Location :Home > thesis
Hydrothermal conditions determine soil potential net N mineralization rates in arid and semi-arid grasslands
Print  |  Close    

Hu SY, Wang CH*, Risch AC, Liu Y, Li Y, Li L, Xu XH, He NP, Han XG, Huang JH*
PubYear : 2022
Volume :   Issue : 
Publication Name : Functional Ecology
Page number : DOI:10.1111/1365-2435.14167
Abstract : 

1. Soil net nitrogen (N) mineralization is a key biogeochemical process influencing plant available N and net primary productivity in terrestrial ecosystems. However, the spatial variations and controlling factors of soil net N mineralization (RPNM) in arid and semi-arid grasslands are less studied and unclear.

2. In this study, we investigated the soil RPNM by performing a laboratory incubation experiment. Soil samples were collected from 30 sites in three east–west transects on the Inner Mongolia Plateau (MP), Loess Plateau (LP) and Tibetan Plateau (TP) along a 3200 km arid and semi-arid grassland gradient, with each transect containing three different grassland types (meadow steppe [MS], typical steppe [TS] and desert steppe [DS], respectively).

3. Results showed that the average RPNM values ranged from -0.37 to 1.29 mg N kg-1 day-1, with a significantly lower RPNM found in the DS (0.08 ± 0.01 mg N kg-1 day-1) compared with those in the MS (0.30 ± 0.03 mg N kg-1 day-1) and in the TS (0.33 ± 0.03 mg N kg-1 day-1) in the MP and LP transects (p < 0.05). This difference could be explained by variations in climatic and soil factors, such as hydrothermal index (HT), the soil pH, soil organic matter (SOM) and precipitation. However, no significant differences in RPNM were found among different grassland types in the TP transect, possibly due to the similarly low microbial activity, as indicated by the microbial biomass carbon values. Across all three grassland transects, HT, SOM and microbial variables were the major factors controlling RPNM, which together explained 20.7% of the variation in RPNM. Further structural equation model analysis indicated HT was an integral predictor of RPNM, directly or indirectly via SOM, under different conditions of precipitation and temperature.

4. Our findings provide field evidence and parameters for biogeochemical cycling to better predict future N transformation processes under changing precipitation and temperature regimes across a wide range of arid and semi-arid grassland ecosystems.

download :