Denitrification in river sediments plays a very important role in removing nitrogen in aquatic ecosystem. To gain insight into the key factors driving denitrification at large spatial scales, a total of 135 sediment samples were collected from Huaihe River and its branches located in the northern of Anhui province. Bacterial community composition and denitrifying functional genes (nirS, nirK, and nosZ) were measured by high-throughput sequencing and real-time PCR approaches. Potential denitrification rate (PDR) was measured by acetylene inhibition method, which varied from 0.01 to 15.69 μg N g⁻¹ h⁻¹. The sequencing results based on 16S rRNA gene found that the main denitrification bacterial taxa included Bacillus, Thiobacillus, Acinetobacter, Halomonas, Denitratisoma, Pseudomonas, Rhodanobacter, and Thauera. Therein, Thiobacillus might play key roles in the denitrification. Total nitrogen and N:P ratio were the only chemical factors related with all denitrification genes. Furthermore, nirS gene abundance could be more susceptible to environmental parameters compared with nirK and nosZ genes. Canonical correspondence analysis indicated that NO₃⁻, NO₂⁻, NH₄⁺ and IP had the significant impacts on the nirS-encoding bacterial community and spatial distributions. There was a significantly positive correlation between Thiobacillus and nirS gene. We considered that higher numbers of nosZ appeared in nutrient rich sediments. More strikingly, PDR was positively correlated with the abundance of three functional genes. Random forest analysis showed that NH₄⁺ was the most powerful predictor of PDR. These findings can yield practical and important reference for the bioremediation or evaluation of wetland systems.

河流沉积物中的反硝化作用在去除水生生态系统中的氮方面起着非常重要的作用。为了深入了解大空间尺度上反硝化作用的关键因素，从位于安徽省北部的淮河及其支流中收集了总共135个沉积物样品。通过高通量测序和实时 PCR 方法测量细菌群落组成和反硝化功能基因（nirS、nirK和nosZ）。潜在的反硝化率 (PDR) 通过乙炔抑制法测量，其范围为 0.01 至 15.69 μg N g ^-1 h ^-1。基于16S rRNA的测序结果基因发现，主要的反硝化细菌分类群包括芽孢杆菌、硫杆菌、不动杆菌、盐单胞菌、脱硝菌、假单胞菌、红丹酸杆菌和Thauera。其中，硫杆菌可能在反硝化过程中起关键作用。总氮和氮磷比是唯一与所有反硝化基因相关的化学因子。此外，与nirK和nosZ基因相比，nirS基因丰度可能更容易受到环境参数的影响。规范对应分析表明NO ₃⁻、NO ₂ ⁻、NH ₄ ⁺和IP 对编码nirS 的细菌群落和空间分布有显着影响。硫杆菌与nirS基因呈显着正相关。我们认为在营养丰富的沉积物中出现了更多的nosZ。更引人注目的是，PDR 与三个功能基因的丰度呈正相关。随机森林分析表明NH ₄ ⁺是PDR 最有力的预测因子。这些发现可为湿地系统的生物修复或评价提供实用且重要的参考。