Machine learning in soil nutrient dynamics of alpine grasslands.

As a terrestrial ecosystem, alpine grasslands feature diverse vegetation types and play key roles in regulating water resources and carbon storage, thus shaping global climate. The dynamics of soil nutrients in this ecosystem, responding to regional climate change, directly impact primary productivity. This review comprehensively explored the effects of climate change on soil nitrogen (N), phosphorus (P), and their balance in the alpine meadows, highlighting the significant roles these nutrients played in plant growth and species diversity. We also shed light on machine learning utilization in soil nutrient evaluation. As global warming continues, alongside shifting precipitation patterns, soil characteristics of grasslands, such as moisture and pH values vary significantly, further altering the availability and composition of soil nutrients. The rising air temperature in alpine regions substantially enhances the activity of soil organisms, accelerating nutrient mineralization and the decomposition of organic materials. Combined with varied nutrient input, such as increased N deposition, plant growth and species composition are changing. With the robust capacity to use and integrate diverse data sources, including satellite imagery, sensor-collected spectral data, camera-captured videos, and common knowledge-based text and audio, machine learning offers rapid and accurate assessments of the changes in soil nutrients and associated determinants, such as soil moisture. When combined with powerful large language models like ChatGPT, these tools provide invaluable insights and strategies for effective grassland management, aiming to foster a sustainable ecosystem that balances high productivity and advanced services with reduced environmental impacts.

Vertical differentiation drives the changes in the main microflora and metabolites of carbon and nitrogen cycling in the early freeze-thaw period in the Qinghai Lake Basin.

Global climate change has altered the frequency of soil freeze-thaw cycles, but the response of soil microorganisms to different elevation gradients during the early freeze-thaw period remains unclear. So far, the influence of the altitudinal gradient on the microbial community and metabolic characteristics in the early freeze-thaw period of the Qinghai Lake Basin remains unclear. To this end, we collected soil at different elevations in the early freeze-thaw period of the Qinghai Lake Basin and investigated the influence of the elevation gradient on soil microbial community characteristics and soil metabolic processes as well as the corresponding environmental driving mechanism by high-throughput sequencing and LC-MS (Liquid Chromatograph-Mass Spectrometer) nontargeted metabolite determination. The results showed that Proteobacteria were the dominant microflora in the Qinghai Lake Basin. The dominant phyla associated with carbon and nitrogen are Proteobacteria and Firmicutes, both of which are significantly affected by elevation. The soil physicochemical factors jointly affected the soil microbial communities and metabolism. Total phosphorus nitrate nitrogen and pH were the main driving factors of the microbial community, and metabolites were sensitive to changes in chemical factors. In short, the microbial community structure and function, soil physicochemical factors and soil metabolic processes were significantly affected by the altitudinal gradient in the early freeze-thaw period, while the microbial community diversity showed no significant response to the altitudinal gradient. Additionally, a high potassium content in the soil may promote the growth and reproduction of bacteria associated with carbon and nitrogen cycling, as well as the production of metabolites.

Modeling the effect of grazing on carbon and water use efficiencies in grasslands on the Qinghai-Tibet Plateau.

BACKGROUND: Carbon and water use efficiencies (CUE and WUE, respectively) are vital indicators of the adaptability of plants to environmental conditions. However, the effects of grazing and climate change on the spatiotemporal changes in CUE and WUE in Qinghai-Tibet Plateau grasslands (QTPG) are still unclear. RESULTS: Using the enhanced Biome-BGCMuSo model in combination with observed data, we estimated and analyzed the spatiotemporal variations in CUE and WUE and their responses to grazing in QTPG from 1979 to 2018. The mean annual CUE was 0.7066 in QTPG from 1979 to 2018 under the actual climate scenario. In general, the grassland CUE was low in the southeast and high in the northwest. Grazing generally decreased CUE in QTPG from 1979 to 2018, and there was an increasing trend in the difference in CUE between the grazing and nongrazing scenarios. The difference in CUE was generally greater in the northwest than in the southeast. The mean annual WUE was 0.5591 g C/kg H2O in QTPG from 1979 to 2018 under the actual climate scenario. After 2000, the grassland WUE exhibited a fluctuating upward trend. In general, the grassland WUE was greater in the southeast than in the northwest. Grazing generally decreased WUE in QTPG from 1979 to 2018, and there was an increasing trend in the difference in WUE between the grazing and nongrazing scenarios. The difference in WUE was generally greater in the northwest than in the southeast. CONCLUSIONS: The findings of this study suggested that the spatiotemporal changes in CUE and WUE in QTPG were closely related to changes in the natural environment and grazing management.

