Long-term phosphorus addition alleviates CO₂ and N₂O emissions via altering soil microbial functions in secondary...

Tropical forests, where the soils are nitrogen (N) rich but phosphorus (P) poor, have a disproportionate influence on global carbon (C) and N cycling. While N deposition substantially alters soil C and N retention in tropical forests, whether P input can alleviate these N-induced effects by regulating soil microbial functions remains unclear. We investigated soil microbial taxonomy and functional traits in response to 10-year independent and interactive effects of N and P additions in a primary and a secondary tropical forest in Hainan Island. In the primary forest, N addition boosted oligotrophic bacteria and phosphatase and enriched genes responsible for C-, P-mineralization, nitrification and denitrification, suggesting aggravated P limitation while N excess. This might stimulate P excavation via organic matter mineralization, and enhance N losses, thereby increasing soil CO₂ and N₂O emissions by 86% and 110%, respectively. Phosphorus and NP additions elevated C-mining enzymes activity mainly due to intensified C limitation, causing 82% increase in CO₂ emission. In secondary forest, P and NP additions reduced phosphatase activity, enriched fungal copiotrophs and increased microbial biomass, suggesting removal of nutrient deficiencies and stimulation of fungal growth. Meanwhile, soil CO₂ emission decreased by 25% and N₂O emission declined by 52-82% due to alleviated P acquisition from organic matter decomposition and increased microbial C and N immobilization. Overall, N addition accelerates most microbial processes for C and N release in tropical forests. Long-term P addition increases C and N retention via reducing soil CO₂ and N₂O emissions in the secondary but not primary forest because of strong C limitation to microbial N immobilization. Further, the seasonal and annual variations in CO₂ and N₂O emissions should be considered in future studies to test the generalization of these findings and predict and model dynamics in greenhouse gas emissions and C and N cycling.