Research advances in N₂O emissions in tropical forest soils and their influencing factors

Tropical forest soil is a significant source of N₂O emissions, exerting a notable impact on global climate change. Due to the complex environmental conditions (high temperature, high humidity, intense precipitation, and strong leaching) in tropical regions, coupled with strong spatial heterogeneity and insufficient observational data, there remains significant uncertainty regarding the N₂O emission flux from tropical forest soil and microbial regulation mechanisms. We reviewed the characteristics of N₂O emissions from tropical forest soil, the mechanisms by which soil microorganisms produce N₂O, influencing factors, as well as the advancements in the application of stable isotope techniques for N₂O source apportionment and process quantification. N₂O emissions from tropical forest soil exhibit notable spatiotemporal heterogeneity. The production processes primarily involve autotrophic/heterotrophic nitrification, denitrification, and their coupled processes, and are synergistically regulated by factors such as soil moisture, temperature, pH, carbon and nitrogen substrate availability, and microbial community structure. Stable isotope tracing techniques (¹⁵N natural abundance method, ¹⁵N labeling method, isotopic isotopomer method) can effectively distinguish the contributions of different microbial processes to N₂O production, evolving from qualitative identification to precise quantitative analysis, providing crucial support for refining the nitrogen cycle theory in tropical forests. Currently, most studies focus on short-term and small-scale experiments. There are uncertainties regarding isotope fractionation parameters and model applicability, limiting their application in assessing N₂O flux at the regional scale and in global tropical regions. In the future, it is essential to strengthen the integration of multi-temporal and multi-spatial scale in situ observations with stable isotope techniques, integrating molecular biology, machine learning, and process modeling methods to explore the mechanisms of different microbial processes. This would enhance our understanding of the mechanisms underlying N₂O emission from tropical forest soil and its response to global change, providing a scientific basis for precise reduction of greenhouse gas emissions in the tropics.