Translator Disclaimer
4 September 2020 Effect of Long-Term Experimental Warming on the Nutritional Quality of Alpine Meadows in the Northern Tibet
Sun Wei, Li Shaowei, Zhang Yangjian, Fu Gang
Author Affiliations +
Abstract

The nutritional quality of grasslands is closely related to recruitment of young and population dynamics of livestock and wild herbivores. However, the response of nutritional quality to climate warming has not been fully understood in the alpine meadow on the Tibetan Plateau, especially in the Northern Tibet. Here, we investigated the effect of experimental warming (beginning in 2008) on nutritional quality in three alpine meadows (site A: 4313 m, B: 4513 m and C: 4693 m) in the Northern Tibet. Crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC) were examined in 2018–2019. Experimental warming only increased the content of CP by 27.25%, ADF by 89.93% and NDF by 41.20%, but it decreased the content of Ash by 57.76% in 2019 at site B. The contents of CP and WSC both increased with soil moisture (SM). The content of CP decreased with vapor pressure deficit (VPD). The combined effect of SM and VPD was greater than air temperature (Ta) in controlling the variations of the CP content, ADF content and nutritional quality. Compared to Ta, VPD explained more of the variation in NDF and Ash content. All of these findings suggest that warming effects on nutritional quality may vary with site and year, and water availability may have a stronger effect on the nutritional quality than temperature in the alpine meadow of the Northern Tibet.

1 Introduction

With the intensification of various human activities, the earth's surface is continuing to undergo a series of changes (e.g. climate change and desertification) (Arft et al., 1999; Lu et al., 2011; Dumont et al., 2015). Research shows that as one of the most significant features of global change, warming strongly affects ecosystem biodiversity, structure, function, and carbon and nutrient cycles at various spatial and temporal scales (Rustad et al., 2001; Klein et al., 2004; Yu et al., 2019a). Nutritional quality of herbage is an important indicator of the status of grassland health and degradation (Birnie-Gauvin et al., 2017; Baranova et al., 2019). Changes in nutritional quality of herbage can directly affect recruitment of young, growth and population dynamics of herbivorous livestock (e.g. yak and sheep) and wild herbivores (e.g. Equus kiang and Pantholops hodgsoni), and so these changes can indirectly affect the reproduction, growth and maintenance of consumers at higher trophic levels (e.g. humans) (Birnie-Gauvin et al., 2017; Augustine et al., 2018). Low nutritional quality of herbage can lead to higher mortality, lower pregnancy rates and fewer offspring for livestock and wild herbivores, and also higher predation risks from wild animals at higher trophic levels (Proffitt et al., 2016). Therefore, understanding the response of nutritional quality of grasslands to climatic warming is very important for predicting future changes in the ecosystem services provided by those grasslands and the protection of wild herbivores.

The Tibetan Plateau, as one of the world's most sensitive regions, continues to attract extensive attention from domestic and overseas scientists (Klein et al., 2008; Zhang et al., 2015a). More than 300 publications on the response of alpine ecosystems (e.g. alpine meadows, alpine steppes and forests) to experimental warming on the Tibetan Plateau have been produced. However, only a few of them have examined the effects of experimental warming on the nutritional quality in alpine grasslands on the Tibetan Plateau (Li and Liu, 2017; Li et al., 2018; Xu et al., 2018). Moreover, these previous studies related to the response of nutritional quality in alpine grasslands to experimental warming were conducted during only one growing season, although the effect of experimental warming on nutritional quality can vary among years (Augustine et al., 2018). Therefore, the response of nutritional quality to climate warming in alpine grasslands on the Tibetan Plateau remains unclear.

As an important region of the National Ecological Safety Construction, the Northern Tibet is mainly occupied by alpine grasslands, which are crucial components of global alpine ecosystems (Piao et al., 2006; Dorji et al., 2013). The surface temperature of the Northern Tibet has increased by approximately 0.45 °C from 2001 to 2015 (Sun et al., 2019), and will continue warming (Diffenbaugh and Field, 2013). Several studies conducted in the Damxung County (Fu et al., 2019; Yu et al., 2019b), the Xainza County (Lu et al., 2013; Ma et al., 2017), the Baingoin County (Ganjurjav et al., 2016; Zhang et al., 2019) and the Nagqu City (Cui et al., 2017; Wu et al., 2020) have investigated the responses of localized alpine grasslands to climate warming under controlled warming conditions in the Northern Tibet. However, to our best knowledge, no studies have examined the response of nutritional quality to warming in the alpine grasslands of the Northern Tibet. Therefore, here we report the effect of experimental warming on nutritional quality in the alpine meadow in the Northern Tibet to better understand how climate warming will affect it in the future.

