sustainability

Article Grazing Affects the Ecological Stoichiometry of the Plant–Soil–Microbe System on the Hulunber Steppe, China

1, 1, 2 1 1 1 Juan Cao †, Ruirui Yan †, Xiaoyong Chen , Xu Wang , Qiang Yu , Yunlong Zhang , Chen Ning 3, Lulu Hou 1, Yongjuan Zhang 4 and Xiaoping Xin 1,*

1 National Hulunber Grassland Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China; [email protected] (J.C.); [email protected] (R.Y.); [email protected] (X.W.); [email protected] (Q.Y.); [email protected] (Y.Z.); [email protected] (L.H.) 2 College of Arts and Sciences, Governors State University, University Park, IL 60484, USA; [email protected] 3 Faculty of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China; [email protected] 4 Department of Grassland Technology Extension, The Institute of Forestry and Grassland in Urumqi City, Xinjiang 830000, China; [email protected] * Correspondence: [email protected]; Tel.: +86-10-62199276 Co-first authors: Juan Cao and Ruirui Yan. These authors contributed equally to this work. †  Received: 5 August 2019; Accepted: 19 September 2019; Published: 24 September 2019 

Abstract: Grazing affects nutrient cycling processes in grasslands, but little is known by researchers about effects on the nutrient stoichiometry of plant–soil–microbe systems. In this study, the influence 1 of grazing intensity (0, 0.23, 0.34, 0.46, 0.69, and 0.92 AU ha− ) on (C), (N) and (P) and their stoichiometric ratios in plants, soil, and microbes was investigated in a Hulunber meadow steppe, Northeastern China. The C:N and C:P ratios of shoots decreased with grazing increased. Leaf N:P ratios <10 suggested that the plant communities under grazing were N-limited. Heavy grazing intensities increased the C:N and C:P ratios of microbial , but grazing intensity had no significant effects on the stoichiometry of soil nutrients. The coupling relationship of C:N ratio in plant–soil–microbial systems was tightly significant compared to C:P ratio and N:P ratio according to the correlation results. The finding suggested grazing exacerbated the between plants and for N and P nutrition by the stoichiometric changes (%) in each grazing level relative to the no grazing treatment. Therefore, for the sustainability of grasslands in Inner Mongolia, N inputs need to be increased and high grazing intensities reduced in meadow steppe , and the grazing load should be controlled within G0.46.

Keywords: aboveground; belowground; microbial biomass; nutrient ratios; N-limitation; rhizosphere; temperate meadow steppe

1. Introduction Grasslands, which occupy about a fifth of the land surface, are among the most important biome globally. Nevertheless, grasslands have been degrading as a consequence of human disturbances and global climate change [1–3]. As the most prevalent land-use type, livestock grazing is related to the sustainable use of grassland ecosystems, because grassland degradation primarily results from imbalances in energy flow and material cycles due to overgrazing. Overgrazing not only threatens the and stability of grassland ecosystems but also results in dramatic shifts in their original structural and functional characteristics [4–7]. Although the effects of grazing on the structure and

Sustainability 2019, 11, 5226; doi:10.3390/su11195226 www.mdpi.com/journal/sustainability Sustainability 2019, 11, 5226 2 of 16 function of grassland ecosystems have been investigated in many studies, the understanding of the mechanisms underlying the responses of grasslands to grazing remains limited. In particular, those mechanisms that govern the relationships between grazing intensity and plant and soil ecological stoichiometry remain unclear [8]. Ecological stoichiometry studies the balance of essential nutrients by examining element ratios at different levels in various ecosystems [9]. The ratios provide more information than the individual nutrient concentrations and increase understanding of the interactions between different trophic levels [10,11]. C, N and P are the most important elements for plant growth and ecosystem attributes and are coupled because of their cycling in plants and soil [12,13]. The C:N:P ratio in soil is an indication of plant nutritional status, and leaf N:P ratios may reflect N- and/or P-limitation [13–16]. The effects of grazing on C, N, and P contents and stoichiometry in different components of grassland ecosystems have been investigated in several studies. The contents of C, N, and P in soils are substantially altered by mid- and long-term grazing through the export of nutrients, particularly in heavily grazed grasslands [8,17]. Grazing can increase N availability in soils through inputs of dung and urine and thus can significantly decrease plant above- and belowground C:N ratios [18,19]. Practically, a change in C:N:P stoichiometry is likely the first step in a cascade of plant-soil feedbacks [18,20,21]. The N and P required for plant growth are principally derived from soil, and therefore, soil nutrient concentrations regulate plant C:N:P stoichiometry [22,23]. Grazing can alter soil microbial , and microbes can affect the stoichiometry of soil available resources, subsequently influencing the nutrient availability for plants [24]. Moreover, when returned to the soil from both above- and belowground compartments, the plant affects the stoichiometry of the microbial . The changes in C:N:P stoichiometry may be associated with changes in the composition of species and functional groups under grazing [19,20]. The study of Elser et al. (2010) showed that species identity and growth form were the key constraints on construction and metabolism, with subsequent effects on ecological stoichiometry [14]. Therefore, the interactions between above- and belowground ecosystem processes in grazed grasslands [12,16,20] and the stoichiometric relationships of the plant–soil–microbial system are also closely linked [24]. Although the ecological stoichiometry in grassland ecosystems has been extensively studied, most of the research focuses on the stoichiometric features of plant leaves or aboveground parts and soils [12]. Few studies have characterized the belowground stoichiometry in plant roots and soil microorganisms, and we have not paid much attention to the influence of grazing activity on the stoichiometry of the plant–microbial–soil system in grassland ecosystems. Therefore, to better understand the linkages between above- and belowground compartments under the influence of grazing, more studies of belowground stoichiometry are needed in grasslands [16]. The Hulunber meadow steppe is one of the largest natural grasslands in the world and accounts for approximately 60% of the total temperate meadow steppe area in China [25,26]. The Hulunber grassland provides much high-quality forage for livestock and is a fundamental source of livelihood for local residents, in addition to providing various ecological services at regional and national scales. However, long-term, high-intensity grazing has resulted in serious degradation of the Hulunber grasslands [25]. In recent years, much effort has been directed to the restoration and sustainable management of the Hulunber grasslands, including fencing to exclude grazers, retiring of livestock, and returning farmlands to grasslands. In this study, the aim was to examine the impacts of grazing intensity on the ecological stoichiometry in the plant–soil–microbe system of meadow steppes of the Hulunber grassland in Northeastern China. The specific objectives of the study were: (1) to quantify the changes in C, N, and P contents in plant shoots and roots, soil, and soil microbial biomass under different levels of grazing, (2) to investigate the changes in C:N:P stoichiometry in the plant–soil–microbe system under different grazing intensities, and (3) to develop the relationships of stoichiometric features between aboveground and belowground parts in this grazed grassland ecosystem. Sustainability 2018, 10, x FOR PEER REVIEW 3 of 15

96 2.1. Discription of the Experimental Site 97 The experiment was conducted at a long-term grazing experimental site (49°19'35" N, 119°56'52" 98 E) in Inner Mongolia, China. The elevation of the study area varies from 666 to 680 m. The annual 99 meanSustainability precipitation2019, 11, 5226 is 349 mm and approximately 85% falls between June and September(Figure3 of 1) 16. 100 The annual mean temperature is 0.08 °C in 2018. The frost-free period is 110 days. According to 101 Chinese soil taxonomy, the main soil type in the study area was classified as chernozem or chestnut 2. Materials and Methods 102 soil.Sustainability The meadow 2018, 10, xsteppe FOR PEER was REVIEW dominated by the plant species Leymus chinensis, Scutellaria baicalensis,3 of 15 103 Carex2.1. Discription duriuscula, of Galium the Experimental verum, Bupleurum Site scorzonerifolium, and Filifolium sibiricum. 10496 2.1. DiscriptionThe long-term of the study Experimental began in Site 2009 when a spilt-plot design with six grazing intensity treatments The experiment was conducted at a long-term grazing experimental site (49 19 35” N, 119 56 52” E) 10597 was establishedThe experiment (Figure was 2). conducted The six grazing at a long densities-term grazing were set experimental using the stocking site (49°19'35"◦ rates0 of G0.00,N, 119°56'52"◦ G0.23,0 in Inner Mongolia, China. The elevation−1 of the study area varies from 666 to 680 m. The annual mean 10698 G0.34,E) in Inner G0.46, Mongolia, G0.69, and China. G0.92 The AU elevation ha (where of the1 AU study = 500 area kg ofvaries adult from cattle). 666 Three to 680 plots m. The(each annual 5 ha) precipitation is 349 mm and approximately 85% falls between June and September (Figure1). The 10799 weremean set precipitation up for each is of 349 the mm grazing and approximately intensity treatments. 85% falls The between six grazing June intensityand September treatments(Figure were 1). annual mean temperature is 0.08 C in 2018. The frost-free−1 period is 110−1 days. According−1 to Chinese 108100 simulatedThe annual with mean stocking temperature rates of is0,◦ 0.082 (G0.23 °C in AU 2018 ha. The), 3 (G0.34 frost-free AU periodha ), 4 is(G0.46 110 days. AU ha According), 6 (G0.69 to soil taxonomy,−1 the main soil type−1 in the study area was classified as chernozem or chestnut soil. The 109101 AUChinese ha ), soil and taxonomy, 8 (G0.92 AU the hamain) head soil typeof 250 in– the300 studykg young area cattle. was classified The cattle as grazed chernozem in the or plots chestnut day meadow steppe was dominated by the plant species Leymus chinensis, Scutellaria baicalensis, Carex 110102 andsoil. nightThe meadow for 120 days steppe annually was dominated from June by to theOctober. plant Beforespecies the Leymus grazing chinensis, experiment Scutellaria was setbaicalensis, up, the duriuscula, Galium verum, Bupleurum scorzonerifolium, and Filifolium sibiricum. 111103 studyCarex duriuscula,area had been Galium under verum, long Bupleurum-term free grazingscorzonerifolium, by cattle andor sheep. Filifolium sibiricum. 104 The long-term study began in 2009 when a spilt-plot design with six grazing intensity treatments 105 was established (Figure 2). The six grazing densities were set using the stocking rates of G0.00, G0.23, 106 G0.34, G0.46, G0.69, and G0.92 AU ha−1 (where 1 AU = 500 kg of adult cattle). Three plots (each 5 ha) 107 were set up for each of the grazing intensity treatments. The six grazing intensity treatments were 108 simulated with stocking rates of 0, 2 (G0.23 AU ha−1), 3 (G0.34 AU ha−1), 4 (G0.46 AU ha−1), 6 (G0.69 109 AU ha−1), and 8 (G0.92 AU ha−1) head of 250–300 kg young cattle. The cattle grazed in the plots day 110 and night for 120 days annually from June to October. Before the grazing experiment was set up, the 111 study area had been under long-term free grazing by cattle or sheep.

