Alpine Steppe Research Articles

A novel alpine land cover classification strategy based on a deep convolutional neural network and multi-source remote sensing data in Google Earth Engine

ABSTRACT Alpine land cover (ALC) is facing many challenges with climatic change, biodiversity reduction and other cascading ecosystem damage triggered by natural and anthropogenic interference. Although several global land cover products and thematic maps are already available, their mapping accuracy of alpine and montane regions remains unsatisfactory due to the data acquisition, methodology, and workflow design constraints. Therefore, in this paper, a deep convolutional neural network (DCNN) in Google Earth Engine (GEE) was developed to map the ALC types of the Yarlung Zangbo river basin (YZRB) in the Tibetan plateau using multi-source remote sensing data. The DCNN algorithm was offline trained using automatically generating samples and online deployed in the GEE for a large-scale ALC mapping. Moreover, a set of fine land cover classification system (containing 14 ALC types) was also established in accordance with the natural situation of the YZRB. The overall accuracy and kappa were 86.24% and 0.8156, which were higher than traditional classification algorithms. The spatial distribution of ALC types was analyzed in different gradient zones, and a clear altitudinal characteristic was noticed. The terrain of the YZRB from upper-stream to down-stream with an elevation dramatically decreases, and corresponding to vertical zonal changes from glacier and permanent snow/ice, barren gravel land, alpine desert steppe, alpine steppe, alpine meadow, shrubs, to tree cover. The product can provide valuable land cover information to support alpine ecosystem conservation.

Using the dynamics of productivity and precipitation-use efficiency to detect state transitions in Eurasian grasslands

In the face of accelerated global dryland expansion and grassland degradation, signaling grassland ecosystem state transitions is an ongoing challenge in ecology. However, there is still a lack of effective indicators and understanding of the mechanisms of grassland ecosystem state transitions at the continental scale. Here, we propose a framework that links ecosystem function-based indicators and critical slowing down (CSD) theory to reveal grassland state transitions. Across precipitation gradients, we quantified the statistical characteristics and spatial patterns in ANPP and PUE dynamics (variability, asymmetry, and sensitivity to precipitation and temperature) in Eurasian grasslands. We show that the CVANPP, CVPUE, AANPP, APUE, SPUE-P, and SANPP-P of temperate steppes were significantly higher than those of alpine steppes, while the SPUE-T and SANPP-T were the inverse. In temperate grasslands, AANPP, APUE, and SANPP-P indicated the transition of typical steppes, and CVANPP, APUE, and SPUE-T indicated the transition from meadow to typical steppes. In alpine grasslands, APUE indicated the transition between alpine deserts and alpine steppes, and AANPP and SANPP-P indicated the transition between alpine steppes and meadow steppes. The interannual variability of precipitation strongly affected xerophyte proportion and demographic processes, which control state transitions in low-resilience grasslands. Community structures and limiting factors (nutrient, light, and/or temperature) regulate state transitions in high-resilience grasslands. Our results demonstrate that function-based indicators are predictive of impending state transitions of temperate and alpine grasslands, highlighting the complementation of ANPP and PUE dynamics that have the potential for predicting grassland ecosystem regime shifts and their underlying mechanisms.

Dynamics and controls of ecosystem multiserviceability across the Qingzang Plateau