2 Materials and methods

2.1 Study area and experimental design

Three sites (site A: 30°30′N, 91°04′E, 4313 m; site B: 30°31′N, 91°04′E, 4513 m; site C: 30°32′ N, 91°03′E, 4693 m), are located in the Damxung County, were set up in July 2008 (Fu and Shen, 2017). Comparing precipitation and temperature data for 1963–2019, 2018 was a warm and wet year, and 2019 was a warm and dry year (Table 1). The HOBO stations were used to monitor soil temperature (Ts), soil moisture (SM), air temperature (Ta) and relative humidity (RH). Vapor pressure deficit (VPD): VPD=0.6108 exp fi01_516.gif was derived from Ta and RH (Fu and Shen, 2017). The environmental temperature decreases, while the environmental moisture increases, from site A to site C (Fu and Shen, 2017). The four treatments included control, warming, clipping and warming + clipping at each meadow site. Each treatment had three replicates. The warming and warming + clipping treatments were warmed by open top chambers (OTCs). Only the clipping and warming + clipping treatments were used in this study. The clipping and warming + clipping treatments had the vegetation clipped at a height of 0.01 m above the ground three times (in June, July and September) in each growing season beginning in 2009. The clipped aboveground biomass was weighed after being oven-dried (65 °C for 48 h). The clipped aboveground biomass of the three sampling times were mixed into a single sample for each plot in 2018 and 2019. Then these mixed samples were then used for analysis of several nutritional components at the whole community level, including crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC).

Table 1

Annual mean temperature (AT) and precipitation (AP), and growing season (June–September) temperature (GST) and precipitation (GSP) in 1963–2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China

img-z2-11_516.gif

2.2 Nutritional content analyses

The Kjeldahl method was used to obtain total nitrogen, which was multiplied by 6.25 to determine CP (Lithourgidis et al., 2006). The Van Soest method was used to determine ADF and NDF (Van Soest et al., 1991). The complete combustion method, Soxhlet extraction method and anthrone-based method were used to determine Ash, EE (Cui et al., 2016) and WSC (Yemm and Willis, 1954), respectively.

2.3 Statistical analyses

A repeated analysis of variance (ANOVA) was used to determine the main and interactive effects of experimental warming and measurement year on Ts, SM, Ta, VPD, CP, ADF, NDF, Ash, EE and WSC for each site. A t-test was used to examine the differences in Ts, SM, Ta, VPD, CP, ADF, NDF, Ash, EE and WSC between non-warming and warming treatments. The permutational multivariate analysis of variance and nonmetric multi-dimensional scaling (NMDS) were used to investigate the nutritional quality, which was determined by the matrix of CP, ADF, NDF, Ash, EE and WSC. Correlation analyses were used to examine the correlations between nutritional content parameters (i.e. CP, ADF, NDF, Ash, EE and WSC) and environmental variables (i.e. Ts, SM, Ta and VPD). When the correlations were statistically significant, univariate regression analyses were then used to examine the relationships between those correlated nutritional content and environmental variables. That is, only the significant relationships between the nutritional content and environmental variables were illustrated. Variation partitioning analyses (vegan) were used to examine the shared and exclusive effects of Ts, SM, Ta and VPD on the content of CP, ADF, NDF, Ash, EE and WSC, and the overall nutritional quality. Repeated ANOVA, t-test and univariate regression analyses were performed by SPSS 16.0. The permutational multivariate analysis of variance, NMDS(labdsv package)( https://cran.r-project.org/web/packages/labdsv/index.html) and variation partitioning analyses were performed using R 3.6.1.

