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The study area was Anjiagou Watershed (35°33′02″–35°35′29″N, 104°38′13″–104°40′25″E), located in Anjiapo Village, Fengxiang Town, Dingxi City, Gansu Province, which belongs to the typical semi-arid loess hilly gully area of the fifth subregion (Fig. 1). The watershed covers an area of 8.54 ha (1 ha = 0.01 km2), with elevation between 1900 m and 2250 m. The area has a temperate continental monsoon climate with an average annual temperature of 6.3°C, average annual precipitation of 427 mm, and evaporation level of 1500 mm, with concentrated and seasonal precipitation (more than 60%) occurring from May to September, mainly in the form of heavy rainfall (Fig. 2). The main soil types are loess and river saline soils (Gong et al., 2007). Before the 1990s, the area was deforested and cleared, and in 1999, the Conversion of Farmland to Forests and Grasses Program was officially launched to plant vegetation in the ratio of 1:2:7 with trees, shrubs, and herbs (Wang and Bennett, 2008). In the early stage of afforestation, the survival rate of the fallow forest and grass was improved by artificial irrigation and replanting measures. The artificially restored vegetation species in the watershed were X. sorbifolium, C. korshinskii, and H. rhamnoides. The herbaceous species were mainly M. sativa (Table 1). Xanthoceras sorbifolium (family: Sapindaceae) is a small- to medium-sized tree endemic to northern China and is an emerging oil crop used for advanced biofuels, functional foods, and pharmaceutical and cosmetic applications (Zhou and Cai, 2021). Caragana korshinskii (family: Leguminosae) is a perennial leguminous shrub widely distributed in arid and semi-arid regions of Eurasia, with important environmental benefits and economic value for sand fixation and water retention (Bai et al., 2017). Hippophae rhamnoides (family: Elaeagnaceae) is a tree species with drought, sand, and salt tolerance, which is planted in large quantities in northwestern China for desertification control and has a high ecological value (Wei et al., 2019). Medicago sativa (family: Leguminosae) is a perennial herbaceous plant with strong drought resistance and adaptation to poor soils, which is widely planted in the region (Ji et al., 2020).
Figure 1. Map of the study area: XS, Xanthoceras sorbifolium forestland; SB, Stipa bungeana grassland; CK, Caragana korshinskii bushland; HR, Hippophae rhamnoides shrubland; MS, Medicago sativa grassland.
Figure 2. Temporal patterns of (a) air temperature and precipitation of the study area, and (b) soil temperature and (c) soil water content in the top 10 cm of the five plant community types: XS, Xanthoceras sorbifolium forestland; SB, Stipa bungeana grassland; CK, Caragana korshinskii bushland; HR, Hippophae rhamnoides shrubland; MS, Medicago sativa grassland.
Plot Area (m2) Longitude and latitude Elevation (m) Main species Coverage (%) Height (cm) MS 20 × 20 104°39′1.82′′E
35°34′48.07′′N1990 Medicago sativa (90%), Stipa bungeana, Artemisia
lavandulifolia90.06±1.58b 62.23±0.23d XS 20 × 20 104°39′10.62′′E
35°34′45.08′′N2018 Xanthoceras sorbifolium (86%), Bupleurum chinense,
Gentiana macrophylla, Leontopodium leontopodioides95.32±2.35c 76.45±2.54e CK 20 × 20 104°39′1.51′′E
35°34′45.00′′N1999 Caragana korshinskii (42%), Potentilla chinensis,
Picris hieracioides50.43±5.45a 16.00±0.79a HR 20 × 20 104°39′0.18′′E
35°34′47.32′′N1998 Hippophae rhamnoides (81%), Leontopodium
leontopodioides, Artemisia annua89.26±0.78b 54.89±1.23c SB 20 × 20 104°39′3.05′′E
35°34′45.48′′N2008 Stipa bungeana (92%), Plantago asiatica, Setaria
viridis, Leymus secalinus98.23±0.63c 35.93±0.44b Notes: XS, Xanthoceras sorbifolium forestland; SB, Stipa bungeana grassland; CK, Caragana korshinskii bushland; HR, Hippophae rhamnoides shrubland; MS, Medicago sativa grassland. The percentage of the main species is the coverage of the dominant species. Values are presented as mean ± standard error. Superscript letters indicate significant differences between plant community types (P < 0.05). Table 1. Basic information on the different plant community types at the experimental sites.