112

113 FigureFigure 1. 1. TheThe data data of of rainfall rainfall and and temperature temperature for for the the study study area area in Inner Mongolia, China.

The long-term study began in 2009 when a spilt-plot design with six grazing intensity treatments was established (Figure2). The six grazing densities were set using the stocking rates of G0.00, G0.23, 1 G0.34, G0.46, G0.69, and G0.92 AU ha− (where 1 AU = 500 kg of adult cattle). Three plots (each 5 ha) were set up for each of the grazing intensity treatments. The six grazing intensity treatments 1 1 1 were simulated with stocking rates of 0, 2 (G0.23 AU ha− ), 3 (G0.34 AU ha− ), 4 (G0.46 AU ha− ), 1 1 112 6 (G0.69 AU ha− ), and 8 (G0.92 AU ha− ) head of 250–300 kg young cattle. The cattle grazed in the plots day and night for 120 days annually from June to October. Before the grazing experiment was set 113 Figure 1. The data of rainfall and temperature for the study area in Inner Mongolia, China. up, the study area had been under long-term free grazing by cattle or sheep.

114

115 Figure 2. Geographical location of the study site with the experimental design and plot layout. The 116 six grazing treatments (n = 3) were set at stocking densities of G0.00, G0.23, G0.34, G0.46, G0.69, 117 andG0.92 AU ha−1 (where 1 Unit = 500 kg of adult cattle). The stocking rates were achieved 118 using 0, 2 (G0.23), 3 (G0.34), 4 (G0.46), 6 (G0.69), and 8 (G0.92) young cows (250–300 kg) per plot.

119 2.2. Sampling and Chemical Measurement

120114 The soils were sampled in early August 2018 from three randomly selected quadrats (1 m × 1 m) 121 in each plot, for a total of 54 quadrats. In each quadrat, soil with plants was sampled to the depth of Figure 2. Geographical location of the study site with the experimental design and plot layout. The six 115 Figure 2. Geographical location of the study site with the experimental design and plot layout. The grazing treatments (n = 3) were set at stocking densities of G0.00, G0.23, G0.34, G0.46, G0.69, andG0.92 116 six grazing1 treatments (n = 3) were set at stocking densities of G0.00, G0.23, G0.34, G0.46, G0.69, AU ha− (where 1 AU = 500 kg of adult cattle). The stocking rates were achieved using 0, 2 (G0.23), 117 andG0.92 AU ha−1 (where 1 Animal Unit = 500 kg of adult cattle). The stocking rates were achieved 3 (G0.34), 4 (G0.46), 6 (G0.69), and 8 (G0.92) young cows (250–300 kg) per plot. 118 using 0, 2 (G0.23), 3 (G0.34), 4 (G0.46), 6 (G0.69), and 8 (G0.92) young cows (250–300 kg) per plot.

119 2.2. Sampling and Chemical Measurement 120 The soils were sampled in early August 2018 from three randomly selected quadrats (1 m × 1 m) 121 in each plot, for a total of 54 quadrats. In each quadrat, soil with plants was sampled to the depth of Sustainability 2019, 11, 5226 4 of 16

2.2. Sampling and Chemical Measurement The soils were sampled in early August 2018 from three randomly selected quadrats (1 m 1 m) × in each plot, for a total of 54 quadrats. In each quadrat, soil with plants was sampled to the depth of 15 cm. The samples were transported to the laboratory to separate the rhizosphere (RS) and bulk (BS) soils. The RS was defined as that soil adhering to the roots, which was obtained by carefully shaking the plants free from loose soil. The soil not tightly adhering to the roots was the BS [6,27]. The plants collected with the soil samples were cut at the collar to separate the aboveground shoots and the belowground roots. Then, the soil and plant samples taken from the three quadrats within a plot were pooled to form one composite plant sample and one composite soil sample, for a total of 36 soil samples and 36 plant samples. The composite soil sample was divided into two portions by weight; one portion was naturally dried in the shade, and the other portion was stored at 20 C before − ◦ further analyses. The naturally dried soil sample was ground to pass through a 0.149-mm mesh sieve, and total C (TC), total N (TN), and total P (TP) were determined. The fresh soil samples were sieved through a 2-mm mesh and used for analyses of microbial biomass C (MBC), N (MBN), and P (MBP). For the analysis of plant TC, TN, and TP, the shoot and root samples were oven-dried to a constant weight at 60 ◦C for 48 h and then ground to a fine powder to pass through a 0.25-mm sieve. The concentration of organic C in soil and plant samples was analyzed by the Walkley–Black modified acid-dichromate FeSO4 titration method. The TN concentration of soil and plant samples was determined using a continuous flow analyzer made in German (AA3). The TP concentration was analyzed colorimetrically by spectrophotometer after digestion with H2SO4 and HC1O4. The soil MBC, MBN, and MBP were determined by the chloroform fumigation direct extraction method. The concentration of MBC, MBN, and MBP was calculated using the following equation:

Efumigated Enon fumigated MBE = − − (1) K where Efumigated and Enon-fumigated are the concentrations of C, N, or P in soil samples extracted after fumigation with chloroform and without fumigation for 24 h, respectively. K is the correction factor, with KC = 0.38, KN = 0.45, and KP = 0.40. To determine the level of enrichment of soil nutrients in the rhizosphere, the enrichment ratio (E) was calculated using the following equation:

R E = (2) B where R and B are the concentrations of nutrients in the RS and BS, respectively.

2.3. Statistical Analysis To analyze the effects of grazing intensity on the nutrient concentrations and stoichiometric characteristics of soils and plants, one-way ANOVA was used. Two-way ANOVAs were used to determine the effects of grazing intensity and soil position (rhizosphere and bulk) or plant (shoots and roots) on stoichiometry. Regression analysis was performed to test whether soil nutrient concentrations were linearly related to microbial biomass or plant nutrient concentrations. The statistical analyses were performed using the SPSS statistical software package (SPSS Version 19.0). In all statistical analyses, differences were accepted at α = 0.05.

3. Results

3.1. Nutrients in Plants and Soil Overall, the concentrations of TC, TN, and TP were significantly higher in shoots than in roots (P < 0.05) (Figure3a–c). Compared with the G0.00 plots, grazing intensity did not significantly alter Sustainability 2018, 10, x FOR PEER REVIEW 5 of 15

166 significantly different in the low and moderate grazing intensity plots (G0.23 to G0.46) (P >0.05), but 167 at high grazing intensities (G0.69 and G0.92), the TC concentration in both RS and BS significantly 168 decreased (P <0.05). The TN concentrations in RS and BS were not significantly different among the 169 six grazing intensity treatments, although the concentrations declined in the highly grazed plots. The 170 TP concentrations in RS and BS were not significantly different between the grazed and non-grazed 171 plots (P >0.05), with the exception of the G0.34 plots in which grazing increased the TP concentration 172 in RS and BS, compared with that in the G0.00 plots. 173Sustainability The2019 MBC, 11 ,and 5226 MBN concentrations were higher in RS than in BS (P <0.05), but for MBP, the 5 of 16 174 differences between RS and BS were not consistent or significant (P >0.05) (Figure 3g–i). Soil MBC 175 concentration was not significantly different between grazed and non-grazed plots in RS and BS. 176the TCCompared concentration with the inG0.00 shoots plots, and the roots.MBN concentration At low and in moderate both RS and grazing BS decreased densities significantly (G0.23 to in G0.46), the 177concentrations the G0.46 and of G0.69 TN and grazing TP in plots. plants The were concentrations not significantly of MBP ainff ected,RS and butBS showed at the high no consistent grazing intensities 178of G0.69response and to G0.92, grazing. the In TN RS andunder TP the concentrations different grazing in intensities, shoots and MBP roots decreased increased in the significantly order G0.34 (P < 0.05) 179 (Figure> G0.233b,c). > G0.00 > G0.92 > G0.46 > G0.69, whereas in BS, the order of decrease in MBP was G0.34 > 180 G0.00 > G0.23 > G0.92 > G0.69 > G0.46.

