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Societal Impact Statement: Rice wild relatives (RWR) provide valuable genetic resources for modern rice breeding, yet knowledge gaps constrain their conservation and further utilization. To address these gaps, the potential distributions of 22 RWR taxa were modeled, and their conservation statuses were assessed. Most taxa were identified as medium priority for further conservation. Further ex‐situ collecting hotspots are in Southeast and South Asia, Northern Australia, West Africa, and tropical Americas, while habitat protection lies in Southeast and South Asia, Northern Australia, and West Africa. Climate change may shift equatorial habitats to higher latitudes and mountain habitats to higher altitudes. Summary: Rice wild relatives (RWR) provide valuable genetic resources for modern rice breeding. However, knowledge gaps on their geographic distributions and conservation status constrain their conservation and further utilization.To fill these critical gaps, we modeled the potential distributions of 22 RWR taxa under current climate scenarios, assessed their conservation status, both ex situ (in genebanks or botanical gardens) and in situ (in protected areas), and examined changes in taxa richness of RWR in predicted areas under future climate scenarios.The RWR were primarily distributed in tropical Asia to tropical Australia, tropical Africa, and South and Central America. We identified 4 out of 22 taxa as high priority (HP) for further conservation action and 18 taxa as medium priority (MP).Hotspots requiring further collecting for ex situ conservation are concentrated in Southeast and South Asia, Northern Australia, West Africa, and tropical Americas. Meanwhile, habitat protection should be enhanced in Southeast and South Asia, Northern Australia, and West Africa. Under future climate change, suitable habitats near the equator are expected to shift toward higher latitudes and some in lower‐latitude basins may become unsuitable due to excessive heat, resulting in decreased taxa richness in these areas. Additionally, suitable habitats in high mountain areas may shift to higher altitudes, potentially augmenting taxa richness in the highlands. Our findings provide vital insights to guide future rescue conservation efforts for RWR. [ABSTRACT FROM AUTHOR]

Microbial necromass carbon (MNC) can reflect soil carbon (C) sequestration capacity. However, changes in the reserves of MNC in response to warming in alpine grasslands across the Tibetan Plateau are currently unclear. Based on large-scale sampling and published observations, we divided eco-clusters based on dominant phylotypes, calculated their relative abundance, and found that their averaged importance to MNC was higher than most other environmental variables. With a deep learning model based on stacked autoencoder, we proved that using eco-cluster relative abundance as the input variable of the model can accurately predict the overall distribution of MNC under current and warming conditions. It implied that warming could lead to an overall increase in the MNC in grassland topsoil across the Tibetan Plateau, with an average increase of 7.49 mg/g, a 68.3% increase. Collectively, this study concludes that alpine grassland has the tendency to increase soil C sequestration capacity on the Tibetan Plateau under future warming. A study on the carbon sequestration capacity of soil in alpine grasslands across the Tibetan Plateau implies that warming will lead to an average increase of 7.49 mg/g microbial necromass carbon in topsoil, an increase of 68.3%. [ABSTRACT FROM AUTHOR]

Before 2008, China lacked high-coverage regional surface observation data, making it difficult for the China Meteorological Administration Land Data Assimilation System (CLDAS) to directly backtrack high-resolution, high-quality land assimilation products. To address this issue, this paper proposes a deep learning model named UNET_DCA, based on the UNET architecture, which incorporates a Dual Cross-Attention module (DCA) for multiscale feature fusion by introducing Channel Cross-Attention (CCA) and Spatial Cross-Attention (SCA) mechanisms. This model focuses on the near-surface 10-m wind field and achieves spatial downscaling from 6.25 km to 1 km. We conducted training and validation using data from 2020–2021, tested with data from 2019, and performed ablation experiments to validate the effectiveness of each module. We compared the results with traditional bilinear interpolation methods and the SNCA-CLDASSD model. The experimental results show that the UNET-based model outperforms SNCA-CLDASSD, indicating that the UNET-based model captures richer information in wind field downscaling compared to SNCA-CLDASSD, which relies on sequentially stacked CNN convolution modules. UNET_CCA and UNET_SCA, incorporating cross-attention mechanisms, outperform UNET without attention mechanisms. Furthermore, UNET_DCA, incorporating both Channel Cross-Attention and Spatial Cross-Attention mechanisms, outperforms UNET_CCA and UNET_SCA, which only incorporate one attention mechanism. UNET_DCA performs best on the RMSE, MAE, and COR metrics (0.40 m/s, 0.28 m/s, 0.93), while UNET_DCA_ars, incorporating more auxiliary information, performs best on the PSNR and SSIM metrics (29.006, 0.880). Evaluation across different methods indicates that the optimal model performs best in valleys, followed by mountains, and worst in plains; it performs worse during the day and better at night; and as wind speed levels increase, accuracy decreases. Overall, among various downscaling methods, UNET_DCA and UNET_DCA_ars effectively reconstruct the spatial details of wind fields, providing a deeper exploration for the inversion of high-resolution historical meteorological grid data. [ABSTRACT FROM AUTHOR]

This article explores the role of fossil organic carbon (FOC) weathering in global biogeochemical cycles. FOC is a unique type of organic carbon that has accumulated and fossilized in the Earth's lithosphere over time. Recent studies have shown that FOC is easily reacted, mobilized, and transformed under surface conditions, releasing CO2 and impacting global biogeochemical cycles. However, there are challenges in understanding FOC weathering, including limited data for calibrating its kinetics and the influence of factors like rock types, tectonic activities, geomorphic processes, and climate. The article suggests that future research should focus on studying FOC weathering in different environments and developing proxies to reconstruct past weathering. It also emphasizes the importance of understanding the connection between FOC weathering and the biogeochemical cycles of other nutrient elements. [Extracted from the article]