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In September 2017, the ecosystems in the study area were classified into several types according to the different vegetation restoration types and the dominant species of the plant community, and five representative plant community types were selected as observations for the measurement of differences in soil CH4 dynamics: X. sorbifolium forestland (XS), Stipa bungeana grassland (SB), C. korshinskii bushland (CK), H. rhamnoides shrubland (HR), and M. sativa grassland (MS). XS, CK, and HR were restored to woodland, mallow shrub community, and buckthorn shrub community, respectively, in 1999 through the implementation of the Conversion of Farmland to Forests and Grasses Program and manual management, without any further management measures. MS was abandoned in 2015 on the basis of cultivated land, planted with M. sativa and enclosed, and no further management measures were taken after survival. SB was abandoned in 1999 and naturally restored to an herbaceous community without any further management measures. Regarding the slope orientation, XS was located on the northeast slope, CK on the northwest slope, HR and MX on the north slope, and SB in the no-slope orientation zone. All sampling plots were set on sloping (but not significantly) arable land (except HR, which had a slope of about 5°). According to data from the local Hydrological and Water Resources Survey, the depth of the water table in the area during the experiment was about 100 m. Full details of the experimental sites are presented in Table 1 and Fig. 3. A completely randomized design was used, and three randomly selected sampling plots (7 m × 7 m) were taken from each plant community type, with a buffer zone of at least 5 m between each sampling plot, for a total of 15 sampling plots.
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Stainless steel bases (50 cm × 50 cm × 15 cm, L × W × H) were laid out in September 2017 within the 15 selected sampling plots following the method in Ma et al. (2020) (Fig. 4). Soil CH4 fluxes were sampled twice a month (biweekly) during the growing season (April to October) and once a month (mid-month) during the non-growing season (November to March) from November 2017 to October 2019 (i.e., 24 months) (Xia et al., 2015). All samples were collected between 0900 local standard time (LST, LST=UTC+8 hours) and 1200 LST. The fluxes measured during this time are considered to be representative of the daily average fluxes (Wang and Wang, 2003; Lin et al., 2009; Ma et al., 2018). After the chamber was closed, air samples (five in total) were taken from inside the chamber at 10-min intervals (at minutes 0, 10, 20, 30, and 40) using a 100 mL polypropylene syringe equipped with a three-way plug valve (Ma et al., 2020). The air samples were transferred to pre-evacuated E-Switch aluminum foil composite film gas sampling bags (Shanghai Shenyuan Scientific Instruments Co., Ltd., Shanghai, China) via the three-way plug valve. Within 48 h, the samples were returned to the laboratory for analysis of CH4 concentrations using a gas chromatograph (YiMeng A90, Changzhou Ban’nuo Instruments Co., Ltd., China). While collecting air samples, the temperature in the chamber and the soil temperature (T10) and soil water content (SWC10) at 10 cm above ground were measured using a portable digital thermometer (JM624, Jinming Instrument Co., Tianjing, China) and a temperature and humidity sensor (GS3, METER Group, Pullman, WA, USA), respectively. Air temperature and precipitation data were obtained from a local weather station located in Anjiagou Watershed. The weather station was set up near the SB sampling plot (Fig. 1), and all sampling plots were within a 500 m radius. Thus, air temperature and precipitation were not subjected to any correction.
Figure 4. Photographs of the chamber: (a) top view and (b) side view of the sampling chamber; (c) side view and (d) top view of the stainless steel base.