Ecosystem multiserviceability (EMS), a comprehensive and significant ecological indicator, reflects the capacity of ecosystems to offer multiple services concurrently. Intensified climate change and human activity are continuously altering ecosystem functions, services, and EMSs. However, numerous studies have only focused on one or a few ecosystem services, rarely taking into account spatial-temporal distribution and drivers of EMS on behalf of different agencies. We calculated EMS including pastoralist (PA), environmental protection agency (EPA), biodiversity conservation agency (BCA), and climate change mitigation agency (CCMA) using grassland production, habitat quality, water conservation, and carbon sequestration. Then, the effects of geographical features, climate factors, and human activities on spatial-temporal patterns of EMS were explored. The result indicated that EMS showed a decreasing tendency from the southeast to northwest on the Qingzang Plateau (QZP). Meanwhile, there were no obvious fluctuations in four simulated scenarios (PA, EPA, BCA and CCMA) among different vegetation types during 2000 to 2015. Notably, EMS of all simulated scenarios decreased in the alpine steppe ecosystem, but negligible changes were found in other ecosystems from 2015 to 2020. Moreover, the relative importance of precipitation in annual mean value (from 2000 to 2020) of PA, EPA, BCA and CCMA were 0.13, 0.11, 0.30 and 0.19, respectively. Overall, precipitation played the dominant role on the dynamics of EMS, followed by elevation and human footprint. Our findings highlighted that understanding the patterns and drivers of EMS could provide a reference for the regional management and maintenance of ecosystem stability on QZP.

Implications for water management in alpine inland river basins: Evidence from stable isotopes and remote sensing

Elucidating the water surplus and loss of different vegetation landscapes in cold regions is important for the conservation and management of water resources in alpine inland rivers. As such, this study is to systematically reveal the water variation in different vegetation landscape zones of the alpine inland river basin, delineate its water resources protection zones, and propose its water resources management strategies. In addition, the study confirms that stable isotope and remote sensing techniques can quantify the variations of water surplus and loss in different vegetation zones of the Qinghai Lake Shaliu River basin, and identifies the alpine desert zone as an important water-producing zone, the alpine meadow zone as an important water storage zone, and the alpine steppe zone as the main water-consuming zone of the basin. At the same time, the alpine meadow zone was also the area with the strongest evapotranspiration. The variations of water surplus and loss in different vegetation zones depended significantly on elevation, and the quality of ecological environment profoundly affected the water holding capacity of the basin. Therefore, according to the variations of water surplus and loss in different vegetation zones of the basin, the alpine desert zone and the alpine meadow zone were the important water resources core protection areas for water production and storage in the basin, and the alpine steppe zone was the general water resources protection area in the basin. The results of this study indicated that the water resources management strategy of alpine inland river basin should be a composite model that improves the quality of ecological environment and combines core protection of water resources in the middle and upper reaches with effective management of water resources in the lower reaches.

Grazing and reclamation-induced microbiome alterations drive organic carbon stability within soil aggregates in alpine steppes

Grazing and reclamation are the major modulators of soil organic carbon (SOC) stability in alpine steppes. However, our understanding of changes in SOC caused by grazing and reclamation at the aggregate scale is limited, and the mediating role of microorganisms remains unclear. Here, based on a long-term observation transect, we selected three land-use types: a long-term enclosed natural steppe (NS), a grazed steppe (GS), and a steppe reclaimed as cropland (CL). We investigated the impacts of grazing and reclamation on soil aggregate distributions, SOC fractions and the microbial community, and microbial contributions to SOC stability. Overall, GS and CL significantly decreased the proportion of >2 mm aggregates (by 32.25–33.72%), and enhanced SOC stability within different aggregate sizes, with the highest SOC stability observed in 0.25–2 mm and <0.25 mm sizes. GS significantly decreased bacterial diversity and increased the relative abundance of Gammaproteobacteria, while CL significantly increased microbial diversity and the relative abundance of Alphaproteobacteria. Importantly, GS enhanced the complexity of the bacterial OTUs networks in >2 mm and <0.25 mm aggregates. GS and CL caused changes in the assembly processes of bacterial communities, shifting from being mainly controlled by variable selection to being mainly controlled by homogenizing dispersal. However, there were only minor differences observed in the microbial community assembly within different aggregate sizes under the same treatment. Random forest models and correlation analysis revealed that the bacterial community, especially the network patterns and community assembly, was a key determinant of SOC stability in soil aggregates. In conclusion, we emphasize the important contribution of soil bacterial network patterns and community assembly to SOC stability in the context of human activities, providing information that may be useful for developing alpine steppe management strategies to enhance soil carbon sequestration.

