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[Display omitted] Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm. [ABSTRACT FROM AUTHOR]

• Non-linear patterns of microbial N genes occurred along precipitation gradient. • Breaking points were clearly related to certain soil types. • Attribution of different environmental factors varied by ecosystem. Despite the importance of microorganisms in soil nitrogen (N) cycling, studies on spatial patterns of microbial N-cycling gene abundances in temperate grasslands are still lacking, whose productivity is limited by N. Here, we investigated N functional genes in soil microorganisms from 60 sites in temperate grasslands across 1661 km in Inner Mongolia, China. Abundances of all N functional genes and 16S rDNA tended to decrease from northeast to southwest, consistent with the changing tend of precipitation but contrary to that of temperature. Non-linear saturation curves dominated patterns for abundances of most N functional genes and 16S rDNA along precipitation as they increased with the rising precipitation when <288–343 mm, but remained stable after these breaking points. Interestingly, these breaking points were clearly related to certain soil types, e.g. nifH did not change with precipitation in Chernozems and Gleysols, but increased with it in other soil types. Non-linear saturation patterns were also observed for most N functional gene and 16S rDNA abundances with temperature and soil total organic carbon. In contrast, no consistent spatial pattern for ratios of N functional genes: 16S rDNA was observed, which varied greatly by different N functional genes. Moreover, decay relationships were discovered for the abundance-based matrix of N functional genes over geographic distance. From the temperate meadows to typical steppes and to temperate desert steppes, the influence of relatively long-term environmental variables increased, but that of short-term ones decreased. Overall, we revealed non-linear patterns of N functional gene abundances along precipitation with a clear relationship with soil type, and discovered that attributions of geographic distance, plant community, historical-contingency and contemporary-disturbance to N functional gene community similarity decay were ecosystem–dependent. [ABSTRACT FROM AUTHOR]

Abstract Grazing intensity and global warming are expected to increase in the forthcoming decades, with uncertain consequences for their interaction on grassland ecosystems and their functions. We investigated the effects of warming, grazing and their interaction in a factorial warming (+1.2–1.7 °C) and grazing (moderate intensity with ca. 50% vegetation consumption) experiment in a Tibetan alpine meadow on microbial communities by studying functional genes involved in soil carbon and nitrogen cycles, using GeoChip technology. Our results showed that microbial functional gene structure and abundances were largely affected by the interactive effect of grazing and warming, rather than the main effect of warming or grazing. Compared to the control, grazing alone significantly increased the functional gene alpha diversity, changed the overall functional community structure, and increased the abundances of C fixation, C degradation, N mineralization and denitrification genes, likely due to the stimulating impact of urine and dung deposition. Warming alone did not change these microbial properties, possibly related to the unchanged soil nutrient status. Despite an increase in soil NO 3 − concentrations and the deposition of urine and dung, the combined treatment did not change functional gene alpha diversity, community structure, or C/N cycling gene abundances, possibly resulting from the limiting effect of water depletion in the combined treatment. Our study revealed antagonistic interactions between warming and grazing on microbial functional gene structure and abundances, which remained stable under the moderate intensity of grazing in future warming scenario in the Tibetan alpine meadow, raising potentially important implications for predicting future soil carbon and nitrogen processes in these systems. Highlights • Grazing alone significantly increased abundances of some key soil C/N cycling genes. • Warming alone had no significant effects on them. • Functional gene structure and abundances remained stable in the combined treatment. • Antagonistic interaction between warming and grazing may result from water depletion. [ABSTRACT FROM AUTHOR]

Resources can affect plant productivity and biodiversity simultaneously and thus are key drivers of their relationships in addition to plant–plant interactions. However, most previous studies only focused on a single resource while neglecting the nature of resource multidimensionality. Here we integrated four essential resources for plant growth into a single metric of resource diversity (RD) to investigate its effects on the productivity–biodiversity relationship (PBR) across Chinese grasslands. Results showed that habitats differing in RD have different PBRs—positive in low-resource habitats, but neutral in medium- and high-resource ones—while collectively, a weak positive PBR was observed. However, when excluding direct effects of RD on productivity and biodiversity, the PBR in high-resource habitats became negative, which leads to a unimodal instead of a positive PBR along the RD gradient. By integrating resource effects and changing plant–plant interactions into a unified framework with the RD gradient, our work contributes to uncovering underlying mechanisms for inconsistent PBRs at large scales. [ABSTRACT FROM AUTHOR]