Table 2

Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (Ts), soil moisture (SM), air temperature (Ta) and vapor pressure deficit (VPD)

img-z3-6_516.gif

3 Results

3.1 Environmental variables

The main and interactive effects of experimental warming and measurement year on Ts, SM, Ta and VPD are shown in Table 2. The main effect of experimental warming was the significant alteration of Ts at sites A, B and C, VPD at sites B and C, and Ta at site C. The main effect of year was the significant alteration of Ts at site A, VPD at sites B and C, and SM at site C. There was a significant interactive effect of experimental warming and year on VPD at site C. The effects of experimental warming on Ts, SM, Ta and VPD are illustrated in Fig. 1. Experimental warming significantly increased Ts by 1.26 °C in 2018 and by 1.31 °C in 2019 at site A, by 1.34 °C in 2019 at site B and by 1.50 °C in 2019 at site C. Experimental warming significantly increased Ta by 1.42 °C at site B and by 1.22 °C at site C in 2018; and it increased VPD by 0.16 kPa in 2019 at site B, and by 0.05 kPa in 2018 and 0.14 kPa in 2019 at site C.

3.2 Nutritional content and nutritional quality

The main and interactive effects of experimental warming and measurement year on the content of CP, ADF, NDF, Ash, EE and WSC are shown in Table 3. The main effect of experimental warming only significantly changed the content of CP, NDF and Ash at site B. The main effect of measuring year showed significant alterations in the content of CP and NDF at all the three sites, WSC at site B, and ADF at site C. The interactive effect of experimental warming and measurement year only had a significant influence on the content of WSC at site B.

The effects of experimental warming on the content of CP, ADF, NDF, Ash, EE and WSC are illustrated in Fig. 2. Experimental warming increased the content of CP by 27.25%, ADF by 89.93% and NDF by 41.20%, but significantly reduced the content of Ash by 57.76% in 2019 at site B. Regardless of experimental warming, at sites A, B and C the contents of CP and NDF in 2019 were lower than those in 2018 by 37.62%, 25.25% and 24.01%, and by 34.62%, 23.98% and 25.48%, respectively. The content of ADF in 2019 was 50.20% lower than that in 2018 at site C. The content of WSC in 2019 was 32.75% greater than that in 2018 at site B.

Experimental warming and measurement year had significant effects on the nutritional quality (Table 4). The stress of the NMDS was 0.10, indicating that the NMDS was acceptable (Fig. 3). The nutritional quality levels between the non-warming and warming treatments in 2019 at site B were separated by the first axis of the NMDS (i.e. NMDS1) (P=0.010). The nutritional quality levels between 2018 and 2019 under warming conditions at site A were separated by the NMDS1 axis (P=0.004). The nutritional quality levels between 2018 and 2019 under non-warming (P=0.031) and warming conditions (P=0.027) were separated by the second axis of the NMDS (i.e. NMDS2) at site B.

Fig. 1

Comparisons of (a) soil temperature (Ts), (b) soil moisture (SM), (c) air temperature (Ta) and (d) vapor pressure deficit (VPD) between non-warming and warming treatments at sites A, B and C in 2018 and 2019

Note: * indicates P<0.05.

img-z4-1_516.jpg

Table 3

Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

img-z4-5_516.gif

3.3 Relationships between nutritional content and environmental variables

The contents of both CP and WSC increased with SM (Fig. 4). The content of CP decreased with VPD (Fig. 4). The SM, Ta and VPD independently explained 10%, 18% and 29% of the variation of the CP content, respectively (Fig. 5a). The SM and VPD co-explained 23% of the variation of the CP content, whereas the SM, Ta and VPD co-explained 10% of the variation of the CP content (Fig. 5a). The SM, Ta and VPD independently explained 21%, 47% and 11% of the variation of the ADF content, respectively, whereas the SM and VPD co-explained 22% of the variation of the ADF content (Fig. 5b). The Ta and VPD independently explained 49% and 56% of the variation of the NDF content, respectively (Fig. 5c), and 22% and 26% of the variation of the Ash content, respectively (Fig. 5d). The SM, Ta and VPD independently explained 11%, 47% and 21% of the variation of the nutritional quality, respectively, whereas the SM and VPD co-explained 19% variation of the nutritional quality (Fig. 5e).

