Coastal nutrient pollution is an ever-present threat to estuaries worldwide. Benthic denitrification has been identified as a crucial ecosystem service to help mitigate increasing N loads to the coast. However, the controls on denitrification in low-nutrient systems are not well constrained and are likely different to those in more widely studied eutrophic systems. This study aims to identify the specific controls on denitrification in low-nutrient estuaries, including the contribution of the macrofaunal community to denitrification rates, and to understand how this important service fits into the network of ecogeochemical processes in these systems. Results show that porewater ammonium concentrations and mud content are good predictors of net N₂ flux in the dark. Additionally, models predict N₂ flux rates much more effectively in the dark than in the light, but the macrofaunal community data, specifically species richness, is a key factor in both increasing the explanatory power of both models by nearly 20%. Additionally, interaction networks reveal that increasing mud content results in a shift in the macrofaunal community and a reduction in the N removal capacity of these intertidal systems.

沿海营养物污染一直是世界范围内河口的威胁。底栖生物反硝化已被认为是一项重要的生态系统服务，可帮助减轻沿海地区不断增加的氮负荷。但是，低营养系统中反硝化的控制措施并没有受到严格限制，并且可能与更广泛研究的富营养化系统中的反硝化方法有所不同。这项研究旨在确定低营养河口反硝化的具体控制措施，包括大型动物群落对反硝化率的贡献，并了解这项重要服务如何适合这些系统中的生态地球化学过程网络。结果表明，在黑暗中，孔隙水铵盐浓度和泥浆含量是净N ₂通量的良好预测指标。此外，模型预测N ₂暗处的通量率要比暗处的通量率要有效得多，但是大型动物群落数据，特别是物种丰富度，是使两个模型的解释力提高近20％的关键因素。此外，相互作用网络表明，增加泥浆含量会导致大型动物群落的转移，并降低这些潮间带系统的除氮能力。