Grasslandification has significant impacts on soil carbon, nitrogen and phosphorus of alpine wetlands on the Tibetan Plateau

Ecological Engineering 58 (2013) 170–179

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Grasslandification has significant impacts on soil carbon, nitrogen and phosphorus of alpine wetlands on the Tibetan Plateau Z.H. Shang a,b,∗ , Q.S. Feng c , G.L. Wu d , G.H. Ren e , R.J. Long a a International Centre for Tibetan Plateau Ecosystem Management, State Key Laboratory of Grassland Farming Systems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China b Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 10085, China c State Key Laboratory of Grassland Farming Systems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China d State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau of Northwest A&F University, Yangling 712100, China e International Centre for Tibetan Plateau Ecosystem Management, State Key Laboratory of Grassland Farming Systems, Lanzhou University, Lanzhou 730020 China

a r t i c l e

i n f o

Article history: Received 3 December 2012 Received in revised form 8 May 2013 Accepted 23 June 2013 Available online 27 July 2013 Keywords: Alpine wetland Grasslandification Carbon Nitrogen Phosphorus Restoration

a b s t r a c t Changes in land use will alter soil profiles of wetlands under climatic change and human disturbance, especially through grasslandification. Grasslandification is the process where a wetland is drained and converted to pasture. Grasslandificationon on the Tibetan plateau has been intensive over the last 40 years, mostly from drainage by humans. However, many previous studies have generally analysed only wetland ecological processes, despite the fact that grasslandificaiton, the biggest change process on the Tibetan plateau, has resulted from social and economic stresses. The assessment of changes to the soil C, N and P by grasslandification is the key to understanding the contribution to carbon management from alpine wetlands and variation of soil nutrition. We experimentally investigated the effect of grasslandification on soil physical (water, pH and EC) and chemical profiles (C, N and P) in grasslandification-pasture plots and reference wetland plots based on previous remote sensing results of the Maqu alpine wetland on the Tibetan plateau. The grasslandification process of alpine wetlands reduced vegetation quality and increased degree of drought, especially relevant with heavy grazing of the pasture. In general, grasslandification reduced the C, N and P content of soils and increased pH and EC, all significantly associated with variation to the vegetation and soil water. Soil C has changed more than N, P with grasslandification, but the soil C:N:P ratio has been relatively stable, and grasslandification has lead the wetland to the habitat with nitrogen limited. Thus, the grasslandification process of alpine wetlands on the Tibetan plateau over the last 40 years has increased net carbon emissions from alpine wetland soil contributions to atmospheric CO2 . The grasslandification of alpine wetland is a drying process and observed changes were mainly influenced by variations of soil water and nutrients. Maintaining vegetation and soil water is an important approach to mitigating soil degradation and carbon emissions from alpine wetlands. In consideration of the current social and economic status of the study site, it is difficult to return or restore the grasslandification area to the original wetland, so the better strategy is to protect the existing wetland and reduce the human disturbance. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Known as the ‘kidneys of the earth’ and ‘carbon sinking pool’, wetlands are ecosystems intermediate between terrestrial ecosystems and aquatic ecosystems (Whiting and Chanton, 2001; Xing et al., 2009). They have unique water, soil and vegetation characteristics and are a vital component of the carbon soil–atmosphere

∗ Corresponding author at: No. 768, Jiayuguan West Road, Lanzhou City, Gansu Province 730020, China. Tel.: +86 931 8914107; fax: +86 931 8914107. E-mail address: [email protected] (Z.H. Shang). 0925-8574/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecoleng.2013.06.035

exchange processes (Lloyd, 2006; Zhang et al., 2010; Page et al., 2011). In general, the losses of carbon, nitrogen and phosphorous from wetland systems by degradation or land-use changes have become an important environmental problem and greenhouse gas source, which has been a recent research focus (Keller et al., 2004; Ju et al., 2010; Yu and Ehrenfeld, 2009; Fan et al., 2010; Aumtong et al., 2009; Dunne et al., 2010; Chen et al., 2011; Song et al., 2011). The wetland system stores large amounts of carbon and is very sensitive to environmental change, such as drought, temperature variation, and land use change (Bedard-Haughn et al., 2006; Lloyd, 2006; Risch and Frank, 2007; Novak et al., 2008; Bai et al., 2010). Better understanding the changes that occur to soil during the

