Shifting plant species composition in response to climate change stabilizes grassland primary production.

The structure and function of alpine grassland ecosystems, including their extensive soil carbon stocks, are largely shaped by temperature. The Tibetan Plateau in particular has experienced significant warming over the past 50 y, and this warming trend is projected to intensify in the future. Such climate change will likely alter plant species composition and net primary production (NPP). Here we combined 32 y of observations and monitoring with a manipulative experiment of temperature and precipitation to explore the effects of changing climate on plant community structure and ecosystem function. First, long-term climate warming from 1983 to 2014, which occurred without systematic changes in precipitation, led to higher grass abundance and lower sedge abundance, but did not affect aboveground NPP. Second, an experimental warming experiment conducted over 4 y had no effects on any aspect of NPP, whereas drought manipulation (reducing precipitation by 50%), shifted NPP allocation belowground without affecting total NPP. Third, both experimental warming and drought treatments, supported by a meta-analysis at nine sites across the plateau, increased grass abundance at the expense of biomass of sedges and forbs. This shift in functional group composition led to deeper root systems, which may have enabled plant communities to acquire more water and thus stabilize ecosystem primary production even with a changing climate. Overall, our study demonstrates that shifting plant species composition in response to climate change may have stabilized primary production in this high-elevation ecosystem, but it also caused a shift from aboveground to belowground productivity.

Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change.

Satellite data indicate significant advancement in alpine spring phenology over decades of climate warming, but corresponding field evidence is scarce. It is also unknown whether this advancement results from an earlier shift of phenological events, or enhancement of plant growth under unchanged phenological pattern. By analyzing a 35-year dataset of seasonal biomass dynamics of a Tibetan alpine grassland, we show that climate change promoted both earlier phenology and faster growth, without changing annual biomass production. Biomass production increased in spring due to a warming-induced earlier onset of plant growth, but decreased in autumn due mainly to increased water stress. Plants grew faster but the fast-growing period shortened during the mid-growing season. These findings provide the first in situ evidence of long-term changes in growth patterns in alpine grassland plant communities, and suggest that earlier phenology and faster growth will jointly contribute to plant growth in a warming climate.

Differential responses of CO2 and latent heat fluxes to climatic anomalies on two alpine grasslands on the northeastern Qinghai-Tibetan Plateau.

Discrete extreme heat events, deluges, and droughts will become more frequent and disproportionately affect the processes and functions of grassland ecosystems. Here, we compared the responses of CO2 and heat fluxes to natural extreme events in 2016 in a lower alpine meadow and neighboring upper shrubland on the northeastern Qinghai-Tibetan Plateau. Unlike insensitive sensible heat flux, latent heat flux (LE) increased by 21.8 % in the meadow and by 56.4 % in the shrubland during a dry period and subsequent compound hot-dry period in August. Changes (Δ, data for 2016 minus the corresponding means from other years) in the heat flux at both sites were determined by changes in solar radiation (ΔSwin), as sufficient soil moisture was available. ΔLE was more sensitive to ΔSwin in the open-canopy shrubland, reflecting its greater capacity for evaporative cooling to buffer climate anomalies. CO2 fluxes responded weakly to extreme wet or dry events but strongly when those events were accompanied by exceptional heat. During single or compound hot events, the mean changes in total ecosystem respiration (ΔTER) increased by about 30 % in both grasslands, although ΔTER was more sensitive to changes in the topsoil temperature in the more productive meadow than in the shrubland. The mean changes in gross primary productivity (ΔGPP) fluctuated by <10 % in the warmer meadow but increased by 29.3 % in the cooler shrubland relative to the respective baseline, probably because of the differences in canopy structure and root depth and the consequent high-temperature stress on vegetation photosynthesis. The changes in net ecosystem CO2 exchange (ΔNEE) were significantly related to ΔTER in the meadow and increased by 55.8 %, whereas ΔNEE was controlled mainly by ΔGPP in the shrubland and decreased by 22.4 %. Overall, both alpine grasslands were resistant to rainfall anomalies but susceptible to exceptional warmth, with the differential responses being ascribed to canopy structure and root depth. Our results provide helpful insights based on which the carbon sequestration and water-holding functions of alpine grasslands during future climate change can be predicted.

Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.

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.

Stability response of alpine meadow communities to temperature and precipitation changes on the Northern Tibetan Plateau.

Biomass temporal stability plays a key role in maintaining sustainable ecosystem functions and services of grasslands, and climate change has exerted a profound impact on plant biomass. However, it remains unclear how the community biomass stability in alpine meadows responds to changes in some climate factors (e.g., temperature and precipitation). Long-term field aboveground biomass monitoring was conducted in four alpine meadows (Haiyan [HY], Henan [HN], Gande [GD], and Qumalai [QML]) on the Qinghai-Tibet Plateau. We found that climate factors and ecological factors together affected the community biomass stability and only the stability of HY had a significant decrease over the study period. The community biomass stability at each site was positively correlated with both the stability of the dominant functional group and functional groups asynchrony. The effect of dominant functional groups on community stability decreased with the increase of the effect of functional groups asynchrony on community stability and there may be a 'trade-off' relationship between the effects of these two factors on community stability. Climatic factors directly or indirectly affect community biomass stability by influencing the stability of the dominant functional group or functional groups asynchrony. Air temperature and precipitation indirectly affected the community stability of HY and HN, but air temperature in the growing season and nongrowing season had direct negative and direct positive effects on the community stability of GD and QML, respectively. The underlying mechanisms varied between community composition and local climate conditions. Our findings highlighted the role of dominant functional group and functional groups asynchrony in maintaining community biomass stability in alpine meadows and we highlighted the importance of the environmental context when exploring the stability influence mechanism. Studies of community stability in alpine meadows along with different precipitation and temperature gradients are needed to improve our comprehensive understanding of the mechanisms controlling alpine meadow stability.

