12 and 0.90; the ratio of (standard error of) prediction to the standard deviation (RPD) ranged between 1.07 and 3.21; the ratio of performance to inter-quartile distance (RPIQ) ranged from 0.3 to 4.3; and the model prediction quality was higher for Po than Pi fractions, and decreased with fertilizer amendment. However, the external-validation results were not precise enough for the labile P fractions (RPD < 1.4) due to the limited number of samples. The results indicate that using NIRS to predict the more stable P pools, combined with Hedley fractionation focusing on the labile P pool, can be a promising approach for soils in alpine grasslands on the Tibetan Plateau.