Coupling effects of soil and vegetation from an ecosystem service perspective

Soil provides diverse ecosystem services (ESs) to people, yet anthropogenic activities result in the degradation and loss of soil ESs. Therefore, there is an urgent need to take effective measures to protect and manage soils for sustainable development. However, the differences in ESs across soil types are not well understood, and the coupling effects of soil and vegetation on ESs at different altitudes remain unclear. In this study, the composition of soil and vegetation types under different altitude gradients were analyzed and the differences/similarities of ESs (in terms of water yield, carbon storage, and soil conservation) among different soil types were identified. Following this, the optimal soil and vegetation combinations under different altitude gradients were determined from an ES perspective. The results revealed that soil types and ESs differed markedly at each altitude gradient. ESs in the high-altitude zone were significantly higher than those in the low-altitude zone (p < 0.01). There was an obvious difference in the ES supply capacity of soil types, with brown earths and dark felty soils exhibiting higher ESs compared to purplish soils, paddy soils, red earths, and yellow earths. The felty soils and alpine steppe combination, brown coniferous forest soils and evergreen needleleaf forest combination, and brown earths and evergreen broadleaf forest combination provided the highest water yield, carbon storage, and soil conservation, respectively. Vegetation can promote or inhibitat soil ESs, depending on the vegetation and soil types. Based on the results, detailed soil and vegetation management measures were proposed for different altitudes. Dark-brown earths and dark felty soils were identified as priority soil types for protection. This study provides an important reference for soil management and landscape restoration.

PH: A core node of interaction networks among soil organo-mineral fractions

Mineral-associated organic matter (MAOM) is the largest soil organic carbon (OC) pool with the longest turnover. MAOM is expected to have relatively little sensitivity to climate change due to mineral protection, but its persistence involves several organo-mineral fractions. The uncertainty in the response of specific organo-mineral fractions to climate change hampers the reliability of predictions of MAOM preservation in the future. Here, we applied a sequential chemical fractionation method integrated with network analysis to investigate MAOM stabilization mechanisms across five alpine ecosystems: alpine desert, alpine steppe, alpine meadow, alpine wetland, and alpine forest. Hierarchical cluster analysis revealed grouping of seven extractable OM fractions in MAOM into three OM clusters: a cluster with weak bondings consisting of water-soluble OM (WSOM) and weakly adsorbed fractions (2.1–21.3% of total OC); a cluster with metal-bound complexes comprising Ca-OM complexes and Fe/Al-OM complexes (3.8–12.2% of total OC); and a cluster with strong bonding composed of Al oxyhydroxides, carbonates and Fe oxyhydroxides (12.2–33.5% of total OC). The relative percentages of OM from soils of the five ecosystems in the three clusters exhibited distinct pH dependence patterns. With the increase in pH, the cluster with weak bondings decreased, and that with strong bondings increased, while the one with metal-bound complexes showed a maximum at weakly acidic pH. Organo-mineral fractions and metal cations in MAOM constructed a complex network with pH as the central node. Results suggest that precipitation does not only alter vegetation type and microbial biomass but also regulate soil pH, which is balanced by specific metal cations, thus resulting in particular pH preference of specific OM clusters. These findings demonstrate that soil pH plays a central role in unveiling MAOM dynamics and can serve as a good predictor of soil organo-mineral fractions across alpine ecosystems.

Vegetation stability characterized the central Tibetan Plateau over the last two millennia but has recently begun to change

The vegetation history of the central Tibetan Plateau over the last two millennia provides an important baseline for exploring future vegetation evolution. In this paper, we analyze high-resolution records of pollen, grain-size, total organic carbon (TOC) and total nitrogen (TN) for a 66.5 cm deep sediment core collected from Beilei Co on the central Tibetan Plateau. Between ca. 210 CE and 1988 CE, pollen spectra together with other proxies show that the Beilei Co region was covered by alpine steppe and experienced a relatively stable environment, with only slight changes in vegetation composition and minor climatic variations. However, since 1988 CE, abundances of Artemisia and Cyperaceae have begun to increase, while those of Chenopodiaceae (current accepted Latin name is Amaranthaceae) and Asteraceae have decreased sharply. Both the pollen assemblages and other proxies show that the study area is currently undergoing a major change and that the period of vegetation stability that has characterized the past two millenia has now ended. We argue that the recent changes in the vegetation may be caused by increasing precipitation and/or thawing permafrost due to global warming. In the future, the alpine steppe around Beilei Co may be replaced by alpine meadow.