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transformation from wetland to grassland is important to better manage and conserve wetlands (Lloyd, 2006; Eaton et al., 2008). The term ‘grasslandification’ has been used to describe the process where desert communities are converted to grasslands (Van Devender et al., 1997; Miller et al., 1999; Baron, 2002). Here, we use the term ‘grasslandification’ to describe the process where an alpine wetland (with a dominance of sedges) is drained and converted to pasture with dominant plant of grasses. Hence, grasslandification has generally caused reduced water levels and vegetation change, which results in variations to the carbon storage capacity. For natural meadow ecosystems, water is more important for holding carbon in the soil than other factors such as nitrogen (Lu et al., 2011). Wetland soils are wetter, with greater amounts of organic matter and nutrient concentrations than surrounding pasture upland soils (Sigua et al., 2004; Dunne et al., 2010; Ewing et al., 2012). Grasslandification has increased global warming (Chen et al., 2011), especially in cold regions (Sigua et al., 2004; Ju et al., 2010; Song et al., 2011). During grasslandification complex environmental changes occur regarding temperature and water, while other disturbances such as grazing, fencing, ploughing and planting have different impacts on soil characteristics especially over different time scales (short and long) (Yang et al., 2009; Rui et al., 2011). Wetland soil-water dynamics change as a result of grasslandification and the effects on C, N and P cycling (Wang et al., 2008; Dunne et al., 2010) in soil depends on specific soil and vegetation properties (Knorr et al., 2008; Yu and Ehrenfeld, 2009; Aumtong et al., 2009; Chen et al., 2011), and soil layers (Don et al., 2011). The balance of C, N and P have been altered through changes to the vegetation caused by conversion of wetland to pasture resulting in the possible release of significant amounts of soil C (Yang et al., 2010). Chen et al. (2011) reported that, compared with wetlands, soil C, N and P of grasslands were significantly lower. Under drainage, more dissolved organic carbon was produced from wetland soil (Song et al., 2011), and the carbon content in soils had a positive effect on water holding (Olness and Archer, 2005). Bai et al. (2010) reported that drainage increased levels of C, N and P in the soil surface layer, but enabled more decomposition of organic C. The P release is very closely related to the retention of C and N when the soil dries from the conversion of wetland to grassland (Dunne et al., 2010). For forest vegetation, some report showed that vegetation changes can result in changes to soil N and P levels, but not C (Sartori et al., 2007). However, change to the vegetation community is the main reason for soil C variation in meadow systems (Whalen et al., 2003; Klump et al., 2007; Bagchi and Rithie, 2010; Wolkovich et al., 2010; Fan et al., 2010; Wang et al., 2011). In general, deep water areas have produced less above-ground vegetation than shallow water areas in alpine wetlands (Hirota et al., 2007). During grasslandification of alpine wetland systems the vegetation changes (Hirota et al., 2007; Xiang et al., 2009; Zhang et al., 2010) and the soil properties become more similar to those of the vegetation than of water. The alpine wetlands of the Tibetan plateau contain a large amount of soil organic carbon, estimated to comprise about 0.2% of the global pool of soil carbon (Wang et al., 2002; Hirota et al., 2005). Studies of these alpine wetlands have shown a continuous decrease in area over the last 50 years through climate change and more intensive human activity e.g. drainage of wetlands in the 1970s to convert areas to pasture for grazing (Zhang et al., 2011; Bai et al., 2013). As a result, the ecological services function has decreased significantly (Li et al., 2010). Alpine wetlands play an important function in the carbon balance in terrestrial ecosystems in China (Pei et al., 2009; Fan et al., 2008) and the status of alpine wetland ecosystems have been studied for a long time (Bai et al., 2005). However, grasslandification has caused the biggest change to the

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natural processes of the alpine meadows and the effects have not been clear until recently (Pei et al., 2009). Soil C, N and P are basic elements useful as indicators to understand the effects of wetland change. In this research we selected typical alpine wetland plots from our previous studies (Feng et al., 2008), which represent the process of grasslandification from wetland to grassland. We studied these in more detail to understand the ecological processes of grasslandification of alpine wetlands on the Tibetan plateau to recommend more sustainable management of wetland ecosystems. This paper has three objectives, (1) evaluating variations of soil C, N and P during the alpine wetland conversion to pasture; (2) identifying the effect of grasslandification on soil water and vegetation; and (3) understanding the impact of grasslandification on alpine wetlands on the Tibetan plateau. 2. Materials and methods 2.1. Study site description This study was conducted in the Maqu alpine wetland (part of Zoige) in the Maqu county of Gansu province located in the northeast corner of Qinghai on the Tibet plateau (101◦ 36 –103◦ 55 E, 32◦ 05 –34◦ 05 N). This is the largest elevated wetland (>3000 m) in the world (Fig. 1a) (Wu et al., 2010; Xiang et al., 2009). The area of Maqu County is 10,190 km2 (Fig. 1b–d) and the alpine wetland in Maqu County was about 14,080 ha in 2006 (Feng et al., 2008). The climate is characterised by two distinct seasons: winter (November–April) is cold and dry, with little precipitation and strong sunshine; and summer (May–October) is wet (Li et al., 2010). In recent years, the annual precipitation has averaged about 620 mm, mainly from July to September, daily air temperature has averaged about 1.2 ◦ C and annual cloud-free solar radiation about 2580 h. The study area was in an alpine meadow soil type (Wu et al., 2010). To evaluate the impact of climate change on grasslandification, we present basic climatic data (temperature and rainfall) over the last 50 years from the climate station at the Maqu alpine wetland (Figs. 2–4). The Maqu alpine wetland has shown the effects of climate change and artificial drainage during grasslandification of alpine wetlands over this time (Li et al., 2010; Xiang et al., 2009; Zhang et al., 2011; Bai et al., 2010). From previous remote sensing studies (Feng et al., 2008), typical grasslandification plots were selected from five study sites (Fig. 1b; referred to as A–E plots) where the wetland and grasslandification plots could be identified from the community structure, soil condition, and wetland area dynamics (Fig. 1c and d; Feng et al., 2008). At each of the five study sites a wetland plot (A0, B0, C0, D0 and E0) was selected as a pre-conversion reference of the wetland system, and another two plots (A1, A2; B1, B2; C1, C2; D1, D2; and E1, E2) were selected as grasslandification plots according to the soil water depth and decreasing proportion of alpine wetland species (e.g. Kobresia tibetica, Blysmus sinocompressus, Caltha palustris). In total, 15 plots were selected, with the basic background of all plots listed in Table 1. 2.2. Soil and vegetation sampling and measurements Each of the five plots had three subplots (20 m × 20 m) as replicates, with 20 soil cores taken at two depths (0–10 cm, 10–20 cm) respectively (Leifeld et al., 2005). Before sampling the soil cores, the above ground vegetation was removed. The soil cores were taken with a metal soil auger, inner diameter of 3.5 cm. All soil cores were taken back to the laboratory and stored below 4 ◦ C for further treatment (Sigua et al., 2004).

