Reclamation of cropland from grassland is regarded as a main reason for grassland degradation; understanding succession from abandoned cropland to grassland is thus crucial for vegetation restoration in arid and semiarid areas. Soil becomes dry when cropland is reverted to grassland, and enzyme and osmotic adjustment compounds may help plants to adapt to a drying environment. Croplands that were abandoned in various years on the Ordos Plateau in China, were selected for the analysis of the dynamics of enzymes and osmotic adjustment compounds in plant species during vegetation succession. With increasing number of years since abandonment, levels of superoxide dismutase increased in Stipa bungeana, first decreased and then increased in Lespedeza davurica and Artemisia frigida, and fluctuated in Heteropappus altaicus. Levels of peroxidase and catalase in the four species fluctuated; levels of proline, soluble sugar and soluble protein either decreased or first increased and then generally decreased. According to a drought resistance index, the drought resistance of the four species was ranked in descending order as follows: S. bungeana > A. frigida > H. altaicus > L. davurica. The drought resistance ability of the different species was closely linked with vegetation succession from communities dominated by annual and biennial species (with main accompanying species of L. davurica and H. altaicus) to communities dominated by perennial species (S. bungeana and A. frigida) when soil became dry owing to increasing evapotranspiration after cropland abandonment. The restoration of S. bungeana steppe after cropland abandonment on the Ordos Plateau is recommended both as high-quality forage and for environmental sustainability.

Experimental design

Field experiments were conducted in July 2017. We selected typical abandoned corn cropland on hard ridge (3, 6, 10, 15 and 20 years since abandonment, based on the information provided by the landowners), and the control was uncultivated natural vegetation near abandoned corn croplands. To ensure similar environments for all sampling plots, all plots were set within 2 km in similar terrain and landform. The species composition of the natural vegetation was similar to the vegetation before the corn croplands were established. Three separate replicates were set up for each age of abandoned cropland and natural vegetation with the same cropping history as well as the same time since abandonment. In each replicate of each age of abandoned cropland and natural vegetation, three leaf-sampling plots (20 m × 20 m) were established, and the topmost fully developed functional leaves (upper portion of stems) were collected from over ten plants chosen randomly in the morning of one day. Leaf samples were collected from the four species that were found in all sample plots: S. bungeana, L. davurica, A. frigida and H. altaicus. All species were deciduous. Leaf samples were immediately placed in a foam box with dry ice, brought to the laboratory, and kept in a -80°C ultralow temperature freezer.

SOD, POD, CAT, MDA, proline (Pro), soluble sugar (SS), and soluble protein (SP) concentrations were analyzed separately with SOD, POD, CAT, MDA, Pro, SS and SP assay kits (Comin Biotechnology Co., Ltd., Suzhou, China) (Pan et al., 2016). Leaf samples that had been maintained at -80°C were ground into a powder with liquid nitrogen. Using a sodium phosphate (Na₂HPO₄/NaH₂PO₄) buffer, SOD, POD, CAT, MDA, Pro and SP were extracted by homogenizing on ice (0.1 g leaf tissue for each SOD, POD, CAT, MDA, Pro and SP assay with 1 mL buffer). To isolate the supernatants for the SOD, POD, CAT and MDA assays, the homogenates were centrifuged at 8,000 ×g at 4°C for 10 min. For the Pro assay, the homogenates were shaken in a boiling water bath (90°C) for 10 min, cooled and then centrifuged at 1,000 ×g at 25°C for 10 min. For the SP assay, the homogenates were centrifuged at 10,000 ×g at 4°C for 10 min. For the SS assay, the leaf samples that had been maintained at -80°C were ground into a powder in liquid nitrogen, then 0.1 g leaf tissue was homogenized with 1 mL distilled water and maintained in a boiling water bath for 10 min. After cooling, the mixture was centrifuged at 8,000 ×g at 25°C for 10 min to produce the supernatant.

In each 20 m × 20 m leaf-sampling plot, quadrats covering 5 m × 5 m for semishrub species and 1 m × 1 m for grass species were established. To ensure accurate measurements of biomass, leaves were not collected in these quadrats for analyses of enzyme activity, MDA, or osmotic adjustment compounds. To obtain the aboveground biomass, the aboveground parts of every species were harvested separately, taken to the laboratory and dried to a constant weight at a temperature of 80°C (Cai et al., 2018).

In each 20 m × 20 m leaf sample plot, intact soil cores were collected randomly using a cutting ring (volume of 100 cm³) from five soil depths (0–5, 5–10, 10–20, 20–30 and 30–40 cm) after removing any rocks and litter. After collecting the soil samples, we immediately measured the fresh weight (FW), and then the samples were taken to the laboratory and oven-dried at 105°C to a constant weight to measure the dry weight (DW). Soil water content (SWC) was calculated as SWC (%) = (FW - DW)/FW.

Statistical analysis

To evaluate the drought resistance ability of a species, principal component analysis (PCA) was used to develop an index (Wold et al., 1987). Averaged data from three replicates for each of the seven parameters (SOD, POD, CAT, MDA, SS, Pro, and SP) related to the drought resistance of S. bungeana, L. davurica, A. frigida and H. altaicus in different abandoned cropland and natural vegetation were converted into 7 principal components for analysis, and then the results of the PCA were used to build a drought resistance index.

The weight (Wi) and the comprehensive evaluation index (D) of each plant were estimated using the following equations (Wang et al., 2015):

      (1)      Wi =Pi/(P1+P2+...+Pn)  i = 1, 2, 3, …, n                    

     (2)      D =U1*W1+U2*W2+...+Un*Wn i = 1, 2, 3, …, n                    

where P_i is the contribution rate of principal component i, U_i is the subordinative function of principal component i, and D is the drought resistance index of the species. The higher the D value, the higher the drought resistance.

Within each of three replicates, samples were collected from three subplots; data from three subplots were averaged as one datum point for each replicate. A statistical analysis was performed by two-way ANOVA. If significant differences were found, Duncan’s test was used to determine mean differences between treatments (P < 0.05) (Kabacoff, 2015). The relationships among SOD, POD, CAT, MDA, Pro, SS and SP were examined using Pearson’s correlation analysis. All statistical analyses, including the test for homogeneity of variance, were performed using SPSS Statistics 17.0 (SPSS Inc., Chicago, IL, USA).

Microsoft Excel was used to create this data file, which contains data for Leaf enzyme activities, MDA, osmotic adjustment compounds and aboveground biomass of dominant species on the Ordos Plateau in China.