Short-term grazing exclusion improved topsoil conditions and plant characteristics in degraded alpine grasslands

Ecological Indicators 108 (2020) 105680

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Short-term grazing exclusion improved topsoil conditions and plant characteristics in degraded alpine grasslands Chenjun Dua,b,c, Jie Jingb,c, Yuan Shend, Haixiu Liue, Yongheng Gaoa,b,

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a

Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China c College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China d College of Life Science & Biotechnology, Mianyang Teachers’ College, Mianyang 621000, China e Ledu Forestry Bureau, Haidong 810699, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Tibetan Plateau Grassland degradation Fencing Soil nutrients Enzyme activity

Grazing exclusion by fencing is one of the most effective practices to recover the degraded alpine grasslands in Tibetan Plateau. In the present study, the effects of 8-year (GE8) and 4-year (GE4) grazing exclusion were studied in comparison with free grazing (FG) in the plant-soil ecosystems of alpine grasslands. Within fencing, improved plant characteristics such as aboveground biomass (AGB), belowground biomass (BGB) and plant total cover developed without grazing and trampling were observed. Also, there were significant improvements of soil organic carbon (SOC), ammonia nitrogen (NH4+-N) and dissolved organic carbon (DOC) concentrations usually in the topsoil (0–30 cm) but a stable C:N ratio with the number of years of grazing exclusion. Fencing enhanced soil main enzyme (invertase, phosphatase, urease and β-glucosidase) activities by providing sufficient substrates for microbial activities. Unexpectedly, GE4 had higher soil invertase, phosphatase, urease and β-glucosidase activities than GE8, which had less plant diversity, richness and higher total cover causing a lowering of soil temperature. Additionally, the results supported the allometric allocation hypothesis for the ABG versus BGB in the grasslands of Tibetan Plateau. Our results indicated that SOC and BGB can be used as indicators of the restoration process of degraded alpine grassland. Cautions should be taken for a long-term fencing in degraded alpine grasslands because of the loss of plant richness, diversity and soil enzyme activities. The present results also suggested that a suitable grazing regime combined with fencing should be focused in the future study of the alpine grasslands. Research results obtained in the present study should, therefore, be helpful to offer a better guidance towards the management practices of the degraded alpine grasslands.

1. Introduction About 40% of the earth's terrestrial area amounting 50 million km2 is covered by grasslands (O'Mara, 2012; Wang and Fang, 2009). Livestock grazing is the principal use of grasslands throughout the world, and thereby creating the basis of local livelihoods (O'Mara, 2012; Sigcha et al., 2018). Grasslands can also provide ecosystem services and functions, via CO2 fixation and keeping balance in the ecosystem stability and providing pasture for livestock (Lavorel et al., 2015; Zhang et al., 2016). China's grasslands are the third largest in the world and nearly 25% of the total area of China is covered with various types of grasslands. These range from temperate grasslands in the north to alpine grasslands in the Tibetan Plateau (Yang et al., 2010a). However, 90% of the grasslands in China has been degraded by overgrazing and to some extent by climate change (Harris, 2010). The Tibetan Plateau is

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the largest and highest plateau in the world, it covers 2.5 million km2 and has an average elevation of 4000 m (Chen et al., 2015). Alpine grasslands in Tibetan Plateau, covering > 60% area, contain 44% of the total grasslands of China (Piao et al., 2012). Alpine grasslands are ecological shelter for China and “Asia's water tower” (Chen et al., 2015; Kato et al., 2006), and also support livestock on which several million herdsmen depend (Hopping et al., 2018). In recent years, the degeneration of grasslands from the Tibetan Plateau is serious. It is ongoing because of increasing population, global climate change and rodent damage (Harris, 2010). A published research showed that 42 and 33% of the SOC and TN stocks, respectively were lost from the alpine grasslands. The loss rates of SOC and TN stocks would continue unless the effective recovery strategies are adopted (Liu et al., 2018). To recover alpine grasslands degradation, a number of restoration measure programs such as “Retire-livestock-and-restore-

Corresponding author at: Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China. E-mail address: [email protected] (Y. Gao).

https://doi.org/10.1016/j.ecolind.2019.105680 Received 26 December 2018; Received in revised form 17 August 2019; Accepted 27 August 2019 1470-160X/ © 2019 Elsevier Ltd. All rights reserved.