500 30 2.5 (a) G：ns (b) Shoots G：** (c) G：** P：** Roots ) P：**

-1 Ac

25 Ac ) P：** ) G*P： ns G*P：** -1 -1 G*P： ** 2.0 Aa Ac Aa Aa Aa 20 Aa Aa Ab Ab Bb 15 1.5 Aa Aa Aa Aa Aa Bb Ba Bab Aa Ba

Ba Ba 10 Aa Ba Bab Ba Ba Plant Total Carbon (g kg (g Carbon Total Plant

Ba Ba kg (g Nitrogen Tootal Plant Ba Ba Ba 1.0

Ba Ba Plant Total Phosphorous (g kg (g Phosphorous Total Plant 5 400 200 100 0 0 0.5 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92

Grazing intensities Grazing intensities Grazing intensities 50 0.8 G：** (d) G：** G：ns RS (e) (f) P：** Ab P：** P：** BS Aa ： G*P： ns

G*P： ns G*P ns )

-1 )

Ab -1 Aa Aa Aa Bb

) Ab Ab Aa Aa 0.6 -1 4 Bab Bab Ab Bab Bb Ba Ba Aa Bab Aa 40 Aa Aa Bab Aa Bab Aa Aa

Ba Ba 0.4 Soil Carbon (g kg (g Carbon Soil Ba Ba Ba

Ba kg (g Nitrogen Tootal Soil Soil Total Phosphorous (g kg (g Phosphorous Total Soil Ba Ba

30 3 0.2 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities Grazing intensities Grazing intensities 30 G：ns (i) (g) RS (h) G：** G：** P：** ： ) P ** -1 P： ns BS ) 50

G*P： ns -1 ) Abc Ac G*P： ns G*P： ns -1 Aa Aa Ab Aa Ab Ab Ab 25 Aab 800 Aab Aa Bbc Bc Bbc Ab Aab 40 Aab Aa Aa Ba Aa Aab Ba Aab Bab Aab Ba Ba Aa 20 30

Ba Ba Aa Aa

Microbomass Nitrogen (mg kg (mg Nitrogen Microbomass Microbomass Carbon (mg kg (mg Carbon Microbomass

Ba kg (mg Phosphorous Microbomass Ba

600 20 15 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 181 Grazing intensities Grazing intensities Grazing intensities 1 182 FigureFigure 3. E 3ff. ectsEffects of sixof six levels levels of of grazing grazing intensities intensities (G0.00, G0.23, G0.23, G0.34, G0.34, G0.46 G0.46,, G0.69, G0.69, and andG0.92G0.92 AU AU ha− ) −1 1 -1 1 -1 1 -1 183 on (aha) total) on carbon (a) total (g carbon kg− ), ( (bg )kg total), (b)nitrogen total nitrogen (g kg− ), (g and kg (),c ) and total (c) phosphorous total phosphorous (g kg − (g) kg concentrations) 184 concentrations in plants (shoots, black bars; roots, white bars); on (d) total carbon1 (g kg-1), (e) total 1 in plants (shoots, black bars; roots, white bars); on (d) total carbon (g kg− ), (e) total nitrogen (g kg− ), 185 nitrogen (g kg-1), and (f) total phosphorous1 (g kg-1) concentrations in soils (RS, rhizosphere soil, black and (f) total phosphorous (g kg− ) concentrations in soils (RS, rhizosphere soil, black bars; BS, bulk 186 bars; BS, bulk soil, white bars); and on (g) soil microbial biomass carbon (mg kg-1), (h) nitrogen (mg soil, white bars); and on (g) soil microbial biomass carbon (mg kg 1), (h) nitrogen (mg kg 1), and 187 kg-1), and (i) phosphorous (mg kg-1) (RS, rhizosphere soil, black bars; BS,− bulk soil, white bars). − 1 188 (i) phosphorousDifferent uppercase (mg kgletters− ) indicate(RS, rhizosphere significant differences soil, black between bars; BS, different bulk positions soil, white (shoots bars). vs. Different 189 uppercaseroots or lettersrhizosphere indicate soil vs. significant bulk soil), and di ffdifferenterences lowercase between letters diff erentindicate positions significant(shoots differences vs. roots or 190 rhizospherebetween different soil vs. grazing bulk soil), intensities. and di Pff-valueserent lowercaseof the ANOVA letters for grazing indicate intensity significant (G), position differences (P), between 191 differentand their grazing interaction intensities. (G * P) are P-values indicated: of * the P ≤0.05; ANOVA ** P ≤0.01; for grazingns, not significant. intensity (G), position (P), and their interaction (G * P) are indicated: * P 0.05; ** P 0.01; ns, not significant. ≤ ≤ The concentrations of TC and TN were significantly greater in RS than in BS, but the concentration of TP was significantly lower in RS than in BS in all grazing treatment plots (P < 0.05) (Figure3d–f). Compared with the G0.00 plots, the TC concentrations in RS and BS were not significantly different in the low and moderate grazing intensity plots (G0.23 to G0.46) (P > 0.05), but at high grazing intensities (G0.69 and G0.92), the TC concentration in both RS and BS significantly decreased (P < 0.05). The TN concentrations in RS and BS were not significantly different among the six grazing intensity treatments, although the concentrations declined in the highly grazed plots. The TP concentrations in RS and BS were not significantly different between the grazed and non-grazed plots (P > 0.05), with the exception of the G0.34 plots in which grazing increased the TP concentration in RS and BS, compared with that in the G0.00 plots. The MBC and MBN concentrations were higher in RS than in BS (P < 0.05), but for MBP, the differences between RS and BS were not consistent or significant (P > 0.05) (Figure3g–i). Soil MBC Sustainability 2018, 10, x FOR PEER REVIEW 6 of 15

192 3.2. Stoichiometric Characteristics in Plants and Soil Sustainability 2019, 11, 5226 6 of 16 193 The increase in grazing intensity generally reduced the C:N and C:P ratios in shoots and roots, 194 except for an increase under G0.46 (Figure 4a,b). Grazing had no significant influence on the N:P 195 concentrationratios of shoots was and notroots significantly with the increase diff inerent grazing between intensity. grazed The highest and N:P non-grazed ratios of shoots plots and in RS and BS. 196 roots occurred under grazing intensities from G0.46 to G0.92 (Figure 4c). 197 ComparedThe highest with the RS C:N G0.00 ratio plots, was in the the MBN G0.23 concentrationtreatment, which in was both significantly RS and BShigher decreased than that significantly in in 198 theG0.69 G0.46 and and G0.92 G0.69 treatments grazing (Figure plots. 4d). TheThe highest concentrations BS C:N ratio of was MBP also in in RSthe andG0.23 BS treatment, showed but no consistent 199 responsethe ratio to was grazing. not significantly In RS under different the from different those grazingat the highest intensities, levels of MBPgrazing. decreased The RS C:P in ratio the order G0.34 200 > G0.23decreased> G0.00 in the >orderG0.92 G0.23> G0.46> G0.00> > G0.46G0.69, > G0.92 whereas > G0.69 in BS,> G0.34. the The order order of was decrease the same in for MBP BS, was G0.34 > 201 G0.00except> G0.23the lowest> G0.92 C:P ratio> G0.69 was in> theG0.46. G0.69 treatment (Figure 4e). In response to grazing intensity, 202 the patterns for RS and BS N:P ratios were the same as those for RS and BS C:P ratios (Figure 4f). 203 3.2. StoichiometricCompared with Characteristics the G0.00 plots, in the Plants RS and and BS Soil microbial biomass C:N ratios were the highest in 204 the G0.69 treatment and the lowest in the G0.23 treatment. The ratios at moderate-to-high grazing 205 intensitiesThe increase were significantly in grazing higher intensity than generallythose at the reduced lowest level the of C:N grazing and intensity C:P ratios (Figure in shoots 4g). and roots, 206 exceptCompared for an with increase the G0.00 under plots, G0.46 the lowest (Figure RS4 anda,b). BS Grazing microbial had biomass no significant C:P ratios were influence in the G0.34 on the N:P ratios 207 of shootstreatment, and whereas roots the with highest the increase ratios were in in grazing the G0.46 intensity. treatment The (Figure highest 4h). The N:P largest ratios RS of and shoots BS and roots 208 microbial biomass N:P ratios were in the G0.23 treatment, whereas the lowest ratios were in the G0.92 occurred under grazing intensities from G0.46 to G0.92 (Figure4c). 209 treatment for RS and in the G0.69 treatment for BS (Figure 4i).

90 500 12 G： ** Ab (a) Shoot G：** G： * P： ** (b) (c) ： 80 Root Bb P： ** P ** G*P：ns 450 11 ： Bab Ac G*P： ns G*P ns Ac 70 Bb Bc Bab 400 10 Aab

60 Bb Aab Aab Bab Bab 350 9 50 Aab Bab Ac Ba Bb Ab

Plant C:P Plant Aa

Plant C:N C:N Plant 300 8 Abc N:P Plant 40 Ab Ab Ba Aa 250 Aa 7 30 Aa Ba Aa 20 200 6 Ba Ba Ba Aa Ba Ba 10 150 5 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92

12 G： ** (d) Soil in RS 120 (e) G： ** (f) G： ** P： ** P： ** P： ** 14 Soil in BS G*P： ns G*P： ns G*P： ns 110 Ac Aa 10 Ab Abc Ab Aab Ac Aab 100 Aa (c) Aab Aab 12 Aa Aa 90 Aab Aa 8 Aa

Aa

Soil C:P C:P Soil Soil C:N Soil Aa 80 N:P Soil Ab Aab Bb 10 Aab Ab Ab 70 Bab Aa 6 Aab Aa Aa Aab Aa 60 Aa Aab Bab Ba Ba Bab 8 50 4 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92

35 50 2.8 G： ns MB G G： **** (g) MBC:N of RS (h) MBC:P of RS MBN:P of RS G： ** P： ** P P：： ** ** (i) Ab 2.6 P： ** BMBC:N of BS Bb ： BMBCP of BS G*P：： ns BMBN:P of BS G*P ns 45 G*P ns G*P： ns 30 Bb Ab 2.4 Bc Bbc Bab 40 2.2 25 Aa Bbc Ab 2.0 Aa Bb Bab Ba 35 Aa Aab Aa 1.8 Bab 20 Ba Ba