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Fig. 1. Location of the study sites and the Maqu alpine wetlands and their change in area. (a) Location of Maqu County and the Tibetan plateau in China. (b) Study sites in Maqu County. (c) Original Maqu alpine wetlands area and the area in 2000. (d) Maqu alpine wetlands area in 2006. (according to Feng et al., 2008).

The above ground vegetation condition was determined by use of quadrats. In each plot, in five quadrats (50 cm × 50 cm), species cover (%) was measured and the height (cm) of 50 random plants from each plant species was measured using a ruler. The location and altitude of each plot were recorded using a handheld GPS (Magellan eXplorist). All field sampling

was carried out in July, locally the peak season for plant growth. Soil analyses (total organic C, total N, P, and available N, P, soil water content, pH and electrical conductivity (EC) were conducted at the Centre for Soil and Forage Analysis, Lanzhou University. Soil water content (SWC) was determined gravimetrically (105 ◦ C,

Fig. 2. Average monthly temperatures (triangles; ◦ C) and precipitation (bars; mm) with standard error values at the study site taken over 42 years from 1968 to 2009. The lines Y(t) and Y(p) display the best fit models for temperature and precipitation respectively with their equations and statistical values.

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Fig. 3. Mean annual temperatures (◦ C) from 1968 to 2009, and mean temperatures (◦ C) for January and July at the study area, with trend lines.

24 h). Soil pH was measured with a potentiometer by a glass membrane electrode in 1:2.5 (w/v) soils to 0.01 M CaCl2 solution mixtures. Total organic content (TOC) was converted from soil organic matter by the Bemmelen index (0.58) (Van Bemmelen, 1890 cited in Pribyl, 2010). Briefly, 0.5 g soil samples were digested with 5 ml of 1 N K2 Cr2 O7 and 10 ml of concentrated H2 SO4 at 180 ◦ C for 5 min, followed by titration of the digests with standardised FeSO4 (ISSCAS, 1978; Miller RH and Keeney, 1982). Soil organic matter, total N (TN) and P (TP), available N (AN), P (AP) and EC were determined according to ISSCAS (1978). All measures were expressed as per g dry weight (dw) of soil.

2.3. Data analysis The soil characteristics reported were averages of the three subplot field replicates (n = 3), each with 20 soil cores. For each study site, soil factors were analysed using analysis of variance (ANOVA) and the grasslandification plots were compared to the reference wetland plots using Dunnett’s post hoc tests, using DPS statistical software and P < 0.05 and P < 0.01 significance levels (Tang and Feng, 1997). The vegetation was described using a parameter V, which was calculated from the formula V = H × Co, where H is the mean height of all species in a plot, and Co is vegetation cover. The C:N, and C:N:P ratios were calculated using TOC, TN and TP.

Fig. 4. Mean annual precipitation (mm) from 1968 to 2009, and mean precipitation (mm) for January and July at the study area.