The CH4 gas flux was calculated as
where F is the gas flow rate (units: mg m−2 h−1),
${\rm d}C/{\rm d}t$ is the gradient of the time series of CH4 concentration (units: ppmv h−1) at the time of sampling, M is the molar mass (units: g mol−1) of the measured gas, P is the pressure (units: hPa) at the sampling plot, and T is the temperature in the chamber (units: K) at the time of sampling. V0, P0, and T0 are the molar volumes (L mol−1) of the gas at standard conditions, air pressure (units: hPa), and absolute temperature (units: K), respectively, and H (units: m) is the height of the sampling box above the ground (Song et al., 2009). The data can be subjected to later calculations only if the goodness-of-fit (R2) of the linear regression results for four or five samples is ≥ 0.80 (Ma et al., 2020). Mean fluxes are expressed as the mean and standard deviation of three replicates.The cumulative flux of CH4 gas was estimated as follows:
where i and i + 1 are the ith and ith + 1 observations, respectively; Fi is the CH4 flux (units: mg m−2 h−1) of the ith observation; and Di is the Julian date of the ith observation.
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In September 2017, the relative coverage, plant height, and dominant species were measured randomly in 15 sampling plots (50 cm × 50 cm) (Ma et al., 2018). At the same time, soil samples were taken from the 0–10 cm layer using a soil auger (diameter: 5 cm) following the diagonal five-point method (four points selected at each end of the “X” and one point at the intersection) (Wang et al., 2020). Five soil samples from the same soil layer in each plot were mixed to form one soil sample, for a total of 15 soil samples. After removing debris such as stones and residual roots, the samples were dried and put into self-sealing bags through 100-mesh soil sieves for determination of the soil pH value, SOC, and total nitrogen (TN).
The soil total porosity (STP) of the 0–10 cm layer was measured using the ring knife method (volume: 100 cm3) (Wang et al., 2020). Soil pH was measured with a pH meter (PHS-3S, INESA Scientific Instrument Co., Shanghai, China), and the soil water ratio of suspension was 1:5 (Wu and Mu, 2019). SOC and TN were determined by referring to the method of Wu et al. (2020).
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The data were organized using Microsoft Excel 2019, and all data were statistically analyzed using SPSS 22.0. One-way analysis of variance (Duncan’s Multiple Range Test, P < 0.05) was used to determine the differences in vegetation properties (coverage, height), soil CH4 fluxes, and soil characteristics [pH, STP, SOC, TN, ratio of carbon to nitrogen (C/N), T10, SWC10] among plant community types. General linear model (GLM) analysis and analysis of covariance (ANCOVA) were used to compare the interaction and effects of different plant community types (PCT) and soil temperature/soil water content on soil CH4. The relationships between environmental variables (T10, SWC10) and soil CH4 fluxes in the five plant community types were analyzed using Pearson correlation analysis (two-tailed). The interrelationships between T10, SWC10, and soil CH4 fluxes in the five plant community types were analyzed using a linear regression method.
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The vegetation properties (dominant species, vegetation cover, plant height) varied clearly at the five sites (Table 1). The plant community type significantly affected the physical properties of the soil (STP, T10, SWC10) throughout the experimental period (P < 0.05, Table 2). The STP of MS was significantly lower than that of the other four plant community types; the mean T10 of the five plant community types from 0 cm to 10 cm showed a trend of XS < SB < CK < HR < MS; and the variation in 10 cm soil SWC ranged from 14.0% to 24.3% (Table 2), showing a trend of CK < SB < HR < MS < XS (Table 2). The average T10 and SWC10 from 0 cm to 10 cm for all five plant community types showed a trend that the growing season was greater than the non-growing season (Figs. 2b and c). The SOC of MS was significantly higher than that of the other four plant community types (P < 0.05). The soil TN of XS was significantly higher than that of the other plant community types, and the soil C/N of XS, CK, and HR was significantly lower than that of the other two plant community types.