Ba Bab Ab Microbiomass N:P Microbiomass

Microbiomass C:P Microbiomass Bab Microbiomass C:N Microbiomass 30 1.6 Aab Ba Bab Aab Aab 1.4 15 Aa Aab Aab 25 Ba Aab Aa 1.2

Aab 10 20 1.0 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities Grazing intensities Grazing intensities

210 1 Figure 4. Effects of six levels of grazing intensity (G0.00, G0.23, G0.34, G0.46, G0.69, and G0.92 AU ha− ) 211 onFigure (a) the 4. C:N,Effects ( bof) six C:P, levels and of ( cgrazing) N:P ratiosintensity of (G0.00, plants G0.23, (shoots, G0.34, solid G0.46, lines; G0.69, roots, and dashedG0.92 AU lines); on the 212 (d)ha−1) C:N, on (e (a)) C:P, the andC:N, ((b)f) N:PC:P, and ratios (c) N:P of soil ratios (RS, of rhizosphereplants (shoots, soil,solid solidlines; lines;roots, dashed BS, bulk lines); soil, on dashed lines); 213 andthe on (d) (C:Ng) the, (e) C:N,C:P, and (h) (f) C:P, N:P and ratios (i) of N:P soil ratios(RS, rhizosphere in soil microbial soil, solid biomasslines; BS, bulk (MB) soil, (RS, dashed rhizosphere soil, 214 solidlines); lines; and on BS, (g) bulk the C:N soil,, (h) dashed C:P, and lines). (i) N:P Diratiosfferent in soil uppercase microbial biomass letters (MB) indicate (RS, rhizosphere significant differences 215 soil, solid lines; BS, bulk soil, dashed lines). Different uppercase letters indicate significant differences between different positions (shoots vs. roots or rhizosphere soil vs. bulk soil), and different lowercase letters indicate significant differences between different grazing intensities. P-values of the ANOVA for grazing intensity (G), position (P), and their interactions (G * P) are indicated: * P 0.05; ** P 0.01; ≤ ≤ ns, not significant.

The highest RS C:N ratio was in the G0.23 treatment, which was significantly higher than that in G0.69 and G0.92 treatments (Figure4d). The highest BS C:N ratio was also in the G0.23 treatment, but the ratio was not significantly different from those at the highest levels of grazing. The RS C:P ratio decreased in the order G0.23 > G0.00 > G0.46 > G0.92 > G0.69 > G0.34. The order was the same for BS, Sustainability 2018, 10, x FOR PEER REVIEW 7 of 15

216 between different positions (shoots vs. roots or rhizosphere soil vs. bulk soil), and different lowercase Sustainability 2019, 11, 5226 7 of 16 217 letters indicate significant differences between different grazing intensities. P-values of the ANOVA 218 for grazing intensity (G), position (P), and their interactions (G * P) are indicated: *P ≤ 0.05; **P ≤ 0.01; 219 ns, not significant. except the lowest C:P ratio was in the G0.69 treatment (Figure4e). In response to grazing intensity, the 220 patterns3.3. Relationships for RS and of BSNutrients N:P ratios and the were Stoichiometry the same between as those Soil for and RS Plants and BS C:P ratios (Figure4f). Compared with the G0.00 plots, the RS and BS microbial biomass C:N ratios were the highest in 221 No significant correlations were found between the concentrations of nutrients in plants and the G0.69 treatment and the lowest in the G0.23 treatment. The ratios at moderate-to-high grazing 222 soils (RS and BS) (P >0.05) (Table S1). However, the concentration of shoot N was significantly 223 intensitiesnegatively were correlated significantly with MBN higher in RS than and thoseBS under at thethe lowestdifferent level levels of of grazing grazing intensityintensity (Table (Figure 4g). 224 ComparedS1). The withregressions the G0.00 between plots, shoot the lowestN and RSMBN and in BSRS microbialand BS also biomass identified C:P significan ratios weret negative in the G0.34 225 treatment,relations whereas (Figure 5 thea,b). highest MBC was ratios significantly were in the positively G0.46 treatment correlated (Figure with soil4h). C, The and largest MBN RS was and BS 226 microbialsignificantly biomass positively N:P ratios correlated were with in the soil G0.23 N (Figure treatment, 5c,d and whereas Table S2). the lowest ratios were in the G0.92 227 treatmentUnder for RS the and different in the grazing G0.69 treatment intensities, for a significantly BS (Figure4 i). positive linear relation was observed 228 between shoot C:N ratios and RS C:N ratios (Figure 6a). The two parameters were also significantly 229 3.3.positively Relationships correlated of Nutrients (Table andS3). theThe Stoichiometryshoot C:N ratios between were Soilsignificantly and Plants negatively correlated with 230 RS and BS microbial biomass C:N ratios (Figure 6b, c and Table S3). The shoot C:P ratios were No significant correlations were found between the concentrations of nutrients in plants and soils 231 significantly positively correlated with RS and BS C:P ratios (Figure 6d,e and Table S3). The root C:P 232 (RSratio and was BS) (Psignificantly> 0.05) (Table positively S1). However,correlated thewith concentration the C:P ratio in of both shoot RS N and was BS significantly (Figure 6f,g negativelyand 233 correlatedTable S3). with For the MBN stoichiometry in RS and between BS under microbial the di biomassfferent and levels soil of under grazing different intensity levels of (Table grazing, S1). The 234 regressionsthe soil C:N between ratio was shoot significantly N and negatively MBN in RScorrelated and BS with also the identified microbial significantbiomass C:N negative ratio (Figure relations 235 (Figure6i and5a,b). Table MBC S2). was By contrast, significantly the soil positively N:P ratiocorrelated was significantly with soil positively C, and correlatedMBN was with significantly the 236 positivelymicrobial correlated biomass N:P with ratio soil (Figure N (Figure 6h and5c,d Table and S2). Table S2).

40 40

(a) y=-0.334x+25.516 y=-0.319x+22.852 2 (b) R =0.206 R2=0.191 P=0.033 P=0.040 30 30

20 20

Shoot N Shoot Shoot N Shoot

10 10

0 0 25 30 35 40 45 50 55 20 25 30 35 40 45 Rhizosphere soil MBN Bulk soil MBN 80 8

(c) y=-1.206x+64.450 (d) y=-1.073x+63.822 2 R2=0.192 R =0.205 P=0.039 P=0.034 60 6

40 4

Soil carbon (g/kg) carbon Soil Soil nitrogen (g/kg) nitrogen Soil 20 2

0 0 600 700 800 900 20 30 40 50 60 237 MBC(mg/kg) MBN(mg/kg) Figure 5. Regressions (y = ax + b, R2 = coefficient of determination) of the concentrations of shoot 238 Figure 5. Regressions (y = ax + b, R2 = coefficient of determination) of the concentrations of soil 1 239 N andmicrobial soil microbial biomass N biomass (MBN) (mg N (MBN)kg-1) and (mg shoot kg N− in) in (a) (a rhizosphere) rhizosphere soil soiland and(b) bulk (b) bulksoil and soil of and the of the 1 1 concentrations of (c) soil microbial biomass C(MBC) (mg kg− ) and soil C (g kg− ) and (d) soil microbial biomass N (MBN) (mg kg 1) and soil N (g kg 1). Regressions are significant at P 0.05. − − ≤ Under the different grazing intensities, a significantly positive linear relation was observed between shoot C:N ratios and RS C:N ratios (Figure6a). The two parameters were also significantly positively correlated (Table S3). The shoot C:N ratios were significantly negatively correlated with RS and BS microbial biomass C:N ratios (Figure6b,c and Table S3). The shoot C:P ratios were significantly positively correlated with RS and BS C:P ratios (Figure6d,e and Table S3). The root C:P ratio was Sustainability 2019, 11, 5226 8 of 16

significantly positively correlated with the C:P ratio in both RS and BS (Figure6f,g and Table S3).

ForSustainability the stoichiometry 2018, 10, x FORbetween PEER REVIEW microbial biomass and soil under different levels8 of 15 grazing, the soil C:N ratio was significantly negatively correlated with the microbial biomass C:N ratio (Figure6i and 240Table S2).concentrations By contrast, of (c) soil the microbial soil N:P biomass ratio C(MB wasC) (mg significantly kg-1) and soil Cpositively (g kg-1) and (d) correlated soil microbial with the microbial 241 biomass N (MBN) (mg kg-1) and soil N (g kg-1). Regressions are significant at P ≤0.05. biomass N:P ratio (Figure6h and Table S2).