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Table 1 Background details for all plots at the five study sites (A–E). The reference wetland plots were: A0; B0; C0; D0; E0 and the remainder were grasslandification plots. Study sites

Plots

Altitude (m)

Longitude and latitude

Description

A

A0 A1 A2

3506.75 3501.70 3506.27

101.6733 E, 33.7841 N 101.7149 E, 33.7657 N 101.7149 E, 33.7660 N

Wetland with shallow water in all years Wetland with seasonal water Meadow community

B

B0 B1 B2

3523.81 3521.41 3520.93

102.0179 E, 33.9493 N 102.0182 E, 33.9507 N 101.6735 E, 33.7841 N

Wetland with season water cover Drying wetland with lot of wetland species Alpine meadow

C

C0 C1 C2

3510.11 3511.55 3511.55

101.7662 E, 33.7716 N 101.7144 E, 33.7671 N 101.7144 E, 33.7671 N

Wetland with short-term seasonal water cover Drying wetland Alpine meadow

D

D0 D1 D2

3434.41 3433.45 3435.13

101.7665 E, 33.7715 N 102.0806 E, 33.6698 N 101.7674 E, 33.7734 N

Peatland with low vegetation cover Drying wetland Alpine meadow

E

E0 E1 E2

3448.83 3433.45 3438.00

102.1621 E, 33.7169 N 102.1573 E, 33.7210 N 102.1601 E, 33.7199 N

Wetland with seasonal water cover Alpine meadow Degraded meadow

Pearson correlation coefficients were determined to assess the relationships between vegetation (H, Co and V) and soil characteristics (SWC, pH, EC, TOC, TN, TP, AN and AP). Multivariate analysis was implemented using the CANOCA 4.5 (and CanoDraw) package (ter Braak, 2002; Box et al., 2011) to illustrate the correlation between soil environmental factors and vegetation plots. Soil factors of SWC, pH, EC, TOC, TN, AN, TP, AP were used in Canonical Correspondence Analysis (CCA programme). Vegetation factors, height (H), cover (Co) and quality (V), were used in the CCA programme. In bioplots of the CCA analysis, soil environmental factors of SWC, pH, EC and other factors are displayed by lines with arrows where the length of each line indicates the relationship between soil environmental variables and vegetation profiles (Fig. 5), study sites (Fig. 6). Correlations between the soil environmental factors and each ordination axes were characterised by the quadrant in which each arrow occurred. The angles between the lines and axes indicate the degree of correlation, with small angles indicating higher significance of co-relationship (Cui et al., 2009). Climatic data from 1968 to 2009 are presented as supplementary data to help explain the effects of climate change on the wetlands.

Fig. 5. Bioplots of vegetation profiles and soil environmental variables by CCA analysis. Hollow triangles and labels represent the vegetation characteristics of Co (vegetation cover), H (vegetation height) and V (vegetation quality i.e.f Co × H). SWC1, SWC2, pH1, pH2, EC1, EC2, TOC1, TOC2, TN1, TN2, AN1, AN2, TP1, TP2 represent soil values (SWC, pH, EC, TOC, TN, AN, TP) at two soil layers of 0–10 cm and 10–20 cm, respectively.

3. Results Temperature and precipitation display the same monthly dynamics in any 1 year, with highest recordings between July to September every year (Fig. 2). Average temperature has increased significantly over the last 40 years (P < 0.01), especially over the last 10 years (Fig. 3). The average monthly temperatures have increased for January, the coldest month, and July, the hottest month. Average annual precipitation over the last 40 years was not different, but large annual variations were observed. There were two periods of high precipitation, during the 1970s and 2005 (Fig. 4). Average precipitation for July (highest rainfall month) has increased little over the last 40 years, with no change in January, the lowest precipitation month (Fig. 4).

Fig. 6. Bioplots of study sites and soil environmental variables by CCA analysis. Hollow circles and labels (A1-E2) represent sampling sites. WC1, SWC2, pH1, pH2, EC1, EC2, TOC1, TOC2, TN1, TN2, AN1, AN2, TP1, TP2 represent soil values (SWC, pH, EC, TOC, TN, AN, TP) at two soil layers of 0–10 cm and 10–20 cm, respectively.

Table 2 Soil characteristics (mean and SE) at all plots, A0-E2.V represents vegetation, L1 and L2 the soil layers (0–10 cm) and (10–20 cm), soil water content (SWC), soil pH (pH), total organic content (TOC), total nitrogen (TN), available N (AN), total phosphorus (TP) and available P (AP). Plots

V

SWC (%) L1

A0 A1

B0 B1 B2 C0 C1 C2 D0 D1 D2 E0 E1 E2 * **

77.43 (3.85) 63.18** (0.97) 46.87** (1.41) 103.31 (6.11) 83.63* (2.20) 77.41** (2.56) 68.43 (1.55) 36.23** (1.60) 19.29** (0.05) 49.93 (6.43) 36.56 (4.82) 17.61** (0.39) 93.96 (4.84) 30.95** (0.93) 18.80** (0.08)

61.83 (3.35) 39.92** (0.68) 34.04** (0.80) 113.12 (5.51) 80.28** (1.49) 79.35** (1.71) 39.03 (0.66) 33.63** (1.25) 23.14** (0.22) 40.22 (0.72) 37.98 (1.09) 16.45** (0.16) 81.45 (4.56) 24.06** (1.15) 16.53** (0.15)

