Enzyme and osmotic adjustment compounds of key species can help explain shrub encroachment in a semiarid sandy grassland

Enzyme and osmotic adjustment compounds of key species can help explain shrub encroachment in a semiarid sandy grassland

Ecological Indicators 101 (2019) 541–551 Contents lists available at ScienceDirect Ecological Indicators journal homepage: www.elsevier.com/locate/e...

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Ecological Indicators 101 (2019) 541–551

Contents lists available at ScienceDirect

Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind

Original Articles

Enzyme and osmotic adjustment compounds of key species can help explain shrub encroachment in a semiarid sandy grassland

T

Liu Yanga,b, Liming Laia, Jihua Zhoua, Sangui Yia,b, Qinglin Suna,b, Heyi Lia,b, Lianhe Jianga, ⁎ Yuanrun Zhenga, a b

Key Laboratory of Resource Plants, West China Subalpine Botanical Garden, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing 100093, China University of Chinese Academy of Sciences, Beijing 100049, China

ARTICLE INFO

ABSTRACT

Keywords: Ordos Plateau Sandy environment Drought resistance Antioxidant enzyme system Osmotic adjustment

Rationale: In arid and semiarid grasslands where shrub encroachment usually occurs, water plays an important role and might control the process of shrub encroachment. Understanding how species adapt to different sandy environments can help explain the shrub encroachment process. Central methods: Four different grades of shrub encroached grasslands were selected as follows: the Agriophyllum squarrosum community in shifting sandy land (SA), the Artemisia ordosica community in semifixed sandy land (SFA), the A. ordosica community in fixed sandy land (FA) and the Stipa bungeana community in fixed sandy land (FS), which are located on the Ordos Plateau (China) and were selected to analyze the dynamics of enzyme and osmotic adjustment compounds of species in different stages of shrub encroachment. Key results: The results showed that from the community in shifting sandy land to the community in fixed sandy land, the average enzyme activities of species decreased and then increased; the malondialdehyde content increased, and the osmotic adjustment compounds increased (or increased and then decreased). The enzyme activities of grasses were significantly higher than those of shrubs. However, there were no significant differences in the malondialdehyde contents of grasses and shrubs. The proline and soluble protein contents of shrubs were significantly higher than those of grasses. The soluble sugar content of grasses was significantly higher than those of shrubs. The D values indicated that the drought resistance of the five species decreased as follows: S. bungeana in FS > S. bungeana in FA > Caragana korshinskii in FA > C. korshinskii in FS > A. ordosica in FS > A. squarrosum in SA > Artemisia sphaerocephala in SFA > A. sphaerocephala in SA > A. ordosica in FA > A. ordosica in SFA. Main conclusions: The results suggest that the five dominant species in different shrub encroachment stages could enhance their drought resistance by upregulating the antioxidant system and osmotic adjustment in response to drought stress. S. bungeana had a higher drought resistance. For different plant functions, grass had a higher drought resistance than shrubs. It is concluded that S. bungeana can adapt to a drier environment; when the surface soil layer becomes dry, S. bungeana communities developed well due to its high drought ability. Compared to A. ordosica, the S. bungeana community can be a dominant community when human disturbance decreased in the Ordos Plateau.

1. Introduction Shrub encroachment is defined as a global phenomenon of increased density and cover of native woody plants in diverse grasslands, especially in arid and semiarid grasslands (Van Auken, 2000). These indigenous woody plants increase their density and coverage because of changes in abiotic or biotic factors. Increasing the number of woody plants is not the cause of shrub encroachment but the result of changes

in other factors (Van Auken, 2009). The shift in plants through time and space from grass to shrub-dominated communities is irreversible and abrupt (D'Odorico et al., 2012). The driving factors involving shrub encroachment are climate change, increasing atmospheric CO2 concentration, heavy grazing pressure, and changes in fire frequency and intensity. Shrub encroachment is usually determined by the interactions and combinations of these driving factors (Belayneh and Tessema, 2017; Devine et al., 2017).

⁎ Correspondence author at: Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, No. 20 Nanxincun, Xiangshan, Beijing 100093, China. E-mail address: [email protected] (Y. Zheng).

https://doi.org/10.1016/j.ecolind.2019.01.044 Received 30 August 2018; Received in revised form 30 December 2018; Accepted 21 January 2019 Available online 29 January 2019 1470-160X/ © 2019 Elsevier Ltd. All rights reserved.