Corrigendum: Comparison of 14 reference evapotranspiration with lysimeter measurements at a site in the humid alpine meadow, northeastern Qinghai-Tibetan Plateau.

[This corrects the article DOI: 10.3389/fpls.2022.854196.].

The Influence Mechanism of Vegetation Type on the Characteristics of nirS-Type Denitrifying Microbial Communities in Qinghai Lake Wetlands.

Soil denitrification is an important process in the emission of N2O, an atmospheric greenhouse gas. Environmental factors of different vegetation types are largely heterogeneous, which may directly or indirectly affect N2O fluxes. Through high-throughput sequencing of the nitrite reductase gene nirS, this study investigated the influence of vegetation type on the structure and diversity of denitrifying microbial communities in Qinghai Lake wetlands, China. The results showed that among the four vegetation types in the Qinghai Lake wetlands, Carex rigescens (CR) had the highest species richness index, and Leymus secalinus (LS) had the lowest species richness index. Species evenness followed the opposite trend. Proteobacteria were the main denitrifying bacterial phylum in the wetland soil of Qinghai Lake. There were 40 differential bacterial flora at different levels in the four vegetation types, most of which belonged to Proteobacteria. Magnetospirillum is a bacterium that differed significantly across the four vegetation types, and it was one of the main denitrifying taxa based on relative abundance in the LS vegetation type. Soil pH was the most important regulating factor of nirS-type denitrifying microbial community in Qinghai Lake wetland. In summary, the succession of vegetation types in the Qinghai Lake Wetlands changes the soil microenvironment and significantly affects the community structure and diversity of the denitrifying microbial communities. The large-area growth of CR might even increase the emission of nitrous oxide. This study can serve as a reference for further exploration of the N2O emission mechanism in the unique habitats of alpine wetlands.

Distribution Characteristics and Controlling Factors of Soil Total Nitrogen: Phosphorus Ratio Across the Northeast Tibetan Plateau Shrublands.

Nitrogen (N) and phosphorus (P) stoichiometry have significant effects on nutrient cycles in terrestrial ecosystems. However, our understanding of the patterns and the driving factors of soil N:P ratios in the Tibetan Plateau shrublands remains limited. Our study aimed to quantify the distribution of soil N:P ratio and its controlling factors based on soil, plant, and climate factors from 59 sites in shrublands across the northeast Tibetan Plateau. The kriging interpolation method was used to quantify the soil N:P distribution. Spatially, the soil N:P ratio was higher in the south than in the north and lower in the west than in the east. The soil N:P ratio in the northeast Tibetan Plateau shrublands was mainly explained by edaphic factors, which also played an important role in regulating the effects of plant and climate factors on soil N:P ratios. Mean annual precipitation, instead of mean annual temperature, significantly controlled the soil N:P ratios, and its effect on the pattern of soil N:P ratios differed between alpine shrublands and desert shrublands. The N:P ratios of different organs in shrublands also played different roles in shaping the soil N:P ratios in alpine and desert shrublands. These results provide support for the hypothesis that edaphic factors were the dominant drivers of spatial variation in soil N:P ratios across the northeast Tibetan Plateau shrublands, and our study contributes to a deeper understanding of biogeochemical cycling at high altitudes.

Comparison of Fourteen Reference Evapotranspiration Models With Lysimeter Measurements at a Site in the Humid Alpine Meadow, Northeastern Qinghai-Tibetan Plateau.