Bacterial strains isolated from root nodules of the legume plant Hedysarum arcticum B. Fedtsch growing on Samoylov Island in the Lena River delta (Arctic zone of Yakutia) were assigned to the genera Rhizobium (family Rhizobiaceae) and Mesorhizobium (Phyllobacteriaceae) of the order Hyphomicrobiales (class Alphaproteobacteria) according to the rrs gene sequencing data. According to phylogenetic analysis of concatemers of the atpD, dnaK, gyrB, and rpoB genes, the strains belonged to the species Rhizobium giardinii and Mesorhizobium norvegicum. The strains were shown to be facultative psychrotrophs growing at 5 and 28°C. These microsymbionts are promising for further study of their symbiotic efficiency regarding other forage legume species, with an aim to establish highly productive agrophytocenoses in the Far North. [ABSTRACT FROM AUTHOR]

Rabbit haemorrhagic disease viruses (RHDV) belong to the family Caliciviridae, genus Lagovirus europaeus, genogroup GI, comprising four genotypes GI.1–GI.4, of which the genotypes GI.1 and GI.2 are pathogenic RHD viruses, while the genotypes GI.3 and GI.4 are non-pathogenic RCV (Rabbit calicivirus) viruses. Among the pathogenic genotypes GI.1 and GI.2 of RHD viruses, an antigenic variant of RHDV, named RHDVa—now GI.1a–RHDVa, was distinguished in 1996; and in 2010, a variant of RHDV—named RHDVb, later RHDV2 and now GI.2–RHDV2/b—was described; and recombinants of these viruses were registered. Pathogenic viruses of the genotype GI.1 were the cause of a disease described in 1984 in China in domestic (Oryctolagus (O.) cuniculus domesticus) and wild (O. cuniculus) rabbits, characterised by a very rapid course and a mortality rate of 90–100%, which spread in countries all over the world and which has been defined since 1989 as rabbit haemorrhagic disease. It is now accepted that GI.1–RHDV, including GI.1a–RHDVa, cause the predetermined primary haemorrhagic disease in domestic and wild rabbits, while GI.2–RHDV2/b cause it not only in rabbits, including domestic rabbits' young up to 4 weeks and rabbits immunised with rabbit haemorrhagic disease vaccine, but also in five various species of wild rabbits and seven different species of hares, as well as wild ruminants: mountain muskoxen and European badger. Among these viruses, haemagglutination-positive, doubtful and harmful viruses have been recorded and described and have been shown to form phylogenogroups, immunotypes, haematotypes and pathotypes, which, together with traits that alter and expand their infectious spectrum (rabbit, hare, wild ruminant, badger and various rabbit and hare species), are the determinants of their pathogenicity (infectivity) and immunogenicity and thus shape their virulence. These relationships are the aim of our consideration in this article. [ABSTRACT FROM AUTHOR]

Nine land types in the northern mining area (BKQ) (mining land, smelting land, living area), the old mining area (LKQ) (whole-ore heap, wasteland, grassland), and southern mining area (NKQ) (grassland, shrubs, farmland) of Xikuang Mountain were chosen to explore the composition and functions of soil bacterial communities under different habitats around mining areas. The composition and functions of soil bacterial communities were compared among the sampling sites using 16S rRNA high-throughput sequencing and metagenomic sequencing. α diversity analysis showed the soil bacterial diversity and abundance in the old mining area were significantly higher than those in the northern mining area. β diversity analysis demonstrated that the soil bacterial community composition was highly similar among different vegetation coverages in the southern mining area. Microbial community function analysis showed the annotated KEGG function pathways and eggNOG function composition were consistent between the grassland of the old mining area and the grassland of the southern mining area. This study uncovers the soil bacterial community composition and functions among different habitats in the mining areas of Xikuang Mountain and will underlie soil ecosystem restoration in different habitats under heavy metal pollution around the mining areas there. [ABSTRACT FROM AUTHOR]

The twin mountains, a common terrain in mountainous areas, tend to induce the acceleration effect under crosswinds, which enhances the wind speed and the turbulence performance of the flow field. To mitigate the impact of the acceleration effect on high-speed trains, structures, and aircraft near the twin mountains, this study investigates the effectiveness of the jet strategies, which are realized on natural mountain slopes by mechanical ventilation, with different jet angles on the flow field and the train. Wind speed tests, flow visualization, wind field prediction, and research on the train's aerodynamic behavior are conducted in this paper using the wind tunnel and the improved delayed detached eddy simulation dynamic models. The results indicate that the wind velocity on the leeward side of the twin mountains increases up to 1.42 folds of the wind velocity of the incoming flow under crosswinds. The jet streams with 0° and 30° angles are the most effective in mitigating the acceleration effect among those tested (0°, 15°, 30°, and 45°), reducing the maximum wind speed by 11.87% and 16%, respectively. Compared with the mitigation effect of the jet stream with the 30° angle, the jet stream with the 0° angle has a better mitigation effect on the aerodynamic loads (4.0%–13.2%) and its fluctuation amplitude (24.4%–42.7%) of the train. These findings are valuable for studying the flow field characteristics of the twin mountains and the designing anti-wind measures for high-speed railways. [ABSTRACT FROM AUTHOR]

The high temporal resolution of thermal infrared imagery from the Geostationary Operational Environmental Satellites R-series (GOES-R) presents an opportunity to observe mountain snow and forest temperatures over the full diurnal cycle. However, the off-nadir views of these imagers may impact or bias temperature observations, especially when viewing a surface composed of both snow and forests. We used GOES-16 and -17 thermal infrared brightness temperature observations of a flat snow- and forest-covered study site at Grand Mesa, Colorado, USA, to characterize how forest coverage and view angle impact these observations. These two geostationary satellites provided views of the study area from the southeast (134.1° azimuth, 33.5° elevation) and southwest (221.2° azimuth, 35.9° elevation), respectively. As part of the NASA SnowEx field campaign in February 2020, coincident brightness temperature observations from ground-based and airborne IR sensors were collected to compare with those from the geostationary satellites. Observations over the course of 2 cloud-free days spanned the entire study site. The brightness temperature observations from each dataset were compared to find their relative differences and how those differences may have varied over time and/or as a function of varying forest cover across the study area. GOES-16 and -17 brightness temperatures were found to match the diurnal cycle and temperature range within ∼ 1 h and ± 3 K of ground-based observations. GOES-16 and -17 were both biased warmer than nadir-looking airborne IR and ASTER observations. The warm biases were higher at times when the sun–satellite phase angle was near its daily minimum. The phase angle, the angle between the direction of incoming solar illumination and the direction from which the satellite is viewing, reached daily minimums in the morning for GOES-16 and afternoon for GOES-17. In morning observations, warm biases in GOES-16 brightness temperature were greater for pixels that contained more forest coverage. The observations suggest that a "thermal infrared shadow-hiding" effect may be occurring, where the geostationary satellites are preferentially seeing the warmer sunlit sides of trees at different times of day. These biases are important to understand for applications using GOES-R brightness temperatures or derived land surface temperatures (LSTs) over areas with surface roughness features, such as forests, that could exhibit a thermal infrared shadow-hiding effect. [ABSTRACT FROM AUTHOR]