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Shrub encroachment has been reported in America, Australia, Africa and Inner Mongolia, where most research on this process is concentrated (Peng et al., 2013; Stevens et al., 2016). Most studies focus on the causes and mechanisms of shrub encroachment, and its impact on the structure and function of ecosystems (Van Auken, 2009; Belay et al., 2013). Ward et al. (2014) assessed the timing and scale of woody plant encroachment in South Africa by using aerial photographs and concluded that global drivers were more important than local drivers. Saha et al. (2015) used precipitation data of Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer (MODIS), and the Normalized Difference Vegetation Index (NDVI) from the 2000–2013 in southern Africa to examine the link between greening and shrub encroachment. Thompson et al. (2017) studied the response of species composition and soil characteristics to the microclimate in different shrub overgrown regions in the United States. Nie et al. (2012) simulated the hydrological consequences of 0 to 100% mesquite encroachment on the upper San Pedro watershed (U.S./Mexico) by using the Soil and Water Assessment Tool (SWAT) model and showed that the annual average basin evapotranspiration increased, while surface runoff and percolation decreased with mesquite encroachment. Munozrobles et al. (2011) studied the hydrological and erosional responses in different vegetation states in semiarid Australia. Li et al. (2016) evaluated the effects of shrub encroachment on soil organic carbon content at a global level. Zhou et al. (2018) studied phosphorus content dynamics to a depth of 120 cm across a subtropical savanna landscape in Texas, USA and showed that total phosphorus content increased and patterns of spatial heterogeneity in soil total phosphorus content altered following shrub encroachment. Caracciolo et al. (2016) illustrated the mechanisms of shrub encroachment into the Northern Chihuahuan Desert grasslands by using a cellular automata model. Based on these research, hypotheses, including the proposal of two opposite types of controls have been put forward to explain shrub encroachment. Niche separation is the most discussed of the bottom-up control mechanisms; it assumes that water is the limiting resource and deep-rooted shrubs and shallow-rooted grasses use different soil water resources. On the other hand, disturbances such as grazing, fire and random extreme drought events are top-down controls that limit plant growth (Cipriotti et al., 2014). A two-layer hypothesis proposes that shallower-rooted grasses use water only from shallow soil water, while deeper-rooted woody species use subsoil water because of vertical niche separation (Walker and Noy-Meir, 1982). Additionally, the resourcepool hypothesis proposes that the shallow soil water pool (growth pool) promotes growth, while the deeper pool (maintenance pool) maintains physiological activities and the survival of deep-rooted species (Ryel et al., 2008). Therefore, soil water availability in different soil layers should be a key reason for shrub encroachment. The decrease in soil water usually causes drought due to a deficit in water supply to the roots coupled with high transpiration rates (Rahdari and Hoseini, 2012). Drought can affect physiological and biochemical changes in plant tissues, and plants can product more reactive oxygen species (ROS) in plastids because of stomatal closure as a response to drought; excessive ROS will cause the denaturation of proteins, peroxidation of lipids and cellular oxidative damage (Pandey and Shukla, 2015). To protect themselves from such damage, plants have developed a defense system that regulates antioxidant enzymessuch as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) (Gonçalves et al., 2017; Li et al., 2018). The accumulation of osmotic adjustment compounds including proline, soluble sugar and soluble protein is also a strategy for adapting to drought. Malondialdehyde (MDA) is the product of membrane lipid peroxidation and could be another indicator for drought resistance (Aguiar-Silva et al., 2016; Filippou et al., 2014; Liu et al., 2017; Sheikh-Mohamadi et al., 2017). Although these results are useful to understand how plants respond to soil water change, there is little research focusing on how grass and woody plants adapt to soil water changes by regulating enzyme activities and osmotic adjustment compounds during shrub encroachment.