Impacts of Climate Change and Human Activities on Plant Species α-Diversity across the Tibetan Grasslands

Plant species α-diversity is closely correlated with ecosystem structures and functions. However, whether climate change and human activities will reduce plant species α-diversity remains controversial. In this study, potential (i.e., potential species richness: SRp, Shannonp, Simpsonp and Pieloup) and actual plant species α-diversity (i.e., actual species richness: SRa, Shannona, Simpsona and Pieloua) during 2000–2020 were quantified based on random forests in grasslands on the Tibetan Plateau. Overall, climate change had positive influences on potential plant species α-diversity across all the grassland systems. However, more than one-third areas showed decreasing trends for potential plant species α-diversity. Climate change increased the SRp at rates of 0.0060 and 0.0025 yr−1 in alpine steppes and alpine meadows, respectively. Temperature change predominated the variations of Shannonp and Simpsonp, and radiation change predominated the variations of SRp and Pieloup. Geography position, local temperature, precipitation and radiation conditions regulated the impacts of climate change on potential species α-diversity. On average, human activities caused 1% plant species loss but elevated the Shannon, Simpson and Pielou by 26%, 4% and 5%, respectively. There were 46.51%, 81.08%, 61.26% and 61.10% areas showing positive effects of human activities on plant species richness, Shannon, Simpson and Pielou, respectively. There were less than 48% areas showing increasing trends of human activities’ impacts on plant species α-diversity. Human activities increased plant species richness by 2% in alpine meadows but decreased plant species richness by 1% in alpine steppes. Accordingly, both the impacts of climate change and human activities on plant species α-diversity were not always negative and varied with space and grassland types. The study warned that both climate change and human activities may not cause as much species loss as expected. This study also cautioned that the impacts of radiation change on plant species α-diversity should be at least put on the same level as the impacts of climate warming and precipitation change on plant α-diversity.

Geographical patterns and drivers of plant productivity and species diversity in the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) has three main grassland types: alpine meadow, alpine steppe, and alpine desert steppe. In this study, we asked how plant productivity and species diversity vary with altitude, longitude and latitude in alpine grasslands of the QTP. We then identified the environmental factors that drive these observed patterns of plant productivity and species diversity. We found that although plant productivity and species diversity varied greatly across large-scale longitudinal and latitudinal gradients, these changes were strongest across the longitudinal gradient. This finding indicates that moisture rather than temperature has the greatest impact on plant productivity and species diversity of the alpine grasslands in the QTP. We also found that besides soil and climate factors, partial pressure of carbon dioxide (pCO2) also has significant effects on plant productivity, and barometric pressure and partial pressure of oxygen (pO2) also have significant effects on species diversity. Furthermore, the relationship between the biomass of grassland-dominant species and species diversity was affected by the spatial scale at which these factors were studied. Our study provides new insights into the interconnections between plant productivity and species diversity and the major factors that influence alpine grasslands. It also provides a scientific basis for the maintenance of plant diversity and ecosystem functions in hypoxic (low-oxygen) regions.

Impacts of human pressure and climate on biodiversity-multifunctionality relationships on the Qinghai-Tibetan Plateau.