Table 4

The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality

img-z4-10_516.gif

Fig. 2

Comparisons of (a) crude protein (CP), (b) acid detergent fiber (ADF), (c) neutral detergent fiber (NDF), (d) crude ash (Ash), (e) ether extract (EE) and (f) water-soluble carbohydrate (WSC) between non-warming and warming treatments at sites A, B and C in 2018 and 2019

Note: * indicates P<0.05.

img-z5-1_516.jpg

4 Discussion

The content of CP (8.37%–17.59%) in this study was greater than the CP requirement for livestock maintenance (7%–9.5%) (Soussana and Luscher, 2007; Roukos et al., 2011; Koidou et al., 2019). The content of NDF (32.93% –58.42%) in this study was lower than the upper limit of dietary intake (60%– 65%) for most animals (Roukos et al., 2011; Samuil et al., 2018). Therefore, the CP and NDF contents may not only meet maintain requirements of livestock, but also indicate a relatively high nutritive value of the vegetation. The content of CP, ADF (16.26%–55.39%), NDF, EE (2.48%–4.38%), Ash (7.89%–21.95%) and WSC (3.08%–6.76%) in this study were equivalent to the results (CP: 2.71%–19.21%; ADF: 9.06%–48.30%; NDF: 12.16%–76.23%; EE: 0.64%–10.90%; Ash: 3.49%–12.47%; WSC: 1.24%–17.27%) observed in alpine meadows on the Tibetan Plateau by previous studies (Xu et al., 2002; Shi et al., 2013; Sun et al., 2015; Zhang et al., 2015b; Fan et al., 2017; Li and Liu, 2017; Zhang et al., 2017; Li et al., 2018).

Increased water availability may have increased the content of CP in this study, which was in line with the results observed in the steppes of Inner Mongolia Autonomous Region, China (Schönbach et al., 2012; Ren et al., 2016a), a C4 tropical grass in Brazil (Habermann et al., 2019), mountain side grasslands in North-West Greece (Roukos et al., 2011) and alpine meadows on the Tibetan Plateau (Yao et al., 2019). This finding may be related to several mechanisms. First, increased water availability may accelerate soil nitrogen mineralization and in turn increase the availability of nitrogen to plants (Austin et al., 2004; Miao et al., 2015). Second, increased water availability may increase the capacity of plants to assimilate nitrogen by affecting the activities of nitrogen anabolism, net photosynthetic rate and/or stomatal conductance (Xu and Zhou, 2006; Habermann et al., 2019). Third, increased water availability may promote new tissues generation and delay the maturation of the plants (Schönbach et al., 2012; Ren et al., 2016a). Fourth, higher precipitation may be accompanied by dimming of the solar radiation, which may result in a greater CP content (Lenart et al., 2002).

Fig. 3

Nonmetric multidimensional scaling (NMDS) analysis of the nutritional quality

Note: Legend abbreviations: ANW18: site A of non-warming treatment in 2018; AW18: site A of warming treatment in 2018; BNW18: site B of non-warming treatment in 2018; BW18: site B of warming treatment in 2018; CNW18: site C of non-warming treatment in 2018; CW18: site C of warming treatment in 2018; ANW19: site A of non-warming treatment in 2019; AW19: site A of warming treatment in 2019; BNW19: site B of non-warming treatment in 2019; BW19: site B of warming treatment in 2019; CNW19: site C of non-warming treatment in 2019; CW19: site C of warming treatment in 2019.

img-z6-1_516.jpg

Fig. 4

Univariate regression analysis between the contents of (a) crude protein (CP) and soil moisture (SM), (b) CP and vapor pressure deficit (VPD), and (c) water-soluble carbohydrate (WSC) and SM

img-z6-9_516.jpg

Our findings implied that water availability may have stronger effects than temperature on the nutritional quality of alpine grasslands. This finding was in line with the results of several previous studies (Schönbach et al., 2012; Ren et al., 2016b; Scocco et al., 2016), and may be attributed to one or more of the following mechanisms. First, forage nutritional quality can be negatively correlated with aboveground plant production (White, 1986; Shi et al., 2013). Water availability can play a more important role in the variation of forage production than air temperature in the same alpine meadows used in this study (Fu et al., 2018). Second, water availability may have a stronger relationship with soil available nitrogen than temperature in the same alpine meadows used in this study (Yu et al., 2014).