Evapotranspiration is a key component in the terrestrial water cycle, and accurate evapotranspiration estimates are critical for water irrigation management. Although many applicable evapotranspiration models have been developed, they are largely focused on low-altitude regions, with less attention given to alpine ecosystems. In this study, we evaluated the performance of fourteen reference evapotranspiration (ET0) models by comparison with large weight lysimeter measurements. Specifically, we used the Bowen ratio energy balance method (BREB), three combination models, seven radiation-based models, and three temperature-based models based on data from June 2017 to December 2018 in a humid alpine meadow in the northeastern Qinghai-Tibetan Plateau. The daily actual evapotranspiration (ETa) data were obtained using large weighing lysimeters located in an alpine Kobresia meadow. We found that the performance of the fourteen ET0 models, ranked on the basis of their root mean square error (RMSE), decreased in the following order: BREB > Priestley-Taylor (PT) > DeBruin-Keijman (DK) > 1963 Penman > FAO-24 Penman > FAO-56 Penman-Monteith > IRMAK1 > Makkink (1957) > Makkink (1967) > Makkink > IRMAK2 > Hargreaves (HAR) > Hargreaves1 (HAR1) > Hargreaves2 (HAR2). For the combination models, the FAO-24 Penman model yielded the highest correlation (0.77), followed by 1963 Penman (0.75) and FAO-56 PM (0.76). For radiation-based models, PT and DK obtained the highest correlation (0.80), followed by Makkink (1967) (0.69), Makkink (1957) (0.69), IRMAK1 (0.66), and IRMAK2 (0.62). For temperature-based models, the HAR model yielded the highest correlation (0.62), HAR1, and HAR2 obtained the same correlation (0.59). Overall, the BREB performed best, with RMSEs of 0.98, followed by combination models (ranging from 1.19 to 1.27 mm day-1 and averaging 1.22 mm day-1), radiation-based models (ranging from 1.02 to 1.42 mm day-1 and averaging 1.27 mm day-1), and temperature-based models (ranging from 1.47 to 1.48 mm day-1 and averaging 1.47 mm day-1). Furthermore, all models tended to underestimate the measured ETa during periods of high evaporative demand (i.e., growing season) and overestimated measured ETa during low evaporative demand (i.e., nongrowing season). Our results provide new insights into the accurate assessment of evapotranspiration in humid alpine meadows in the northeastern Qinghai-Tibetan Plateau.

Soil Moisture Variations in Response to Precipitation Across Different Vegetation Types on the Northeastern Qinghai-Tibet Plateau.

An understanding of soil moisture conditions is crucial for hydrological modeling and hydrological processes. However, few studies have compared the differences between the dynamics of soil moisture content and soil moisture response to precipitation infiltration under different types of vegetation on the Qinghai-Tibet Plateau (QTP). In this study, a soil moisture sensor was used for continuous volumetric soil moisture measurements during 2015 and 2016, with the aim of exploring variations in soil moisture and its response to precipitation infiltration across two vegetation types (alpine meadow and alpine shrub). Our results showed that temporal variations in soil moisture at the surface (0-20 cm) and middle soil layers (40-60 cm) were consistent with precipitation patterns for both vegetation types. However, there was a clear lag in the soil moisture response to precipitation for the deep soil layers (80-100 cm). Soil moisture content was found to be significantly positively related to precipitation and negatively related to air temperature. Aboveground biomass was significantly negatively associated with the surface soil moisture content (0-20 cm) during the growing season. Statistically significant differences were observed between the soil water content of the surface, middle, and deep soil layers for the two vegetation types (p < 0.05). Soil moisture (19.81%) in the surface soil layer was significantly lower than that in the deep soil layer (24.75%) for alpine shrubs, and the opposite trend was observed for alpine meadows. The maximum infiltration depth of alpine shrubs was greater than that of alpine meadows under extremely high-precipitation events, which indicates that alpine shrubs might be less susceptible to surface runoff under extreme precipitation events. Furthermore, low precipitation amounts did not affect precipitation infiltration for either vegetation type, whereas the infiltration depth increased with precipitation for both vegetation types. Our results suggest that a series of small precipitation events may not have the same effect on soil moisture as a single large precipitation event that produces the equivalent total rainfall.

