DOI: 10.5061/dryad.8gtht76s3
title: Hydrothermal conditions determine soil potential net N mineralization rates in arid and semi-arid grasslands

description: Soil net nitrogen (N) mineralization is a key biogeochemical process
 influencing plant available N and net primary productivity (NPP) 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. 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 3,200 km arid and semi-arid grassland gradient, with each transect
 containing three different grassland types (meadow steppe, typical steppe,
 and desert steppe, respectively). Results showed that the average RPNM
 values ranged from -0.37 to 1.29 mg N kg–1 d–1, with a significantly lower
 RPNM found in the desert steppe (0.08 ± 0.01 mg N kg–1 d–1) compared with
 those in the meadow steppe (0.30 ± 0.03 mg N kg–1 d–1) and in the typical
 steppe (0.33 ± 0.03 mg N kg–1 d–1) in the MP and LP transects (p &lt;
 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
 MBC 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 SEM analysis indicated
 HT was an integral predictor of RPNM, directly or indirectly via SOM,
 under different conditions of precipitation and temperature. 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.
description: Soil sampling was conducted between July 18 and August 23, 2018.
 We first randomly selected eight plots (1 m × 1 m), with 10 m apart from
 each plot at each site. Then, topsoil (0-10 cm) from five soil cores (10
 cm in diameter) were collected after removing surface litter from each
 plot. Subsequently, the 5 soil samples were combined to form a composite
 sample. In total, 240 soil samples (3 transects × 10 sites × 8 replicates)
 were collected from 30 sites. Visible roots and litter residues were
 manually removed from each soil sample, and fresh soil samples were sieved
 using a 2 mm mesh sieve. The sieved soil samples were split into two
 subsamples; one subset was used for the laboratory incubation to estimate
 the RPNM and was stored at 4°C. The remaining soil was air-dried to
 analyze soil basic properties including soil organic matter (SOM), total
 carbon (TC), total nitrogen (TN), pH value, soil microbial biomass carbon
 (MBC), and microbial biomass nitrogen (MBN). Soil
 organic matter was measured by wet oxidation with
 KCr<sub>2</sub>O<sub>7</sub> +
 H<sub>2</sub>SO<sub>4</sub> and titrated with
 FeSO<sub>4</sub>. The TC and TN content were analyzed using an
 elemental analyzer (EA3000, Euro Vector, Pavia, Italy). Soil pH (1:2.5
 soil to water ratio) was measured using a pH meter (FE20K, Mettler-Toledo,
 Greinfensee, Switzerland). MBC and MBN were determined based on chloroform
 fumigation methods (Vance et al., 1987). Briefly, fumigated and
 unfumigated soil samples were first extracted using 0.5 M
 K<sub>2</sub>SO<sub>4</sub> and then the extracted
 solution was analyzed using a C/N analyzer (multi-N/C 3100 Analytic Jena
 AG, Jena, Germany). The MBC and MBN were calculated by subtracting the
 difference of dissolved organic C and N content between fumigated and
 unfumigated soil samples and dividing it by the conversion coefficient.
 The conversion coefficients used were 0.45 for MBC and 0.54 for
 MBN. Soil samples (30 g, dry weight) were placed in
 150-ml plastic bottles (eight replicates for each site) and were adjusted
 to approximately 60% water holding capacity (WHC) with deionized water.
 Then, the incubation bottles were sealed with parafilm and pre-incubated
 for 24 h at 25°C for short-term equilibration. Then, the pre-incubated
 soil samples were divided into two subsamples. One soil subsample was used
 for measuring the initial
 NH<sub>4</sub><sup>+</sup>-N and
 NO<sub>3</sub><sup>-</sup>-N concentrations
 (c(NH<sub>4</sub><sup>+</sup>-N) t0 and
 c(NO<sub>3</sub><sup>-</sup>-N)
 t<sub>0</sub>) and the other subsample was incubated for
 7-days in the chambers. The optimum temperature for soil microbial
 activity in the three transects might be different because of the
 long-term microbial adaption to different climatic conditions (especially
 temperature and precipitation). We incubated the collected soil samples at
 15℃ for samples from the Tibetan Plateau, at 20℃ for samples from the
 Inner Mongolia Plateau, and at 25℃ for samples from the Loess Plateau. The
 incubation temperature for soils from each plateau was chosen based on the
 mean highest daily temperature from mid-July to mid-August, corresponding
 to the hottest time period in the year for each plateau. This also covered
 the period during which the field work was conducted. This gives the
 maximum potential N mineralization rate that can realistically occur for
 the three steppes in each plateau. During the 7-day incubation period, the
 soil samples were maintained at a constant WHC with deionized water every
 2–3 days. After the incubation, the
 NH<sub>4</sub><sup>+</sup>-N and
 NO<sub>3</sub><sup>-</sup>-N concentrations
 (c(HN<sub>4</sub><sup>+</sup>-N) t<sub>1
 </sub>and c(NO<sub>3</sub><sup>-</sup>-N)
 t<sub>1</sub>) were measured. The RPNM on a
 dry mass basis was calculated as the difference in
 NH<sub>4</sub><sup>+</sup>-N and
 NO<sub>3</sub><sup>-</sup>-N concentrations before
 and after incubating the samples (Wang et al., 2006): <em>R</em><sub>PNM</sub> = (∆c (NH<sub>4</sub><sup>+</sup>-N) + ∆c(NO<sub>3</sub><sup>−</sup> -N)) / ∆t               (1) where ∆t is the incubation time. The hydrothermal index (HT) was used to determine the equilibrium state of hydrothermal resource allocation (Zhang et al., 2020). HT is the ratio of the normalized mean annual precipitation (MAP<sub>norm</sub>) to the normalized mean annual temperature (MAT<sub>norm</sub>), as shown in Equations 2–4 according to Zhang et al. (2020): MAP<sub>norm</sub> = (MAP − MAP<sub>min</sub>) / (MAP<sub>max</sub> − MAP<sub>min</sub>)           (2) MAT<sub>norm</sub> = (MAT − MAT<sub>min</sub>) / (MAT<sub>max</sub> − MAT<sub>min)</sub>         (3) HT = MAP<sub>norm</sub> / MAT<sub>norm </sub>                      (4) where MAP<sub>???</sub> is the minimum of the average annual precipitation across the 30 grassland sites included in this study, MAP<sub>???</sub> is the regional maximum, MAT<sub>???</sub> is the regional minimum of the average annual temperature across the 30 grassland sites in this study, and MAT<sub>???</sub> is the regional maximum temperature.