Our findings suggested that warming may not always change the nutritional quality of alpine meadows on the Tibetan Plateau. This finding strengthened the results obtained in alpine meadows on the Tibetan Plateau by several previous studies. For example, experimental warming altered the content of CP (Li and Liu, 2017), EE, Ash, ADF and NDF (Li and Liu, 2017; Xu et al., 2018) in alpine meadows of the Haibei station. The effects of experimental warming on the content of CP, EE and ADF varied with soil water availability in alpine meadows of the Beiluhe experimental station (Li et al., 2018). These findings may be attributed to one or more of the following mechanisms. First, although the increased soil temperature in this study was lower than those in at least two of the three previous studies (Li et al., 2018; Xu et al., 2018), increased soil temperature may not be correlated with the effect of experimental warming on the content of CP in leaves (Lu et al., 2011). Second, the effect of experimental warming on the content of CP in leaves can decrease with an increasing duration of experimental warming (Bai et al., 2013). The warming duration was less than nine years for at least two of the three previous studies (Li et al., 2018; Xu et al., 2018), whereas the duration was greater than ten years in this study. Third, experimental warming may accelerate soil nitrogen and phosphorus mineralization and the plant's capacity to assimilate nitrogen and phosphorus, but the drying effect that is induced by experimental warming may suppress soil nitrogen and phosphorus mineralization and the plant's capacity to assimilate nitrogen and phosphorus (Gauly et al., 2013; Dumont et al., 2015). However, the probability of this occurring may be low considering the non-significant change in SM in the current study. Fourth, warming may have contrasting effects on plant production and nutritional quality (Li et al., 2018). For example, warming could decrease plant production only when it was a dry growing season at site A, but not at B or C (Fu and Shen, 2016). Warming had significant effects on herbaceous biomass only when the mean annual temperature was no more than –2 °C (Lin et al., 2010). The temperature decreased from site A to C (Fu and Shen, 2016), and the mean annual temperature in this study was greater than those in the three previous studies (Li and Liu, 2017; Li et al., 2018; Xu et al., 2018). Fifth, the nutrient content may change under experimental warming conditions when precipitation is near a certain threshold but not above/below a certain threshold (Augustine et al., 2018). Precipitation increased from site A to C (Fu and Shen, 2016). The mean annual precipitation in this study was lower than those in two of the three previous studies (Li and Liu, 2017; Xu et al., 2018), but greater than that for the third previous study (Li et al., 2018).

Fig. 5

Variation partitioning analysis (VPA), showing the shared and exclusive effects of soil moisture (SM), air temperature (Ta) and vapor pressure deficit (VPD) on (a) crude protein (CP), (b) acid detergent fiber (ADF), (c) neutral detergent fiber (NDF), (d) crude ash (Ash), and (e) the nutritional quality

Note: The fractions of unexplained variation are not illustrated.

img-z7-1_516.jpg

5 Conclusions

In summary, experimental warming only significantly altered the content of CP, ADF, NDF, Ash and the nutritional quality in one (i.e. Site B with an elevation of 4513 m) of the three alpine meadow sites during a dry year. Water availability had stronger effects than temperature on the content of CP, ADF, NDF, Ash, WSC and the nutritional quality, and it had positive effects on the content of CP and WSC. Therefore, understanding the effect of climate warming on nutritional quality may need to consider water availability, which may vary with site and year, in the alpine meadow on the Tibetan Plateau.

References

1.

Arft A M, Walker M D, Gurevitch J, et al. 1999. Responses of tundra plants to experimental warming: Meta-analysis of the international tundra experiment. Ecological Monographs , 69(4): 491–511. Google Scholar

2.

Augustine D J, Blumenthal D M, Springer T L, et al. 2018. Elevated CO2 induces substantial and persistent declines in forage quality irrespective of warming in mixedgrass prairie. Ecological Applications , 28(3): 721–735. Google Scholar

3.

Austin A T, Yahdjian L, Stark J M, et al. 2004. Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia , 141(2): 221–235. Google Scholar

4.

Bai E, Li S L, Xu W H, et al. 2013. A meta-analysis of experimental warming effects on terrestrial nitrogen pools and dynamics. New Phytologist , 199(2): 441–451. Google Scholar

5.

Baranova A, Oldeland J, Wang S L, et al. 2019. Grazing impact on forage quality and macronutrient content of rangelands in Qilian Mountains, NW China. Journal of Mountain Science , 16(1): 43–53. Google Scholar

6.

Birnie-Gauvin K, Peiman K S, Raubenheimer D, et al. 2017. Nutritional physiology and ecology of wildlife in a changing world. Conservation Physiology , 5. https://doi.org/10.1093/conphys/cox030Google Scholar

7.

Cui G X, Yuan F, Degen A A, et al. 2016. Composition of the milk of yaks raised at different altitudes on the Qinghai-Tibetan Plateau. International Dairy Journal , 59: 29–35. Google Scholar

8.