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grassland” and “Start-up Re-grass Program” were established successively in China (Hu et al., 2016) to achieve a goal of recovering grassland degradation through grazing exclusion (Wei et al., 2012). It has been regarded as an effective method by preventing large animals like cattle or sheep from eating off grasses to relieve degradation of the grasslands (Medina-Roldan et al., 2012; Mekuria and Aynekulu, 2013). To our knowledge, there has been a good number of published research information focusing mainly on plant diversity, soil carbon storage, soil properties, soil nutrients (N and P) and greenhouse gas exchanges by fencing (Lu et al., 2015; Medina-Roldan et al., 2012; Mekuria and Aynekulu, 2013; Wei et al., 2012; Wu et al., 2010). Also, several metaanalysis were synthesized to show summary effects of grazing exclusion in China's grasslands (Hu et al., 2016; Xiong et al., 2016). However, despite the importance of grazing exclusion in alpine grasslands, the response of soil conditions on grazing exclusion are controversial. For instance, there were positive (Wu et al., 2010), neutral (Dong et al., 2012) and negative (Shi et al., 2013) fencing-effect on soil C storage. Also, previous studies on this subject focused (Sun et al., 2018; Wu et al., 2010) mainly on topsoil (0–30 cm). Few of those were devoted to assessing vertical distribution of soil characteristics through a depth range of 0–50 cm in the alpine grasslands of Tibetan Plateau. In addition, there was also a lacking of information on the analyses of fencingeffect on soil enzyme activity, although it is crucial for the biogeochemical cycles of C and N (Vasconcellos et al., 2013). The selected sites of the present study, which are located in the eastern part of the Tibetan Plateau and where short-term (8 years and 4 years) grazing exclusion are practiced (Fig. 1). This has made it possible to understand the effects of short-term fencing treatment on both vegetation and soil properties in a much better way. Of course, overgrazing is the most important factor for grasslands degeneration or fragmentation in this region (Li et al., 2013). In the present study, an investigation was conducted to evaluate the response of degraded alpine grassland ecosystems to grazing exclusion. The main objectives of the present study were, (i) to examine the above- and below-ground plant biomass and litter biomass due to fencing, (ii) to assess the effect of grazing exclusion on the dynamics of soil C and N (i.e., SOC, TN, DOC, NH4+-N, NO3–-N) concentrations, and (iii) to investigate how microbial C, N and soil enzyme activities (i.e., invertase, phosphatase, urease, β-glucosidase) response to grazing exclusion by fencing.

2. Materials and methods 2.1. Study sites The study site is an alpine grassland situated 15 km northeast of Hong Yuan county (32°49′N, 102°36′E, altitude of 3500 m) in Sichuan Province, China. It is located at the eastern part of the Tibetan Plateau (Fig. 1). The climate of the area is temperate monsoon having a characteristic of the continental plateau. It has a year round harsh continental cold climate. According to the latest 20 years of local meteorological database, the mean annual temperature is about 1.1 °C (Gao et al., 2016). Annually it ranges from −10.9 °C in January to 10.3 °C in July. The mean precipitation is 752 mm, with the principal rain period during a cool summer. > 86% of the mean annual precipitation is received from May to September. The vegetation is typical alpine grassland dominated by Elymus nutans Griseb, Kobresia setchwanensis HandMazz and pygmaea with other distinctive plants e.g., Aster alpine, Gueldenstaedtia diversifolia and Potentilla anserine (Gao et al., 2016). Trees and shrubs are very infrequent in the present sites. The soil is classified as Mat Crygelic Cambisol. In this study, three sites were selected for the treatments. Those were, GE8 (fenced from May 2009 with metal fences), GE4 (fenced from May 2013 with metal fences) and FG (no-fencing). Three sites had long years of grazing history which experienced an annual grazing density of 1–3 yaks ha−1 before fencing, the main grazer was yak (B. grunniens). In the FG category, both the winter (October to June) and summer grazing regimes (all other months) were practiced. Lands of the three study sites were adjoined and the initial climatic conditions, soil and vegetation characteristics were identical. 2.2. Experimental design and sampling The sampling time for the present investigation was selected as midAugust 2017 since it is typical for obtaining peak AGB in the alpine grasslands. In each of the study sites, four homogeneously selected 10 × 10 m blocks were studied (Fig. 1). At least 20 m buffer area was left between each block of the same study site. Thus, a total of 12 blocks (4 replicates × 3 treatments) were available for carrying out the present research. Although, the excluded and grazing sites were limited to one location, the treatment sites were selected at the landscape level.

Fig. 1. Location of the study area and sampling plots. 2

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Table 1 Plant cover, richness, diversity and biomass of FG, GE4 and GE8 alpine grasslands. Treatment

Cover (%) Richness Shannon-Wiener index Aboveground Total aboveground (g m−2) Aboveground green (g m−2) Litter (g m−2) Grass biomass (g m−2) Sedge biomass (g m−2) Legume biomass (g m−2) Weed biomass (g m−2) Belowground Total belowground (g m−2) 0–10 cm (g m−2) 10–20 cm (g m−2) 20–30 cm (g m−2) 30–40 cm (g m−2) 40–50 cm (g m−2) Root : shoot

F

P

FG

GE4

GE8

48.1 ± 0.9a 9.8 ± 0.4a 1.9 ± 0.1a

72.3 ± 1.9b 23.5 ± 1.0b 2.9 ± 0.1b

95.0 ± 1.2c 19.8 ± 0.6c 2.2 ± 0.1c

206.6 71.5 44.5

< 0.001 < 0.001 < 0.001

178.3 ± 8.8c 150.6 ± 8.4c 27.7 ± 1.6c 4.3 ± 0.1a 12.9 ± 1.7ab 11.0 ± 0.3a 122.5 ± 7.7a

289.4 ± 13.8b 197.9 ± 10.3b 91.6 ± 4.3b 33.0 ± 0.8b 23.6 ± 3.8ab 12.5 ± 0.5a 125.2 ± 8.0a