Interannual characteristics and driving mechanism of CO2 fluxes during the growing season in an alpine wetland ecosystem at the southern foot of the Qilian Mountains.

The carbon process of the alpine ecosystem is complex and sensitive in the face of continuous global warming. However, the long-term dynamics of carbon budget and its driving mechanism of alpine ecosystem remain unclear. Using the eddy covariance (EC) technique-a fast and direct method of measuring carbon dioxide (CO2) fluxes, we analyzed the dynamics of CO2 fluxes and their driving mechanism in an alpine wetland in the northeastern Qinghai-Tibet Plateau (QTP) during the growing season (May-September) from 2004-2016. The results show that the monthly gross primary productivity (GPP) and ecosystem respiration (Re) showed a unimodal pattern, and the monthly net ecosystem CO2 exchange (NEE) showed a V-shaped trend. With the alpine wetland ecosystem being a carbon sink during the growing season, that is, a reservoir that absorbs more atmospheric carbon than it releases, the annual NEE, GPP, and Re reached -67.5 ± 10.2, 473.4 ± 19.1, and 405.9 ± 8.9 gCm-2, respectively. At the monthly scale, the classification and regression tree (CART) analysis revealed air temperature (Ta) to be the main determinant of variations in the monthly NEE and GPP. Soil temperature (Ts) largely determined the changes in the monthly Re. The linear regression analysis confirmed that thermal conditions (Ta, Ts) were crucial determinants of the dynamics of monthly CO2 fluxes during the growing season. At the interannual scale, the variations of CO2 fluxes were affected mainly by precipitation and thermal conditions. The annual GPP and Re were positively correlated with Ta and Ts, and were negatively correlated with precipitation. However, hydrothermal conditions (Ta, Ts, and precipitation) had no significant effect on annual NEE. Our results indicated that climate warming would be beneficial to the improvement of GPP and Re in the alpine wetland, while the increase of precipitation can weaken this effect.

Atmospheric water vapor and soil moisture jointly determine the spatiotemporal variations of CO2 fluxes and evapotranspiration across the Qinghai-Tibetan Plateau grasslands.

Alpine grasslands play important functions in mitigating climate change and regulating water resources. However, the spatiotemporal variability of their carbon and water budgets remains unquantified. Here, 47 site-year observations of CO2 and water vapor fluxes (ET) are analyzed at sites situated along a hydrothermal gradient across the Qinghai-Tibetan Plateau, including an alpine wetland (wettest), an alpine shrub (coldest), an alpine meadow, an alpine meadow-steppe, and an alpine steppe (driest and warmest). The results show that the benchmarks for annual net ecosystem exchange (NEE) are -79.3, -77.8, -66.7, 20.2, and 100.9 g C m-2 year-1 at the meadow, shrub, meadow-steppe, steppe, and wetland, respectively. The peak daily NEE normalized by peak leaf area index converges to 0.93 g C m-2 d-1 at the 5 sites. Except in the wetland (722.8 mm), the benchmarks of annual ET fluctuate from 511.0 mm in the steppe to 589.2 mm in the meadow. Boosted regression trees-based analysis suggests that the enhanced vegetation index (EVI) and net radiation (Rn) determine the variations of growing season monthly CO2 fluxes and ET, respectively, although the effect is to some extent site-specific. Inter-annual variability in NEE, ecosystem respiration (RES), and ET are tightly (R2 > 0.60) related to the inter-growing season NEE, RES, and ET, respectively. Both annual RES and annual NEE are significantly constrained by annual gross primary productivity (GPP), with 85% of the per-unit GPP contributing to RES (R2 = 0.84) and 15% to NEE (R2 = 0.12). Annual GPP significantly correlates with annual ET alone at the drier sites of the meadow-steppe and the steppe, suggesting the coupling of carbon and water is moisture-dependent in alpine grasslands. Over half of the inter-annual spatial variability in GPP, RES, NEE, and ET is explained by EVI, atmospheric water vapor, topsoil water content, and bulk surface resistance (rs), respectively. Because the spatial variations of EVI and rs are strongly regulated by atmospheric water vapor (R2 = 0.48) and topsoil water content (R2 = 0.54), respectively, we conclude that atmospheric water vapor and topsoil water content, rather than the expected air/soil temperatures, drive the spatiotemporal variations in CO2 fluxes and ET across temperature-limited grasslands. These findings are critical for improving predictions of the carbon sequestration and water holding capacity of alpine grasslands.

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.

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.

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.

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.

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.

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.

[Periodic fluctuation features of air temperature, precipitation, and aboveground net primary production of alpine meadow ecosystem on Qinghai-Tibetan Plateau].

With Mexican Hat function as mother function, a wavelet analysis was conducted on the periodic fluctuation features of air temperature, precipitation, and aboveground net primary production (ANPP) in the Alpine Meadow Ecosystem Research Station, Chinese Academy of Sciences from 1980 to 2007. The results showed that there was a main period of 13 years for the annual fluctuations of air temperature, precipitation, and ANPP. A secondary period of 2 years for the annual fluctuations of air temperature and ANPP had lesser influence, whereas that of 4 years for the annual fluctuation of precipitation had greater effect. Lagged correlation analysis indicated that the annual fluctuation of ANNP was mainly controlled by the air temperature in a 20 years scale and had a weak 5-9 years lag effect, but there was a less correlation between ANPP and precipitation.