Cui S J, Meng F D, Ji S N, et al. 2017. Responses of phenology and seed production of annual Koenigia islandica to warming in a desertified alpine meadow. Agricultural and Forest Meteorology , 247: 376–384. Google Scholar

9.

Diffenbaugh N S, Field C B. 2013. Changes in ecologically critical terrestrial climate conditions. Science , 341(6145): 486–492. Google Scholar

10.

Dorji T, Totland O, Moe S R, et al. 2013. Plant functional traits mediate reproductive phenology and success in response to experimental warming and snow addition in Tibet. Global Change Biology , 19(2): 459–472. Google Scholar

11.

Dumont B, Andueza D, Niderkorn V, et al. 2015. A meta-analysis of climate change effects on forage quality in grasslands: Specificities of mountain and Mediterranean areas. Grass & Forage Science , 70(2): 239–254. Google Scholar

12.

Fan X, Yang D, Hao L, et al. 2017. Annual analysis of nutritional quality of pasture in Haiyan County, Qinghai Province. Pratacultural Science , 34(11): 2359–2365. Google Scholar

13.

Fu G, Shen Z X. 2016. Environmental humidity regulates effects of experimental warming on vegetation index and biomass production in an alpine meadow of the Northern Tibet. Plos One , 11(10). https://doi.org/10.1371/journal.pone.0165643Google Scholar

14.

Fu G, Shen Z X. 2017. Clipping has stronger effects on plant production than does warming in three alpine meadow sites on the Northern Tibetan Plateau. Scientific Reports , 7. https://doi.org/10.1038/s41598-017-16645-2Google Scholar

15.

Fu G, Shen Z X, Zhang X Z. 2018. Increased precipitation has stronger effects on plant production of an alpine meadow than does experimental warming in the Northern Tibetan Plateau. Agricultural and Forest Meteorology , 249: 11–21. Google Scholar

16.

Fu G, Zhang H R, Sun W. 2019. Response of plant production to growing/non-growing season asymmetric warming in an alpine meadow of the Northern Tibetan Plateau. Science of the Total Environment , 650: 2666–2673. Google Scholar

17.

Ganjurjav H, Gao Q Z, Gornish E S, et al. 2016. Differential response of alpine steppe and alpine meadow to climate warming in the central Qinghai-Tibetan Plateau. Agricultural and Forest Meteorology , 223: 233–240. Google Scholar

18.

Gauly M, Bollwein H, Breves G, et al. 2013. Future consequences and challenges for dairy cow production systems arising from climate change in Central Europe—A review. Animal , 7(5): 843–859. Google Scholar

19.

Habermann E, de Oliveira E A D, Contin D R, et al. 2019. Warming and water deficit impact leaf photosynthesis and decrease forage quality and digestibility of a C4 tropical grass. Physiologia Plantarum , 165(2): 383–402. Google Scholar

20.

Klein J A, Harte J, Zhao X Q. 2004. Experimental warming causes large and rapid species loss, dampened by simulated grazing, on the Tibetan Plateau. Ecology Letters , 7(12): 1170–1179. Google Scholar

21.

Klein J A, Harte J, Zhao X Q. 2008. Decline in medicinal and forage species with warming is mediated by plant traits on the Tibetan Plateau. Ecosystems , 11(5): 775–789. Google Scholar

22.

Koidou M, Mountousis I, Dotas V, et al. 2019. Temporal variations of herbage production and nutritive value of three grasslands at different elevation zones regarding grazing needs and welfare of ruminants. Archives Animal Breeding , 62(1): 215–226. Google Scholar

23.

Lenart E A, Bowyer R T, Hoef J V, et al. 2002. Climate change and caribou: Effects of summer weather on forage. Canadian Journal of Zoology , 80(4): 664–678. Google Scholar

24.

Li C Y, Peng F, Xue X, et al. 2018. Productivity and quality of alpine grassland vary with soil water availability under experimental warming. Frontiers in Plant Science , 9: 1790. https://doi.org/10.3389/fpls.2018.01790Google Scholar

25.

Li J R, Liu Z H. 2017. High-cold meadow plants respond to long-term warming. Qinghai Prataculture , 26(3): 13–17. (in Chinese) Google Scholar

26.