The spatial variability of microorganisms in grasslands can provide important insights regarding the biogeographic patterns of microbial communities. However, information regarding the degree of overlap and partitions of microbial communities across different habitats in grasslands is limited. This study investigated the microbial communities in three distinct habitats from Xilingol steppe grassland, i.e. animal excrement, phyllosphere, and soil samples, by Illumina MiSeq sequencing. All microbial community structures, i.e. for bacteria, archaea, and fungi, were significantly distinguished according to habitat. A high number of unique microorganisms but few coexisting microorganisms were detected, suggesting that the structure of microbial communities was mainly regulated by species selection and niche differentiation. However, the sequences of those limited coexisting microorganisms among the three different habitats accounted for over 60% of the total sequences, indicating their ability to adapt to variable environments. In addition, the biotic interactions among microorganisms based on a co-occurrence network analysis highlighted the importance of Microvirga, Blastococcus, RB41, Nitrospira, and four norank members of bacteria in connecting the different microbiomes. Collectively, the microbial communities in the Xilingol steppe grassland presented strong habitat preferences with a certain degree of dispersal and colonization potential to new habitats along the animal excrement- phyllosphere-soil gradient. This study provides the first detailed comparison of microbial communities in different habitats in a single grassland, and offers new insights into the biogeographic patterns of the microbial assemblages in grasslands. [ABSTRACT FROM AUTHOR]

Highlights • Grazing interacted extreme drought timing to regulate steppe ecosystem CO 2 exchange. • Extreme drought reduced CO 2 uptake in a fenced steppe regardless of seasonal timing. • Early-season drought caused largest declines in CO 2 uptake in a grazed steppe. Abstract Climate models predict a substantial increase in the frequency of extreme drought, suggesting subsequent impacts on the carbon (C) and water cycles. Although many studies have investigated the impacts of extreme drought on ecosystem functioning, it remains unknown how the timing of extreme drought within a growing season may affect carbon and water cycling. Here we conducted a 3-year field experiment to investigate the influence of seasonal drought timing on ecosystem carbon and water exchange by excluding rainfall (for consecutive 30 days) during three periods of the growing season (May–June, July–August and August–September) in fenced and grazed sites of a semiarid temperate steppe in Inner Mongolia, China. In the fenced steppe, extreme drought reduced growing-season net CO 2 uptake regardless of drought timing, while in the grazed steppe, early-growing season drought caused relatively larger reductions to net CO 2 uptake than drought imposed later in the season. The effect of extreme drought on evapotranspiration (ET) was similar to that of CO 2 exchange at the fenced site, with consistent reductions of seasonally-integrated ET for all treatments compared with the ambient condition. In contrast, at the grazed site, the response of ET to extreme drought was more variable, possibly due to the absence of litter and greater bare ground. Surprisingly, both gross and net carbon uptake declined with increasing ET at the grazed site, while the fenced site showed the positive water-carbon linkage typically seen in semiarid ecosystems. The different responses of CO 2 and water exchanges for the fenced and grazed sites were regulated predominately by soil temperature and soil water content. Together, our results show that drought timing within the growing season can significantly alter drought impacts on ecosystem water and CO 2 exchanges, and that grazing management may further mediate the response. [ABSTRACT FROM AUTHOR]