80 80 80 y=-1.073x+63.822 (a) y=10.593x-72.7678 (b) y=-1.206x+64.450 (c) 2 2 R2=0.258 R =0.192 70 R =0.205 P=0.018 P=0.039 P=0.034 60 60 60

50 40 40

40

Shoots C:N Shoots

Shoots C:N Shoots Shoots C:N Shoots

30 20 20

20

0 0 10 9.0 9.5 10.0 10.5 11.0 11.5 12.0 10 15 20 25 30 35 10 15 20 25 30 35 Rhizosphere soil C:N Rhizosphere soil MB C:N Bulk soil MB C:N 600 600 600 (d) y=5.254x-160.562 (e) y=4.859x-13.412 (f) y=2.336x+152.833 2 R2=0.453 R2=0.356 R =0.171 500 P=0.001 500 P=0.005 500 P=0.049

400 400 400

Shoot C:P Shoot Shoot C:P Shoot 300 300 C:P Root 300

200 200 200

100 100 100 70 80 90 100 110 120 50 60 70 80 90 100 70 80 90 100 110 120 Rhizosphere soil C:P Rhizosphere soil C:P Bulk soil C:P 600 14 14

y=2.539x+192.071 (h) y=2.365x+3.574 (g) (i) y=-0.051x+11.850 2 2 2 12 R =0.282 R =0.200 13 R =0.127 P=0.0009 500 P=0.036 P=0.033 10 12

400 8

11 Soil C:N C:N Soil Soil N:P N:P Soil 6 Root C:P Root 300 10 4

200 9 2

100 8 0 50 60 70 80 90 100 10 15 20 25 30 35 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 242 Bulk C:P MB C:N MB N:P 2 243 FigureFigure 6. 6. RegressionsRegressions (y (y = ax= ax + b,+ R2b, = R coefficient= coe ffi of cient determination) of determination) between stoichiometric between stoichiometric 244 characteristicscharacteristics in in thethe plant–soil–microbeplant–soil–microbe system. system. (a) Shoot (a) ShootC:N and C:N rhizosphere and rhizosphere soil C:N; (b) soil shoot C:N; (b) shoot C:N 245 andC:N rhizosphere and rhizosphere soil microbial soil microbial biomass biomass C:N(MBC:N(MB C C:N);:N); (c) ( c shoot) shoot C:N C:N and and bulk bulk soil microbial soil microbial biomass 246 biomass C:N(MB C:N); (d) shoot C:P and rhizosphere soil C:P; (e) shoot C:P and bulk soil C:P; (f) root C:N(MB C:N); (d) shoot C:P and rhizosphere soil C:P; (e) shoot C:P and bulk soil C:P; (f) root C:P and 247 C:P and rhizosphere soil C:P; (g) root C:P and bulk soil C:P; (i) soil C:N and microbial biomass 248 rhizosphereC:N(MB C:N soil); (f) C:P; soil N:P (g) and root microbial C:P and biomass bulk N:P soil(MB C:P; N: (Pi)). Regressions soil C:N and are significant microbial at biomassP ≤ 0.05. C:N(MB C:N); (h) soil N:P and microbial biomass N:P(MB N:P). Regressions are significant at P 0.05. 249 4. Discussion ≤ 4. Discussion 250 4.1. Effects of Grazing on Stoichiometric Characteristics of Plants 2514.1. EffectsThe ofdecrease Grazing in shoot on Stoichiometric C:N and C:P ratios Characteristics (Figure 4a,b) with of Plants the increase in grazing intensity was 252 related to the C, N, and P contents in the plant tissues. Grazing did not significantly affect the TC 253 contentThe decrease of plants (Figure in shoot 3a), C:N because and the C:P TC ratios content (Figure was considered4a,b) with as relatively the increase stable inframework grazing intensity was 254related materials. to the However, C, N, andheavy P grazing contents (G0.69 in and the G0.92) plant resulted tissues. in higher Grazing concentrations did not significantlyof TN and TP affect the TC 255content in plants ofplants (Figure (Figure3b,c). Therefore,3a), because the change the of TC TN contentand TP is wasconsistent considered with a previous as relatively study which stable framework 256materials. found that However, herbivory heavyled to increases grazing in (G0.69 the TN and TP G0.92) concentrations resulted of in plant higher tissues concentrations in a grassland of TN and TP 257 [28], although the significant increase occurred only under heavy grazing. At low to moderate in plants (Figure3b,c). The change of TN and TP is consistent with a previous study which found that 258 grazing intensities, notwithstanding that diminish the photosynthetic area of leaves with 259herbivory high N content, led to increases new tissues in are the formed TN and with TP high concentrations concentrations of of TN plant and tissuesTP in the in compensatory a grassland [28], although 260the significantregrowth [29]. increase The increase occurred in concentrations only under of TN heavy and TP grazing. observed Atunder low the to heaviest moderate grazing grazing in intensities, notwithstanding that herbivores diminish the photosynthetic area of leaves with high N content, new tissues are formed with high concentrations of TN and TP in the compensatory regrowth [29]. The increase in concentrations of TN and TP observed under the heaviest grazing in this study could be explained by the following. First, the vegetation under high grazing intensity mostly consists of young metabolic tissues without heavy weathering, which are rich in nutrients [29]. Moreover, Sustainability 2019, 11, 5226 9 of 16 with the mineralization of urine and feces, the availability of soil N and P could increase, stimulating uptake by plants. Additionally, the changes in species composition under high grazing intensities can also affect the availability of nutrients. For example, grazing can increase the number of forbs, which can absorb more N than graminoids [6,30]. In addition, unpalatable and grazing-tolerant annual species become dominant under heavy grazing pressure, and those species usually have higher nutrient contents with lower leaf C:N ratios than perennial grass species [6,8,13,30]. According to the growth rate hypothesis, with higher growth rates have lower C:N, C:P, and N:P ratios, primarily because the rapid growth of organisms requires the synthesis of considerable amounts of protein and RNA [31]. Simultaneously, plants with strong vegetative growth have lower C:N ratios, whereas those with strong reproductive growth have lower C:P ratios [9]. Thus, the decrease in shoot C:N and C:P ratios with the increase in grazing intensity was primarily because plants accelerated vegetative and reproductive growth to complete the life history. Similarly, the root C:N ratios decreased with increasing grazing intensities, most likely because root activities increased. Grazing promotes the aggregation of roots at the soil surface, particularly fine roots, and the proportion of fine roots in the total root system of the topsoil increases with the intensity of grazing [32,33]. The finer the root diameter is, the higher the N and P contents and the higher the root activity [34,35]. In this study, the root C:N ratios were greater than the shoot C:N ratios, which were attributed to the lower N content in roots because of higher lignification. The changes in shoot C:P and C:N ratios were consistent, which was likely related to the coupling of N and P in plant physiological processes. Although the root C:P ratios tended to decrease with increasing grazing intensity, the ratio was significantly reduced only under high grazing intensities. Grazing had no significant influence on the N:P ratios of shoots and roots, with the exception of the shoot N:P ratio in the G0.92 treatment (Figure4c). Leaf N:P ratios <10 and >20 correspond to N- and P-limitation, respectively [23]; therefore, the plant communities under grazing in this study were likely N-limited.

4.2. Effects of Grazing on Stoichiometric Characteristics of Soil The RS and BS C:N ratios decreased from light to heavy grazing, which was mainly caused by the decreases in TC in the heavier grazing treatments. The TC concentrations in RS and BS were not significantly different in the low and moderate grazing intensity plots (G0.23 to G0.46), whereas the TC concentration in both RS and BS significantly decreased under heavy grazing (G0.69 and G0.92) (Figure3d). The TN concentrations in RS and BS were not significantly di fferent among the six grazing intensity treatments, although the concentrations declined in the highly grazed plots (Figure3e). These decreases in TC and TN may be explained because aboveground biomass decreases significantly under heavy grazing, which can lead directly to reductions in litter inputs as the for soil C and N. Plant removal by herbivores also tends to decrease C allocation to roots, because root elongation and root biomass are reduced [36,37]. The reduction of carbon and nitrogen content in heavier grazing would affect the structure and function of the entire grassland ecosystem, and thus affect the sustainable use of grassland ecosystems. The decreases in litter and root biomass inputs may in turn decrease soil and microbial biomass C. The decrease in RS and BS C:N ratios also was an indication of increased availability of soil N. In addition, because heavy grazing exposes more bare soil, the increase in temperatures facilitates rapid [29,38]. The C:P ratio is an indicator of the utilization and release of P for soil microbes, and relatively low C:P ratios promote the availability of P via mineralization by bacterial species with different strategies of P acquisition [39]. In this study, the decrease of C:P ratio shows that the availability of P increased with grazing compared with that in the control, except in the G0.23 treatment, which is consistent with the increased demand for P in shoots. The RS and BS N:P ratios decreased with grazing compared with those in the control, except for soils in the G0.23 treatment, and the values were significantly smaller than the global average (13.1 or 17.5) [40,41]. The low N:P ratios also suggested relatively low N content in the study area. Sustainability 2019, 11, 5226 10 of 16

4.3. Responses of Microbial Biomass to Grazing In the high grazing treatments, the microbial biomass C:N and C:P ratios increased. That is because grazing did not significantly affect MBC, by contrast, MBN and MBP increased under light grazing (G0.23 and G0.34) but then decreased under high grazing (G0.46 to G0.92). In previous studies, the shifts in microbial biomass C:N:P were related to changes in the microbial community, given that microbes (e.g., bacteria and fungi) have specific elemental compositions [42–44]. Because of the lower metabolic activity and nutrient (N or P) requirements of fungi than bacteria, higher C:N and C:P ratios are an indication of a fungal rather than a bacterial community [6,44]. Indeed, Xun et al. (2018), in the same study plots as in this study, found that bacteria became prevalent with increasing grazing intensity [45]. Thence, the increase in microbial biomass C:N and C:P ratios in this study could be related to the utilization of N and P under high grazing intensities. As noted above, plants under high grazing intensities have increased demand for N and P, and under those conditions, plants could out-compete microorganisms for N and P, resulting in a decrease in MBN and MBP. In this study, the microbial biomass N:P ratio was well constrained in the grazing treatments and was lower than the global average (6.9 or 5.6) [40,41,44]. According to a previous study, a relatively high microbial biomass N:P ratio suggests P limitation and low soil P availability, which can strongly limit microbial activity and other ecosystem processes [40]. The low microbial biomass N:P ratios were primarily due to the low N in the study area, and the reduction in microbial biomass N:P ratios indicated that N-limitation was more serious with the increase in grazing intensity.