Lin D L, Xia J Y, Wan S Q. 2010. Climate warming and biomass accumulation of terrestrial plants: A meta-analysis. New Phytologist , 188(1): 187–198. Google Scholar

27.

Lithourgidis A S, Vasilakoglou I B, Dhima K V, et al. 2006. Forage yield and quality of common vetch mixtures with oat and triticale in two seeding ratios. Field Crops Research , 99(2-3): 106–113. Google Scholar

28.

Lu M, Yang Y H, Luo Y Q, et al. 2011. Responses of ecosystem nitrogen cycle to nitrogen addition: A meta-analysis. New Phytologist , 189(4): 1040–1050. Google Scholar

29.

Lu X Y, Fan J H, Yan Y, et al. 2013. Responses of soil CO2 fluxes to short-term experimental warming in alpine steppe ecosystem, Northern Tibet. Plos One , 8(3): e59054. https://doi.org/10.1371/journal.pone.0059054Google Scholar

30.

Ma X X, Yan Y, Hong J T, et al. 2017. Impacts of warming on root biomass allocation in alpine steppe on the north Tibetan Plateau. Journal of Mountain Science , 14(8): 1615–1623. Google Scholar

31.

Miao F H, Guo Z G, Xue R, et al. 2015. Effects of grazing and precipitation on herbage biomass, herbage nutritive value, and yak performance in an alpine meadow on the Qinghai-Tibetan Plateau. Plos One , 10(6). https://doi.org/10.1371/journal.pone.0127275Google Scholar

32.

Piao S L, Fang J Y, He J S. 2006. Variations in vegetation net primary production in the Qinghai-Xizang Plateau, China, from 1982 to 1999. Climatic Change , 74(1-3): 253–267. Google Scholar

33.

Proffitt K M, Hebblewhite M, Peters W, et al. 2016. Linking landscape-scale differences in forage to ungulate nutritional ecology. Ecological Applications , 26(7): 2156–2174. Google Scholar

34.

Ren H Y, Han G D, Lan Z C, et al. 2016a. Grazing effects on herbage nutritive values depend on precipitation and growing season in Inner Mongolian grassland. Journal of Plant Ecology , 9(6): 712–723. Google Scholar

35.

Ren H Y, Han G D, Schonbach P, et al. 2016b. Forage nutritional characteristics and yield dynamics in a grazed semiarid steppe ecosystem of Inner Mongolia, China. Ecological Indicators , 60: 460–469. Google Scholar

36.

Roukos C, Papanikolaou K, Karalazos A, et al. 2011. Changes in nutritional quality of herbage botanical components on a mountain side grassland in North-West Greece. Animal Feed Science and Technology , 169(1-2): 24–34. Google Scholar

37.

Rustad L E, Campbell J L, Marion G M, et al. 2001. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia , 126(4): 543–562. Google Scholar

38.

Samuil C, Stavarache M, Sirbu C, et al. 2018. Influence of sustainable fertilization on yield and quality food of Mountain Grassland. Notulae Botanicae Horti Agrobotanici Cluj-Napoca , 46(2): 410–417. Google Scholar

39.

Schönbach P, Wan H, Gierus M, et al. 2012. Effects of grazing and precipitation on herbage production, herbage nutritive value and performance of sheep in continental steppe. Grass and Forage Science , 67(4): 535–545. Google Scholar

40.

Scocco P, Piermarteri K, Malfatti A, et al. 2016. Increase of drought stress negatively affects the sustainability of extensive sheep farming in sub-Mediterranean climate. Journal of Arid Environments , 128: 50–58. Google Scholar

41.

Shi Y, Ma Y L, Ma W H, et al. 2013. Large scale patterns of forage yield and quality across Chinese grasslands. Chinese Science Bulletin , 58(10): 1187–1199. Google Scholar

42.

Soussana J F, Luscher A. 2007. Temperate grasslands and global atmospheric change: A review. Grass and Forage Science , 62(2): 127–134. Google Scholar

43.

Sun J, Hou G, Liu M, et al. 2019. Effects of climatic and grazing changes on desertification of alpine grasslands, Northern Tibet. Ecological Indicators , 107. https://doi.org/j.ecolind.2019.105647Google Scholar

44.

Sun P, Cui Z, Liu S, et al. 2015. Seasonal evaluation of nutrition and carrying capacity of grazing pastures in the Three-River Source Region. Acta Prataculturae Sinica , 24(12): 92–101. (in Chinese) Google Scholar

45.