L1 5.65 (0.02) 5.61 (0.09) 5.34** (0.03) 5.18 (0.01) 6.26** (0.08) 5.97** (0.08) 6.89 (0.05) 7.35** (0.01) 7.97** (0.06) 7.91 (0.01) 6.44** (0.16) 6.21** (0.04) 5.65 (0.05) 6.55** (0.00) 6.48** (0.09)

EC L2

L1

5.69 0.34 (0.07) (0.01) 5.65 0.30 (0.03) (0.03) 5.69 0.38 (0.02) (0.03) 5.57 0.24 (0.04) (0.01) 6.05 0.37** (0.17) (0.02) 5.93 0.11** (0.11) (0.01) 7.72 0.30 (0.03) (0.02) 7.88** 0.44** (0.05) (0.02) 8.25** 0.25* (0.01) (0.01) 8.04 0.56 (0.02) (0.01) 6.54** 0.49 (0.12) (0.12) ** 6.11 0.20** (0.04) (0.03) 5.57 0.35 (0.03) (0.04) 6.58** 0.36 (0.01) (0.01) 7.54** 0.23** (0.07) (0.00)

TOC (%) L2 0.20 (0.01) 0.17 (0.02) 0.13** (0.01) 0.18 (0.01) 0.29** (0.01) 0.21 (0.02) 0.31 (0.00) 0.33 (0.01) 0.26* (0.03) 0.35 (0.01) 0.29 (0.04) 0.17** (0.01) 0.18 (0.01) 0.18 (0.01) 0.26** (0.01)

L1 17.39 (0.81) 8.26** (0.22) 13.53** (0.66) 25.53 (1.24) 19.98** (0.72) 19.44** (0.19) 14.79 (0.54) 7.46** (0.33) 1.89** (0.21) 6.56 (0.08) 8.19 (1.21) 3.56* (0.19) 19.91 (0.78) 7.49** (0.11) 5.29** (0.28)

TN (%) L2 **

9.05 (0.69) 5.89** (0.19) 6.34 (0.16) 18.06 (0.16) 18.94 (3.88) 15.57 (1.34) 5.56 (0.20) 4.83* (0.24) 0.96** (0.09) 6.63 (0.14) 7.05 (0.70) 3.24** (0.26) 17.11 (0.10) 4.69** (0.14) 3.13** (0.07)

TP (%)

AN (mg kg-1))

AP (mg kg-1)

L1

L2

L1

L2

L1

L2

L1

L2

1.26 (0.03) 0.68** (0.03) 1.12* (0.06) 1.99 (0.05) 1.64** (0.04) 1.16** (0.06) 1.13 (0.06) 0.70** (0.02) 0.15** (0.02) 0.64 (0.00) 0.74 (0.13) 0.32* (0.00) 1.40 (0.13) 0.61** (0.01) 0.49** (0.02)

0.68 (0.07) 0.48** (0.02) 0.46** (0.02) 1.43 (0.04) 1.18 (0.05) 1.05* (0.08) 0.46 (0.02) 0.44 (0.01) 0.07** (0.01) 0.59 (0.00) 0.61 (0.06) 0.31** (0.02) 1.08 (0.05) 0.33** (0.03) 0.32** (0.01)

0.21 (0.02) 0.14* (0.02) 0.20 (0.01) 0.16 (0.00) 0.15 (0.02) 0.16 (0.00) 0.13 (0.00) 0.11** (0.00) 0.06** (0.00) 0.09 (0.00) 0.08 (0.01) 0.07 (0.00) 0.26 (0.01) 0.10** (0.00) 0.08** (0.00)

0.23 (0.03) 0.10** (0.02) 0.14* (0.00) 0.12 (0.01) 0.29 (0.15) 0.17 (0.00) 0.10 (0.00) 0.09** (0.00) 0.06** (0.00) 0.08 (0.00) 0.08 (0.00) 0.06** (0.00) 0.23 (0.00) 0.08** (0.00) 0.08** (0.00)

437.68 (2.49) 285.57** (19.52) 418.30 (21.65) 473.55 (57.41) 462.07 (35.96) 324.17* (14.71) 366.64 (12.69) 228.02** (12.20) 63.86** (7.16) 189.42 (2.87) 276.48 (45.75) 151.15 (6.37) 390.51 (10.45) 205.68** (2.71) 189.85** (6.88)

260.45 (21.30) 174.64** (2.38) 175.07** (8.20) 342.97 (30.14) 349.57 (13.21) 354.45 (21.94) 153.11 (6.41) 161.44 (4.29) 40.18** (3.89) 162.63 (3.95) 217.35 (34.07) 129.15 (1.66) 265.00 (49.69) 119.01** (11.23) 125.42** (2.67)

