Although salinity and sodicity are worldwide problems, information on greenhouse gas (GHG) emissions from agricultural salt-affected soils is scarce. The CO₂–C and N₂O–N emissions were quantified from three zones intertwined within a single U.S. northern Great Plains field: a highly productive zone (electrical conductivity with 1:1 soil/water mass ratio [EC_1:1] = 0.4 dS m^–1; sodium adsorption ratio [SAR] = 1.8), a transition zone (moderately salt-affected; EC_1:1 = 1.6 dS m^–1; SAR = 4.99), and a saline/sodic zone (EC_1:1 = 3.9 dS m^–1; SAR = 22). In each zone, emissions were measured every 4 h for 7 d in four randomly placed chambers that were treated with two N rates (0 and 224 kg N ha^–1). The experiment was conducted in 2018 and 2019 during similar seasonal periods. Soil samples taken from treatments after GHG measurement were analyzed for soil inorganic N, and microbial biomass from different communities was quantified using phospholipid fatty acid analysis. Real-time polymerase chain reaction was used to quantify the number of copies of some specific denitrification functional genes. The productive zone had the highest CO₂–C, the lowest N₂O–N emissions, and the greatest microbial biomass, whereas the saline/sodic zone had the lowest CO₂–C, the highest N₂O–N emissions, and the lowest microbial biomass. Within a zone, urea application did not influence CO₂–C emissions; however, N₂O–N emissions from the urea-treated saline/sodic zone were 84 and 57% higher than from the urea-treated productive zone in 2018 and 2019, respectively. The copy number of the nitrite reductase gene, nirS, was 42-fold higher in the saline/sodic zone than in the productive soil, suggesting that the saline/sodic soil had a high potential for denitrification. These findings suggest N₂O–N emissions could be reduced by not applying N to saline/sodic zones.

中文翻译：

---

来自包括受盐影响土壤的田地的 CO2 和 N2O 排放和微生物群落结构

尽管盐度和碱度是世界性问题，但有关受盐分影响的农业土壤的温室气体 (GHG) 排放的信息很少。CO ₂ –C 和 N ₂ O–N 排放量来自美国北部大平原地区的三个区域：一个高产区（土壤/水质量比为_{1:1 的}电导率 [EC _1:1 ] = 0.4 dS m ^–1；钠吸附比 [SAR] = 1.8)、过渡区（中度受盐影响；EC _1:1  = 1.6 dS m ^–1；SAR = 4.99）和盐水/钠区（EC _{1 :1}  = 3.9 dS m ^–1; SAR = 22）。在每个区域，在 7 天中每 4 小时在四个随机放置的室中测量排放，这些室用两种 N 率（0 和 224 kg N ha ^–1）处理。该实验于 2018 年和 2019 年在相似的季节期间进行。对温室气体测量后处理的土壤样品进行土壤无机氮分析，并使用磷脂脂肪酸分析量化来自不同群落的微生物生物量。实时聚合酶链反应用于量化某些特定反硝化功能基因的拷贝数。生产区的 CO ₂ -C最高，N ₂ O-N 排放量最低，微生物生物量最大，而盐碱区的 CO ₂ -C最低，N 最高₂ O-N 排放，以及最低的微生物生物量。在一个区域内，尿素应用不影响CO ₂ –C 排放；然而，2018 年和 2019 年，尿素处理的盐水/钠区的N ₂ O-N 排放量分别比尿素处理的生产区高 84% 和 57%。亚硝酸盐还原酶基因nirS的拷贝数在盐碱区比在生产土壤中高 42 倍，表明盐碱土具有很高的反硝化潜力。这些发现表明，如果不对盐碱区/钠区施氮，可以减少N ₂ O-N 排放。