Many studies have investigated the effects of environmental context on biodiversity or multifunctionality in alpine regions, but it is uncertain how human pressure and climate may affect their relationships. Here, we combined the comparative map profile method with multivariate datasets to assess the spatial pattern of ecosystem multifunctionality and further identify the effects of human pressure and climate on the spatial distribution of biodiversity-multifunctionality relationships in alpine ecosystems of the Qinghai-Tibetan Plateau (QTP). Our results indicate that at least 93% of the areas in the study region show a positive correlation between biodiversity and ecosystem multifunctionality across the QTP. Biodiversity-multifunctionality relationships with increasing human pressure show a decreasing trend in the forest, alpine meadow, and alpine steppe ecosystems, while an opposite pattern was found in the alpine desert steppe ecosystem. More importantly, aridity significantly strengthened the synergistic relationship between biodiversity and ecosystem multifunctionality in forest and alpine meadow ecosystems. Taken together, our results provide insights into the importance of protecting and maintaining biodiversity and ecosystem multifunctionality in response to climate change and human pressure in the alpine region.

Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth’s Third Pole

The carbon sequestration capacity of alpine grasslands, composed of alpine meadows and steppes, in the Tibetan Plateau has an essential role in regulating the regional carbon cycle. However, inadequate understanding of its spatiotemporal dynamics and regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed the spatial and temporal patterns and mechanisms of the net ecosystem exchange (NEE) of carbon dioxide in the Tibetan Plateau. The carbon sequestration of the alpine grasslands ranged from 26.39 to 79.19 Tg C year-1 and had an increasing rate of 1.14 Tg C year-1 between 1982 and 2018. While alpine meadows were relatively strong carbon sinks, the semiarid and arid alpine steppes were nearly carbon neutral. Alpine meadow areas experienced strong increases in carbon sequestration mainly because of increasing temperatures, while alpine steppe areas had weak increases mainly due to increasing precipitation. Carbon sequestration capacity of alpine grasslands on the plateau has undergone persistent enhancement under a warmer and wetter climate.

Carbon budgets and environmental controls in alpine ecosystems on the Qinghai-Tibet Plateau

Rapid warming in alpine regions exerts important effects on carbon cycling in alpine ecosystem, which are sensitive to environmental changes. So far, little is known about the spatial and temporal variation in carbon budgets and the main influencing factors over different ecosystems. Here, we examined the monthly and annual gross primary production (GPP), net ecosystem CO2 exchange (NEE) and ecosystem respiration (ER) during 2004–2017 in four types of ecosystems (i.e., alpine meadow, steppe, forest and cropland) on the Tibetan Plateau. We explored the relationships between carbon fluxes and environmental factors. The results show that forest, cropland and alpine meadow ecosystems acted as carbon sinks, with NEE values ranging from −21.25 ± 3.54 to −308.75 ± 21.65 g C m-2a-1, while alpine steppe and overmature forest ecosystems serve as carbon sources (mean annual NEE: 23.12 ± 15.88 g C m-2a-1). The temperature sensitivity values (Q10) of ER in the forest (9.39) and alpine steppe (7.47) ecosystems were greater than those in the alpine meadow ecosystems (Q10 = 4.20), indicating that the carbon emissions in the forest and alpine steppe ecosystems were more sensitive to warming. Multiple linear regression analysis indicated that the carbon fluxes (GPP, NEE, ER) of alpine steppe and alpine meadow in the permafrost regions were more sensitive to water forcing (precipitation, soil water content), while in the forest and cropland ecosystems temperature forcing (air and soil temperature) were strong predictors of all the carbon flux indices. Our results showed differential responses of carbon budgets among ecosystems, which could be considered in the future modeling of carbon cycle in alpine regions.

A functional metagenomics study of soil carbon and nitrogen degradation networks and limiting factors on the Tibetan plateau.

