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Atmospheric nitrogen (N) deposition is a recognized threat to plant diversity in temperate and northern parts of Europe and North America. This paper assesses evidence from field experiments for N deposition effects and thresholds for terrestrial plant diversity protection across a latitudinal range of main categories of ecosystems, from arctic and boreal systems to tropical forests. Current thinking on the mechanisms of N deposition effects on plant diversity, the global distribution of G200 ecoregions, and current and future (2030) estimates of atmospheric N-deposition rates are then used to identify the risks to plant diversity in all major ecosystem types now and in the future. This synthesis paper clearly shows that N accumulation is the main driver of changes to species composition across the whole range of different ecosystem types by driving the competitive interactions that lead to composition change and/or making conditions unfavorable for some species. Other effects such as direct toxicity of nitrogen gases and aerosols, long-term negative effects of increased ammonium and ammonia availability, soil-mediated effects of acidification, and secondary stress and disturbance are more ecosystem- and site-specific and often play a supporting role. N deposition effects in mediterranean ecosystems have now been identified, leading to a first estimate of an effect threshold. Importantly, ecosystems thought of as not N limited, such as tropical and subtropical systems, may be more vulnerable in the regeneration phase, in situations where heterogeneity in N availability is reduced by atmospheric N deposition, on sandy soils, or in montane areas. Critical loads are effect thresholds for N deposition, and the critical load concept has helped European governments make progress toward reducing N loads on sensitive ecosystems. More needs to be done in Europe and North America, especially for the more sensitive ecosystem types, including several ecosystems of high conservation importance. The results of this assessment show that the vulnerable regions outside Europe and North America which have not received enough attention are ecoregions in eastern and southern Asia (China, India), an important part of the mediterranean ecoregion (California, southern Europe), and in the coming decades several subtropical and tropical parts of Latin America and Africa. Reductions in plant diversity by increased atmospheric N deposition may be more widespread than first thought, and more targeted studies are required in low background areas, especially in the G200 ecoregions.

Aims Alpine ecosystems are important terrestrial carbon (C) pools, and microbial decomposers play a key role in cycling soil C. Microbial metabolic limitations in these ecosystems, however, have rarely been studied. The objectives of this study are to reveal the characteristics of microbial nutrient limitation, and decipher the drivers in the alpine ecosystems. Methods Models of extracellular enzymatic stoichiometry were applied to examine and compare the metabolic limitations of the microbial communities in bulk and rhizosphere soils along an altitudinal gradient (2800–3500 m a.s.l.) under the same type of vegetation ( Abies fabri ) on Gongga Mountain, eastern Tibetan Plateau. Results The soil microbial communities suffered from relative C and phosphorus (P) limitations in the alpine ecosystem despite of high soil nutrient contents here. Partial least squares path modelling (PLS-PM) revealed that the limitations were directly regulated by soil nutrient stoichiometry, followed by nutrient availability. The C and P limitations were higher at the high altitudes (3000–3500 m) than that at the low altitude (2800 m), which mainly attribute to changes of soil temperature and moisture along the altitudinal gradient. This suggested that global warming may relieve microbial metabolic limitation in the alpine ecosystems, and then is conducive to the retention of organic C in soil. Furthermore, the C and P limitations varied significantly between the bulk and rhizosphere soils at the high altitudes (3200–3500 m), but not at the low altitudes. This indicated the influences of vegetation on the microbial metabolisms, while the influences could decrease under the scenario of global warming. Conclusions Our study suggests that the alpine ecosystems with high organic C storage harbour abundant microbial populations limited by relative C and P, which have sensitive metabolic characteristics. This could thus potentially lead to large fluctuations in the soil C turnover under climate change. The study provides important insights linking microbial metabolisms to the environmental gradients, and improves our understanding of C cycling in alpine ecosystems.