Biological nitrogen fixation, conducted by soil diazotrophs, is the primary nitrogen source for natural grasslands. However, the diazotrophs in grassland soils are still far from fully investigated. Particularly, their regional-scale distribution patterns have never been systematically examined. Here, soils (0–5 cm) were sampled from 54 grasslands on the Tibetan Plateau to examine the diazotroph abundance, diversity, and community composition, as well as their distribution patterns and driving factors. The diazotroph abundance was expressed as nifH gene copies, measured using real-time PCR. The diversity and community composition of diazotrophs were analyzed through MiSeq sequencing of nifH genes. The results showed that Cyanobacteria (47.94%) and Proteobacteria (45.20%) dominated the soil diazotroph communities. Most Cyanobacteria were classified as Nostocales which are main components of biological crusts. Rhizobiales, most of which were identified as potential symbiotic diazotrophs, were also abundant in approximately half of the soil samples. The soil diazotroph abundance, diversity, and community composition followed the distribution patterns in line with mean annual precipitation. Moreover, they also showed significant correlations with prokaryotic abundance, plant biomass, vegetation cover, soil pH values, and soil nutrient contents. Among these environmental factors, the soil moisture, organic carbon, available phosphorus, and inorganic nitrogen contents could be the main drivers of diazotroph distribution due to their strong correlations with diazotroph indices. These findings suggest that autotrophic and symbiotic diazotrophs are the predominant nitrogen fixers in Tibetan grassland soils, and highlight the key roles of water and nutrient availability in determining the soil diazotroph distribution on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The nitrogen (N) cycle is a collection of important biogeochemical pathways mediated by microbial communities and is an important constraint in response to elevated CO 2 in many terrestrial ecosystems. Previous studies attempting to relate soil N cycling to microbial genetic data mainly focused on a few gene families by PCR, protein assays and functional gene arrays, leaving the taxonomic and functional composition of soil microorganisms involved in the whole N cycle less understood. In this study, 24 soil samples were collected from the long-term experimental site, BioCON, in 2009. A shotgun metagenome sequencing approach was employed to survey the microbial gene families involved in soil N cycle in the grassland that had been exposed to elevated CO 2 (eCO 2 ) for >12 years. In addition to evaluating the responses of major N cycling gene families to long-term eCO 2 , we also aimed to characterize the taxonomic and functional composition of these gene families involved in soil N transformations. At the taxonomic level, organic N metabolism and nitrate reduction had the most diverse microbial species involved. The distinct taxonomic composition of different N cycling processes suggested that the complex N cycle in natural ecosystems was a result of multiple processes by many different microorganisms. Belowground microbial communities that mediate N cycling responded to eCO 2 in several different ways, including through stimulated abundances of the gene families related with organic decomposition, dissimilatory nitrate reduction, and N 2 fixation, and suppressed abundances of the gene families in glutamine synthesis and anammox. This study provides a genetic basis of the microorganisms involved in key processes in the N cycle in complex ecosystems, and shows that long-term eCO 2 selectively affects N cycling pathways instead of tuning up every process. [ABSTRACT FROM AUTHOR]

Diazotrophs are the major organismal group responsible for atmospheric nitrogen (N) fixation in natural ecosystems. The extensive diversity and structure of N-fixing communities in grassland ecosystems and their responses to increasing atmospheric CO remain to be further explored. Through pyrosequencing of nifH gene amplicons and extraction of nifH genes from shotgun metagenomes, coupled with co-occurrence ecological network analysis approaches, we comprehensively analyzed the diazotrophic community in a grassland ecosystem exposed to elevated CO (eCO) for 12 years. Long-term eCO increased the abundance of nifH genes but did not change the overall nifH diversity and diazotrophic community structure. Taxonomic and phylogenetic analysis of amplified nifH sequences suggested a high diversity of nifH genes in the soil ecosystem, the majority belonging to nifH clusters I and II. Co-occurrence ecological network analysis identified different co-occurrence patterns for different groups of diazotrophs, such as Azospirillum/Actinobacteria, Mesorhizobium/Conexibacter, and Bradyrhizobium/Acidobacteria. This indicated a potential attraction of non-N-fixers by diazotrophs in the soil ecosystem. Interestingly, more complex co-occurrence patterns were found for free-living diazotrophs than commonly known symbiotic diazotrophs, which is consistent with the physical isolation nature of symbiotic diazotrophs from the environment by root nodules. The study provides novel insights into our understanding of the microbial ecology of soil diazotrophs in natural ecosystems. [ABSTRACT FROM AUTHOR]

The plant productivity and species richness (P-SR) relationship has been a central topic in ecology for decades. It is increasingly recognized that climate resources (CR, temperature and precipitation) might affect the P-SR relationship as (1) the response of plant productivity and species richness to CR are different; (2) plant-plant interactions change along the CR gradient. However, little is known about how these effects mediate the shape and strength of the P-SR relationship from local-site to regional scales. Here, we proposed a cross-scale framework to disentangle the climatic control over the P-SR relationship in grasslands using the HerbDivNet dataset, which covers 28 natural grasslands in 19 countries and 6 continents with wide precipitation and temperature gradients. Our results showed that, at the local-site scale, a humped-back P-SR relationship is common at sites under poor and rich CR conditions, whereas both the shape and strength of the P-SR relationship strongly vary among sites under moderate CR condition. However, at the regional scale, the humped-back P-SR relationship is only observed under poor CR condition. We suggested that the asynchronous responses of productivity and species richness to increasing CR is an abiotic driver of the inconsistent P-SR relationships along the climatic gradient in addition to the changing plant-plant interactions suggested by the stress-gradient hypothesis. These findings help to reconcile the long-standing debate over the P-SR relationship and highlight the importance of CR conditions in developing or comparing grassland ecosystem theories and management at small scales. • Climate effects cause inconsistent P-SR relationships from local to regional scales. • Asynchronous response of P and SR to CR is an abiotic driver of P-SR relationship. • Unimodal P-SR relationship at regional scale only exists with poor CR. • None unimodal P-SR relationships at site scale are mostly observed with moderate CR. • Shape and strength of P-SR relationship strongly vary among sites with moderate CR. [ABSTRACT FROM AUTHOR]