Plot STP (%) T10 (°C) SWC10 (%) pH SOC (g kg−1) TN (g kg−1) C/N MS 49.45 ± 0.42a 19.68 ± 2.08c 0.17 ± 0.01a 6.75 ± 0.16a 11.08 ± 0.32d 0.45 ± 0.05b 25.73 ± 3.84b XS 73.39 ± 3.16c 6.75 ± 1.46a 0.24 ± 0.01b 6.92 ± 0.22a 10.58 ± 0.09cd 0.77 ± 0.00c 13.68 ± 0.11a CK 71.06 ± 2.24c 15.80 ± 1.80bc 0.14 ± 0.01a 6.58 ± 0.34a 5.45 ± 0.55a 0.29 ± 0.01a 18.86 ± 1.88a HR 62.85 ± 0.34b 17.81 ± 1.88bc 0.16 ± 0.01a 6.67 ± 0.15a 7.91 ± 0.21b 0.45 ± 0.00b 17.71 ± 0.54a SB 68.36 ± 1.03bc 11.57 ± 1.62ab 0.15 ± 0.01a 7.00 ± 0.41a 9.57 ± 0.30c 0.32 ± 0.00a 29.92 ± 0.86b Notes: STP, soil total porosity; SOC, soil organic carbon; TN, total nitrogen; C/N, carbon nitrogen ratio; T10, soil temperature of top 10 cm; SWC10, soil moisture of top 10 cm. Superscript letters indicate significant differences between plant community types (P < 0.05). Table 2. Physicochemical properties of soil (0–10 cm depth) from sites with different plant community types.
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Throughout the observation period, soil CH4 fluxes of the five different plant community types showed net uptake, with fluxes ranging from −0.061 mgC m−2 h−1 to −0.086 mgC m−2 h−1. The soil CH4 fluxes differed significantly (P < 0.05) among the different plant community types (Fig. 5), and the average soil CH4 fluxes of SB were 1.29, 1.42, 1.20, and 1.08 times higher than those of MS, XS, CK, and HR, respectively. The cumulative soil CH4 fluxes of the five different plant community types ranged from 14.986 kgC ha−1 to 19.796 kgC ha−1 throughout the observation period, showing a trend of XS < MS < CK < HR < SB (Table 3).
Figure 5. Annual average soil CH4 flux under different plant community types: MS, Medicago sativa grassland; XS, Xanthoceras sorbifolium forestland; CK, Caragana korshinskii bushland; HR, Hippophae rhamnoides shrubland; SB, Stipa bungeana grassland. Lowercase letters indicate statistically significant differences within observations among different plant community types (P = 0.05).
MS (kgC ha−1) XS (kgC ha−1) CK (kgC ha−1) HR (kgC ha−1) SB (kgC ha−1) Y1 −5.943 ± 0.743 −7.532 ± 0.500 −7.803 ± 0.499 −8.938 ± 0.956 −8.554 ± 1.450 Y2 −9.330 ± 0.475 −7.454 ± 0.524 −8.781 ± 0.728 −9.724 ± 0.426 −11.241 ± 0.449 Total −15.273 ± 0.295 −14.986 ± 0.500 −16.585 ± 1.127 −18.662 ± 0.737 −19.796 ± 1.566 Notes: Values are presented as mean ± standard error. Y1, November 2017 to October 2018; Y2, November 2018 to October 2019. Table 3. Cumulative estimates of soil CH4 uptake under different plant community types.
Throughout the observation period, there were significant seasonal variations in soil CH4 fluxes among the five different plant community types (Fig. 6), with soil CH4 uptake occurring mainly during the growing season [SB (−0.101 ± 0.007 mgC m−2 h−1) > HR > CK > MS > XS (−0.073 ± 0.005 mgC m−2 h−1)]. In addition, soil CH4 uptake began to decrease with fluctuation in November and reached its lowest value in February, after which the soil CH4 flux gradually increased in volatility and reached a peak in April–June.
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GLM analysis of plant community type and soil CH4 flux showed that the interaction terms for PCT × T10 and PCT × SWC10 were not significantly different for soil CH4 fluxes (P > 0.05, Table 4), indicating that there were no interactive effects of plant community type and T10/SWC10 on soil CH4 flux. The ANCOVA of plant community type and soil CH4 flux showed that excluding the effect of T10, there was a significant effect of plant community type on soil CH4 flux (P < 0.05); and excluding the effect of SWC10, there was a significant effect of plant community type on soil CH4 flux (P < 0.05) (Table 4).