Freeze–thaw (FT) erosion intensity may exhibit a future increasing trend with climate warming, humidification, and permafrost degradation in the Qinghai–Tibet Plateau (QTP). The present study provides a reference for the prevention and control of FT erosion in the QTP, as well as for the protection and restoration of the regional ecological environment. FT erosion is the third major type of soil erosion after water and wind erosion. Although FT erosion is one of the major soil erosion types in cold regions, it has been studied relatively little in the past because of the complexity of several influencing factors and the involvement of shallow surface layers at certain depths. The QTP is an important ecological barrier area in China. However, this area is characterized by harsh climatic and fragile environmental conditions, as well as by frequent FT erosion events, making it necessary to conduct research on FT erosion. In this paper, a total of 11 meteorological, vegetation, topographic, geomorphological, and geological factors were selected and assigned analytic hierarchy process (AHP)-based weights to evaluate the FT erosion intensity in the QTP using a comprehensive evaluation index method. In addition, the single effects of the selected influencing factors on the FT erosion intensity were further evaluated in this study. According to the obtained results, the total FT erosion area covered 1.61 × 106 km2, accounting for 61.33% of the total area of the QTP. The moderate and strong FT erosion intensity classes covered 6.19 × 105 km2, accounting for 38.37% of the total FT erosion area in the QTP. The results revealed substantial variations in the spatial distribution of the FT erosion intensity in the QTP. Indeed, the moderate and strong erosion areas were mainly located in the high mountain areas and the hilly part of the Hoh Xil frozen soil region. [ABSTRACT FROM AUTHOR]

The intermittency of gravity wave potential energy (GWPE) in the upper troposphere and stratosphere was investigated using the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) temperature data over three typical mountains (Tibetan Plateau, Rocky Mountains, and Andes). These typical mountains have high sea level elevations but different land–sea contrast. The probability density function (PDF) of GWPE has the independent variable of GWPE and dependent variable of occurrence probability of GWPE over a region. Our analysis showed that the PDFs of GWPE over these three mountains roughly followed lognormal distributions in all heights and months. But, the key parameters (mean value and standard deviation) of lognormal distribution varied with heights and months. Above each mountain, the two key parameters exhibited similar temporal and spatial distributions. They had the largest values around the tropopause region, smaller values in the lower stratosphere (~20–30 km), and larger values in the upper stratosphere (~35–45 km). The intermittency of GWs is represented as the ratio of the GWPE at 50th percentile to the GWPE at 90th percentile. The weakest intermittency was at ~20–30 km (above the zonal mean winds of zero) over the Tibetan Plateau and Rocky Mountains in all months and over the Andes from November to March, respectively. Generally, the weakest intermittency (~0.4) occurred in the region where the key parameters were the smallest around summer. The key parameters of lognormal distribution were dominated by annual variation over the Andes throughout the height range, 8–50 km. However, the semiannual variations are also significant in the lower stratosphere over the Tibetan Plateau and Rocky Mountains. The seasonal variations in the intermittency were not as obvious as those of the key parameters. The lognormal distributions and the intermittencies derived here provide an observational constraint on the tunable parameters in GW parameterization schemes. [ABSTRACT FROM AUTHOR]

Mountainous forests are pivotal in the global carbon cycle, serving as substantial reservoirs and sinks of carbon. However, generating a reliable estimate remains a considerable challenge, primarily due to the lack of representative in situ measurements and proper methods capable of addressing their complex spatial variation. Here, we proposed a deep learning-based method that combines Residual convolutional neural networks (ResNet) with in situ measurements, microwave (Sentinel-1 and VOD), and optical data (Sentinel-2 and Landsat) to estimate forest biomass and track its change over the mountainous regions. Our approach, integrating in situ measurements across representative elevations with multi-source remote sensing images, significantly improves the accuracy of biomass estimation in Tibet's complex mountainous forests (R2 = 0.80, root mean squared error = 15.8 MgC ha−1). Moreover, ResNet, which addresses the vanishing gradient problem in deep neural networks by introducing skip connections, enables the extraction of complex spatial patterns from limited datasets, outperforming traditional optical-based or pixel-based methods. The mean value of forest biomass was estimated as 162.8 ± 21.3 MgC ha−1, notably higher than that of forests at comparable latitudes or flat regions in China. Additionally, our findings revealed a substantial forest biomass carbon sink of 3.35 TgC year−1 during 2015–2020, which is largely underestimated by previous estimates, mainly due to the underestimation of mountainous carbon stock. The significant carbon density, combined with the underestimated carbon sink in mountainous regions, emphasizes the urgent need to reassess mountain forests to better approximate the global carbon budget. [ABSTRACT FROM AUTHOR]