The Three-River Source Nature Reserve is located in the core area of the Qinghai-Tibetan Plateau, with the alpine swamp, meadow and steppe as the main ecosystem types. However, the microbial communities in these alpine ecosystems, and their carbon and nitrogen degrading metabolic networks and limiting factors remain unclear. We sequenced the diversity of bacteria and fungi in alpine swamps, meadows, steppes, and their degraded and artificially restored ecosystems and analyzed soil environmental conditions. The results indicated that moisture content had a greater influence on soil microbial community structure compared to degradation and restoration. Proteobacteria dominated in high moisture alpine swamps and alpine meadows, while Actinobacteria dominated in low moisture alpine steppes and artificial grasslands. A metabolic network analysis of carbon and nitrogen degradation and transformation using metagenomic sequencing revealed that plateau microorganisms lacked comprehensive and efficient enzyme systems to degrade organic carbon, nitrogen, and other biological macromolecules, so that the short-term degradation of alpine vegetation had no effect on the basic composition of soil microbial community. Correlation analysis found that nitrogen fixation was strong in meadows with high moisture content, and their key nitrogen-fixing enzymes were significantly related to Sphingomonas. Denitrification metabolism was enhanced in water-deficient habitats, and the key enzyme, nitrous oxide reductase, was significantly related to Phycicoccus and accelerated the loss of nitrogen. Furthermore, Bacillus contained a large number of amylases (GH13 and GH15) and proteases (S8, S11, S26, and M24) which may promote the efficient degradation of organic carbon and nitrogen in artificially restored grasslands. This study illustrated the irrecoverability of meadow degradation and offered fundamental information for altering microbial communities to restore alpine ecosystems.

Carbon in Chinese grasslands: meta-analysis and theory of grazing effects

Globally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha−1) and typical steppes (3 to 4 sheep ha−1), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha−1) and alpine steppes (7 to 8 sheep ha−1) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the ‘intermediate disturbance hypothesis’. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha−1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks.Graphical

Environmental changes drive soil microbial community assembly across arid alpine grasslands on the Qinghai-Tibetan Plateau, China

Soil microbes play a key role in regulating ecosystem functions in arid alpine grasslands, which are extremely sensitive to environmental changes. However, the exact mechanism by which multiple environmental factors interact to shape local soil microbial community assembly is unclear. Therefore, exploring how changing environmental factors affect microbial community assembly responds to will help us predict microbial-mediated ecosystem processes under climate change. Here, we conducted large-scale field sampling from 30 alpine grassland sites (e.g., alpine meadow (AM), alpine steppe (AS) and alpine desert steppe (ADS)) across arid ecosystems on the Qinghai-Tibetan Plateau (QTP), China. Soil bacterial and fungal community assembly and their relationships with spatial, climatic, and vegetation-soil factors were studied with the Molecular Ecological Network Analysis Pipeline (MENAP), analysis of variance (ANOVA), canonical correspondence analysis (CCA) and structural equation models (SEMs). The results showed that the soil microbial diversity and co-occurrence network complexity increased significantly from ADS to AS and AM, and bacteria were more susceptible to environmental factors than fungi. The relative abundances of the dominant bacterial phyla, including Acidobacteria, Proteobacteria, Actinobacteria and Gemmatimonadetes, showed a statistically significant increase, while the relative abundance of the fungal phyla Basidiomycota and Glomeromycota showed significant differences across arid alpine grasslands. Variation partitioning analysis (VPA) revealed that vegetation-soil factors contributed the most to explaining the bacterial community composition, whereas spatial factors contributed the most to explaining the variation in the fungal community composition. The results obtained from the SEMs suggested that latitude and soil pH had the greatest impact on the diversity of bacteria and fungi, respectively. Taken together, the results of this study provide a comprehensive perspective on how the soil microbial communities respond to changes in environmental factors across arid alpine grasslands on the QTP, China.

Differences in respiration components and their dominant regulating factors across three alpine grasslands on the Qinghai−Tibet Plateau