GLM analysis ANCOVA analysis Fixed factors F Sig. Fixed factors F Sig. PCT 1.353 0.251 PCT 60.392 0.000 T10 55.539 0.000 T10 4.841 0.001 PCT × T10 0.803 0.524 − − − PCT 1.579 0.181 PCT 4.121 0.044 SWC10 3.844 0.051 SWC10 3.153 0.015 PCT × SWC10 0.324 0.862 − − − Notes: Soil CH4 fluxes were used as dependent variables, while the corresponding SWC10 or T10 were covariates. The fixed factor was plant community type (PCT). The F-value is the ratio of the two mean squares (effect term/error term). Significant values (P < 0.05) are indicated in bold. Table 4. Results of GLM analysis and ANCOVA.
There was a highly significant positive correlation (R2 = 0.60–0.74, P < 0.01) between soil CH4 flux and T10 under different plant community types (Table 5). There was also a significant positive correlation (R2 = 0.44–0.57, P < 0.05) between soil CH4 flux and SWC10 in MS, XS, and CK (Table 5). The results of linear regression analysis for the different environmental variables under different vegetation community types showed that the variations in T10 and SWC10 explained 36.0%–55.2% and 6.18%–33.3% of the temporal variation in soil CH4, respectively (P < 0.01) (Fig. 7).
Plot T10 SWC10 MS Pearson 0.607** 0.444* Sig. (two-tailed) 0.002 0.030 XS Pearson 0.600** 0.577** Sig. (two-tailed) 0.002 0.003 CK Pearson 0.743** 0.491* Sig. (two-tailed) 0.000 0.015 HR Pearson 0.660** 0.249 Sig. (two-tailed) 0.000 0.241 SB Pearson 0.606** 0.295 Sig. (two-tailed) 0.002 0.162 Notes: A double asterisk (**) indicates significance at p < 0.01, while a single asterisk (*) indicates significance at p < 0.05. T10, soil temperature of top 10 cm; SWC10, soil water content of top 10 cm. Negative fluxes values indicating absorption (sinks) have been converted to positive values to facilitate the analysis. Table 5. Pearson correlation coefficients and their two-tailed significance between environmental factors (T10 and SWC10) and soil CH4 flux under different plant community types during November 2017 to October 2019.
Plot | Area (m2) | Longitude and latitude | Elevation (m) | Main species | Coverage (%) | Height (cm) |
MS | 20 × 20 | 104°39′1.82′′E 35°34′48.07′′N | 1990 | Medicago sativa (90%), Stipa bungeana, Artemisia lavandulifolia | 90.06±1.58b | 62.23±0.23d |
XS | 20 × 20 | 104°39′10.62′′E 35°34′45.08′′N | 2018 | Xanthoceras sorbifolium (86%), Bupleurum chinense, Gentiana macrophylla, Leontopodium leontopodioides | 95.32±2.35c | 76.45±2.54e |
CK | 20 × 20 | 104°39′1.51′′E 35°34′45.00′′N | 1999 | Caragana korshinskii (42%), Potentilla chinensis, Picris hieracioides | 50.43±5.45a | 16.00±0.79a |
HR | 20 × 20 | 104°39′0.18′′E 35°34′47.32′′N | 1998 | Hippophae rhamnoides (81%), Leontopodium leontopodioides, Artemisia annua | 89.26±0.78b | 54.89±1.23c |
SB | 20 × 20 | 104°39′3.05′′E 35°34′45.48′′N | 2008 | Stipa bungeana (92%), Plantago asiatica, Setaria viridis, Leymus secalinus | 98.23±0.63c | 35.93±0.44b |
Notes: XS, Xanthoceras sorbifolium forestland; SB, Stipa bungeana grassland; CK, Caragana korshinskii bushland; HR, Hippophae rhamnoides shrubland; MS, Medicago sativa grassland. The percentage of the main species is the coverage of the dominant species. Values are presented as mean ± standard error. Superscript letters indicate significant differences between plant community types (P < 0.05). |