545.1 ± 16.1a 300.8 ± 10.1a 244.4 ± 9.4a 103.3 ± 1.2c 71.7 ± 10.0c 16.1 ± 4.3a 108.7 ± 5.3a

151.6 45.6 255.5 2798.0 18.7 0.8 1.2

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.46 0.35

1415.3 ± 25.5c 1127.9 ± 42.5c 114.6 ± 3.6c 71.9 ± 2.6c 52.5 ± 1.3bc 48.5 ± 2.6c 9.5 ± 0.4c

1766.3 ± 62.8b 1348.3 ± 53.8ab 196.6 ± 6.3b 101.9 ± 3.3b 60.9 ± 2.9bc 58.6 ± 2.7bc 9.0 ± 0.6bc

2176.8 ± 68.8a 1515.9 ± 47.6ab 334.2 ± 13.0a 178.6 ± 6.3a 85.5 ± 3.1a 62.6 ± 2.6ab 7.3 ± 0.3ab

57.5 12.2 124.3 117.5 1182.3 211.8 5.2

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.05

Values indicate mean ± SE, N = 4. Total aboveground biomass was sum of aboveground green biomass and litter biomass, total belowground biomass was sum of 0–50 cm belowground biomass, root: shoot ratio was calculated with total belowground biomass and aboveground green biomass. F and P values are the significance by the one-way ANOVA. Different letters in a row indicate significant differences between three grasslands by the Tukey's HSD test, P < 0.05.

++ 8505, Netherlands). SOC and TN were analyzed by a C and N analyzer. Soil microbial C (MC) and N (MN) were determined using fumigation method (Durenkamp et al., 2010). An enzyme-linked immunosorbent assay (ELISA) test kit (Tian et al., 2012) was used to detect soil invertase, phosphatase, urease and β-glucosidase activities.

These included homogeneous topography, soil texture, and random sampling. But pseudoreplication among the study sites could be considered as unavoidable like other previous studies (Hafner et al., 2012; Medina-Roldan et al., 2012; Shi et al., 2013). Vegetation cover and species were visually estimated by 1–2 experienced observers (Zhou et al., 2011). The Shannon-Wiener index (H) was calculated by using the following formula (1):

2.4. Data analysis

s

H= -∑ PilnPi i

After assumptions of normality (Shapiro-Wilk's test) and homoscedasticity (Bartlett-test), all the data were made ready for statistical analysis. A two-way ANOVA analysis by the general linear model (GLM) was used to assess the effects of grazing exclusion treatment and soil depth factors on soil nutrient, BGB and soil enzyme activity. To evaluate the differences among ABG, litter biomass, BGB, root:shoot ratio, soil nutrient and enzyme activity among FG, GE4 and GE8 grasslands, multiple comparisons of means were done using a Tukey's HSD test. The effect sizes of individual variables (i.e., BGB, soil water content, nutrients and enzyme activity in 0–50 cm) were quantified to illustrate differences between the fencing (8 years and 4 years) and the free grazing grassland. Specially, the effects were calculated by using the following formulas (2–4):

(1)

where, Pi is the ratio of the number of each species to the total number of all species and s is the number of all species in the community (richness). Four 0.5 × 0.5 m randomly selected quadrates were run in each block for sampling biomass. The AGB was harvested by clipping to the soil surface with a scissor. The sampling of BGB was performed by using a bucket auger of 8 cm in diameter. The studied profile was composed by 10 cm layer up to 50 cm depth. In total, 60 samples were obtained to measure BGB (4 replicates × 5 depths × 3 treatments). Similarly, a total of 60 composite soil samples were sampled using the same bucket auger as mentioned above. The collected soil samples were immediately placed in a cooler cube at a temperature of 4 °C and brought to the laboratory for further analyses. Soil samples were collected for 0–10 cm and 10–20 cm by using a standard container (100 cm3 in volume) to measure soil bulk density. 2.3. Sample analysis Following the previous research carried out in Tibetan Plateau (Wang et al., 2017), the AGB were screened manually into four different functional types namely, grass, sedge, legume and weed types, respectively. The BGB was cleaned by freshwater using a 0.5 mm sieve. Aboveground, litter and belowground biomass samples were oven-dried at 65 °C for 48 h to constant weight and weighed to the nearest 0.01 g. For soil samples, fine roots, fine gravels and litters were separated manually. Then all the soil samples were air-dried and passed through a 2 mm sieve. A sub-sample was dried at 105 °C for 48 h to constant weight to measure the soil gravimetric moisture content and soil bulk density (Luo et al., 2018). Soil DOC, NH4+-N and NO3–-N concentrations were measured using a continuous flow auto-analyzer (Skalar San

4 years effect size =

(GE4 - FG) × 100% FG

(2)

8 years effect size =

(GE8−FG) × 100% FG

(3)

GE8 vs GE4 =

(GE8 - GE4) × 100% GE4

(4)