Much recent scientific focus has been on the impact of climate change on human and natural environments. However, a particular research gap that we address is evaluating the effect of global warming on land surface temperatures across different spatial contexts, such as elevation, in mountain regions. Our aim is to establish the effect of global warming on daytime land surface temperatures at various elevations and slope aspects of the central Alborz Mountains in northern Iran. The land surface temperature (LST) component is extracted from MODIS Terra sensor satellite images for the period 2001–2021 on a monthly basis (240 images were used). Results indicated that increasing surface temperature trends are more pronounced than decreasing trends. Significant increasing surface temperature trends are observed for the months of January through December and June through July. In contrast, October records significant decreasing trends across all study areas and geographic domains. Rates of surface temperature increases are lower in the northern zones compared to the southern zones of the Central Alborz, for elevations ranging from 1500 to 4000 m above sea level. A key finding is that global warming has increased surface temperatures on both the northern and southern aspects of the western and mid regions of the Central Alborz Mountains, while no changes are noted for the eastern region. [ABSTRACT FROM AUTHOR]

Aims: The Middle East, located in the arid belt of the Earth, is home to a diverse range of biodiversity, with its mountain ecosystems being the most important centres of species diversity and endemism. In this study, the impact of climate change on alpine bird species in the Middle East was assessed across five mountain systems: Alborz–Kopet‐Dagh, Caucasus–Pontic, Levant–Taurus, Sarawat–Hijaz and Zagros–Central Iran. Location: Middle East. Methods: Using species distribution models (SDMs), 38 native alpine bird species were analysed under different climate change scenarios. We also identified future multispecies in situ and ex situ climate refugia and assessed the efficiency of the current protected areas (PAs) system in protecting them. Results: The results indicated that, on average, habitat suitability for these species is projected to decline by 36.83% (2050, SSP2‐4.5) to 60.10% (2070, SSP5‐8.5) with an upward range shift. Based on stacking range change of the species, Levant–Taurus, Zagros–Central Iran and Alborz–Kopet–Dagh mountain ranges will experience the highest amount of habitat loss, respectively, with Caucasus–Pontic being least affected. The gap analysis showed that the existing PAs system covers only 13% and 10% of the in situ and ex situ climatic refugia, respectively. Conclusions: Our findings underscore the significance of mountainous regions in the Middle East for the persistence of alpine bird species and the urgent need to prioritize climate refugia in transboundary and participatory conservation plans. It is crucial to prevent habitat degradation and alteration resulting from human activities in these areas to ensure the persistence of alpine species and their habitats. [ABSTRACT FROM AUTHOR]

Environmental factors impact species richness differently across taxonomic groups, and understanding the geographic patterns and drivers influencing alpine plant richness remains limited. This study compiled global distribution data of 404 species of Gentiana, an alpine genus, and analyzed the relative effects of different environmental factors and several previously proposed models on the variation of Gentiana richness. By evaluating the effects of range size and regions on the relationships between Gentiana richness and environmental factors, we found that all tested environmental factors had weak effects on richness variation for all species and wide‐ranging species, while habitat heterogeneity was the best predictor for narrow‐ranging species. Habitat heterogeneity was the main driver of richness variation in Europe and Asia, but not in North America. The multiple regression model that included variables for energy, water, seasonality, habitat heterogeneity and past climate change had the highest explanatory power, but it still explained less than 50% of the variation in species richness for all Gentiana species at both global and regional scale, except for Europe. The limited explanatory power of environmental factors in explaining species richness patterns for all species, along with the variations observed among regions, suggest that other factors, such as evolutionary processes and biogeographic history may have also influenced the geographic patterns of Gentiana species richness. In conclusion, our results indicate a limited influence of climate factors on alpine species richness, while habitat heterogeneity, along with its impacts on speciation and dispersal, likely play significant roles in shaping the richness of alpine Gentiana species. [ABSTRACT FROM AUTHOR]

The recent rapid improvement of machine learning techniques had a large impact on the way seismological data can be processed. During the last years several machine learning algorithms determining seismic onset times have been published facilitating the automatic picking of large data sets. Here we apply the deep neural network PhaseNet to a network of over 900 permanent and temporal broad-band stations that were deployed as part of the AlpArray research initiative in the Greater Alpine Region (GAR) during 2016–2020. We selected 384 well distributed earthquakes with M L ≥ 2.5 for our study and developed a purely data-driven pre-inversion pick selection method to consistently remove outliers from the automatic pick catalogue. This allows us to include observations throughout the crustal triplication zone resulting in 39 599 P and 13 188 S observations. Using the established VELEST and the recently developed McMC codes we invert for the 1-D P - and S -wave velocity structure including station correction terms while simultaneously relocating the events. As a result we present two separate models differing in the maximum included observation distance and therefore their suggested usage. The model AlpsLocPS is based on arrivals from ≤130 km and therefore should be used to consistently (re)locate seismicity based on P and S observations. The model GAR1D_PS includes the entire observable distance range of up to 1000 km and for the first time provides consistent P - and S -phase synthetic traveltimes for the entire Alpine orogen. Comparing our relocated seismicity with hypocentral parameters from other studies in the area we quantify the absolute horizontal and vertical accuracy of event locations as ≈2.0 and ≈6.0 km, respectively. [ABSTRACT FROM AUTHOR]

Aim: Glacial refugia are areas of primary importance for the evolution and conservation of biodiversity. Yet, their geographic location remains loosely defined even in intensively studied areas, preventing a thorough understanding of their role in the spatiotemporal biodiversity dynamics. With this study, we aim to locate the major glacial refugia within the biodiversity hotspot of the Italian peninsula, to understand the processes that warranted the long‐term persistence of biodiversity in the face of climate changes. Location: Italian peninsula. Taxon: Terrestrial vertebrates. Methods: We calibrated species distribution models (SDM) for 22 lineages of terrestrial vertebrates endemic to the Italian peninsula and projected the SDMs to the last‐glacial maximum conditions. Then, we combined single‐lineage projections to investigate the location and spatiotemporal dynamics of multi‐species glacial refugia. Results: Multi‐species refugia were mostly found in coastal areas that have been flooded by the post‐glacial marine transgressions, and that are currently below the sea level. Indeed, we identified six major areas acting as glacial refugia, mainly located outside the current coastline in the southern part of the peninsula and along the western coast. These areas were close to previously inferred locations of glacial refugia and genetic diversity hotspots, but none coincided with them. Conclusions: Results from this study outline glacial refugia as highly dynamic units. Most of the identified refugial areas have been lost by post‐glacial sea‐level rise. Accordingly, species persistence through the Late Pleistocene was not granted by long‐term environmental stability, but by the opportunity to shift species' distributions along altitudinal gradients, following changes in climate and habitat suitability. Notably, our results decouple glacial refugia from hotspots of genetic diversity. Thus, the current location of a hotspot should not be taken as evidence for the occurrence of a glacial refugium in that location—even though a refugium is likely to be located somewhere nearby. [ABSTRACT FROM AUTHOR]

