Soil moisture controls the spatio-temporal pattern of soil respiration under different land use systems in a semi-arid ecosystem of Delhi, India

Abstract

Background: Soil respiration (SR) is a critical process for understanding the impact of climatic conditions and land degradation on the carbon cycle in terrestrial ecosystems. We measured the SR and soil environmental factors over 1 year in four land uses with varying levels of disturbance and different vegetation types viz., mixed forest cover (MFC), Prosopis juliflora (Sw.) forest cover (PFC), agricultural field (AF), and vegetable field (VF), in a semi-arid area of Delhi, India. Our primary aim was to assess the effects of soil moisture (SM), soil temperature (ST), and soil microbial activity (SMA) on the SR. Methods: The SR was measured monthly using an LI-6400 with an infrared gas analyser and a soil chamber. The SM was measured using the gravimetric method. The ST (10 cm) was measured with a probe attached to the LI-6400. The SMA was determined by fluorescein diacetate hydrolysis. Results: The SR showed seasonal variations, with the mean annual SR ranging from 3.22 to 5.78 μmol m−2 s−1 and higher SR rates of ~ 15–55% in the cultivated fields (AF, VF) than in the forest sites (MFC, PFC). The VF had significantly higher SR (P < 0.05) than the other land uses (AF, PFC, MFC), which did not vary significantly from one another in SR (P < 0.05). The repeated measures ANOVA evaluated the significant differences (P < 0.05) in the SR for high precipitation months (July, August, September, February). The SM as a single factor showed a strong significant relationship in all the land uses (R2 = 0.67–0.91, P < 0.001). The effect of the ST on the SR was found to be weak and non-significant in the PFC, MFC, and AF (R2 = 0.14–0.31; P > 0.05). Contrasting results were observed in the VF, which showed high SR during summer (May; 11.21 μmol m−2 s−1) and a significant exponential relationship with the ST (R2 = 0.52; P < 0.05). The SR was positively related to the SMA (R2 = 0.44–0.5; P < 0.001). The interactive equations based on the independent variables SM, ST, and SMA explained 91–95% of the seasonal variation in SR with better model performance in the cultivated land use sites (AF, VF). Conclusion: SM was the key determining factor of the SR in semi-arid ecosystems and explained ~ 90% of the variation. Precipitation increased SR by optimizing the SM and microbial activity. The SMA, along with the other soil factors SM and ST, improved the correlation with SR. Furthermore, the degraded land uses will be more susceptible to temporal variations in SR under changing climatic scenarios, which may influence the carbon balance of these ecosystems.