Positive, zero or negative effect size meant increase, no change or decrease, respectively. A general linear model was used to evaluate the relationship between log (ABG) and log (BGB), SOC and TN. Correlation analyses were conducted to test their relationships among soil enzyme activities over the depth of 0–50 cm, plant richness and diversity index of three sites. All the above-mentioned statistical analyses were performed using R.3.4.3 software (R Development Core Team, 2017). 3

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Table 2 Results of two-way ANOVA tests for the effects of grassland treatment (GT), soil depth (SD), and their interactions (GT × SD) on belowground biomass, soil water content, nutrient, microbial biomass carbon, microbial biomass nitrogen, and enzyme activity. (DF: Degrees of freedom). DF Sources GT SD GT × SD Sources GT SD GT × SD Sources GT SD GT × SD Sources GT SD GT × SD

2 4 8 2 4 8 2 4 8 2 4 8

F BGB 44.9 1390.0 9.5 C:N 0.9 20.6 0.3 MC 28.5 229.2 1.5 Invertase 34.5 649.3 12.8

P

< 0.001 < 0.001 < 0.001 0.422 < 0.001 0.959 < 0.001 < 0.001 0.178 < 0.001 < 0.001 < 0.001

F

P

WC 10.4 32.7 6.0 NH4+-N 54.1 312.8 12.7 MN 9.2 91.7 0.6 β-glucosidase 15.5 432.4 4.9

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.783

F SOC 27.4 391.7 7.9 NO3–-N 60.3 90.0 14.2 Phosphatase 12.8 444.4 3.3

P

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001

F TN 15.4 246.9 4.4 DOC 41.9 344.2 6.1 Urease 2.7 585.7 0.2

P

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.08 < 0.001 0.98

< 0.001 < 0.001 < 0.001

3. Results

insignificant.

3.1. Response of plant characteristics

3.3. Response of soil microbial C, N and enzyme activities

Plant total cover increased with grazing exclusion years. FG had the lowest plant richness (< 50%) and diversity (average 1.9). Unexpectedly, when the both GE8 and GE4 were compared with each other, GE4 had significant higher plant richness and Shannon-Wiener index than GE8 (Table 1). For biomass of different functional plant types, grass and sedge increased significantly with the number of years of grazing exclusion (P < 0.001). Data obtained from the GE8 experimental grasslands showed that the total aboveground, total belowground (0–50 cm) and litter biomass were significantly higher than FG. Litter biomass was 8.82 times higher in GE8 than in FG sites (Table 1). For BGB, soil depth, treatment and their interactions showed significant effects (Table 2, P < 0.001). The BGB of FG, GE4 and GE8 decreased with soil depth. Grazing exclusion increased root:shoot ratio continuously with the number of years of grazing exclusion. > 90% of root biomass was located within the top 30 cm of soil (Fig. 2A). However, fencing increased percent of distribution root biomass in 10–20 and 20–30 cm, but slightly affected on 40–50 cm depth of the soil profile. When the BGB of 0–50 cm in grazing and fencing sites were pooled together (Fig. 5), it can be seen that in GE4 and GE8 belowground biomass increased by 34.57 and 94.29%, respectively. The slope of regression between log (ABG) and log (BGB) were 1.52 (Fig. 2B, P < 0.001).

There was a significant effect of soil depth and treatment (Table 2, P < 0.001) but with insignificant (Table 2, P > 0.05) interaction on MC and MN. For each site, MC and MN decreased with soil depth (Fig. 4). As expected, MC and MN generally increased with the number of years of grazing exclusion (Fig. 4). Compared to FG, soil MN increased significantly (P < 0.05) only in 0–10 cm soil layer in GE8 site but GE4 had slight effects on MN (P > 0.05). In GE8, MC in 0–30 cm layers also improved significantly but not in deep layers (Fig. 4). Soil depth, treatment and their interaction had significant (Table 2, P < 0.001) effects on invertase, phosphatase and β-glucosidase activities. For each site, soil invertase, phosphatase, urease and β-glucosidase activities fell similarly with an exponential downward tendency with increasing depth. It is interesting to note that when GE8 was compared to GE4, most results on soil enzymes fell down with the age of grazing exclusion (Fig. 4C-F). Specifically, on an average, invertase, phosphatase, urease and β-glucosidase in GE8 decreased by 5.53, 5.53, 10.50 and 10.00%, respectively (Fig. 5C, P < 0.05). 4. Discussions The present study has been conducted to see the effects of shortterm fencing on plant characteristics, soil nutrients and enzyme activities in degraded alpine grasslands. As consistent with the previous studies (Sun et al., 2018; Wu et al., 2010; Zhang et al., 2018), plant total cover, total aboveground biomass, litter fall biomass and belowground biomass increased with the number of years of grazing exclusion. Unexpectedly, plant diversity, richness and soil enzyme activities showed a trend of FG < GE8 < GE4. This indicated that fencing is beneficial to degraded alpine grasslands recovery but 8 years fencing might not bring continuous benefit for plant species diversity and soil microbial activities in this typical alpine area (Wu et al., 2009). Plant’s recovery through fencing enhanced soil nutrients, which decreased with soil depth as well as BGB in three grasslands. Fencing enhanced upper 40 cm belowground biomass but generally improved 20 cm topsoil nutrients (Figs. 2-4), showing improvement of soil conditions lagged behind the plant recovery.