Aim: High‐elevation specialist species are threatened by climate change and habitat loss, and their distributions are becoming increasingly reduced and fragmented. In such a context, dispersal ability is crucial to maintain gene flow among patches of suitable habitat. However, information about dispersal is often lacking for these species, especially for those taxa that are usually considered as good dispersers such as birds. We adopted a landscape genomics approach to investigate dispersal in a climate‐sensitive high‐elevation specialist bird. Our aims were to assess the levels of gene flow within a wide mountain area, and to assess the effects of geographic distance and landscape characteristics on dispersal, by testing the isolation by distance (IBD) hypothesis against the isolation by resistance (IBR) hypothesis. Location: European Alps. Taxon: Montifringilla nivalis. Methods: We sampled individuals from several breeding areas and obtained single nucleotide polymorphism (SNP) data by ddRAD sequencing. We then calculated site‐ and individual level genetic distances and individual inbreeding coefficients. To test IBD versus IBR, we related genetic distances to both geographic distances and different measures of landscape resistance by using maximum likelihood population effects models. Results: Gene flow among breeding areas was partly restricted, and we found support for IBD, indicating that geographic distance limits snowfinch dispersal. Spatial patterns of genetic distances suggested that philopatry strongly contributed to determine the observed IBD. High inbreeding coefficients in several individuals indicated frequent mating among relatives. Main Conclusions: Restricted dispersal and frequent inbreeding within 'sky island' systems can also occur in highly mobile species, because their potential ability to cover very large distances can be counteracted by high philopatry levels that are likely related to high dispersal costs. IBD and philopatry will increasingly hinder snowfinch dispersal among suitable areas within the future more restricted and fragmented breeding range, increasing the risks of local extinctions. [ABSTRACT FROM AUTHOR]

Land use changes modify soil properties, including aggregate structure, and thus, profoundly affect soil quality and health. However, the effects of land use changes originating from alpine grassland on soil aggregates and aggregate-associated organic carbon have received little attention. Soil aggregate fraction, aggregate-associated organic carbon and relevant influencing factors were determined at 0–20, 20–40 cm soil layers for alpine grassland, cropland and abandoned land in the eastern Qinghai–Tibet Plateau (QTP), and their relationships were analyzed by partial least square regression (PLSR). Results showed the following: (1) conversion from alpine grassland to cropland resulted in a significant decline macroaggregate fraction (R0.25), mean weight diameter (MWD), mean weight diameter (GMD), soil organic carbon (SOC), and microaggregate-associated SOC; (2) almost all aggregate stability indexes, SOC, and aggregate-associated SOCs were significantly positively correlated with silt and glomalin, suggesting that the binding of fine particles (silt) with the organic cementing agent (glomalin) was probably a key mechanism of SOC formation and aggregate stability in the studied region; (3) compared with biotic factors such as SOC, glomalin and root biomass, abiotic factors including silt and sand can better predict aggregate stability and SOC fraction using the PLSR model. The above results indicated that the conversion of alpine grassland to other land use types in high altitude areas would destroy soil structure and decrease soil organic carbon content, and then reduce soil quality. [ABSTRACT FROM AUTHOR]

Aim: Species–area relationships (SAR) are widely utilized for estimating the species richness and its spatial turnover across various scales. Despite the prevalent characterization of SAR using the power law in many microbial community studies, its efficacy remains unvalidated. This study aims to characterize the microbial SAR and its mechanisms in alpine grassland soils on the Qinghai‐Tibet Plateau (QTP). Location: Qinghai‐Tibet Plateau, China. Time Period: August 2014. Major Taxa Studied: Soil bacteria. Methods: Soil samples were collected from five alpine grassland sites on the QTP. Employing a nested sampling strategy at each site, soil samples were collected in plot sizes ranging from 0.5 × 0.5 m2 to 2048 × 2048 m2. Soil bacterial communities were analysed by sequencing 16S ribosomal RNA gene amplicons using an Illumina MiSeq. Results: The bacterial SAR exhibited a logarithmic power law (R2: 0.952–0.999), outperforming the power law (R2: 0.701–0.852). Consequently, the most widely adopted power law led to an overestimation of species richness by up to 15.07% in areas >256 × 256 m2, and the regional maximum theoretical richness based on Chao1 by up to 9.88%. Mechanistically, the passive sampling hypothesis was refuted through the rarefied species richness analysis, and the disproportionate effect hypothesis was rejected based on analyses of the effective numbers of species number conversions for the probability of interspecific encounters (SPIE). Notably, Pearson and multiple linear regression analyses indicated that the spatial turnover of bacterial richness was determined by the environmental heterogeneity (R2: 0.855–0.999), rather or better than environmental variables themselves, supporting the 'environment heterogeneity hypothesis'. Main Conclusions: Soil bacterial SAR in alpine grasslands exhibited a logarithmic power relationship. Spatial turnover was primarily governed by the environmental heterogeneity. In contrast, the traditional power law leads to an overestimation of soil bacterial diversity at the regional scale. [ABSTRACT FROM AUTHOR]

