Comparative effects of the recovery from sulfuric and nitric acid rain on the soil enzyme activities and metabolic functions of soil microbial communities

Acid rain (AR) is a serious issue in China, particularly in the Yangtze River Delta region where the economy has undergone rapid development. Over the last few years. the composition of acid rain in the Yangtze River Delta region has gradually changed from sulfuric acid rain (SAR) to nitric add rain (NAR) due to controls on SO2 emissions, but increased NOx emissions. These changes have made ecosystems more complex. For this study, we halted AR treatments in Quercus acutissima forest plots that had received simulated AR for one year and monitored them from the following February to November. We investigated their soil resident enzyme and microbial metabolic activities, as well as community functional diversity. The results revealed that AR treatments negatively affected both the soil microbial activity and soil microbial community functional diversity; however, both managed to recover over time, once the AR treatments were stopped. During the AR treatment and recovery periods, four main categories (carbohydrates, carboxylic acids, amino adds, and polymers) were dominantly utilized. The utilization of pyruvic add, which was affected by the AR treatments, as well as o-mannitol and tween 80, accounted for changes in the peak values of the C substrate groups during the AR treatment recovery period. Finally, changes in the activities of soil enzymes recorded following AR recovery, were closely related to the utilization of six C substrate groups. Our results suggested that the recovery of soils following the cessation of NAR stress was more rapid than from SAR. Further, that short-term NAR could be easily treated during the transformation from SAR to NAR in the Yangtze River Delta region. These results might also enrich the basic data relating to post-AR treatments on the soil environment, while having significance toward guiding further studies on the recovery of ecosystems from AR. (C) 2020 Published by Elsevier B.V.