3.2. Response of soil C and N concentrations For each of the three experimental alpine grassland sites, SOC, TN, NO3–-N, NH4+-N and DOC concentrations decreased with depth (Fig. 3). Soil depth, treatment and their interaction showed significant effects (Table 2, P < 0.001) on their concentrations. GE8 increased SOC, TN, NO3–-N and DOC concentrations significantly (Fig. 3, P < 0.05) in 0–10 and 10–20 cm soil layers, but in 20–50 cm soil layers those were enhanced slightly. Fencing had a marginally significant (Table 2, P > 0.05) influence on soil C:N ratio in all soil layers, but soil depth showed a significant effect on C:N ratio (Table 2, P < 0.001). Compared with FG, GE4 decreased soil NO3–-N concentration in 0–50 cm layers, but the data were not statistically significant (Fig. 3E, P > 0.05). On the contrary, an increase of soil NH4+-N concentration in 0–50 cm layers was observed in GE4, especially in 30–40 and 40–50 cm layers. When the C:N ratio of 0–50 cm in grazing and fencing sites were pooled together (Fig. 5), it has been seen that the change of C:N ratio in GE4 (2.88% at average, −4.43 to 10.18% at 95% CI) and GE8 (5.84% at average, −0.05 to 11.74% at 95% CI) were

4.1. Effects of fencing on plant characteristics, soil nutrients and enzyme activities Short-term fencing is beneficial to degraded alpine grasslands recovery. On the one hand, fencing directly excluded livestock pasturing 4

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Fig. 2. Showing the proportional distributions of root biomass (A) in top of 50 cm of soil (0–50 cm, of which every 10 cm serve as a layer) in three experimental alpine grasslands. The relationship between log (ABG) and log (BGB) alpine grasslands (B), data from three sites were pooled together, the shaded regions indicate 95% confidence interval (CI).

frequently used to assess the ecological factors related to plant growth (Sun et al., 2018). Similar to previous studies observed in Tibetan Plateau grassland (Zeng et al., 2015), our results supported allometric biomass allocation hypothesis (Fig. 2B). Grazing exclusion can reduce the loss of nutrient from soil-plant system to livestock (Deng et al., 2017; Wu et al., 2009). Fencing improved soil nutrients (i.e., SOC, TN, DOC, MC and MN) but usually did not change soil C:N ratio (Figs. 3-5). The pattern of these soil nutrients in all the three study sites decreased with soil depth as similar to the distributional pattern of BGB (Figs. 3–5). A stable C:N ratio or C-N coupling (Fig. 7) during the entire recovery process indicate that the resultant soil nutrients through plant litter decomposition is a vital pathway (Sun et al., 2013). Although, exclusion of livestock cut the input of N through urine depositions which happens to be a very important source of mineral N (Taboada et al., 2011). The cold climate prevailed in the alpine grasslands lead to accumulation of soil nutrients (Chen et al., 2016; Ding et al., 2017).The higher soil nutrients in the topsoil of Tibetan alpine grasslands could be owing to the lower belowground biomass (> 90% upper to 30 cm, Fig. 2) distribution (Yang et al., 2010b) and litter fall deposition from the aboveground biomass production (Table 1). A marginal change of soil nutrients in 30–50 cm has, possibly been caused by natural conditions rather than fencing treatment effects (Liu et al., 2012; Liu et al., 2014; Yang et al., 2010b). In consistent with other researchers (Cools et al., 2014; Tian et al., 2010), a decreasing trend of C:N ratio with soil depth in three sites might be due to recently fallen litter materials and fewer humification processes in topsoil than deeper layers. We found that MC:MN and soil

of aboveground biomass, especially for palatable plants such as grass and sedge (Wu et al., 2009). So, the biomass of these functional types decreased highly (Table 1) under grazing conditions (Hu et al., 2016). Also, soil compaction usually inhibits plant biomass accumulation in pastures (Pulido et al., 2018) and forests (Alameda et al., 2012). A tendency of more anaerobic environment under soil compaction (Fig. 6) by grazer trampling could limit productivity, especially for root growth (Dolores Bejarano et al., 2010). Generally, grasslands productivity increased with plant diversity (Cardinale et al., 2007; van Ruijven and Berendse, 2005), fencing also increased biomass by enhancing structural and compositional diversity (Table 1). Interesting to note that although, GE4 had higher plant diversity and richness than GE8 in contrast to biomass, a longer fencing treatment should be a caution, provided that GE8 did not bring continuous benefit for biodiversity (Table 1). On the other hand, in agreement with previous study carried out in natural Tibetan Plateau alpine grasslands (Li et al., 2011), BGB was mainly distributed at the 0–20 cm and declined abruptly with increasing depth whether fencing were done or not (Fig. 2A). The unchanged pattern of BGB under fencing treatment may be the fact that our fencing time was short. A tendency of increased BGB distribution (%) over 10–20 and 20–30 cm soil layers under grazing exclusion was observed (Fig. 2A). Provided that a more stable root distribution under grazing exclusion might be beneficial to nutrients uptake (Sun and Wang, 2016) and preventing freezing disaster because of prevailing strong cold climate and regular thawing-freezing cycles in this area (Hong et al., 2015; Yang et al., 2010a,b,c; Yang et al., 2009). Furthermore, allocation of aboveground and belowground biomass is