4.4. Linkages between Above- and Belowground Nutrients The cycling of nutrients between soil and plants is mediated by microbes in ecosystems, including grasslands (Figure7)[ 24]. Based on the correlation analysis, plant elements had no significant relationships with those in the soil (Table S1). This absence of correlation could be explained because plants primarily absorb the available forms of N and P, which account for only a small portion of the TN and TP. However, shoot N was significantly negatively correlated with RS and BS MBN (Figure5a,b and Table S1). Generally plants release 10–30% of photosynthetic products into the soil [46], which includes energy and C and N resources for microbes. In this grazing system, the negative correlation between shoot N and MBN of RS and BS suggested that grazing exacerbated the competition between plants and microorganisms for N nutrition. The changes in the C, N, and P contents in the plant–soil–microbe system under different levels of grazing were then compared with those in the no grazing treatment (Figure8). Notably, the shifts in N and P in the soil were small; whereas the changes in values for plants and microorganisms were larger (Figure8). The changes were particularly notable under high grazing treatments, with N and P contents in plants increasing and those in microbes decreasing relative to the no grazing treatment. From the trend chart, we can get another message that the N and P contents of plants were more affected by grazing intensity than those in microbes. In this study, the microbial biomass C:N ratios decreased with soil C:N ratios, and simultaneously, the shoot C:N ratios were negatively correlated with RS and BS microbial biomass C:N ratios. These results also suggested the competition between plants and microorganisms for N nutrition was exacerbated. Moreover, unlike a previous study in which the N:P ratios between soil and plant were positively correlated [24], in this study, the shoot C:N ratios increased linearly with the RS C:N ratios, and the C:P ratios of plant shoots and roots increased linearly with the RS and BS C:P ratios (Table S3). Because C is generally not a limiting factor for plant growth, these results demonstrated tight coupling of N and P between plant and soil. Similarly, the stoichiometric ratios under each grazing treatment were compared with those in the no grazing treatment for the whole system, and the soil stoichiometric ratios changed less under grazing than those for plants and microorganisms (Figure9). The stoichiometric changes in plants and microorganisms included both increases and decreases relative to no grazing. Changes also occurred with the increase in grazing intensity, particularly under high grazing treatments (Figure9). The C:N and C:P ratios in plants decreased, whereas the C:N and C:P ratios in microbes increased. Thus, the trend graphs of the shifts in N and P contents and C:N Sustainability 2018, 10, x FOR PEER REVIEW 11 of 15

363 in N and P contents and C:N and C:P ratios in the plant–soil–microbe system also indicated that

364 grazingSustainability exacerbated2019, 11, 5226 plant and microbial competition for nutrients, with the greatest impact under11 of 16 365 highSustainability grazing 2018 intensity, 10, x FOR (Figures PEER REVIEW 8 and 9 ). However, N:P ratios in plants increased with the increase11 of in 15 366 grazing intensity, whereas those in the microorganisms only decreased slightly. The plants N:P ratios 367363 areandin moreN C:P and ratiosvariable P contents in than the plant–soil–microbe andthose C:N of microorganismsand C:P ratios system in and alsothe soil, plant indicated indicating–soil– thatm icrobethat grazing plants system exacerbated are also more indicated sensitive plant andthat to 368364 grazing.microbialgrazing exacerbated competition plant for nutrients, and microbial with thecom greatestpetition impact for nutrients, under high with grazing the greatest intensity impact (Figures under8 365 andhigh9). grazing However, intensity N:P ratios (Figures in plants 8 and increased9). However, with N:P the ratios increase in plants in grazing increased intensity, with whereas the increase those in 366 ingrazing the microorganisms intensity, whereas only those decreased in the slightly.microorganisms The plants only N:P decreased ratios are slightly. more variable The plants than N:P those ratios of 367 microorganismsare more variable and than soil, those indicating of microorganisms that plants are and more soil, sensitive indicating to that grazing. plants are more sensitive to 368 grazing.

369

370 Figure 7. Conceptual model of the interactions in a grazed plant–soil–microbial system.

371369

370 FigureFigure 7.7. ConceptualConceptual modelmodel ofof thethe interactionsinteractions inin aa grazedgrazed plant–soil–microbialplant–soil–microbial system.system.

30 200 (a) Shoot (b) Shoot 371 Root Root RS 150 RS 20 RS MB RS MB BS BS BS MB BS MB 100 10 30 200 (a) Shoot 50 (b) Shoot 0 Root Root RS RS 20 150 RS MB 0 RS MB -10 BS BS BS MB BS MB

100 the C change compared with G0.00(%) with compared C change the

10 G0.00(%) with compared N change the -50 -20 50 0 -100 G0.23 G0.34 G0.46 G0.69 G0.92 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities 0 Grazing intensities -10 100

the C change compared with G0.00(%) with compared C change the Shoot (c) G0.00(%) with compared N change the -50 Root 80 -20 RS RS MB 60 BS -100 G0.23 G0.34 G0.46 G0.69 RS MBG0.92 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities40 Grazing intensities 100 20 (c) Shoot Root 80 RS 0 RS MB 60 BS -20 RS MB

the P change compared with G0.00(%) with compared P change the 40 -40 20 -60 G0.23 G0.34 G0.46 G0.69 G0.92 0 Grazing intensities

-20 the P change compared with G0.00(%) with compared P change the 372 FigureFigure 8 8.. TrendTrend chart chart of of the the changes changes-40 (%) (%) in in (a) (a) C, C, (b) (b )N, N, and and (c) (c) P P contents contents at at each each level level of of grazing grazing −11 373 intensityintensity (G0.23, (G0.23, G0.34, G0.34, G0.46, G0.46, G0.69, G0.69,-60 and and G0.92 G0.92 AU AU ha ha−) )relative relative to to the the no no grazing grazing treatment treatment (G0.00) (G0.00) G0.23 G0.34 G0.46 G0.69 G0.92 374 inin plants plants (shoots (shoots and and roots), roots), soil soil (RS, (RS, rhizosphere rhizosphere;; BS, BS, bulk bulk soil), soil), and and soil soil microbial microbial biomass biomass (MB). (MB). Grazing intensities 372 Figure 8. Trend chart of the changes (%) in (a) C, (b) N, and (c) P contents at each level of grazing 373 intensity (G0.23, G0.34, G0.46, G0.69, and G0.92 AU ha−1) relative to the no grazing treatment (G0.00) 374 in plants (shoots and roots), soil (RS, rhizosphere; BS, bulk soil), and soil microbial biomass (MB). Sustainability 2018, 10, x FOR PEER REVIEW 12 of 15 Sustainability 2019, 11, 5226 12 of 16 375

100 80 (a) Shoot (b) Shoot Root Root 60 RS RS RS MB RS MB 50 BS 40 BS BS MB BS MB 20

0 0

-20

-50 -40 the C:N change compared with G0.00(%) with compared change C:N the the C:P change compared with G0.00(%) with compared change C:P the -60

-100 -80 G0.23 G0.34 G0.46 G0.69 G0.92 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities Grazing intensities

60 (c) Shoot Root 40 RS RS MB BS 20 RS MB

0

-20

-40 the N:P change compared with G0.00(%) with compared change N:P the

-60 G0.23 G0.34 G0.46 G0.69 G0.92 Grazing intensities

376 FigureFigure 9. Trend 9. Trend chart chart of the of stoichiometric the stoichiometric changes changes (%) in (%) (a) in C:N (a) ratio,C:N ratio, (b) C:P (b) ratio, C:P ratio, and (andc) N:P (c) ratioN:P ratio 1 −1 377 at eachat each level level of grazing of grazing intensity intensity (G0.23, (G0.23, G0.34, G0.34, G0.46, G0.46, G0.69, G0.69, and G0.92and G0.92 AU ha AU− ) ha relative) relative to the to no the no 378 grazinggrazing treatment treatment (G0.00) (G0.00) in plants in plants (shoots (shoots and roots),and roots), soil (RS,soil rhizosphere;(RS, rhizosphere; BS, bulk BS, bulk soil), soil), and soiland soil 379 microbialmicrobial biomass biomass (MB). (MB).

4.5. Role of the Rhizosphere in Nutrient Cycles 380 4.5. Role of the Rhizosphere in Nutrient Cycles 381 TheThe rhizosphere rhizosphere is an is active an active zone zone in the in soilthe adjacentsoil adjacent to plant to plant roots roots in which in which microorganisms microorganisms 382interact interact with with root root exudates exudates [27, 47[27,47,48].,48]. The The higher higher TC, TC, TN, TN, MBC MBC and and MBN MBN in in the the RS RS than than in in the the BS BS are 383are consistentconsistent with with general general observations, observations, although although the the TP TP content content was was lower lower in thein the RS thanRS than in the in BS.the BS. 384That’s That’s because because that that the rootthe root exudates exudates released released by plant by plant roots roots consist consist of a complexof a complex of substances of substances (i.e., (i.e., 385sugars, sugars, amino amino acids, acids, proteins, proteins, and soand on), so whichon), which increase increase the availability the availability of nutrients of nutrients and stimulateand stimulate 386microorganism populations populations and and activities activities in the in rhizospherethe rhizosphere [49– 51[49–51].]. Simultaneously, Simultaneously, soil microbessoil microbes 387a ffectaffect plant plant growth growth via stimulating via stimulating the production the production of exoenzymes of exoenzymes that that decompose decompose soil organicsoil organic matter matter 388and therebyand thereby increase increase soil nutrientsoil nutrient availability availability to plants to plants [27,51 [27,51].]. The higherThe higher soil Psoil in BSP in than BS than in RS in was RS was 389most most likely likely because because P is very P is easily very immobilizedeasily immobilize in soil,d and in soil, any Pand in theany rhizosphere P in the rhizosphere was likely rapidly was likely 390consumed rapidly and consumed not sufficiently and not replenished. sufficiently We replenished. also found that We no also significant found that diff erencesno significant were observed differences in the E ,E and E ratios with the increase in grazing intensity (Table1) which were consistent with 391 wereC observedN P in the EC, EN and EP ratios with the increase in grazing intensity (Table 1) which were 392those consistent reported bywith Yang those et al.reported (2018). by Although Yang et the al. nutrient(2018). Although enrichment the rate nutrient did not enrichment differ significantly rate did not 393with differ the grazing significantly gradient, with the the rhizosphere grazing gradient, was essential the rhizosphere for the migration was essential of soil for nutrients the migration from soil of soil 394to plants.nutrients from soil to plants.