Greenhouse gases (GHGs) emissions from high-cold terrestrial ecosystems underlain by permafrost on the Qinghai–Tibet Plateau (QTP) have received widespread attention. However, the dominant factors regulating ecosystem respiration (Re) and its components (soil respiration Rs and heterotrophic respiration Rh) and how the differences in carbon emissions from different ecotypes and seasons remain are still unclear. We conducted a 2-year field investigation (August 2018 to October 2020) and applied the structural equation model (SEM) to clarify the changes in the factors controlling the respiration components during different seasons. The results indicate that the Re and its controlling factors in three alpine grassland ecosystems (alpine steppe, alpine meadow, and swamp meadow) vary with seasons. Furthermore, autotrophic respiration (Ra) contributes the most to the seasonal changes in Re. The Re gradually increases in the early growing season and rapidly decreases in the late growing season. Rh remains relatively stable during the year. Under these seasonal variations in the respiration components, the dominant factors controlling Re in the nongrowing season are the temperature of the atmosphere–soil interface (heat flux, atmospheric temperature, and soil temperature at 5 cm depth) and microbial activity (microbial carbon and pH) with the variable importance projections >1.5. During the growing season, the dominant factors regulating Re, Rs, and Rh are the soil temperature with a standardized direct effect (SDE) of 0.424, soil nutrient conditions (total nitrogen and pH) with SDEs of 0.570–0.614, and microbial activity (microbial carbon) with a SDE of 0.591, respectively. In addition, meteorological conditions have an important impact on the respiration components during the growing season. Specifically, the atmospheric vapor pressure is the dominant factor regulating the three respiration components (standardized total effects = 0.44−0.53, p < 0.001). The optimal soil water contents during the growing season (water content at which Re reaches the maximum) are 10% in the alpine steppe, 13%–15% in the alpine meadow, and 40%–43% in the swamp meadow, respectively. The effect of the soil water content on Re is more important in arid ecosystems (alpine steppe and alpine meadow) than in wet ecosystem (swamp meadow). The alleviation of water limitations in arid ecosystems may potentially increase Re.

Shrub encroachment increases soil carbon and nitrogen stocks in alpine grassland ecosystems of the central Tibetan Plateau

Shrub encroachment can significantly affect the ecosystem structure and functioning of alpine grasslands. However, little is known about how this phenomenon alters soil organic carbon stocks (SOCS) and soil nitrogen stocks (STNS) in different alpine grassland ecosystems within the same region. Here we addressed this research gap by investigating the SOCS and STNS of encroached and non-encroached plots in alpine meadow and alpine steppe ecosystems on the central Tibetan Plateau. We found that, in both ecosystems, shrub encroachment significantly increased herbaceous plant richness, diversity, and aboveground biomass, but more notably in alpine meadow. Conversely, shrub encroachment increased belowground plant biomass in alpine steppe but had the opposite effect in alpine meadow, where belowground biomass was four times lower at encroached than at non-encroached plots. Importantly, encroaching shrubs resulted in significantly higher SOCS and STNS in both ecosystems, with alpine steppe showing the greatest carbon and nitrogen gains. The shrub encroached plots had 34.24 % and 97.25 % higher carbon stocks and 70.87 % and 67.34 % higher nitrogen stocks than non-encroached plots at the alpine meadow and alpine steppe, respectively. Increases in carbon and nitrogen stocks occurred mostly at the 10–30 cm soil layer and were highly correlated with shrub-induced changes in the herbaceous community composition. Overall, our results indicated that (1) shrub encroachment promoted carbon and nitrogen accumulation in the soils of both alpine meadow and alpine steppe and (2) the degree of accumulation and the mechanisms behind these changes varied between the two alpine grasslands. Our findings advance the general understanding of the soil carbon and nitrogen dynamics in shrub‐encroached alpine grasslands and highlight the importance of investigating how this phenomenon affects different ecosystems within the same region.

Quantifying the Contribution of Driving Factors on Distribution and Change of Net Primary Productivity of Vegetation in the Mongolian Plateau