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Fig. 3. Showing the concentrations of SOC, TN and C:N ratio and NH4+-N, NO3–-N, and DOC concentrations of three experimental alpine grasslands (A-F) along 0–50 cm soil depth. C:N ratio was calculated with SOC and TN. Values indicate mean ± SE, N = 4. * in top of figure indicates significant differences between the fencing and no-fencing grasslands by the Tukey's HSD test (P < 0.05).

continuously (Table 1), soil temperature could be lower in GE8 than GE4 owing to the blocking of sunlight by dense vegetation, especially during our sampling period (maximum biomass). On the other hand, an intense lowering temperature effect or “cooling effect” by transpiration in longer fencing grasslands could occur because of higher plant cover and biomass (Table 1). Secondly, plant diversity and richness index are associated with enzymatic activity (Zhang et al., 2018), more diverse plant composition contribute to a more diverse litter production and/or root exudates input for soil microorganism, thus consequently greater microbial diversity and enzymatic activity might have occurred (Thakur et al., 2015). Correlation analyses showed that soil enzyme activities had positive relationship to plant richness and diversity index (Table 3). A significant higher plant richness and diversity in GE4 than GE8 could explain this unexpected phenomenon (Table 1). In addition, soil nutrients could also affect enzymatic activity by driving the bacterial and fungal communities, especially NH4+-N and NO3–-N concentrations (Pommier et al., 2018). In the review of the above, these findings suggest that plant biomass and soil nutrients may nearly be deteriorating with decreasing of plant diversity, richness and soil enzymatic activities under longer age of fencing in alpine grasslands. Therefore, caution should be taken against a relatively long fencing duration in the degraded alpine grasslands.

C:N ratios in 30–50 cm were nearly identical from three sites (about 8), but a higher soil C:N than MC:MN ratios in topsoil (Fig. 3C, 8A). These showing the breakdown of plant litter and residues by the microbial activities, whereby root biomass tends to have higher C:N ratio accompanied by low C:N ratio of microbial biomass (Cools et al., 2014). In addition, in contrast to the NH4+-N, a higher soil NO3–-N was found in FG than GE4 (Fig. 3). To explain this, assimilation by plants should be considered. In Tibetan Plateau alpine grasslands, all species of plants preferred NO3–-N to NH4+-N (Wang et al., 2012) and GE4 had greater above-belowground biomass than FG (Table 1). Furthermore, an increase in belowground biomass density after fencing leaded to relative higher available soil water content (Fig. 8B), which can improve recovery of plants (Lal, 2018; Wang et al., 2015). A greater soil enzyme activity was observed in two fencing sites than in FG (Figs. 4-5). This finding is consistent with a previous study in semiarid grasslands (Zhang et al., 2018) but inconsistent with a study in Basque Country (Aldezabal et al., 2015). This study indicated that grazing exclusion improved soil enzyme activity by providing sufficient substrates (i.e., biomass, DOC, TN) for microbial community (Vasconcellos et al., 2013). In contrast to prevailing view, when compared to GE4, GE8 did not enhance soil invertase, phosphatase, urease and β-glucosidase continuously. Firstly, we suppose this unexpected phenomenon could be explained from the soil temperature. On the one hand, grazing exclusion enhanced plant total cover and biomass 6

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Fig. 4. Effects of grazing exclusions for 8 and 4 years on MC, MN, phosphatase, invertase, urease, and β-glucosidase activities in alpine grasslands (A-F). Values indicate mean ± SE, N = 4. * in the top of figure indicates significant differences between the fencing and no-fencing grasslands by the Tukey's HSD test (P < 0.05).

Excluding grazing also affects seed bank (Franca et al., 2018; Matejkova et al., 2003), such as easily dispersed seeds may disperse into exposed areas without livestock trample (Middleton, 2002). However, seed dispersal that needs to be spread by grazers should be limited, such as Xanthium sibiricum. A study in a steppe ecosystem showed that 25-year grazing exclusion increased the species richness in the soil seed bank but decreased the belowground species evenness (Zhao et al., 2011). Giving importance to it, allowing a very short grazing regime in winter in fencing grasslands may bring some positive effects on degraded grasslands in a typically frozen soil area. Allowance of this short grazing not only benefits easy seed transmission but also seed with difficult transmission. The practice of short grazing can also alleviate the shortage of winter pasture in this area to some extent. Furthermore, a previous study in this area indicated that warm-seasonal grazing is suitable for topsoil nutrient sequestration, but cold-seasonal grazing is suitable for deep soil nutrient restoration (Wu et al., 2017a,b). Moderate grazing and periodic resting could increase plant productivity, recover community composition and increase soil C stock in alpine meadow (Cui et al., 2014; Hafner et al., 2012). Seasonal grazing also brings benefit for livestock productivity (Cingolani et al., 2005), which supports local livelihood. Therefore, A suitable grazing regime should be focused on this fragile ecosystem in the future study.