Backgroud: The genus Mesorhizobium is shown by phylogenomics to be paraphyletic and forms part of a complex that includes the genera Aminobacter, Aquamicrobium, Pseudaminobacter and Tianweitania. The relationships for type strains belong to these genera need to be carefully re-evaluated. Results: The relationships of Mesorhizobium complex are evaluated based on phylogenomic analyses and overall genome relatedness indices (OGRIs) of 61 type strains. According to the maximum likelihood phylogenetic tree based on concatenated sequences of 539 core proteins and the tree constructed using the bac120 bacterial marker set from Genome Taxonomy Database, 65 type strains were grouped into 9 clusters. Moreover, 10 subclusters were identified based on the OGRIs including average nucleotide identity (ANI), average amino acid identity (AAI) and core-proteome average amino acid identity (cAAI), with AAI and cAAI showing a clear intra- and inter-(sub)cluster gaps of 77.40–80.91% and 83.98–86.16%, respectively. Combined with the phylogenetic trees and OGRIs, the type strains were reclassified into 15 genera. This list includes five defined genera Mesorhizobium, Aquamicrobium, Pseudaminobacter, Aminobacterand Tianweitania, among which 40/41 Mesorhizobium species and one Aminobacter species are canonical legume microsymbionts. The other nine (sub)clusters are classified as novel genera. Cluster III, comprising symbiotic M. alhagi and M. camelthorni, is classified as Allomesorhizobium gen. nov. Cluster VI harbored a single symbiotic species M. albiziae and is classified as Neomesorhizobium gen. nov. The remaining seven non-symbiotic members were proposed as: Neoaquamicrobium gen. nov., Manganibacter gen. nov., Ollibium gen. nov., Terribium gen. nov., Kumtagia gen. nov., Borborobacter gen. nov., Aerobium gen. nov.. Furthermore, the genus Corticibacterium is restored and two species in Subcluster IX-1 are reclassified as the member of this genus. Conclusion: The Mesorhizobium complex are classified into 15 genera based on phylogenomic analyses and OGRIs of 65 type strains. This study resolved previously non-monophyletic genera in the Mesorhizobium complex. [ABSTRACT FROM AUTHOR]

The present study aimed to determine the major cause of the high mortality affecting farmed gilthead seabream (Sparus aurata) and controlling this disease condition. Fifteen diseased S. aurata were sampled from a private fish farm located at Eldeba Triangle, Damietta, fish showed external skin hemorrhages, and ulceration. Bacterial isolates retrieved from the diseased fish were identified biochemically as Pseudomonas putida and then confirmed by phylogenetic analysis of the 16 S rRNA gene sequence. P. putida was also isolated from three batches of tilapia-trash feed given to S. aurata. Biofilm and hemolytic assay indicated that all P. putida isolates produced biofilm, but 61.11% can haemolyse red blood cells. Based on the antibiotic susceptibility test results, P. putida was sensitive to florfenicol with minimum inhibitory concentrations ranging between 0.25 and 1.0 µg mL− 1, but all isolates were resistant to ampicillin and sulfamethoxazole-trimethoprim. Pathogenicity test revealed that P. putida isolate (recovered from the tilapia-trash feed) was virulent for S. aurata with LD50 equal to 4.67 × 107 colony forming unit (CFU) fish− 1. After intraperitoneal (IP) challenge, fish treated with 10 mg kg− 1 of florfenicol showed 16.7% mortality, while no mortality was recorded for the fish group that received 20 mg kg− 1. The non-treated fish group showed 46.7% mortality after bacterial challenge. HPLC analysis of serum florfenicol levels reached 1.07 and 2.52 µg mL− 1 at the 5th -day post-drug administration in the fish groups received 10 and 20 mg kg− 1, respectively. In conclusion, P. putida was responsible for the high mortality affecting cultured S. aurata, in-feed administration of florfenicol (20 mg kg− 1) effectively protected the challenged fish. [ABSTRACT FROM AUTHOR]

Warming and precipitation anomalies affect terrestrial carbon balance partly through altering microbial eco-physiological processes (e.g., growth and death) in soil. However, little is known about how such processes responds to simultaneous regime shifts in temperature and precipitation. We used the 18O-water quantitative stable isotope probing approach to estimate bacterial growth in alpine meadow soils of the Tibetan Plateau after a decade of warming and altered precipitation manipulation. Our results showed that the growth of major taxa was suppressed by the single and combined effects of temperature and precipitation, eliciting 40-90% of growth reduction of whole community. The antagonistic interactions of warming and altered precipitation on population growth were common (~70% taxa), represented by the weak antagonistic interactions of warming and drought, and the neutralizing effects of warming and wet. The members in Solirubrobacter and Pseudonocardia genera had high growth rates under changed climate regimes. These results are important to understand and predict the soil microbial dynamics in alpine meadow ecosystems suffering from multiple climate change factors. [ABSTRACT FROM AUTHOR]

Background: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. Methods: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0–17 from 2017–2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. Results: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7–13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6–12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4–10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. Conclusions: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs. [ABSTRACT FROM AUTHOR]

Mountains exert a drag on the atmospheric flow through breaking gravity waves, known as orographic gravity‐wave drag (OGWD). This article presents a theoretical analysis of the impacts and limitations of missing processes in current parameterization schemes for OGWD and examines the significance of various approximations. We derive OGWD analytically for multiple three‐dimensional bell‐shaped mountains, while previous studies have derived OGWD for a single three‐dimensional elliptic mountain. We take into account the geometric overlap between the mountains, vertical shear of the horizontal wind, nonhydrostatic atmosphere, and Coriolis forces. Our findings show that OGWD depends on the direction of the incoming wind and the degree of overlap between two mountains. OGWD increases with the Richardson and Rossby numbers; however, it decreases with the Froude number. Even when the mountain is isotropic, an associated transverse force is generated if the sheared flow passes over the mountain on the f$$ f $$‐plane. By calculating OGWD analytically from more complex terrain and airflow, this study can contribute to the development of an advanced OGWD parameterization in the numerical models used for climate and weather prediction. [ABSTRACT FROM AUTHOR]