Alpine grassland management based on ecosystem service relationships on the southern slopes of the Qilian Mountains, China.

Grassland management is one of the most important means to address grassland degradation on the Qinghai-Tibet Plateau, but at present, the primary goal is still to improve grassland productivity, and little research has been conducted on grassland management based on its ecosystem service relationships. Based on remote sensing and meteorological data, we calculated and analyzed the spatial and temporal changes, trade-offs and synergistic relationships between livestock production and water retention services in alpine grassland on the southern slopes of the Qilian Mountains (SSQM), and designed a grazing management plan for sustainable development in the region. The results showed that the value of livestock production and water retention services of alpine grassland decreased from east to west, and their relationship is dominated by synergy and complemented by trade-offs. The synergistic relationships are concentrated in the Qinghai Lake Basin in the south and the river valleys in the north, while the trade-offs are scattered in the steeper terrain in the western and eastern parts of the study area. The scenario of preserving all water retention services and losing some livestock production services is sustainable. Based on this scenario we divided the alpine grassland of the study area into maintenance grazing, rotational grazing and grazing exclusion of 65.8%, 32.0% and 2.2%, respectively. Our study demonstrates that ecosystem service relationships have the potential to guide grassland management, and the results will provide new approaches to alpine grassland management.

Restoration of Degraded Grassland Significantly Improves Water Storage in Alpine Grasslands in the Qinghai-Tibet Plateau.

Alpine grassland has very important water conservation function. Grassland degradation seriously affects the water conservation function; moreover, there is little understanding of the change of water state during grassland restoration. Our study aims to bridge this gap and improve our understanding of changes in soil moisture during the restoration process. In this study, the water storage, vegetation, and meteorology of a non-degradation grassland (grazing intensity of 7.5 sheep/ha) and a severely degraded grassland (grazing intensity of 12-18 sheep/ha) were monitored in the Qinghai-Tibet Plateau for seven consecutive years. We used correlation, stepwise regression, and the boosted regression trees (BRT) model analyses, five environmental factors were considered to be the most important factors affecting water storage. The severely degraded grassland recovered by light grazing treatment for 7 years, with increases in biomass, litter, and vegetation cover, and a soil-water storage capacity 41.9% higher in 2018 compared to that in 2012. This increase in soil-water storage was primarily due to the increase in surface soil moisture content. The key factors that influenced water storage were listed in a decreasing order: air temperature, litter, soil heat flux, precipitation, and wind speed. Their percentage contributions to soil-water storage were 50.52, 24.02, 10.86, 7.82, and 6.77%, respectively. Current and future climate change threatens soil-water conservation in alpine grasslands; however, grassland restoration is an effective solution to improve the soil-water retention capacity in degraded grassland soils.

Moderate grazing increased alpine meadow soils bacterial abundance and diversity index on the Tibetan Plateau.

The response of grassland soil bacterial community characteristics to different grazing intensities is central ecological topics. However, the underlying mechanisms between bacterial abundance, diversity index, and grazing intensity remain unclear. We measured alpine meadow soil bacterial gene richness and diversity index under four grazing intensities using 16S rDNA sequence analysis on the Tibetan Plateau. The results suggest that extreme grazing significantly decreased alpine meadow both bacterial gene abundance and diversity index (p < .05). The lowest operational taxonomic unit numbers were 3,012 ± 447 copies under heavy grazing in the growing season. It was significantly lower than heavy grazing with approximately 3,958 ± 119 copies (p < .05). The Shannon index for medium and high grazing grassland bacterial diversity was slightly higher than for light grazing in the growing season. Furthermore, the lowest index was approximately 9.20 ± 0.50 for extreme grazing of grassland in the growing season. The average bacterial gene abundance and diversity index in the dormancy period were slightly higher than that in the growing season. Soil bulk density, pH, ammonium, and nitrate nitrogen were the main positive factors driving grazed grassland bacterial communities. Our study provides insight into the response of alpine meadows to grazing intensity, demonstrating that moderate grazing increases bacterial community diversity in grazed grasslands.