Inner Mongolia grassland accounts for approximately 24% of the total grassland area in China; here, grassland degradation is serious, and the shrub area has reached nearly 5.1 million hectares (Zhang et al., 2006). The Ordos Plateau located in the southern part of Inner Mongolia Autonomous Region was historically a grassland with abundant grass and water, but due to unreasonable reclamation and overgrazing during the past 600–700 years, zonal vegetation (Stipa bungeana) has been encroached seriously by a semishrub species (Artemisia ordosica), therefore, the Ordos Plateau could serve as an ideal place to study the process of shrub encroachment (Cai et al., 2018). The environments on Ordos Plateau affected by long term shrub encroachment can be divided into shifting sandy land, semifixed sandy land and fixed sandy land (Cai et al., 2018). In these three kinds of sandy lands, the following four types of plant communities represent the successional stages of encroachment: Agriophyllum squarrosum community in shifting sandy land (SA), A. ordosica community in semifixed sandy land (SFA), A. ordosica community in fixed sandy land (FA) and S. bungeana community in fixed sandy land (FS). These communities can be regarded as a series of different grades of shrub encroachment (i.e., SA, FSA, FA, and FS represent extremely severe, severe, moderate, and slight grades of encroachment, respectively) (Ding et al., 2011). Accordingly, the species composition (from shrub dominated to grass dominated vegetation) and soil water conditions change considerably during shrub encroachment (Cai et al., 2018). Therefore, the dominant shrub and grass species in different shrub encroachment stages might have different abilities to resist drought by different regulation abilities of enzymes and osmotic adjustment compounds, which could help to explain shrub encroachment. However, the role of enzymes and osmotic adjustment compounds of dominant species during shrub encroachment is still unclear. We hypothesized that S. bungeana in fixed sandy land have higher drought tolerance than A. ordosica in semifixed and fixed sandy land and A. sphaerocephala in shifting sandy land with different soil water availabilities. To test this hypothesis, we chose four grades of shrub encroachment on the Ordos Plateau and measured the changes in enzyme activity, malondialdehyde, and osmotic adjustment compounds in grass and shrub species. The objectives of this study are as follows: (1) to understand how the enzyme activity, malondialdehyde, and osmotic adjustment compounds of main species changed in different shrub encroachment stages and (2) to understand their roles in shrub encroachment. Answering these questions will provide a basis for the better understanding of drought resistant strategies for grass and shrub species and help make decisions on the restoration of shrub-encroached grassland. 2. Materials and methods 2.1. Study area The Ordos Plateau is located in the southern part of the Inner Mongolia Autonomous Region (37°35′24″-39°29′37.6″N, 106°42′40″111°27′20″E) and is a relatively independent and special geographical area in the inland arid and semiarid region of northern China. Its elevation is 850–1600 m. The regions to the east, west and north are surrounded by the Yellow River, and that to the south is mainly surrounded by the Mu Us sandy land and beach land. The plateau belongs to a typical semiarid continental climate, with an annual average temperature of 6–8 °C and annual precipitation of 150–450 mm concentrated from Jul. to Sep. The average annual amount of sunshine is 3011 h, and the frost-free period is generally 140–157 days. The landform types are complex, with beam and sandy lands (including shifting sandy land, semifixed sandy land and fixed sandy land). Zonal vegetation is a warm-temperate S. bungeana steppe (Cai et al., 2018). Currently, A. ordosica is the dominant species of the most widely distributed sandy plant community. The research site was located in Ejin Horo Town in the middle of Ejin Horo Banner at 39°12′-39°24′N and 542

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mixed thoroughly and the absorbance levels at 560 nm were determined using a spectrophotometer. The results were expressed as units of enzyme activity, U/g fresh weight (FW). POD activity was determined by measuring the oxidation of guaiacol in the presence of hydrogen peroxide (H2O2) at 470 nm. One unit of POD activity (U) was defined as the amount of enzyme required to increase the absorbance at 470 nm by 0.01 per min per mL. The reaction mixture consisted of 15 μL supernatant, 270 μL distilled water, 520 μL sodium acetate and acetic acid, 130 μL H2O2 and 135 μL guaiacol, added in order. The reaction mixture was mixed immediately, and the increase in absorbance at 470 nm from 30 s (A1) up to 1.5 min (A2) was determined using a spectrophotometer. The POD activity was calculated using the formula POD = 7133 × (A2 − A1)/W, where W represents the FW. The results were expressed as units of enzyme activity, U/g FW. CAT activity was determined by following the consumption of H2O2 at 240 nm. One unit of POD activity (U) was defined as the amount of enzyme catalyzing the decomposition of 1 nmol of H2O2 per min. The reaction mixture consisted of 100 μL H2O2 and 20 mL sodium phosphate (Na2HPO4/ NaH2PO4) buffer. A 35-μL aliquot of the supernatant was mixed thoroughly with 1 mL reaction mixture, and then the decrease in absorbance at 240 nm (A1) up to 1 min (A2) was determined using a spectrophotometer. The CAT activity was calculated using the formula CAT = 678 × (A1 − A2)/W, where represents the FW. The results were expressed as units of enzyme activity, U/g FW. To measure MDA, the reaction mixture consisted of 0.6 mL trichloroacetic acid and thiobarbituric acid. A 0.2-mL aliquot of the supernatant was added and the sample was placed in a boiling water bath (90 °C) for 30 min. After cooling, the mixture was centrifuged at 10,000×g at 25 °C for 10 min. The absorbance levels of the supernatant at 532 nm (A532) and 600 (A600) nm were recorded and expressed as nmol/g FW. The MDA content was calculated using the formula MDA = 25.8 × (A532 − A600)/W, where W represents the FW. To measure Pro, 0.5 mL supernatant, 0.5 mL glacial acetic acid and 0.5 mL ninhydrin plus phosphoric acid were added to each experimental tube. The mixture was maintained in a boiling water bath for 30 min and shaken every 10 min. After cooling, 0.5 mL toluene was added to the mixture and shaken for 30 s. The absorbance of the supernatant at 520 nm (A520) was recorded and expressed as μg/g FW. The Pro content was calculated using the formula Pro = 19.2 × (A520 + 0.0021)/W, where W represents the FW. To measure SP, the reaction mixture consisted of 1000 μL bicinchoninic acid, sodium carbonate, sodium tartaric, sodium hydroxide, sodium bicarbonate and copper (II) sulfate pentahydrate. Blank, standard and control tubes were run in the same manner but contained 200 μL distilled water, bovine serum albumin plus distilled water and supernatant, respectively. In the blank, standard and control tubes, the solutions were mixed thoroughly and maintained at room temperature for 10 min, then the absorbance at 595 nm was recorded and expressed as mg/g FW. The SP content was calculated using the formula SP = 50 × (Acontrol − Ablank)/(Astandard − Ablank). To measure SS, the reaction mixture consisted of 1000 μL sulfuric acid and 100 μL ethyl acetate plus anthrone. Control and blank tubes were run in the same manner but contained 200 μL supernatant plus distilled water and 400 μL distilled water, respectively. In control and blank tubes, the solutions were mixed thoroughly and maintained in a boiling water bath for 10 min. After cooling, the absorbance of the supernatant at 620 nm was determined using a spectrophotometer and expressed as mg/g FW. The SS content was calculated using the formula SS = 1.17 × (Acontrol − Ablank + 0.07)/W, where W represents the FW.