4.2. Implication for degraded alpine grasslands management Short-term grazing exclusion decreased soil bulk density owing to the absence of grazer trampling combined with seasonally frozen ground degradation in this fragile ecosystem (Fig. 6). Frost heaving under long-term fencing in this area could lead to environmental deterioration (Yang et al., 2010a,b,c). Therefore, an optimum grazing exclusion time since restoration should not only combine with fencingeffect but also the local environment (i.e., precipitation, wind, freezing and thawing) and local policy (Hu et al., 2016; Medina-Roldan et al., 2012; Xiong et al., 2016). For example, effects of hydrological status, nutrient and wind erosion and their interaction in the arid and wetland areas should be considered under grazing exclusion (Hu et al., 2016; Merriam et al., 2018). Our results showed that GE4 had higher enzymatic activity, plant richness and diversity than GE8 (Fig. 4C-F, Table 1). This proves that a long-term fencing should be dealt with caution in this fragile ecosystem. Our study sites are located in the highest and biggest alpine regions of the world, where temperature is the major limiting factor for plants growth (An et al., 2018). So, grasslands restoration should also combine with annual temperature in the future, which might be having a rising trend. Short-term grazing exclusion, such as in spring lead to a recover of richness and productivity (Fedrigo et al., 2018), while plant community diversity is strongly related to recovery processes in grasslands (Wang et al., 2014; Wu et al., 2017a,b; Wu et al., 2013). However, a long-term grazing exclusion might not lead to increase species richness (Oba et al., 2001).

5. Conclusion Our study revealed that short-term grazing exclusion by fencing in 7

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Fig. 5. Showing the effects of grazing exclusion in the experimental alpine grasslands. (A) for 4 and (B) for 8 years of exclusion. (C) shows additional effects of exclusion i.e. 8 years versus 4 years on alpine grasslands. Values are change in percent (%) and 95% confidence intervals. 4 years effect size = (GE4 - FG) / FG × 100%, 8 years effect size = (GE8 - FG) / FG × 100%, GE8 versus GE4 = (GE8 - GE4) / GE4 × 100%. N = 60, * P < 0.05, ** P < 0.001.

Fig. 7. Regression between soil SOC and TN, databases of FG, GE4 and GE8 were pooled together, N = 60. The shaded regions indicate 95% confidence interval.

Fig. 6. Soil bulk density of three treatment alpine grasslands in 0–20 cm soil depth, values indicate mean ± SE, N = 4. Different letters in top of figure indicate significant differences between three grasslands by the Tukey's HSD test (P < 0.05). 8

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Fig. 8. MC:MN ratio and water content of three treatment alpine grasslands (A, B) in 0–50 cm soil depth, values indicate mean ± SE, N = 4. Table 3 Pearson's correlation coefficients among soil enzyme activities over the depth of 0–50 cm, plant richness and diversity index of three sites (N = 12).