Biomass allocation and productivity-richness relationship across four grassland types at the Qinghai Plateau.

Aboveground biomass (AGB) and belowground biomass (BGB) allocation and productivity-richness relationship are controversial. Here, we assessed AGB and BGB allocation and the productivity-richness relationship at community level across four grassland types based on the biomass data collected from 80 sites across the Qinghai Plateau during 2011-2012. The reduced major axis regression and general linear models were used and showed that (a) the median values of AGB were significantly higher in alpine meadow than in other three grassland types; the ratio of root to shoot (R/S) was significantly higher in desert grassland (36.06) than intemperate grassland (16.60), alpine meadow (13.35), and meadow steppe (19.46). The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. (b) The slopes between log AGB and log BGB in the temperate grassland and meadow steppe were 1.09 and 1, respectively, whereas that in the desert grassland was 1.12, which was significantly different from the isometric allocation relationship. A competitive relationship between AGB and BGB was observed in the alpine meadow with a slope of -1.83, indicating a trade-off between AGB and BGB in the alpine meadow. (c) A positive productivity-richness relationship existed across the four grassland types, suggesting that the positive productivity-richness relationship might not be affected by the environmental factors at the plant location. Our results provide a new insight for biomass allocation and biodiversity-ecosystem functioning research.

Moderate grazing promotes the root biomass in Kobresia meadow on the northern Qinghai-Tibet Plateau.

Grazing is an important modulator of both plant productivity and biodiversity in grassland community, yet how to determine a suitable grazing intensity in alpine grassland is still controversy. Here, we explore the effects of different grazing intensities on plant biomass and species composition, both at community level and functional group level, and examines the productivity-species richness relationship under four grazing patterns: no grazing (CK), light grazing (LG), moderate grazing, (MG) and heavy grazing (HG), attempt to determine a suitable grazing intensity in alpine grassland. The results were as follows. The total aboveground biomass (AGB) reduced with increasing grazing intensity, and the response of plant functional groups was different. AGB of both sedges and legumes increased from MG to HG, while the AGB of forbs reduced sharply and the grass AGB remained steady. There was a significant positive relationship between productivity and species richness both at community level and functional group level. In contrast, the belowground biomass (BGB) showed a unimodal relationship from CK to HG, peaking in MG (8,297.72 ± 621.29 g/m2). Interestingly, the grassland community tends to allocate more root biomass to the upper soil layer under increasing grazing intensities. Our results suggesting that moderate levels of disturbance may be the optimal grassland management strategy for alpine meadow in terms of root production.

Nitrogen controls the net primary production of an alpine Kobresia meadow in the northern Qinghai-Tibet Plateau.

Net primary production (NPP) is a fundamental property of natural ecosystems. Understanding the temporal variations of NPP could provide new insights into the responses of communities to environmental factors. However, few studies based on long-term field biomass measurements have directly addressed this subject in the unique environment of the Qinghai-Tibet plateau (QTP). We examined the interannual variations of NPP during 2008-2015 by monitoring both aboveground net primary productivity (ANPP) and belowground net primary productivity (BNPP), and identified their relationships with environmental factors with the general linear model (GLM) and structural equation model (SEM). In addition, the interannual variation of root turnover and its controls were also investigated. The results show that the ANPP and BNPP increased by rates of 15.01 and 143.09 g/m2 per year during 2008-2015, respectively. BNPP was mainly affected by growing season air temperature (GST) and growing season precipitation (GSP) rather than mean annual air temperature (MAT) or mean annual precipitation (MAP), while ANPP was only controlled by GST. In addition, available nitrogen (AN) was significantly positively associated with BNPP and ANPP. Root turnover rate averaged 30%/year, increased with soil depth, and was largely controlled by GST. Our results suggest that alpine Kobresia meadow was an N-limited ecosystem, and the NPP on the QTP might increase further in the future in the context of global warming and nitrogen deposition.