Fig. 1. The location of the study sites on the Ordos Plateau, abbreviations for sampling sites are shown in Table 1.

109°33′-109°51′E, with an elevation of 1350–1432 m (Fig. 1). 2.2. Experimental design Field experiments were conducted in July 2017 in four different grades of shrub encroached grasslands (SA, SFA, FA, FS) (Fig. A.1), with three replicates for each grade. In each replicate, one leaf sample plot of 20 m × 20 m was established. Leaf samples were collected from A. squarrosum (grass) and Artemisia sphaerocephala (semi-shrub) in SA, A. ordosica (semi-shrub) and A. sphaerocephala in SFA, A. ordosica, S. bungeana (grass) and Caragana korshinskii (shrub) in FA, and S. bungeana, A. ordosica and C. korshinskii in FS (Fig. A.2). Hereafter, we consider semi-shrub and shrub areas as shrubs. The topmost fully developed functional leaves (upper portion of the stem) of representative plants were collected from over thirty plants in the morning one day to measure physiological and biochemical indices. The leaf samples were immediately kept in a foam box with dry ice, brought to the laboratory, and kept at −80 °C. SOD, POD, CAT, MDA, proline (Pro), soluble sugar (SS) and soluble protein (SP) concentrations were analyzed with SOD, POD, CAT, MDA, Pro, SS and SP assay kits, respectively (Comin Biotechnology Co., Ltd. Suzhou, China) (Pan et al., 2016). Briefly, 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 tissues 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 8000×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 1000×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 8000×g at 25 °C for 10 min to produce the supernatant. SOD activity was determined by measuring its ability to inhibit the photochemical reduction of nitroblue tetrazolium (NBT) at 560 nm. One unit of SOD activity (U) was defined as the amount of enzyme that caused a 50% decrease in the SOD-inhibited NBT reduction. The reaction mixture consisted of 240 μL potassium phosphate buffer (K2HPO4/ KH2PO4) plus ethylenediaminetetraacetic acid, 510 μL xanthine, 6 μL xanthine oxidase and 180 μL NBT. Controls and blanks tubes were run in the same manner but contained 90 μL supernatant and distilled water, respectively. In controls and blanks tubes, the solutions were

2.3. Statistical test To evaluate the drought resistance ability of a species, principal component analysis (PCA) was used to develop an index (Wold et al., 1987). Seven parameters (SOD, POD, CAT, MDA, SS, Pro, and SP) 543