Background and aims Microbial communities play an important regulatory role in soil carbon and nutrient cycling in terrestrial ecosystems. Most studies on microbial communities and biogeochemical cycling focus on surface soils (0–20 cm). However, relatively little is known about how structure and functioning of microbial communities shift with depth in a soil profile, which is crucial to understand biogeochemical cycling in deep soils. Methods We combined a number of complementary techniques to investigate the microbial biomass, community composition and diversity, and potential functioning along soil profile (0–70 cm) in two alpine ecosystems (meadow and shrubland) on the Tibetan Plateau. Results The microbial biomass and fungi:bacteria ratio declined significantly with depth, while the ratio of Gram-positive to Gram-negative bacteria increased with depth in both ecosystems. Microbial community composition showed significant differences among soil depths and between ecosystems. The relative abundance of some phylum of archaea, bacteria or fungi (e.g. Basidiomycota , Bacteroidetes ) changed significantly with soil depth and ecosystem type. Bacteria diversity declined with depth, while archaea richness (OTU number) increased with depth and fungi diversity and richness did not show clear trend with depth. The co-occurrence network analysis further showed that surface soil microbes were more connected and interacted among each other compared to deep soil microbes. Moreover, total enzymatic activities and soil C mineralization rate declined with depth in both ecosystems. We also detected shifts with depth in some functional guilds of bacteria (based on faprotax database) in both ecosystems and fungi (based on FUNGuild database) only in shrubland. Conclusions The biomass, community composition and diversity, and potential functioning of microbial communities all shifted significantly along soil profile in both ecosystems, and the vertical patterns of diversity varied among different microbial groups. This may have important implications for carbon and nutrient cycling along the soil profile in alpine ecosystems.

Within the context of species distribution models, scrutiny arises from the choice of meaningful environmental predictors. Thermal conditions are not the sole driver, but are the most widely acknowledged abiotic driver of plant life within alpine ecosystems. We linked long-term measurements of direct, plant-relevant, near-surface temperatures to plant species frequency. Across 47 sites located along environmental gradients within the Scandinavian mountain chain, the thermal preferences of 26 focal species of vascular plants, lichens, and bryophytes were explored. Based on partial least-squares regression, we applied a relative importance analysis to derive inductively the thermal variables that were best related to a species’ frequency. To discover potential seasonal variability of thermal controls, analyses were both differentiated according to meteorological season and integrated across the entire year. The pronounced interspecies and temporal variability of thermal constraints revealed the thermal niches were much more nuanced and variable than they have commonly been represented. This finding challenges us to present, interrogate, and interpret data representing these thermal niches, which seems to be required in order to move beyond purely probabilistic and correlative descriptions of species’ range limits. Thus, this information will help improve predictions of species distributions in complex arctic-alpine landscapes.

All ecosystems face ecological challenges in this century. Therefore, it is becoming increasingly important to understand the ecology and degree of local adaptation of functionally important Arctic‐alpine biomes by looking at the most diverse taxon of metazoans: the Arthropoda. This is the first study to utilize metabarcoding in the Alpine tundra, providing insights into the effects of micro‐environmental parameters on alpha‐ and beta‐diversity of arthropods in such unique environments. To characterize arthropod diversity, pitfall traps were set at three middle‐alpine sampling sites in the Scandinavian mountain range in Norway during the snow‐free season in 2015. A metabarcoding approach was then used to determine the small‐scale biodiversity patterns of arthropods in the Alpine tundra. All DNA was extracted directly from the preservative EtOH from 27 pitfall traps. In order to identify the controlling environmental conditions, all sampling locations were equipped with automatic data loggers for permanent measurement of the microenvironmental conditions. The variables measured were: air temperature [°C] at 15 cm height, soil temperature [°C] at 15 cm depth, and soil moisture [vol.%] at 15 cm depth. A total of 233 Arthropoda OTUs were identified. The number of unique OTUs found per sampling location (ridge, south‐facing slope, and depression) was generally higher than the OTUs shared between the sampling locations, demonstrating that niche features greatly impact arthropod community structure. Our findings emphasize the fine‐scale heterogeneity of arctic–alpine ecosystems and provide evidence for trait‐based and niche‐driven adaptation. The spatial and temporal differences in arthropod diversity were best explained by soil moisture and soil temperature at the respective locations. Furthermore, our results show that arthropod diversity is underestimated in alpine‐tundra ecosystems using classical approaches and highlight the importance of integrating long‐term functional environmental data and modern taxonomic techniques into biodiversity research to expand our ecological understanding of fine‐ and meso‐scale biogeographical patterns. Our study examines the alpha‐ and beta‐diversity of arthropods in the Arctic‐alpine biomes of the Scandes using environmental DNA (eDNA)/metabarcoding. We found that micro‐climatological parameters such as air/soil temperature and soil moisture significantly influence the arthropod community structure, highlighting the fine‐scale heterogeneity of these ecosystems. Our study emphasizes the importance of integrating long‐term functional environmental data and modern taxonomic techniques to accurately assess arthropod diversity and broaden our understanding of biogeographical patterns in alpine‐tundra ecosystems.