Impacts of climate change and human factors on land cover change in inland mountain protected areas: a case study of the Qilian Mountain National Nature Reserve in China.

Over the past few decades, natural reserves have been affected by both climate change and human activities, and their land cover has changed dramatically, especially in mountain reserves, which are more sensitive to climate change and human activities. This paper used long-term Landsat and MODIS NDVI remote sensing data to monitor the changes of land cover and vegetation conditions in the Qilian Mountain National Nature Reserve (QMNNR) in China from 1975 to 2015, and analysed the impacts of climate change and human activities in combination with meteorological and socioeconomic data. The results show that the land cover structure of the QMNNR has remained stable over the past 40 years, but the total area of natural vegetation has decreased by 49.55 km2, the artificial surface and cropland has expanded by 13.68 and 32.57 km2 in some areas, respectively, and the glacier has retreated by 33.34 km2 as a whole. The warming and humidification trend of the climate is the leading factor for glacial retreat and the improvement of the overall vegetation condition, while population growth and economic benefits lead to the expansion of cropland and artificial surfaces in some areas, thus causing the reduction of 18.80 and 28.30 km2 in shrubland and grassland. This study proves that the system of protected areas plays a key role in maintaining the stability of the ecosystem structure and that reducing the population density around the protected areas and changing the mode of economic development can effectively reduce the intensity of human interference. Under the background of climate warming, the change of the ecosystem function in mountain protected areas is full of uncertainty, so management and protection strategies need to be studied in depth.

Responses of biomass allocation across two vegetation types to climate fluctuations in the northern Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau (QTP) is particularly sensitive to global climate change, especially to elevated temperatures, when compared with other ecosystems. However, few studies use long-term field measurements to explore the interannual variations in plant biomass under climate fluctuations. Here, we examine the interannual variations of plant biomass within two vegetation types (alpine meadow and alpine shrub) during 2008-2017 and their relationships with climate variables. The following results were obtained. The aboveground biomass (AGB) and belowground biomass (BGB) response differently to climate fluctuations, the AGB in KPM was dominated by mean annual precipitation (MAP), whereas the AGB in PFS was controlled by mean annual air temperature (MAT). However, the BGB of both KPM and PFS was only weakly affected by climate variables, suggesting that the BGB in alpine ecosystems may remain as a stable carbon stock even under future global climate change. Furthermore, the AGB in PFS was significantly higher than KPM, while the BGB and R/S in KPM were significantly higher than PFS, reflecting the KPM be more likely to allocate more photosynthates to roots. Interestingly, the proportion of 0-10 cm root biomass increased in KPM and PFS, whereas the other proportions both decreased, reflecting a shift in biomass toward the surface layer. Our results could provide a new sight for the prediction how alpine ecosystem response to future climate change.

Moderate Grazing Promotes Grassland Nitrous Oxide Emission by Increasing Ammonia-Oxidizing Archaea Abundance on the Tibetan Plateau.

Grasslands are suffering from long-term overgrazing because of the population inflation. Furthermore, nitrous oxide (N2O) is a major greenhouse gas that also depletes stratospheric ozone. However, the emission rate of grassland N2O and underlying mechanisms remained unclear under different grazing intensities. We conducted a field manipulation under four grazing intensities to compare its N2O fluxes and main affected factors. It was indicated that alpine meadow N2O emission rates increased from 39.7 ± 3.1 to 47.8 ± 2.3 µg m-2 h-1 (p < 0.05), then decreased to 43.4 ± 4.1 and 32.9 ± 1.4 µg m-2 h-1 with grazing intensity increasing from 4 to 8, 12 and 16 sheep ha-1, respectively. Multiple-stepwise regression analysis indicated that the predominant affected soil factors were separately TN and BD, pH and BD, also pH and BD, SOC and BD. Simple linear regression models revealed that ammonia-oxidizing archaea (AOA) contributed much to N2O emission (R2 = 0.77). Additionally, the R2 coefficient of linear regression was 0.87 between nosZ genes and N2O emission rates in alpine meadow. Much attention should be paid to protecting alpine meadow from degradation to mitigate N2O emission source on the Tibetan Plateau.

