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Seasonality of gross ammonification and nitrification altered by precipitation in a semi-arid grassland of Northern China
- Source :
- Soil Biology and Biochemistry. 154:108146
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Gross ammonification (GA) and gross nitrification (GN) are key regulators of the bioavailability of nitrogen (N) in terrestrial ecosystems. In arid and semi-arid grassland ecosystems, the impacts of precipitation change on in situ GA and GN and their seasonal variations are understudied. A manipulative experiment with five precipitation levels (−60%, −30%, unchanged ambient precipitation as control, +30%, +60% of ambient precipitation) was set up in May 2012. After a 2-year equilibration period, the 15N pool dilution technique was applied to determine GA and GN rates in surface soil (0–5 cm) within 8 sampling dates ranging from the onset to the end of the growing season. Pronounced temporal variability of GA and GN rates were observed with the highest GA and GN rates in the mid-growing season (August) and the lowest in the post-growing season (October). GA rates during the growing season were primarily controlled by precipitation and soil water availability, while this effect diminished at the onset and end of the growing season when the temperature dropped. In contrast, GN was predominately controlled by ammonium (NH4+) production through GA. In the peak-growing season, the +60% precipitation treatment enhanced GA and GN rates by up to 4-fold, while the −30% precipitation treatment marginally suppressed GA and GN rates. The −60% precipitation treatment suppressed GA and GN rates to below detection limits across the entire study period, suggesting that extreme and persistent droughts greatly inhibited N turnover in the surface soil, thereby forcing plants to mobilize and access nutrients from deeper soil layers. Our findings provide a season-specific mechanistic insight into precipitation impacts on topsoil gross N turnover and suggest that the N cycling represented in ecosystem models needs to consider a mechanism that allows a strong suppression of microbial functions under extreme droughts.
Details
- ISSN :
- 00380717
- Volume :
- 154
- Database :
- OpenAIRE
- Journal :
- Soil Biology and Biochemistry
- Accession number :
- edsair.doi...........71612741c333bf95db61593443c007c4