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related to the drought resistance of A. squarrosum, A. sphaerocephala, A. ordosica, C. korshinskii and S. bungeana were converted into 7 principal components for the principal component analysis; 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):

activities (except for SOD) and malondialdehyde content of A. ordosica increased significantly (P < 0.05); for S. bungeana, superoxide dismutase activity decreased (P < 0.05), while peroxidase and catalase activity increased (P < 0.05) (Fig. 2). 3.2. Responses of osmotic adjustment compounds In SA, the osmotic adjustment compounds content of A. squarrosum was significantly lower than that of A. sphaerocephala (P < 0.05). In SFA, the osmotic adjustment compounds content of A. ordosica was lower than that of A. sphaerocephala (P < 0.05). In FA and FS, the proline content of C. korshinskii was the highest, followed by A. ordosica, and the lowest content was observed for S. bungeana (P < 0.05); the soluble sugar content of S. bungeana was the highest, followed by C. korshinskii, and the lowest content was observed in A. ordosica (P < 0.05). The soluble protein content of A. ordosica in FA was the highest, and soluble protein content of C. korshinskii in FS was the highest. For the A. ordosica community shifting from FA to FS, the soluble sugar content increased (P < 0.05), while the proline and soluble protein contents decreased (P < 0.05). For S. bungeana, the trends of soluble sugar and soluble protein content were opposite to those of A. ordosica (Fig. 2).

n

Wi = Pi/

Pi

i = 1, 2, 3, …, n

(1)

i=1 n

D=

[Ui × wi] i = 1, 2, 3, …, n

(2)

i=1

where Pi represents the contribution rate of the principal component i, Ui represents the subordinate function of the principal component i, and D represents the comprehensive evaluation index for the drought resistance of a species (the comprehensive drought resistance index). The higher the D value is, the higher the drought resistance. A statistical analysis was performed by a two-way ANOVA. If significant differences were found, Duncan’s test was used to determine differences between treatment means (P < 0.05) (Kabacoff, 2015). All statistical analyses were performed using SPSS Statistics 17.0 (SPSS Inc., Chicago, IL, USA).

3.3. Responses of enzyme activities, malondialdehyde content and osmotic adjustment compounds in different successional stages

3. Results In general, the F values were highly significant for the shrub encroachment stages and species for enzyme, malondialdehyde content and osmotic adjustment compounds (P < 0.001). The exception was for POD in response to the shrub encroachment stages (P > 0.05) (Table 1).

In communities shifting from SA, SFA, and FA to FS, the average enzyme activities of all species in the communities decreased initially and then increased (P < 0.05); malondialdehyde content increased (P < 0.05); proline content increased and then decreased (P > 0.05); soluble sugar content increased (P > 0.05); and soluble protein content increased and then decreased (P < 0.05) (Fig. 3).

3.1. Responses of enzyme activity and malondialdehyde content

3.4. Responses of enzyme activities, malondialdehyde content and osmotic adjustment compounds in different plant functional types

In SA, the enzyme activity and malondialdehyde content of A. squarrosum were significantly higher than those of A. sphaerocephala (P < 0.05); in SFA, the superoxide dismutase and catalase activity of A. ordosica were higher than those of A. sphaerocephala, while the opposite was true for peroxidase activity and malondialdehyde content (P < 0.05); in FA and FS, enzyme activity and malondialdehyde content of S. bungeana and C. korshinskii were significantly higher than those of A. ordosica (P < 0.05). In the shift from FA to FS, enzyme

The enzyme activities of grasses were significantly higher than those of shrubs (P < 0.05). The average superoxide dismutase, peroxidase, and catalase activities of grasses were 1.44, 6.06, and 3.26 times those of shrubs, respectively. There was no significant difference between grasses and shrubs in malondialdehyde content. The proline content of shrubs was significantly higher than that of grasses (P < 0.05); the average proline content of shrubs was 2.26 times that of grasses. The soluble sugar content of grasses was significantly higher (1.29 times) than that of shrubs (P < 0.05). The soluble protein content of shrubs was significantly higher (1.68 times) than that of grasses (P < 0.05) (Fig. 4).

Table 1 Results of a two-way ANOVA with shrub encroachment stages and species. Fvalues are shown. Enzyme, malondialdehyde content and osmotic adjustment compounds were analyzed for five species (Agriophyllum squarrosum, Artemisia sphaerocephala, Artemisia ordosica, Caragana korshinskii, Stipa bungeana) in shrub encroachment stages (SA, SFA, FA, FS). Parameter

SOD POD CAT MDA Pro SS SP df

3.5. Comprehensive drought resistance index (D)

Effect Shrub encroachment stages

Species (S)

S×S

11.464*** 1.188ns 193757.259*** 33.092*** 132.148*** 51.739*** 495.049*** 3

128.679*** 1195.488*** 2590.047*** 144.268*** 1339.046*** 2258.946*** 625.789*** 4