Construction of the Qinghai-Tibet Railway (QTR) increased the links between inland China and the Qinghai-Tibet Plateau (QTP). The QTR accelerated surrounding tourism, boosted the local economy and led to rapid development of livestock raising. To assess how distance from the railway and different regions has influenced the impact of the QTR on the alpine ecosystem, human footprint maps were produced to indicate human pressures, and the normalized difference vegetation index (NDVI), an index of vegetation greenness, was used to characterize the growth of alpine vegetation. The construction and operation of the QTR have increased human pressures, while the establishment of nature reserves has effectively reduced human pressures. The QTR contributes significantly to the increased human pressures in the Tibetan region compared with the Qinghai region and exerts negative impacts on alpine vegetation. Although the warmer and wetter climate trend has proven beneficial in enhancing alpine vegetation greenness, the declining trend of alpine vegetation has been stronger in regions with more intensive human pressures, especially in the grazing areas and the tourist areas around Lhasa. These results suggest that the impact of the QTR on alpine vegetation in Tibet is greater than that in Qinghai and that the spatial extent of the indirect impact of the QTR in Tibet is confined to approximately 30 km from the railway. These results will provide guidance and a theoretical basis for the protection of the alpine environment on the QTP under intensified anthropogenic influence.

Long-time series global fractional vegetation cover (FVC) products have received widespread international publication, and they supply the essential data required for eco-monitoring and simulation study, assisting in the understanding of global warming and preservation of ecosystem stability. However, due to the insufficiency of high-precision FVC ground-measured data, the accuracy of these FVC products in some regions (such as the Qinghai–Tibet Plateau) is still unknown, which brings a certain impact on eco-environment monitoring and simulation. Here, based on current international mainstream FVC products (including GEOV1 and GEOV2 at Copernicus Global Land Services, GLASS from Beijing Normal University, and MuSyQ from National Earth System Science Data Center), the study of the dynamic change of vegetation cover and its influence factors were conducted in the three-rivers source region, one of the core regions on the Qinghai–Tibet Plateau, via the methods of trend analysis and partial correlation analysis, respectively. Our results found that: (1) The discrepancy in the eco-environment assessment results caused by the inconsistency of FVC products is reflected in the statistical value and the spatial distribution. (2) About 70% of alpine grassland in the three-rivers source region changing trend is controversial. (3) The limiting or driving factors of the alpine grassland change explained via different FVC products were significantly discrepant. Thus, before conducting these studies in the future, the uncertainties of the FVC products utilized should be validated first to acquire the fitness of the FVC products if the accuracy information of these products is unavailable within the study area. In addition, more high-precision FVC ground-measured data should be collected, helping us to validate FVC product uncertainty.