19.14 (4.78) 7.29* (0.87) 25.46 (1.56) 16.21 (0.06) 21.09* (1.45) 10.31** (0.49) 17.42 (3.81) 16.38 (2.25) 6.46* (0.21) 14.41 (1.76) 6.24** (1.30) 9.76* (0.82) 23.04 (2.58) 17.34 (0.31) 5.39** (0.60)

10.72 (3.64) 4.56 (0.29) 16.72 (1.62) 15.66 (0.44) 14.53 (1.27) 11.48* (0.34) 11.63 (3.20) 9.59 (2.27) 5.53 (0.09) 11.17 (0.66) 4.49* (1.00) 8.63 (0.77) 12.04 (0.38) 12.48 (1.68) 4.78** (1.04)

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A2

10.80 (0.58) 5.95** (0.98) 4.05** (0.02) 27.55 (2.91) 12.60** (1.61) 4.20** (0.82) 2.86 (0.19) 2.45 (0.18) 1.70** (0.26) 3.25 (0.58) 4.24 (0.19) 5.53 (1.49) 19.50 (2.32) 3.60** (0.03) 1.75** (0.24)

Ph L2

p < 0.05 level. p < 0.01 level.

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Table 3 The C:N and C:N:P ratios of soil profiles at all plots. Plots

First soil layer (0–10 cm)

Second soil layer (10–20 cm)

C:N

C:N:P

C:N

C:N:P

A0 A1 A2 B0 B1 B2 C0 C1 C2 D0 D1 D2 E0 E1 E2

13.81:1 12.12:1 12.08:1 12.84:1 12.18:1 16.69:1 13.07:1 10.67:1 12.95:1 10.19:1 11.03:1 10.98:1 14.24:1 12.36:1 10.73:1

82.66:5.98:1 57.91:4.78:1 67.36:5.58:1 158.59:12.35:1 132.09:10.84:1 123.33:7.39:1 115.58:8.85:1 65.96:6.18:1 29.64:2.29:1 77.10:7.57:1 97.17:8.81:1 53.27:4.85:1 77.27:5.42:1 76.89:6.22:1 62.92:8.87:1

13.22:1 12.14:1 13.88:1 12.66:1 15.99:1 14.86:1 12.12:1 10.90:1 13.63:1 11.20:1 11.50:1 10.56:1 15.78:1 14.28:1 9.75:1

40.04:3.03:1 60.48:4.98:1 46.01:3.32:1 148.83:11.76:1 64.77:4.05:1 93.76:6.31:1 57.49:4.74:1 54.59:5.01:1 16.96:1.24:1 80.65:7.20:1 90.87:7.90:1 51.49:4.88:1 74.47:4.72:1 60.25:4.22:1 38.48:3.95:1

At five study sites, except the D sites (D0, D1 and D2), the vegetation characteristics (V) have been significantly reduced by grasslandification (Table 2). Soil water content (SWC) was reduced by grasslandification at all sites compared with their reference plots, especially significant at A2, B2, C2, D2 and E2 (P < 0.01). For pH and EC levels, changes with grasslandification were inconclusive, some sites increased and some decreased. Compared with the reference plots, grasslandification of alpine wetland has resulted in a decline of the soil water and nutrition processes. With grasslandification, at all sites except A sites, TOC, TN and AN decreased significantly, and at all sites except B sites, TP decreased significantly. AP decreased significantly at C, D and E sites, but not at A and B (Table 2). Changes in the second soil layer were similar to those of the first soil layer, but smaller. Over all levels of C, N and P decreased with grasslandification at our sites and when SWC was under 30%, the C, N and P reductions were significant (P < 0.01) (Table 2). At A, C and E sites grasslandification reduced the C:N ratio in the top soil layer, and in the second soil layer the C:N values increased at A–D sites and decreased at E sites (Table 3). All C:P values decreased with grasslandification at all sites. The N:P values decreased with grasslandification at all sites except for E sites. All stoichiometric values of C, N and P in the lower layer were lower than the first soil layers (Table 3). In general, the grasslandification of wetlands reduced soil C more than N and P. The change in vegetation had a positive effect on SWC, TOC, TN, TP, AN and AP and a negative effect on pH and EC (Table 4). Soil water (SWC) had a negative effect on pH and EC, and a positive effect on other soil characteristics. Soil C, N and P increased with vegetation and soil water content. pH had a negative relation with all C, N, P, and EC had a negative relation with TOC and TP of all T, N and P (Table 4). In the Canonical correspondence analysis (CCA) (Figs. 5, 6), the vertical axis shows soil pH, salinity and AP, while the horizontal axis shows SWC, C and N. The vegetation change during the grasslandification of wetlands was mainly influenced by soil water, carbon, and nitrogen, with. The change in soil water caused the largest variation to vegetation and soil nutrients. Plots A0, B0, B1 and E0 had higher soil water, C, N and P content (Table 2) than the others and were grouped together (Fig. 6) having a profile of wetland plots. Plots B2, C2, D0 and E2 had higher pH, and close relationship with EC, (Table 2) and formed a group under CCA analysis (Fig. 6) with characteristics of degraded grassland. Lots of plots such as C0, A2, D2, A1, C1, D1 and E1 have significant characteristics transitional between wetlands and pastures, and these formed a final group (Fig. 6). All plots could be divided into three groups: wetland plots;

transitional plots and pasture plots (Fig. 6) indicating that grasslandification of alpine wetlands is a degrading process of the wetlands as measured by the soil profile trends in the study plots (Table 2; Fig. 6)