10.333*** 325.328*** 1145.849*** 22.292*** 147.402*** 209.986*** 529.502*** 12

The contribution rate was over 80% of the first two principal components, which contained almost all information of the measured parameters. The eigenvalue of the first principal component was 4.495; its contribution rate was 64.217%; and the corresponding characteristic vectors of SOD, POD, CAT and MDA were large. The eigenvalue of the second principal component was 1.134; its contribution rate was 16.197%; and the corresponding characteristic vectors of Pro, SS and SP were large (Table 2, Table A.1). Based on the standardized characteristic vector, the linear combinatorial equations of the first two principal components and 7 parameters were obtained and expressed as follows:

Abbreviations: A. squarrosum community in shifting sandy land (SA), A. ordosica community in semi-fixed sandy land (SFA), A. ordosica community in fixed sandy land (FA), S. bungeana community in fixed sandy land (FS). Superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), malondialdehyde (MDA), proline (Pro), soluble sugar (SS), soluble protein (SP). Significance levels: ***, P < 0.001; ns, P > 0.05.

C (1) = 0.440X 1 + 0.444X 2 + 0.408X 3 + 0.399X 4 0.325X 7 544

0.200X 5 + 0.372X 6 (3)

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Fig. 2. Responses of SOD, POD, CAT, MDA, Pro, SS and SP (Mean ± SE) of every species in different shrub encroachment stages. Each bar represents the mean of three replicates; bars with different lowercase letters are significantly different from each other at p < 0.05 (Duncan Test). Abbreviations are shown in Table 1.

545

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Fig. 3. Responses of average enzyme, malondialdehyde content and osmotic adjustment compounds (Mean ± SE) of all species in each shrub encroachment stages. Each bar represents the mean of three replicates; bars with different lowercase letters are significantly different from each other with different shrub encroachment stages at p < 0.05 (Duncan Test). Abbreviations are shown in Table 1.

C (2) = 0.001X 1 + 0.146X 2 + 0.389X 7

components and Eq. (1), Wi was calculated, and based on the values of Wi, C(i), Ui and Eq. (2), the value of D was calculated. The D values indicate that the drought resistance of species in different successional stages decreased as follows: S. bungeana in FS (0.901) > S. bungeana in FA (0.847) > C. korshinskii in FA (0.569) > C. korshinskii in FS (0.502) > A. ordosica in FS

0.228X 3 + 0.358X 4 + 0.695X 5 + 0.406X 6 (4)

where X1, X2, …X7 represent SOD, POD, CAT, MDA, Pro, SS and SP, respectively. Based on the contribution rates of the first two principal 546

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Fig. 4. Responses of enzyme, malondialdehyde content and osmotic adjustment compounds (Mean ± SE) in two plant functions (Grass and shrub). Each bar represents the mean of three replicates; bars with different lowercase letters are significantly different from each other with different plant functions at p < 0.05 (Duncan Test). Abbreviations are shown in Table 1.

(0.331) > A. squarrosum in SA (0.241) > A. sphaerocephala in SFA (0.179) > A. sphaerocephala in SA (0.173) > A. ordosica in FA (0.151) > A. ordosica in SFA (0.139) (Table A.2).

4. Discussion 4.1. Effects of enzyme activity The balance between ROS generation and elimination can be disturbed by drought stress. Normally, the antioxidant enzyme defense 547

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4.3. Effects of osmotic adjustment compounds

Table 2 Results of principal component analysis. Principal component

Eigenvalue

Contribution rate (%)

Cumulative contribution rate (%)

1 2 3 4 5 6 7

4.495 1.134 0.718 0.316 0.204 0.120 0.012

64.217 16.197 10.254 4.517 2.918 1.720 0.176

64.217 80.414 90.668 95.185 98.104 99.824 100.000

Osmotic adjustment has been considered as a vital mechanism in plant adaptation to stress; specifically, lower osmotic potentials are needed to sustain turgor pressure under conditions of water scarcity (Kaur and Asthir, 2017). Proline is an efficient osmoregulator, and its accumulation is caused by a combination of increased biosynthesis and slow oxidation in mitochondria in leaves under low water potential (Zhang et al., 2015). Soluble sugar and soluble protein function similarly, based on clear evidence that proline, soluble sugar and soluble protein contents change under different water conditions (Zhang et al., 2015). In our study, from the shifting sandy land to fixed sandy land, the communities’ average proline, soluble sugar and soluble protein contents of species changed but not significantly (Except soluble protein in SFA). In the SA and SFA stages, the content of osmotic adjustment compounds of A. sphaerocephala was higher than that in A. squarrosum and A. ordosica, suggesting that A. sphaerocephala had a relatively higher level of osmoregulation, although it was replaced by A. ordosica.