Table 1. Rhizosphere enrichment ratios (rhizosphere soil/bulk soil) of total carbon (EC), total nitrogen 395 Table 1. Rhizosphere enrichment ratios (rhizosphere soil/bulk soil) of total carbon (EC), total nitrogen (EN), and total phosphorous (EP) under different grazing intensities (G0.00, G0.23, G0.34, G0.46, G0.69, 396 (EN), and total phosphorous (EP) under different grazing intensities (G0.00, G0.23, G0.34, G0.46, G0.69, and G0.92 AU ha 1). 397 and G0.92 AU− ha−1). G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 G0.00 G0.23 G0.34 G0.46 G0.69 G0.92 E 1.15 0.05a 1.12 0.04a 1.16 0.06a 1.20 0.09a 1.19 0.02a 1.17 0.02a C EC ±1.15±0.05a ±1.12±0.04a 1.16±0.06a± 1.20±0.09a± 1.19±0.02a± 1.17±0.02a± EN 1.17 0.06a 1.20 0.04a 1.20 0.04a 1.24 0.08a 1.22 0.03a 1.25 0.03a EN ±1.17±0.06a ±1.20±0.04a 1.20±0.04a± 1.24±0.08a± 1.22±0.03a± 1.25±0.03a± EP 0.88 0.01a 0.89 0.05a 0.89 0.01a 0.90 0.02a 0.86 0.08a 0.90 0.09a −EP −±0.88±0.01a− −±0.89±0.05a− −0.89±0.01a± − −0.90±0.02a± − −0.86±0.08a± − −0.90±0.09a± Values are the mean SE (n = 3). Different letters indicate a significant difference between grazing levels. 398 Values are the mean± ± SE (n = 3). Different letters indicate a significant difference between grazing 399 levels. Sustainability 2019, 11, 5226 13 of 16

5. Conclusions Grazing decreased the C:N and C:P ratios of plant shoots. With leaf N:P ratios of <10 and >20 corresponding to N- and P-limitation, respectively, the results suggested that the meadow steppe in this study was an N-limited grassland ecosystem. TN and TP contents and C:N and C:P ratios of plants and microorganisms significantly changed when grazing intensity was greater than G0.46. Correlation results indicated that the coupling relationship of C:N ratios in plant–soil–microbial systems was tightly significant compared to C:P ratio and N:P ratio. The study showed that grazing exacerbated the competition between plant and microbial for nutrients, particularly at the intensity that is greater than G0.46. As an important terrestrial ecosystem in China, the sustainable development of grassland ecosystems is critical to the improvement of our environment. Our study gave the evidence that for the sustainability of grasslands in Inner Mongolia, N inputs need to be increased and high grazing intensities reduced in meadow steppe ecosystems, and the grazing load should be controlled within G0.46.

Supplementary Materials: The following are available online at http://www.mdpi.com/2071-1050/11/19/5226/s1, Table S1: Correlations between nutrients (C, N, P) of plants (shoots and roots) and those of rhizosphere and bulk soils and soil microbial biomass, Table S2: Correlations between nutrients (C, N, P) in soil and soil microbial biomass and between the nutrient stoichiometry of soil and soil microbial biomass (C:N, C:P, N:P), Table S3: Correlations for nutrient stoichiometry (C:N, C:P, N:P) between plants (shoots and roots) and rhizosphere and bulk soils and soil microbial biomass. Author Contributions: J.C. conceived and designed the experiments; J.C. executed the experiments and measured the data; J.C. and R.Y. analyzed the data and wrote the paper; J.C., R.Y., X.C., Q.Y., Y.Z. (Yunlong Zhang) and C.N. revised the manuscript. Data curation, L.H.; Formal analysis, Y.Z. (Yongjuan Zhang); Funding acquisition, X.X.; Methodology, X.W. Funding: This study was sponsored by the National Natural Science Foundation of China (41471093, 41671044, 31971769), the National Key Research and Development Program of China (2016YFC0500601, 2017YFE0104500, 2017YFC0503906), Fundamental Research Funds for Central Nonprofit Scientific Institutions (1610132018009, 1610132019031, 1010132019040), and the China Agriculture Research System (CARS-34). Acknowledgments: We acknowledge the assistance of Xiaotong Jia, Minghui Jing, and Wei Zhou in the field and laboratory. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Knapp, A.K.; Fay, P.A.; Blair, J.M.; Collins, S.L.; Smith, M.D.; Carlisle, J.D.; Harper, C.W.; Danner, B.T.; Lett, M.S.; McCarron, J.K. Rainfall variability, carbon cycling, and plant in a mesic grassland. Science 2002, 298, 2202–2205. [CrossRef][PubMed] 2. Reed, M.; Stringer, L.C. Climate Change and Desertification: Anticipating, Assessing & Adapting to Future Change in Drylands; Agropolis International: Montpellier, France, 2015. 3. Eldridge, D.J.; Delgado-Baquerizo, M.; Travers, S.K.; Val, J.; Oliver, I. Do grazing intensity and herbivore type affect soil health? Insights from a semi-arid gradient. J. Appl. Ecol. 2017, 54, 976–985. [CrossRef] 4. McNaughton, S.J. Grazing as an optimization process: Grass-ungulate relationships in the serengeti. Am. Nat. 1979, 113, 691–703. [CrossRef] 5. Zhou, G.Y.; Zhou, X.H.; He, Y.H.; Shao, J.J.; Hu, Z.H.; Liu, R.Q.; Zhou, H.M.; Hosseinibai, S. Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: A meta-analysis. Glob. Chang. Biol. 2017, 23, 1167–1179. [CrossRef][PubMed] 6. Yang, Z.A.; Zhu, Q.A.; Zhan, W.; Xu, Y.Y.; Zhu, E.X.; Gao, Y.H.; Li, S.Q.; Zheng, Q.Y.; Zhu, D.; He, Y.X.; et al. The linkage between vegetation and soil nutrients and their variation under different grazing intensities in an alpine meadow on the eastern Qinghai-Tibetan Plateau. Ecol. Eng. 2018, 110, 128–136. [CrossRef] 7. Liu, S.J.; Yang, X.D.; Ives, A.R.; Feng, Z.L.; Sha, L.Q. Effects of seasonal and perennial grazing on soil fauna community and microbial biomass carbon in the subalpine meadows of Yunnan, Southwest China. Pedosphere 2017, 27, 371–379. [CrossRef] Sustainability 2019, 11, 5226 14 of 16