4. Discussion Results from our study showed that grasslandification of wetlands significantly affected soil water, pH, EC and soil C, N and P. Compared to the reference plots at every study site, wetland grasslandification exhibited decreases in vegetation, soil C, N and P, an increase in pH and some increase of EC. It appears that soils with greater C levels have higher EC and pH (Ewing et al., 2012). The more decomposition of C in soil may help to produce higher EC and pH, contrary with the findings of Grybos et al. (2009). However, similar soil and vegetation results to our study were displayed in American wetlands when converted to beef cattle pasture (Sigua et al., 2004, 2009). Although there were some increases in C, N and P during grasslandification (e.g. A1 and A2, D0–D1), the overall trend was a decrease in C, N and P under grasslandification. Normally, drying of wetlands results in a reduction of soil nutrients (Xiao et al., 2012), and the grasslandification of our survey plots represented a drying process (Table 2; Fig. 6). Our data confirm that the drying involved in the conversion of wetland to pasture influences soil physical properties of pH and EC. Most of the grasslandification plots had higher pH and EC than the wetland reference plots (Tables 2 and 4) and for the B, C and Esites, soil pH was statistically significantly higher. The change in pH and EC displayed the same trend during the grasslandification process, our results being partly consistent with those obtained by Sigua et al. (2004) and Reiners et al. (1994), who showed the grasslandification plots were higher pH with lower EC values. However, in our study sites, some meadow plots had lower pH (e.g. A1, A2, D1 and D2), but higher EC (A2, B1, C1 and E1) levels (Table 2). The reason may be that the background and history are very different at all our study sites. Wetland soils are characterised by a slow turnover of organic material (Fisher and Reddy, 2001), especially in the cold climate of the Tibetan plateau (Hirota et al., 2005). Associated with the soil physical profile, water is the key factor in determining species composition, structure and biomass of natural vegetation (Clair et al., 2009; Lu et al., 2011). Converted the vegetation condition of meadow promote soil water fluctuations that may, in turn, stimulate decomposition and mineralisation of C (Sigua et al., 2004, 2009). One notable change during grasslandification was a dramatic reduction of TOC, TN and TP caused by a decline in soil water and vegetation, especially during drying of wetlands. When soil water (%) is reduced to less than 30%, soil carbon and nitrogen decrease by more than 50%. Yang et al. (2009, 2010) also emphasised the importance of soil water for carbon dynamics on the Tibetan plateau. Maintaining vegetation and soil water is of considerable importance in mitigating C emission resulting from the grasslandification of wetlands. Lower SWC and TN in the meadow plots may be associated with nutrient cycling and plant and animal consumption of P and N (Sigua et al., 2004; 2009). Plants use P and N for energy transfer and reproduction. In some meadow plots with higher vegetation cover and higher soil C, N and P levels, it has been recognised in our study, that some plots with higher vegetation cover and biomass have more C, N and P (e.g. D1, D2) under the general trend of grasslandification process (Table 2). All meadow plots in our study were grazed. During foraging animals consume P and N, therefore plots with low vegetation levels have low soil N and P storage. P and N is used for animal growth, and returned to the soil as manure and

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177

Table 4 Pearson correlation coefficients for vegetation characteristics and soil environmental factors. Pearson coefficients Co V SWC pH EC TOC TN TP AN AP

H *

0.51 0.99** 0.85** −0.58* −0.22 0.81** 0.84** 0.58* 0.70** 0.42

Co

V

SWC

pH

EC

TOC

TN

TP

AN

1.00 0.59* 0.47 −0.74** −0.20 0.51* 0.53* 0.54* 0.60* 0.58*

1.00 0.83** −0.61* −0.24 0.80** 0.83** 0.59* 0.70** 0.45

1.00 −0.57* −0.16 0.97** 0.96** 0.76** 0.90** 0.53*

1.00 0.56* −0.63** −0.61* −0.64** −0.71** −0.37

1.00 −0.20 −0.11 −0.15 −0.1300 0.06

1.00 0.98** 0.81** 0.95** 0.60*

1.00 0.76** 0.95** 0.61*

1.00 0.83** 0.67**

1.00 0.61*

Co, H and V represent the vegetation characteristics of cover, height and quality (Co × H). * p < 0.05 level. ** p < 0.01 level.

