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. 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. 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). 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.

中文翻译：

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在印度德里的半干旱生态系统中，土壤水分控制着不同土地利用系统下土壤呼吸的时空格局。

土壤呼吸（SR）是了解气候条件和土地退化对陆地生态系统碳循环的影响的关键过程。我们测量了四种土地利用中1年内的SR和土壤环境因子，这些土地利用具有不同程度的干扰和不同的植被类型，即混合森林覆盖率（MFC），朱s（Prosopis juliflora）（PFC），农田（AF） ）和印度德里半干旱地区的菜田（VF）。我们的主要目的是评估土壤水分（SM），土壤温度（ST）和土壤微生物活性（SMA）对SR的影响。使用带有红外气体分析仪和土壤箱的LI-6400每月测量一次SR。使用重量法测量SM。用连接到LI-6400的探针测量ST（10厘米）。SMA通过荧光素二乙酸酯水解测定。SR表现出季节性变化，耕地（AF，VF）的年均SR在3.22至5.78μmolm−2 s-1之间，SR率约为15–55％，高于林地（MFC， PFC）。VF的SR显着高于其他土地用途（AF，PFC，MFC），SR彼此之间无显着差异（P <0.05）。重复测量方差分析评估了高降水月份（7月，8月，9月，2月）SR的显着差异（P <0.05）。在所有土地利用中，SM作为一个单一因素显示出很强的显着关系（R2 = 0.67–0.91，P <0.001）。在PFC，MFC和AF中，发现ST对SR的影响微弱而无统计学意义（R2 = 0.14-0.31； P> 0.05）。在VF中观察到相反的结果，VF在夏季（5月； 11.21μmolm-2 s-1）具有较高的SR，并且与ST呈显着的指数关系（R2 = 0.52； P <0.05）。SR与SMA呈正相关（R2 = 0.44-0.5； P <0.001）。基于自变量SM，ST和SMA的交互式方程式解释了SR的91–95％的季节性变化，并在耕地使用地点（AF，VF）具有更好的模型性能。SM是半干旱生态系统中SR的关键决定因素，可解释约90％的变化。通过优化SM和微生物活性，降水增加了SR。SMA和其他土壤因子SM和ST改善了与SR的相关性。此外，在气候变化的情况下，退化的土地利用将更容易受到SR随时间变化的影响，