In recent years, multiple disturbances have significantly altered terrestrial ecosystems in arid and semi-arid regions, particularly on the Mongolian Plateau (MP). Net primary productivity (NPP) of vegetation is an essential component of the surface carbon cycle. As such, it characterizes the state of variation in terrestrial ecosystems and reflects the productive capacity of natural vegetation. This study revealed the complex relationship between the natural environment and NPP in the ecologically fragile and sensitive MP. The modified Carnegie–Ames–Stanford Approach (CASA) model was used to simulate vegetation NPP. Further, the contributions of topography, vegetation, soils, and climate to NPP’s distribution and spatiotemporal variation were explored using the geographic detector model (GDM) and structural equation model (SEM). The study’s findings indicate the following: (1) NPPs for different vegetation types in the MP were in the order of broad-leaved forest &gt; meadow steppe &gt; coniferous forest &gt; cropland &gt; shrub &gt; typical steppe &gt; sandy land &gt; alpine steppe &gt; desert steppe. (2) NPP showed an increasing trend during the growing seasons from 2000 to 2019, with forests providing larger vegetation carbon stocks. It also maintained a more stable level of productivity. (3) Vegetation cover, precipitation, soil moisture, and solar radiation were the key factors affecting NPP’s spatial distribution. NPP’s spatial distribution was primarily explained by the normalized difference vegetation index, solar radiation, precipitation, vegetation type, soil moisture, and soil type (-statistics = 0.86, 0.71, 0.67, 0.67, 0.57, and 0.57, respectively); the contribution of temperature was small (-statistics = 0.26), and topographic factors had the least influence on NPP’s distribution, as their contribution amounted to less than 0.20. (4) A SEM constructed based on the normalized difference vegetation index (NDVI), solar radiation, precipitation, temperature, and soil moisture explained 17% to 65% of the MP’s NPP variations. The total effects of the MP’s NPP variations in absolute values were in the order of NDVI (0.47) &gt; precipitation (0.33) &gt; soil moisture (0.16) &gt; temperature (0.14) &gt; solar radiation (0.02), and the mechanisms responsible for NPP variations differed slightly among the relevant vegetation types. Overall, this study can help understand the mechanisms responsible for the MP’s NPP variations and offer a new perspective for regional vegetation ecosystem management.

Characteristics and drivers of plant C, N, and P stoichiometry in Northern Tibetan Plateau grassland.

Understanding vegetation C, N, and P stoichiometry helps us not only to evaluate biogeochemical cycles and ecosystem functions but also to predict the potential impact of environmental change on ecosystem processes. The foliar C, N, and P stoichiometry in Northern Tibetan grasslands, especially the controlling factors, has been highlighted in recent years. In this study, we have collected 340 plant samples and 162 soil samples from 54 plots in three grassland types, with the purpose of evaluating the foliar C, N, and P stoichiometry and underlying control factors in three grassland types along a 1,500-km east-to-west transect in the Northern Tibetan Plateau. Our results indicated that the averaged foliar C, N, and P concentrations were 425.9 ± 15.8, 403.4 ± 22.2, and 420.7 ± 30.7g kg-1; 21.7 ± 2.9, 19.0 ± 2.3, and 21.7 ± 5.2g kg-1; and 1.71 ± 0.29, 1.19 ± 0.16, and 1.59 ± 0.6g kg-1 in the alpine meadow (AM), alpine steppe (AS), and desert steppe (DS) ecosystems, respectively. The foliar C and N ratios were comparable, with values of 19.8 ± 2.8, 20.6 ± 1.9, and 19.9 ± 5.8 in the AM, AS, and DS ecosystems, respectively. Both the C/P and N/P ratios are the lowest in the AM ecosystem, with values of 252.2 ± 32.6 and 12.8 ± 1.3, respectively, whereas the highest values of 347.3 ± 57.0 and 16.2 ± 3.2 were obtained in the AS ecosystem. In contrast, the soil C, N, C/P, and N/P values decreased from the AM to DS ecosystem. Across the whole transects, leaf C, N, and P stoichiometry showed no obvious trend, but soil C and N concentrations showed an increasing trend, and soil P concentrations showed a decreasing trend with the increasing longitude. Based on the general linear model analysis, the vegetation type was the dominant factor controlling the leaf C, N, and P stoichiometry, accounting for 42.8% for leaf C, 45.1% for leaf N, 35.2% for leaf P, 52.9% for leaf C/N, 39.6% for leaf C/P, and 48.0% for leaf N/P; the soil nutrients and climate have relatively low importance. In conclusion, our results supported that vegetation type, rather than climatic variation and soil nutrients, are the major determinants of north Tibet grassland leaf stoichiometry.