Van Soest P J, Robertson J B, Lewis B A. 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. Journal of Dairy Science , 74(10): 3583–3597. Google Scholar

46.

White L M. 1986. Forage yield and quality of warm-season and cool-season grasses. Journal of Range Management , 39(3): 264–268. Google Scholar

47.

Wu H B, Wang X X, Ganjurjav H, et al. 2020. Effects of increased precipitation combined with nitrogen addition and increased temperature on methane fluxes in alpine meadows of the Tibetan Plateau. Science of the Total Environment , 705: 135818. https://doi.org/10.1016/j.scitotenv.2019.135818Google Scholar

48.

Xu S X, Zhao X Q, Sun P, et al. 2002. A simulative study on effects of climate warming on nutrient contents and in vitro digestibility of herbage grown in Qinghai-Xizang Plateau. Acta Botanica Sinica , 44(11): 1357–1364. (in Chinese) Google Scholar

49.

Xu W, Zhu M Y, Zhang Z H, et al. 2018. Experimentally simulating warmer and wetter climate additively improves rangeland quality on the Tibetan Plateau. Journal of Applied Ecology , 55(3): 1486–1497. Google Scholar

50.

Xu Z Z, Zhou G S. 2006. Nitrogen metabolism and photosynthesis in Leymus chinensis in response to long-term soil drought. Journal of Plant Growth Regulation , 25(3): 252–266. Google Scholar

51.

Yao X X, Wu J P, Gong X Y. 2019. Precipitation and seasonality affect grazing impacts on herbage nutritive values in alpine meadows on the Qinghai-Tibet Plateau. Journal of Plant Ecology , 12(6): 993–1008. Google Scholar

52.

Yemm E W, Willis A J. 1954. The estimation of carbohydrates in plant extracts by anthrone. Biochemical Journal , 57(3): 508–514. Google Scholar

53.

Yu C Q, Han F S, Fu G. 2019a. Effects of 7 years experimental warming on soil bacterial and fungal community structure in the Northern Tibet alpine meadow at three elevations. Science of the Total Environment , 655: 814–822. Google Scholar

54.

Yu C Q, Shen Z X, Zhang X Z, et al. 2014. Response of soil C and N, dissolved organic C and N, and inorganic N to short-term experimental warming in an Alpine meadow on the Tibetan Plateau. Scientific World Journal , 2014: 152576. https://doi.org/10.1155/2014/152576Google Scholar

55.

Yu C Q, Wang J W, Shen Z X, et al. 2019b. Effects of experimental warming and increased precipitation on soil respiration in an alpine meadow in the Northern Tibetan Plateau. Science of the Total Environment , 647: 1490–1497. Google Scholar

56.

Zhang X, Luo L, Jin Y, et al. 2017. Changes in nutrients of dominant species on montane shrub grassland in the Lhasa River Basin. Chinese Journal of Grassland , 39(3): 90–95. (in Chinese) Google Scholar

57.

Zhang X Z, Shen Z X, Fu G. 2015a. A meta-analysis of the effects of experimental warming on soil carbon and nitrogen dynamics on the Tibetan Plateau. Applied Soil Ecology , 87: 32–38. Google Scholar

58.

Zhang Y, Chen X J, Cheng Y X, et al. 2015b. Effects of stocking rates on functional group diversity and forage quality in rangeland of Qilian Mountain, China. Journal of Environmental Biology , 36(4): 713–719. Google Scholar

59.

Zhang Y, Dong S K, Gao Q Z, et al. 2019. “Rare biosphere” plays important roles in regulating soil available nitrogen and plant biomass in alpine grassland ecosystems under climate changes. Agriculture Ecosystems & Environment , 279: 187–193. Google Scholar

Appendices

e01_516.gif
Sun Wei, Li Shaowei, Zhang Yangjian, and Fu Gang "Effect of Long-Term Experimental Warming on the Nutritional Quality of Alpine Meadows in the Northern Tibet," Journal of Resources and Ecology 11(5), 516-524, (4 September 2020). https://doi.org/10.5814/j.issn.1674-764x.2020.05.009
Received: 27 March 2020; Accepted: 2 June 2020; Published: 4 September 2020
JOURNAL ARTICLE
9 PAGES


SHARE
ARTICLE IMPACT
Back to Top