system can eliminate excessive ROS efficiently (Hu et al., 2017). SOD catalyzes the disproportionation of superoxide to O2 and H2O2 (Magalhães et al., 2019). POD and CAT transform H2O2 into H2O and O2, and additionally, CAT can maintain the redox balance (SheikhMohamadi et al., 2017). Previous studies have shown that when plants suffer from drought stress, the antioxidant enzyme activity increases or shows an increase followed by decrease trend (Ansari et al., 2016). In communities shifting from SA, SFA, and FA to FS, the soil moisture generally decreases because of higher rates of evaporation and transpiration (Ding et al., 2011); therefore, the species inhabiting these different environments have different levels of drought resistance. In our study, from the community in shifting sandy land to the community in fixed sandy land, the average enzyme activities of species decreased initially and then increased (P < 0.05). In semifixed sandy land, enzyme activities decreased, possibly due to the appearance of A. ordosica, which is more drought resistant. Enzyme activities then increased in fixed sandy lands, demonstrating that the activities of three enzymes that may function as ROS scavengers at the late fixed sandy stage. At the SA stage, the enzyme activities in A. squarrosum were higher than those in A. sphaerocephala, for the SFA stage, the enzyme activities in A. ordosica was higher than those in A. sphaerocephala (except for the POD activity). These results imply that higher levels of antioxidant enzyme activities are associated with higher drought tolerance and were beneficial to A. ordosica at the SFA stage. In FA and FS, the enzyme activities of S. bungeana and C. korshinskii were significantly higher than those of A. ordosica (except for CAT activity at the FS stage), suggesting a higher resistance to drought stress for S. bungeana and C. korshinskii, which was prepared for S. bungeana to enter the FA stage and remain stable at the FS stage. In terms of plant functional types, the enzyme activities of grasses were significantly higher than those of shrubs, suggesting that grasses were more drought tolerant, which helped S. bungeana become dominant.

4.4. Drought resistance and succession implications In examining the adaptation by these dominant species to these different environments, the following aspects are worth highlighting: first, the comprehensive drought resistance index (D) indicated that, in decreasing order, the drought resistance of the dominant species is S. bungeana > C. korshinskii > A. ordosica > A. squarrosum > A. sphaerocephala from communities in shifting sandy land to communities in fixed sandy land. This finding is basically consistent with the biological and ecological characteristics of these species. A. squarrosum is an annual grass with shallow roots. A. sphaerocephala is a perennial semishrub species with deep roots. A. ordosica is a semi-shrub or small shrub species with a deep root system that reaches down to 1 m deep and is mainly distributed at the 30 cm soil layer. C. korshinskii is a shrub species. S. bungeana is a perennial grass species with a root system mainly distributed in the 0–10 cm soil layers. In the SA stage, community coverage was low and the soil water content was relatively high, especially in the deep layer in the sandy soil. In the SFA stage, species richness and community coverage gradually increased from shifting sandy land to semi-fixed, then A. ordosica appeared because of the relatively improved soil texture and high soil water content in the deep soil layer, which was beneficial to this deep-rooted plant. A. ordosica had high enzyme activities and low MDA content, suggesting it had high drought resistance and the ability to grow in a relatively drier environment compared to SA. In the FA stage, the soil became drier and the soil texture improved, compared to SFA; A. ordosica became the dominant species, rain seepage to deep soil decreased, and therefore, the soil water content improved in the shallow soil layer while the deep soil layer became drier, which was beneficial to shallow-rooted S. bungeana. With its high enzyme activities, S. bungeana became the dominant species in the FS stage, ultimately replacing A. ordosica. This scenario is consistent with the two layers hypothesis (Cipriotti et al., 2014). Second, for the same species in different environments, when soil became drier, the same species could increase their ability to tolerate drought (e.g., in terms of the D value, S. bungeana in FS > S. bungeana in FA; A. ordosica in FS > A. ordosica in FA > A. ordosica in SFA; A. sphaerocephala in SFA > A. sphaerocephala in SA). Generally, our results agree well with the two layer hypothesis (Cipriotti et al., 2014); however, soil water did not always decrease directly in different layers. For example, soil moisture generally decreased from SA, SFA, and FA to FS. In the early successional stage, the soil moisture in the surface layer was low but high in the deep soil layer; however, in the late successional stage, opposite soil moisture conditions were true. If there was no rain for a long time, the soil moisture conditions might be different from the abovementioned