• Grassland degradation is predictable on a large scale by Random Forest. • Specific microbial groups, mainly Solirubrobacter, were screened as credible biomarkers. • Grassland degradation exhibited a longitudinal pattern and was correlated with current Net primary productivity. Extensive grassland degradation under climate change and intensified human activities has threatened ecological security and caused a variety of environmental problems. However, it is still challenging to predict the grassland degradation status on a large scale because it is a multi-factorial phenomenon with complex changes in ecosystem structure and function, which is hard to be fully characterized through mechanism models. The emergence of machine learning algorithms provides a potential to model complex systems and mine information from multi-source data without elucidating underlying mechanisms. Here, we utilized random forest and neural network algorithms to predict the grassland degradation represented by the net primary productivity (NPP) changing rate based on multi-source data including geographic, meteorological, plant traits, land use type and microbial variables in the Chinese Northern grassland. Particularly, the microbial roles in determining the degradation status were concerned. Results show that a high prediction precision was achieved by random forest model, rather than by neural network model, with a mean relative error of 16.9% and a mean square error of 9.273e-05. Besides identified longitude, arid index and current NPP state, specific soil microbial groups, mainly Solirubrobacter, were screened as credible biomarkers. Regarding model fitting, geographic, meteorological and plant variables explained 61.8% of the total variance, which was enhanced up to 72.8% by the rest microbial markers. These findings provide a theoretical basis to establish a pre-warning system for grassland management and policy-making. [ABSTRACT FROM AUTHOR]

The alpine grassland on the Qinghai-Tibet Plateau covers an area of about 1/3 of China's total grassland area and plays a crucial role in regulating grassland ecological functions. Both environmental changes and irrational use of the grassland can result in severe grassland degradation in some areas of the Qinghai-Tibet Plateau. However, the magnitude and patterns of the physical and anthropogenic factors in driving grassland variation over northern Tibet remain debatable, and the interactive influences among those factors are still unclear. In this study, we employed a geographical detector model to quantify the primary and interactive impacts of both the physical factors (precipitation, temperature, sunshine duration, soil type, elevation, slope, and aspect) and the anthropogenic factors (population density, road density, residential density, grazing density, per capita GDP, and land use type) on vegetation variation from 2000 to 2015 in northern Tibet. Our results show that the vegetation index in northern Tibet significantly decreased from 2000 to 2015. Overall, the stability of vegetation types was sorted as follows: the alpine scrub > the alpine steppe > the alpine meadow. The physical factors, rather than the anthropogenic factors, have been the primary driving factors for vegetation dynamics in northern Tibet. Specifically, meteorological factors best explained the alpine meadow and alpine steppe variation. Precipitation was the key factor that influenced the alpine meadow variation, whereas temperature was the key factor that contributed to the alpine steppe variation. The anthropogenic factors, such as population density, grazing density and per capita GDP, influenced the alpine scrub variation most. The influence of population density is highly similar to that of grazing density, which may provide convenient access to simplify the study of the anthropogenic activities in the Tibet plateau. The interactions between the driving factors had larger effects on vegetation than any single factor. In the alpine meadow, the interaction between precipitation and temperature can explain 44.6% of the vegetation variation. In the alpine scrub, the interaction between temperature and GDP was the highest, accounting for 27.5% of vegetation variation. For the alpine steppe, the interaction between soil type and population density can explain 29.4% of the vegetation variation. The highest value of vegetation degradation occurred in the range of 448–469 mm rainfall in the alpine meadow, 0.61–1.23 people/km2 in the alpine scrub and –0.83–0.15 °C in the alpine steppe, respectively. These findings could contribute to a better understanding of degradation prevention and sustainable development of the alpine grassland ecosystem in northern Tibet. [ABSTRACT FROM AUTHOR]