Plastic materials, including microplastics, accumulate in all types of ecosystems, even in remote and cold environments such as the European Alps. This pollution poses a risk for the environment and humans and needs to be addressed. Using shotgun DNA metagenomics of soils collected in the eastern Swiss Alps at about 3,000 m a.s.l., we identified genes and their proteins that potentially can degrade plastics. We screened the metagenomes of the plastisphere and the bulk soil with a differential abundance analysis, conducted similarity-based screening with specific databases dedicated to putative plastic-degrading genes, and selected those genes with a high probability of signal peptides for extracellular export and a high confidence for functional domains. This procedure resulted in a final list of nine candidate genes. The lengths of the predicted proteins were between 425 and 845 amino acids, and the predicted genera producing these proteins belonged mainly to Caballeronia and Bradyrhizobium. We applied functional validation, using heterologous expression followed by enzymatic assays of the supernatant. Five of the nine proteins tested showed significantly increased activities when we used an esterase assay, and one of these five proteins from candidate genes, a hydrolase-type esterase, clearly had the highest activity, by more than double. We performed the fluorescence assays for plastic degradation of the plastic types BI-OPL and ecovio® only with proteins from the five candidate genes that were positively active in the esterase assay, but like the negative controls, these did not show any significantly increased activity. In contrast, the activity of the positive control, which contained a PLA-degrading gene insert known from the literature, was more than 20 times higher than that of the negative controls. These findings suggest that in silico screening followed by functional validation is suitable for finding new plastic-degrading enzymes. Although we only found one new esterase enzyme, our approach has the potential to be applied to any type of soil and to plastics in various ecosystems to search rapidly and efficiently for new plastic-degrading enzymes. [ABSTRACT FROM AUTHOR]

This paper introduces the AtsMOS workflow, designed to enhance mountain meteorology predictions through the downscaling of coarse numerical weather predictions using local observational data. AtsMOS provides a modular, open-source toolkit for local and large-scale forecasting of various meteorological variables through modified Model Output Statistics – and may be applied to data from a single station or an entire network. We demonstrate its effectiveness through an example application at the summit of Mt. Everest, where it improves the prediction of both meteorological variables (e.g. wind speed, temperature) and derivative variables (e.g. facial frostbite time) critical for mountaineering safety. As a bridge between numerical weather prediction models and ground observations, AtsMOS help produce insights for hazard mitigation, water resource management, and other weather-dependant issues in mountainous regions and beyond. [ABSTRACT FROM AUTHOR]

Pollinators are vital for food security and the maintenance of terrestrial ecosystems. Bumblebees are important pollinators across northern temperate, arctic, and alpine ecosystems, yet are in decline across the globe. Vairimorpha bombi is a parasite belonging to the fungal class Microsporidia that has been implicated in the rapid decline of bumblebees in North America, where it may be an emerging infectious disease. To investigate the evolutionary basis of pathogenicity of V. bombi , we sequenced and assembled its genome using Oxford Nanopore and Illumina technologies and performed phylogenetic and genomic evolutionary analyses. The genome assembly for V. bombi is 4.73 Mb, from which we predicted 1,870 protein-coding genes and 179 tRNA genes. The genome assembly has low repetitive content and low GC content. V. bombi 's genome assembly is the smallest of the Vairimorpha and closely related Nosema genera, but larger than those found in the Encephalitozoon and Ordospora sister clades. Orthology and phylogenetic analysis revealed 18 core conserved single-copy microsporidian genes including the histone acetyltransferase (HAT) GCN5. Surprisingly, V. bombi was unique to the microsporidia in not encoding the second predicted HAT ESA1. The V. bombi genome assembly annotation included 265 unique genes (i.e. not predicted in other microsporidia genome assemblies), 20% of which encode a secretion signal, which is a significant enrichment. Intriguingly, of the 36 microsporidian genomes we analyzed, 26 also had a significant enrichment of secreted signals encoded by unique genes, ranging from 6 to 71% of those predicted genes. These results suggest that microsporidia are under selection to generate and purge diverse and unique genes encoding secreted proteins, potentially contributing to or facilitating infection of their diverse hosts. Furthermore, V. bombi has 5/7 conserved spore wall proteins (SWPs) with its closest relative V. ceranae (that primarily infects honeybees), while also uniquely encoding four additional SWPs. This gene class is thought to be essential for infection, providing both environmental protection and recognition and uptake into the host cell. Together, our results show that SWPs and unique genes encoding a secretion signal are rapidly evolving in the microsporidia, suggesting that they underpin key pathobiological traits including host specificity and pathogenicity. [ABSTRACT FROM AUTHOR]

Mountain forests provide multiple benefits but are threatened by climate change-induced forest dieback. Although many studies summarize perceptions of forest ecosystem services, relatively few deal with mountain forests. The local population's perception of forest dieback in mountain forests in relation to climate change has rarely been investigated so far. Their perspective is relevant as local people are often deeply attached to "their" forests, they actively use forest ecosystems and—as voters and taxpayers—they need to support the state's adaptation and funding measures. Therefore, this study investigates the climate change and forest dieback perception of local inhabitants in two mountain areas of Southern Germany (the German Alps and the Bavarian Forest) with a quantitative survey based on representative online samples (n = 709). Relying conceptually on van der Linden's (J Environ Psychol 41:112–124, 2015. https://doi.org/10.1016/j.jenvp.2014.11.012) climate change risk perception model, the results show that experiential processing, cognitive and socio-cultural factors are related to locals' forest dieback and climate change perception, while socio-demographics show no or few connections. Nearly two-thirds (64.7%) of the respondents perceive moderate to strong forest dieback, while more than half (55.0%) of the respondents already observe consequences of climate change. The perceptions of climate change and forest dieback are positively correlated with medium to high strength. This shows that forest dieback could be interpreted as an indicator of climate change, which is difficult to observe due to its long-term nature. We identify three groups of respondents regarding preferred forest adaptation strategies to climate change. In general, respondents support nature-based forest adaptation strategies over intense measures. [ABSTRACT FROM AUTHOR]