8. Tessema, Z.K.; de Boer, W.F.; Baars, R.M.T.; Prins, H.H.T. Changes in soil nutrients, vegetation structure and herbaceous biomass in response to grazing in a semi-arid savanna of Ethiopia. J. Arid Environ. 2011, 75, 662–670. [CrossRef] 9. Sterner, R.W.; Elser, J.J. Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere; Princeton University Press: Princeton, NJ, USA, 2002. 10. Elser, J.J.; Sterner, R.W.; Galford, A.E.; Chrzanowski, T.H.; Findlay, D.L.; Mills, K.H.; Paterson, M.J.; Stainton, M.P.; Schindler, D.W. Pelagic C:N:P stoichiometry in a eutrophied : Responses to a whole-lake food-web manipulation. Ecosystems 2000, 3, 293–307. [CrossRef] 11. Zeng, Y.L.; Fang, X.; Xiang, W.H.; Deng, X.W.; Peng, C.H. Stoichiometric and nutrient resorption characteristics of dominant tree species in subtropical Chinese forests. Ecol. Evol. 2017, 7, 11033–11043. [CrossRef] 12. Yang, X.J.; Huang, Z.Y.; Zhang, K.L.; Cornelissen, J.H.C. C:N:P stoichiometry of artemisia species and close relatives across northern China: Unravelling effects of climate, soil and taxonomy. J. Ecol. 2015, 103, 1020–1031. [CrossRef] 13. Zheng, S.X.; Ren, H.Y.; Li, W.H.; Lan, Z.C. Scale-dependent effects of grazing on plant C:N:P stoichiometry and linkages to ecosystem functioning in the Inner Mongolia grassland. PLoS ONE 2012, 7, e51750. [CrossRef] [PubMed] 14. Elser, J.J.; Fagan, W.F.; Kerkhoff, A.J.; Swenson, N.G.; Enquist, B.J. Biological stoichiometry of plant production: Metabolism, scaling and ecological response to global change. New Phytol. 2010, 186, 593–608. [CrossRef] 15. Batjes, N.H. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 2014, 65, 10–21. [CrossRef] 16. Fan, H.B.; Wu, J.P.; Liu, W.F.; Yuan, Y.H.; Hu, L.; Cai, Q.K. Linkages of plant and soil C:N:P stoichiometry and their relationships to forest growth in subtropical plantations. Plant Soil 2015, 392, 127–138. [CrossRef] 17. Pineiro, G.; Paruelo, J.M.; Oesterheld, M. Potential long-term impacts of livestock introduction on carbon and nitrogen cycling in grasslands of southern South America. Glob. Chang. Biol. 2006, 12, 1267–1284. [CrossRef] 18. Heyburn, J.; McKenzie, P.; Crawley, M.J.; Fornara, D.A. Effects of grassland management on plant C:N:P stoichiometry: Implications for soil element cycling and storage. Ecosphere 2017, 8, e01963. [CrossRef] 19. Bai, Y.F.; Wu, J.G.; Clark, C.M.; Pan, Q.M.; Zhang, L.X.; Chen, S.P.; Wang, Q.B.; Han, X.G. Grazing alters ecosystem functioning and C:N:P stoichiometry of grasslands along a regional precipitation gradient. J. Appl. Ecol. 2012, 49, 1204–1215. [CrossRef] 20. Bardgett, R.D.; Wardle, D.A. Herbivore-mediated linkages between aboveground and belowground communities. 2003, 84, 2258–2268. [CrossRef] 21. Frank, D.A. Ungulate and topographic control of nitrogeN: Phosphorus stoichiometry in a temperate grassland; soils, plants and mineralization rates. Oikos 2008, 117, 591–601. [CrossRef] 22. Zhang, J.H.; Zhao, N.; Liu, C.C.; Yang, H.; Li, M.L.; Yu, G.C.; Wilcox, K.; Yu, Q.; He, N.P. C:N:P stoichiometry in China’s forests: From organs to ecosystems. Funct. Ecol. 2018, 32, 50–60. [CrossRef] 23. Gusewell, S. N:P ratios in terrestrial plants: Variation and functional significance. New Phytol. 2004, 164, 243–266. [CrossRef] 24. Bell, C.; Carrillo, Y.; Boot, C.M.; Rocca, J.D.; Pendall, E.; Wallenstein, M.D. Rhizosphere stoichiometry: Are C:N:P ratios of plants, soils, and enzymes conserved at the plant species-level? New Phytol. 2014, 201, 505–517. [CrossRef] 25. Yan, R.R.; Tang, H.J.; Xin, X.P.; Chen, B.R.; Murray, P.J.; Yan, Y.C.; Wang, X.; Yang, G.X. Grazing intensity and driving factors affect soil nitrous oxide fluxes during the growing seasons in the Hulunber meadow steppe of China. Environ. Res. Lett. 2016, 11, 054004. [CrossRef] 26. Xu, D.W.; Chen, B.R.; Yan, R.R.; Yan, Y.C.; Sun, X.B.; Xu, L.J.; Xin, X.P. Quantitative monitoring of grazing intensity in the temperate meadow steppe based on remote sensing data. Int. J. Remote Sens. 2018, 40, 2227–2242. [CrossRef] 27. Chaudhary, D.R.; Gautam, R.K.; Yousuf, B.; Mishra, A.; Jha, B. Nutrients, microbial community structure and functional gene of rhizosphere and bulk soils of halophytes. Appl. Soil Ecol. 2015, 91, 16–26. [CrossRef] 28. Baron, V.S.; Mapfumo, E.; Dick, A.C.; Naeth, M.A.; Okine, E.K.; Chanasyk, D.S. Grazing intensity impacts on pasture carbon and nitrogen flow. J. Range Manag. 2002, 55, 535–541. [CrossRef] Sustainability 2019, 11, 5226 15 of 16

29. Han, G.D.; Hao, X.Y.; Zhao, M.L.; Wang, M.J.; Ellert, B.H.; Willms, W.; Wang, M.J. Effect of grazing intensity on carbon and nitrogen in soil and vegetation in a meadow steppe in Inner Mongolia. Agric. Ecosyst. Environ. 2008, 125, 21–32. [CrossRef] 30. Jiang, L.L.; Wang, S.P.; Pang, Z.; Wang, C.S.; Kardol, P.; Zhou, X.Q.; Rui, Y.C.; Lan, Z.C.; Wang, Y.F.; Xu, X.L. Grazing modifies inorganic and organic nitrogen uptake by coexisting plant species in alpine grassland. Biol. Fertil. Soils 2016, 52, 211–221. [CrossRef] 31. Elser, J.J.; Acharya, K.; Kyle, M.; Cotner, J.; Makino, W.; Markow, T.; Watts, T.; Hobbie, S.; Fagan, W.; Schade, J.; et al. Growth rate-stoichiometry couplings in diverse biota. Ecol. Lett. 2003, 6, 936–943. [CrossRef] 32. Greenwood, K.L.; Hutchinson, K.J. Root characteristics of temperate pasture in New South Wales after grazing at three stocking rates for 30 years. Grass Forage Sci. 1998, 53, 120–128. [CrossRef] 33. Fan, G.Y.; Zhang, J.N.; Zhang, Y.S.; Li, G.; Wang, Q.; Yang, D.L. Effects of grazing on plant root distribution and soil physicochemical properties in Stipa baicalensis grassland. Chin. J. Ecol. 2010, 29, 1715–1721. 34. Pregitzer, K.S.; Laskowski, M.J.; Burton, A.J.; Lessard, V.C.; Zak, D.R. Variation in sugar maple root respiration with root diameter and soil depth. Tree Physiol. 1998, 18, 665–670. [CrossRef] 35. Li, X.Z.; Chen, Z.Z. Influences of stocking rates on C, N and P contents in plant-soil system. Acta Agrestia Sin. 1998, 6, 90–98. 36. Bagchi, S.; Ritchie, M.E. Introduced grazers can restrict potential soil carbon sequestration through impacts on plant community composition. Ecol. Lett. 2010, 13, 959–968. [CrossRef] 37. McSherry, M.E.; Ritchie, M.E. Effects of grazing on grassland soil carbon: A global review. Glob. Chang. Biol. 2013, 19, 1347–1357. [CrossRef] 38. Snyman, H.A.; du Preez, C.C. Rangeland degradation in a semi-arid South Africa—II: Influence on soil quality. J. Arid Environ. 2005, 60, 483–507. [CrossRef] 39. García-Oliva, F.; Tapia-Torres, Y.; Montiel-Gonzalez, C.; Perroni-Ventura,Y.Carbon, Nitrogen, and Phosphorus in Terrestrial Pools: Where Are the Main Nutrients Located in the Grasslands of the Cuatro Ciénegas Basin? In and Geochemistry of Cuatro Cienegas; Springer: Berlin/Heidelberg, Germany, 2018; pp. 1–13. 40. Cleveland, C.C.; Liptzin, D. C:N:P stoichiometry in soil: Is there a “redfield ratio” for the microbial biomass? Biogeochemistry 2007, 85, 235–252. [CrossRef] 41. Xu, X.F.; Thornton, P.E.; Post, W.M. A global analysis of soil microbial biomass carbon, nitrogen and phosphorus in terrestrial ecosystems. Glob. Ecol. Biogeogr. 2013, 22, 737–749. [CrossRef] 42. Fanin, N.; Fromin, N.; Buatois, B.; Hättenschwiler, S. An experimental test of the hypothesis of non-homeostatic stoichiometry in a plant litter—Microbe system. Ecol. Lett. 2013, 16, 764–772. [CrossRef] 43. Zimmerman, A.E.; Allison, S.D.; Martiny, A.C. Phylogenetic constraints on elemental stoichiometry and resource allocation in heterotrophic marine bacteria. Environ. Microbiol. 2014, 16, 1398–1410. [CrossRef] 44. Chen, Y.L.; Chen, L.Y.; Peng, Y.F.; Ding, J.Z.; Li, F.; Yang, G.B.; Kou, D.; Liu, L.; Fang, K.; Zhang, B.B.; et al. Linking microbial C:N:P stoichiometry to microbial community and abiotic factors along a 3500-km grassland transect on the Tibetan Plateau. Glob. Ecol. Biogeogr. 2016, 25, 1416–1427. [CrossRef] 45. Xun, W.B.; Yan, R.R.; Ren, Y.; Jin, D.Y.; Xiong, W.; Zhang, G.S.; Cui, Z.L.; Xin, X.P.; Zhang, R.F. Grazing-induced microbiome alterations drive soil organic carbon turnover and productivity in meadow steppe. Microbiome 2018, 6, 170. [CrossRef] 46. Bowen, G.D.; Rovira, A.D. The rhizosphere and its management to improve plant growth. Adv. Agron. 1999, 66, 1–102. 47. Murphy, C.A.; Foster, B.L.; Gao, C. Temporal dynamics in rhizosphere bacterial communities of three perennial grassland species. Agronomy 2016, 6, 17. [CrossRef] 48. Zhang, C.; Liu, G.B.; Xue, S.; Wang, G.L.; Wang, J.; Song, Z.L. Effects of rhizosphere interactions of grass interspecies on the soil microbial properties during the natural succession in the loess plateau. Eur. J. Soil Biol. 2018, 85, 79–88. [CrossRef] 49. Uren, N.C. Types, amounts, and possible functions of compounds released into the rhizosphere by soil-grown plants. In The Rhizosphere; CRC Press: Boca Raton, FL, USA, 2000; pp. 35–56. Sustainability 2019, 11, 5226 16 of 16

50. Raaijmakers, J.M.; Paulitz, T.C.; Steinberg, C.; Alabouvette, C.; Moenne-Loccoz, Y. The rhizosphere: A playground and battlefield for soilborne pathogens and beneficial microorganisms. Plant Soil 2009, 321, 341–361. [CrossRef] 51. Aira, M.; Gomez-Brandon, M.; Lazcano, C.; Baath, E.; Dominguez, J. Plant genotype strongly modifies the structure and growth of maize rhizosphere microbial communities. Soil Biol. Biochem. 2010, 42, 2276–2281. [CrossRef]

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).