Background Teide National Park (Canary Islands) is an alpine volcanic ecosystem with shrub vegetation in which legume Spartocytisus supranubius is the most characteristic key species for nitrogen input to the ecosystem. Aims and methods Bacterial and fungal communities in bulk and rhizosphere soils were analysed through high-throughput sequencing in undisturbed and wildfire-impacted areas to identify key microorganisms in burned and unburned soils. Results Microbial communities in undisturbed areas exhibited comparable diversity in bulk and rhizosphere soils, but differed in structure and composition. An unusual abundance of non-photosynthetic Chloroflexi from the oligotrotrophic class Ktedonobacteria dominated the bulk soils, surpassing Proteobacteria, Acidobacteria and Actinobacteria. The rhizosphere effect resulted in a microbiome with a more balanced abundance of these four phyla and enriched in potentially plant growth-promoting microorganisms. The impact of a wildfire on the shrub vegetation resulted in a microbial community, especially the fungal community, reduced in diversity and changed in structure and composition, with many of the most characteristic rhizosphere genera becoming vanished, while others took advantage of the postfire conditions and became predominant. Conclusion The microbial communities of Teide National Park in fire-affected soils, particularly in the rhizosphere environment of the legume shrubland are significantly altered two years after a wildfire, remaining far from unburned scenarios, suggesting a slow recovery in alpine ecosystem with dry volcanic soils. Pseudarthrobacter (Actinobacteria) and Coprinellus (Basidiomycota), the two most fire-favoured genera, are good indicators of fire severity and are proposed as bioindicators to monitor the recovery of the soil ecosystem.

Climate warming may cause alpine grassland degradation by decreasing plant growth and increasing pika grazing, although the concurrent precipitation change may further confound the plant and pika responses to warming. We aim to investigate the interactive effect of changes in temperature, precipitation and pika herbivory on plant growth. A 2-year field manipulation experiment of 2 °C warming and 15–30% increased precipitation was conducted in an alpine grassland ecosystem. During the growing season, warming significantly reduced plant height growth of the two dominant species Stipa purpurea and Kobresia macrantha, whereas increased precipitation and its interactions with warming stimulated plant height growth. Regarding the widespread species S. purpurea, warming significantly increased the frequency, consumption, and intensity of pika herbivory, whereas increased precipitation significantly reduced pika herbivory intensity, resulting in a net positive effect of increased precipitation and its interactions with warming and pika herbivory on plant growth. However, the pika grazing on K. macrantha varied little with warming and precipitation change. There was generally a much larger effect of pika grazing on S. Purpurea than on K. macrantha, which corresponded to higher specific leaf area and nitrogen content in S. purpurea than in K. macrantha. The diet selection of pika may explain why the sensitivity of pika herbivory to warming and precipitation change differed between the two dominant plant species. Our data suggest that the effect of pika grazing on Stipa plants is amplified by climatic warming, and such a negative effect could be alleviated by increased precipitation.

The widely spread alpine grassland ecosystem in the Three River Headwaters Region (TRHR) plays an essential ecological role in carbon sequestration and soil and water conservation. In this study, we test the latest high spatial resolution hyperspectral (Zhuhai-1 OHS) remote sensing imagery to examine different alpine grassland coverage levels using Multiple Endmember Spectral Mixture Analysis (MESMA). Our results suggest that the 3-endmember (3-EM) MESMA model can provide the highest image pixel unmixing percentage, with a percentage exceeding 97% and 96% for pixel scale and landscape scale, respectively. The overall accuracy shows that Zhuhai-1 OHS imagery obtained the highest overall accuracy (83.7%, k = 0.77) in the landscape scale, but in the pixel scale, it is not as good as Landsat 8 OLI imagery. Overall, we can conclude that the hyperspectral imagery combined 3-EM MESMA model performs better in both pixel scale and landscape scale alpine grassland coverage mapping, while the multispectral imagery with the 3-EM MESMA model can satisfy requirements of alpine grassland coverage mapping at the pixel scale. The approaches and workflow to mapping alpine grassland in this study can help monitor alpine grassland degradation; not only in the Qinghai–Tibetan Plateau (QTP), but also in other grassland ecosystems.