The Response of Shallow Groundwater Levels to Soil Freeze-Thaw Process on the Qinghai-Tibet Plateau.

The Qinghai-Tibet plateau has the world's largest area of seasonally frozen ground. Here, shallow groundwater displays behavior that is distinct from that elsewhere in the world. In the present study, we explore the seasonal and interannual variation of the shallow groundwater levels from 2012 to 2016, and attempt to quantitatively evaluate the relative influences of individual driving factors on the shallow groundwater levels based on boosted regression trees. The results show that: (1) on a seasonal scale, the groundwater levels were characterized by a double peak and double valley relationship, while on an interannual scale the groundwater levels showed a slightly downwards trend from 2012 to 2016; and (2) during the frozen period, the seasonal variation of groundwater levels was determined by mean air temperature through its effect on the soil thaw-freeze process, accounting for 53.15% of total variation. Meanwhile, ET0 and rainfall exerted little impact on the seasonal variation of groundwater levels, which might be attributed to the aquitard of frozen soil that impedes the exchange between surface water and groundwater. Moreover, there was a lag between groundwater levels and soil freezing-thawing. During the non-frozen period, the mean air temperature was again the most important factor impacting the variation of groundwater levels, through its effect on ET0 , and accounted for 40.75% of total variation, while rainfall had little effect on groundwater levels when rainfall intensity was less than 12 mm/day. These results will benefit predictions of future trends in groundwater levels within the context of global warming.

Ecosystem Carbon Storage in Alpine Grassland on the Qinghai Plateau.

The alpine grassland ecosystem can sequester a large quantity of carbon, yet its significance remains controversial owing to large uncertainties in the relative contributions of climate factors and grazing intensity. In this study we surveyed 115 sites to measure ecosystem carbon storage (both biomass and soil) in alpine grassland over the Qinghai Plateau during the peak growing season in 2011 and 2012. Our results revealed three key findings. (1) Total biomass carbon density ranged from 0.04 for alpine steppe to 2.80 kg C m-2 for alpine meadow. Median soil organic carbon (SOC) density was estimated to be 16.43 kg C m-2 in alpine grassland. Total ecosystem carbon density varied across sites and grassland types, from 1.95 to 28.56 kg C m-2. (2) Based on the median estimate, the total carbon storage of alpine grassland on the Qinghai Plateau was 5.14 Pg, of which 94% (4.85 Pg) was soil organic carbon. (3) Overall, we found that ecosystem carbon density was affected by both climate and grazing, but to different extents. Temperature and precipitation interaction significantly affected AGB carbon density in winter pasture, BGB carbon density in alpine meadow, and SOC density in alpine steppe. On the other hand, grazing intensity affected AGB carbon density in summer pasture, SOC density in alpine meadow and ecosystem carbon density in alpine grassland. Our results indicate that grazing intensity was the primary contributing factor controlling carbon storage at the sites tested and should be the primary consideration when accurately estimating the carbon storage in alpine grassland.

Methane emissions by alpine plant communities in the Qinghai-Tibet Plateau.

For the first time to our knowledge, we report here methane emissions by plant communities in alpine ecosystems in the Qinghai-Tibet Plateau. This has been achieved through long-term field observations from June 2003 to July 2006 using a closed chamber technique. Strong methane emission at the rate of 26.2+/-1.2 and 7.8+/-1.1microg CH4 m-2h-1 was observed for a grass community in a Kobresia humilis meadow and a Potentilla fruticosa meadow, respectively. A shrub community in the Potentilla meadow consumed atmospheric methane at the rate of 5.8+/-1.3microg CH4 m-2h-1 on a regional basis; plants from alpine meadows contribute at least 0.13Tg CH4 yr-1 in the Tibetan Plateau. This finding has important implications with regard to the regional methane budget and species-level difference should be considered when assessing methane emissions by plants.