Richness Shannon-Wiener index

Phosphatase

Urease

Invertase

β-glucosidase

0.76* 0.86**

0.27 ns 0.25 ns

0.77* 0.92**

0.74* 0.78*

Mismatch in elevational shifts between satellite observed vegetation greenness and temperature isolines during 2000–2016 on the Tibetan Plateau. Glob. Change Biol. 24, 5411–5425. Cardinale, B.J., Wright, J.P., Cadotte, M.W., Carroll, I.T., Hector, A., Srivastava, D.S., Loreau, M., Weis, J.J., 2007. Impacts of plant diversity on biomass production increase through time because of species complementarity. PNAS 104, 18123–18128. Chen, L., Liang, J., Qin, S., Liu, L., Fang, K., Xu, Y., Ding, J., Li, F., Luo, Y., Yang, Y., 2016. Determinants of carbon release from the active layer and permafrost deposits on the Tibetan Plateau. Nat. Commun. 7. Chen, X.Q., An, S., Inouye, D.W., Schwartz, M.D., 2015. Temperature and snowfall trigger alpine vegetation green-up on the world's roof. Glob. Change Biol. 21, 3635–3646. Cingolani, A.M., Posse, G., Collantes, M.B., 2005. Plant functional traits, herbivore selectivity and response to sheep grazing in Patagonian steppe grasslands. J. Appl. Ecol. 42, 50–59. Cools, N., Vesterdal, L., De Vos, B., Vanguelova, E., Hansen, K., 2014. Tree species is the major factor explaining C: N ratios in European forest soils. For. Ecol. Manage. 311, 3–16. Cui, S., Zhu, X., Wang, S., Zhang, Z., Xu, B., Luo, C., Zhao, L., Zhao, X., 2014. Effects of seasonal grazing on soil respiration in alpine meadow on the Tibetan plateau. Soil Use Manag. 30, 435–443. Deng, L., Shangguan, Z.P., Wu, G.L., Chang, X.F., 2017. Effects of grazing exclusion on carbon sequestration in China's grassland. Earth Sci. Rev. 173, 84–95. Ding, J., Chen, L., Ji, C., Hugelius, G., Li, Y., Liu, L., Qin, S., Zhang, B., Yang, G., Li, F., Fang, K., Chen, Y., Peng, Y., Zhao, X., He, H., Smith, P., Fang, J., Yang, Y., 2017. Decadal soil carbon accumulation across Tibetan permafrost regions. Nat. Geosci. 10, 420–424. Dolores Bejarano, M., Villar, R., Maria Murillo, A., Luis Quero, J., 2010. Effects of soil compaction and light on growth of Quercus pyrenaica Willd. (Fagaceae) seedlings. Soil Tillage Res. 110, 108–114. Dong, S.K., Wen, L., Li, Y.Y., Wang, X.X., Zhu, L., Li, X.Y., 2012. Soil-Quality Effects of Grassland Degradation and Restoration on the Qinghai-Tibetan Plateau. Soil Sci. Soc. Am. J. 76, 2256–2264. Durenkamp, M., Luo, Y., Brookes, P.C., 2010. Impact of black carbon addition to soil on the determination of soil microbial biomass by fumigation extraction. Soil Biol. Biochem. 42, 2026–2029. Fedrigo, J.K., Ataide, P.F., Azambuja Filho, J., Oliveira, L.V., Jaurena, M., Laca, E.A., Overbeck, G.E., Nabinger, C., 2018. Temporary grazing exclusion promotes rapid recovery of species richness and productivity in a long-term overgrazed Campos grassland. Restor. Ecol. 26, 677–685. Franca, A., Re, G.A., Sanna, F., 2018. Effects of grazing exclusion and environmental conditions on the soil seed bank of a Mediterranean grazed oak wood pasture. Agrofor. Syst. 92, 909–919. Gao, Y., Cooper, D.J., Ma, X., 2016. Phosphorus additions have no impact on plant biomass or soil nitrogen in an alpine meadow on the Qinghai-Tibetan Plateau. China. Applied Soil Ecology. 106, 18–23. Hafner, S., Unteregelsbacher, S., Seeber, E., Lena, B., Xu, X., Li, X., Guggenberger, G., Miehe, G., Kuzyakov, Y., 2012. Effect of grazing on carbon stocks and assimilate partitioning in a Tibetan montane pasture revealed by 13CO2 pulse labeling. Glob. Change Biol. 18, 528–538. Harris, R.B., 2010. Rangeland degradation on the Qinghai-Tibetan plateau: a review of the evidence of its magnitude and causes. J. Arid Environ. 74, 1–12. Hong, J., Wang, X., Wu, J., 2015. Effects of soil fertility on the N: P stoichiometry of herbaceous plants on a nutrient-limited alpine steppe on the northern Tibetan Plateau. Plant Soil 391, 179–194. Hopping, K.A., Knapp, A.K., Dorji, T., Klein, J.A., 2018. Warming and land use change concurrently erode ecosystem services in Tibet. Glob. Change Biol. 24, 5534–5548. Hu, Z., Li, S., Guo, Q., Niu, S., He, N., Li, L., Yu, G., 2016. A synthesis of the effect of grazing exclusion on carbon dynamics in grasslands in China. Glob. Change Biol. 22,

* P < 0.05, ** P < 0.001, ns Not significant.

the degraded alpine grasslands of eastern Tibetan Plateau led to improvement of plant characteristics, topsoil nutrients and enzymatic activity. This suggests that fencing could be an effective method to recover degraded grasslands by improving the soil–plant system in this area. In the ecosystem of alpine grasslands, different indicators such as plant biomass, cover, SOC and TN increased with the length of grazing exclusion years, but soil C:N ratio was generally stable during the entire recovery process. However, the GE4 had greater enzymatic activity, plant richness and diversity than GE8. These indicators might be more sensitive to grazing exclusion than soil nutrients. Caution should be taken when assessing recovery of degraded alpine grassland based on enzymatic activity. A long-term fencing should be done cautiously in this fragile ecosystem. The present results also suggested that suitable age of fencing should be focused in the future study in Tibetan Plateau. Our study should, therefore, be helpful to offer a better understanding towards mechanisms of biogeochemical cycles of the ecosystem and offer a better guidance towards the degraded alpine grassland management practices in the near future. Acknowledgements The authors would like to acknowledge the financial support from the National Key Research and Development Program of China (2016YFC0501802), the International Cooperation Program of Qinghai Province of China (2019-HZ-807), the Key Research and Development Program of Sichuan Province of China (18ZDYF0318), and the Hundred Young Talents Program of the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (SDSQB-2016-02). References Alameda, D., Villar, R., Iriondo, J.M., 2012. Spatial pattern of soil compaction: Trees' footprint on soil physical properties. For. Ecol. Manage. 283, 128–137. Aldezabal, A., Moragues, L., Odriozola, I., Mijangos, I., 2015. Impact of grazing abandonment on plant and soil microbial communities in an Atlantic mountain grassland. Appl. Soil Ecol. 96, 251–260. An, S., Zhu, X., Shen, M., Wang, Y., Cao, R., Chen, X., Yang, W., Chen, J., Tang, Y., 2018.

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