4.2. Effects of malondialdehyde MDA is the final product of membrane lipid peroxidation of plant cells and is used as an indicator of oxidative stress. In our study, from shifting sandy land to fixed sandy land, the average MDA content of species in the communities increased (P < 0.05), reflecting the higher level of damage experienced by species. This result agrees with Ansari et al. (2016) who found that the MDA content of two muskmelon (Cucumis melo) genotypes increased under progressive water stress. In the SA stage, the MDA content of A. squarrosum was higher than that of A. sphaerocephala, and in SFA stage, the MDA content of A. sphaerocephala was higher than that of A. ordosica, suggesting that A. ordosica suffered less membrane damage. In the two fixed sandy lands, although the MDA contents of S. bungeana and C. korshinskii were higher than that of A. ordosica, the former two also had high levels of enzyme activities, thus, they were able to live in the two fixed sandy lands. In terms of plant functional types, grasses and shrubs did not differ in MDA content, showing that MDA may not play an important role in drought stress for the studied species. 548

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conditions; for example, in the early successional stage, the soil moisture in the deep soil layer might be low because of transpiration by deep-root shrub species, while in the late successional stage, soil moisture in surface layer might be low because of transpiration by shallow-root grass species, and soil moisture in deep layer might be high because of rain seepage and no or little transpiration. This might also be the reason why shrub species could encroach grasslands when zonal vegetation of S. bungeana was degraded, and the soil texture became sandier due to human disturbance and wind erosion. Therefore, the drought resistance of some species in different environments did not always increase as the soil got drier (as we expected) and, thus, there is a need for further and more detailed observations before and after rain for a longer period of time in future.

prehensive evaluation showed that the drought resistance of dominant species could be ranked in descending order as follows: S. bungeana > C. korshinskii > A. ordosica > A. squarrosum > A. sphaerocephala from communities in shifting sandy land to communities in fixed sandy land. S. bungeana is the most drought resistant of the five species. In terms of plant functional types, grass showed a greater drought resistance than shrubs. We recommend that S. bungeana be restored as zonal vegetation. During vegetation restoration in sandy lands, semishrub and shrub species, such as A. sphaerocephala, A. ordosica and C. korshinskii, can be used during the early successional stage, because the soil moisture content is high in the deep layer. When shrub vegetation develops, during the late successional stage, the soil texture is improved and the soil becomes dry in the deep layer. Then, the grass species S. bungeana can be used, resulting in the gradual restoration of zonal vegetation.

5. Conclusions In four different grades of shrub encroached environments, five dominant species (A. squarrosum, A. sphaerocephala, A. ordosica, C. korshinskii and S. bungeana) enhanced their drought resistance capabilities by upregulating their antioxidant systems, and their osmotic adjustment-related compounds, in response to drought stress. A com-

Acknowledgment This work was supported by the National Natural Science Foundation of China (grant number 41330749). We also appreciate editor, Prof. Zurlini and reviewers for reviewing this manuscript.

Appendix A

Fig. A.1. Pictures of plant communities in the different shrub encroachment stages. Agriophyllum squarrosum community in shifting sandy land (SA), Artemisia ordosica community in semifixed sandy land (SFA), A. ordosica community in fixed sandy land (FA) and Stipa bungeana community in fixed sandy land (FS).

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Fig. A.2. Pictures for species used in the study. Table A.1 Component matrix of principal component analysis. Abbreviations are shown in Table 1. Parameter

Principal component

SOD POD CAT MDA Pro SS SP

1

2

0.932 0.942 0.864 0.845 −0.425 0.789 −0.689

0.001 0.155 −0.243 0.381 0.740 0.432 0.414

Table A.2 Values of the component score Ci, subordinate function Ui and comprehensive evaluation D of the five species. Species

C(1)

C(2)

U(1)

U(2)

D

Order

Agriophyllum squarrosum in SA Artemisia sphaerocephala in SA A. sphaerocephala in SFA Artemisia ordosica in SFA A. ordosica in FA Caragana korshinskii in FA Stipa bungeana in FA A. ordosica in FS C. korshinskii in FS S. bungeana in FS Weights

−0.329

−2.140

0.302

0.000

0.241

6

−1.732

0.012

0.068

0.588

0.173

8

−2.140 −1.947 −1.677 0.555 3.281 −0.200 0.325 3.865

1.114 −0.068 −0.520 1.521 0.136 −0.802 1.029 −0.281

0.000 0.032 0.077 0.449 0.903 0.323 0.410 1.000 0.799

0.889 0.566 0.443 1.000 0.622 0.365 0.866 0.508 0.201

0.179 0.139 0.151 0.569 0.847 0.331 0.502 0.901

7 10 9 3 2 5 4 1

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