urine, but most manure is collected by local resident for fuel, and most of the time livestock are kept in sheds (Xiang et al., 2009). As a result N and P will be removed from the system and levels will gradually decline from the grasslandification process on the Tibetan plateau. Following grasslandification the pastures were grazed and often the study sites were over-grazed (Wu et al., 2009; Xiang et al., 2009). The removal of aboveground biomass by grazing directly decreases the litter input, but in pastures lightly grazed, C storage in soil surface layers can increase (Rui et al., 2011). So, if plant biomass inputs in pasture plots were high, the soil C will increase compared with wetland plots (e.g. D0–D1). Both aboveground and belowground biomass varied temporally within and among the vegetation zones of alpine wetlands (Hirota et al., 2007). Therefore, good vegetation is a key to maintaining SOC in natural ecosystems (Klump et al., 2007; Don et al., 2011). However, most wetland drying results in release of SOC from the soil (Sigua et al., 2004; Page et al., 2011). Previous evaluations of the effects of wetland drying on soil showed reduced carbon in alpine wetlands (Xiang et al., 2009; Chen et al., 2011; Zhang et al., 2011). However, Bai et al. (2010) found higher C, N and P levels in drained wetland plots, and even with the reduction in soil water there was no significant positive effect on carbon. Our results from stoichiometric analysis of C, N and P showed that C changed more than N, P with grasslandification. Perhaps a reason was that livestock grazing can modify the balance of N and P to a minor extent during grasslandification (Rui et al., 2011; Sigua et al., 2009). In contrast to soil C and N the soil C:N:P ratio in alpine grasslands remained relatively stable during grasslandification, but the lower soil layer had higher N and P proportions than the top layer (Table 3). All soil N:P ratios in the study site were less than 14 at all sites. According to the results of Koerselman and Meuleman (1996), soils were N limiting types, even very N limiting in our study. Sometimes, increasing N and P inputs into soil by livestock grazing activities can reduce the corresponding soil C:N ratio by increasing N and P re-cycling (Gelsomino et al., 2006).Although the manure of local livestock on pasture is collected from the pasture and livestock are held in sheds after day-time grazing, some N and P will be returned though animal grazing activity during the day. However, soil C was reduced significantly by the drying process, so that the C:N and C:P ratios of soil were reduced by grasslandification of wetland (Table 3). Based on the CCA results, vegetation change was mainly influenced by soil water and nutrition and plots could be divided three groups: wetland plots; transitional plots; and pasture plots (Figs. 5 and 6). In bioplots of CCA analysis, soil factors such as water, pH, EC, and others nutrition are presented by lines with the arrow. Length of each line indicates the relationship between soil factors and vegetation profiles, or between factors and plots

(Cui et al., 2009; Andrew et al., 2012). Characteristics of correlations between soil factors and each ordination axes were indicated by quadrants where each arrow was placed (Cui et al., 2009; Box et al., 2011). Meanwhile, results could be identified by variation of soil profiles (Table 2) and from Pearson correlation coefficients (Table 4). More accurate evaluations of grasslandification should be attempted through more quantitative studies of plot vegetation and soils because some of the plots were seasonal wetland sites with those pasture characteristics. In the last 40 years much of the alpine wetlands of the Tibetan plateau have been converted to pasture, with some even becoming desert (Xiang et al., 2009; Zhang et al., 2011). The average annual conversion rate being 0.72% (Bai et al., 2013). This has resulted in a huge carbon emission during the change of wetland. Because land use change always leads to carbon change (Contant et al., 2001; Ewing et al., 2012), the basic management rule for natural ecosystems is that we should minimise change to the original land use as much as possible. Grasslandification of alpine wetlands produces not only carbon losses, but also huge losses to terrestrial ecological service (Zhang et al., 2010). Although engineering can restore the pastures to wetlands (Sigua et al., 2009), it would be difficult to achieve the restoration due to the social and economic stresses at our study site (Li et al., 2010). The engineering required would prove difficult (Lloyd, 2006) especially in the very cold and high environments of the Tibetan plateau. Therefore, instead of using engineering to restore wetlands on the Tibetan plateau, the priority is protection of the existing wetland. 5. Conclusions Overall, our results show that, associated with decreasing vegetation and soil water content, there is a general trend of decreasing C, N and P during the grasslandification process compared with the reference wetland plots on the Tibetan plateau. Thus, the grasslandification process on the Tibetan plateau over last 40 years has resulted in increased atmospheric CO2 contributions. Changes in C, N and P during grasslandification were sensitive to change in the two important characteristics of vegetation and soil water. The current social and economic status of the areas exacerbates the difficulties in restoring the converted grassland areas to their original wetlands. Thus we suggest that a better strategy is to protect the existing wetlands, and reduce and better manage the grazing disturbance of converted grassland areas. Acknowledgments This research was supported by the National Natural Science Foundation of China (No. 41171417), and the project of ‘UNDP/GEF Wetland Biodiversity Conservation and Sustainable Use in China

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