Mountain is the most traditional tourism destination in China. On the basis of analyzing the particularity and its spatial differentiation of human-environment relationship in mountain tourism destination, this paper conducts empirical analysis in Yulong Snow Mountain by land use type classification. Firstly, ENVI is used to preprocess the Landsat-8 images of the research area. Then the visual interpretation is performed by ArcGIS to classify land use types. Based on the above, the differentiation status of human-environment relationship is analyzed. It concluded that: (1) Under the influence of natural factors such as piedmont, climate, altitude, gradient, slope, geological environment, and geomorphic characteristics, the uneven spatial distribution of human-environment relationship in mountain tourism destination is greatly affected by vegetation, rainfall, heat distribution, wind direction, suitability for human activities, and especially the topography; (2) The Yulong Snow Mountain forms three distinct levels of spatial differentiation in human-environment relationships between the east and west slopes, between high, medium and low elevations, and between different gradients. [ABSTRACT FROM AUTHOR]

A single extremely halophilic strain was isolated from salt brine produced when a fresh water lake flooded a large salt mine located beneath the lake. The water that entered this mine contained less than 0.34 M NaCl, but over time, this sealed brine became saturated by Cenozoic age salt (121–125 million-year BCE). The isolated strain requires at least 1.7 M NaCl for survival and grows optimally in 3.1 M NaCl. Therefore, it could not have survived or been present in the waters that flooded this salt mine. The strain grows at a pH range from 6.5 to 9.0 and has a wide tolerance to temperatures from 25 ℃ to at least 60 ℃. The comparison of 16S rRNA and rpoB′ genes revealed that strain 1–13-28T is related to Halorubrum tebenquichense DSM 14210T showing 98.6% and 98.1% similarities, respectively. Phylogenetic analyses based on 16S rRNA, rpoB′ genes and 122 concatenated archaeal genes show that the strain 1–13-28T consistently forms a cluster with Halorubrum tebenquichense of the genus Halorubrum. Strain 1–13-28T contained sulfated mannosyl glucosyl diether, and the polar lipid profile was identical to those of most Halorubrum species. Based on the overall combination of physiological, phylogenetic, polar lipids and phylogenomic characteristics, strain 1–13-28T (= ATCC 700083T = CGMCC 1.62627T) represents a newly identified species within the genus Halorubrum for which the name Halorubrum hochsteinianum is proposed. [ABSTRACT FROM AUTHOR]

Degrading rock wall permafrost was found responsible for the increase in rockfall and landslide activity in several cold mountain regions across the globe. In Greenland, rock wall permafrost has so far received little attention from the scientific community, despite mountains being a predominant feature on the ice-free coastline and landslide activity being significant. In this study, we aim to make a first step towards a better understanding of rock wall permafrost in Greenland by modelling rock wall temperatures in the mountain area around the town of Sisimiut, which is 68° N on the west coast of Greenland. We first acquire rock surface temperature (RST) data for the period September 2020–September 2022 to model rock surface temperatures from weather forcing. The model is then applied to weather data from 1870 to 2022, generating rock surface temperatures to force transient heat transfer simulations over the same period. By extrapolating this method at the landscape scale, we obtain permafrost distribution maps and ad hoc simulations for complex topographies. Our model results are compared to temperature data from two lowland boreholes (100 m depth) and geophysical data describing frozen and unfrozen conditions across a mid-elevation mountain ridge. Finally, we use regional carbon pathway scenarios 2.6 and 8.5 to evaluate future evolution of rock wall temperatures until the end of the 21st century. Our data and simulation describe discontinuous permafrost distribution in rock walls up to roughly 400 m a.s.l. Future scenarios suggest a decline of deep frozen bodies up to 800 m a.s.l., i.e. the highest summits in the area. In summary, this study depicts a picture of warm permafrost in this area, highlighting its sensitivity to ongoing climate change. [ABSTRACT FROM AUTHOR]

Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences. We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example, Austrocedrus chilensis and Nothofagus dombeyi forests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland of Nothofagus antarctica representing a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems. The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences. [ABSTRACT FROM AUTHOR]

Patterns of variation in the size of vulture foraging groups, and their ecological causes and consequences, remain little explored despite strong links with the carrion recycling service that this key functional group provides. We documented the group size-frequency pattern of Andean condors Vultur gryphus gathered to feed on 42 equine carcasses experimentally placed in Bolivia, between 2012 and 2019, along an elevation range of 1,300–4,500 m asl. Based on the location (altitude and latitude) of the foraging groups, we examined the relationship between their size and species' population parameters (size and trend), habitat conditions, and livestock carcass availability and predictability. Condors utilized a high frequency (93%) of carcasses forming groups that ranged from 1 to 80 individuals (mean = 25, median = 18) and shaped a "lazy-J curve" typical pattern of size-frequency distribution whereby few groups (5, 12%) were large (> 55 individuals) and most (21, 50%) were relatively small (<19 individuals). Group size related to altitude in that most larger groups formed at lower sites (below c. 3,000 m asl), likely following an altitudinal gradient whereby larger groups are more likely to form around larger carcasses (i.e. cattle), which are more likely to occur at lower elevations. Regardless of population size, group size could be an adaptive response of condors via local enhancement for improving individual scavenging efficiency. Many information gaps on this topic still exist, thus we provide a set of questions to address them, especially amidst the unrestricted impacts of human activities that condition vulture survival globally. [ABSTRACT FROM AUTHOR]

The genus Xanthomonas has been primarily studied for pathogenic interactions with plants. However, besides host and tissue-specific pathogenic strains, this genus also comprises nonpathogenic strains isolated from a broad range of hosts, sometimes in association with pathogenic strains, and other environments, including rainwater. Based on their incapacity or limited capacity to cause symptoms on the host of isolation, nonpathogenic xanthomonads can be further characterized as commensal and weakly pathogenic. This study aimed to understand the diversity and evolution of nonpathogenic xanthomonads compared to their pathogenic counterparts based on their cooccurrence and phylogenetic relationship and to identify genomic traits that form the basis of a life history framework that groups xanthomonads by ecological strategies. We sequenced genomes of 83 strains spanning the genus phylogeny and identified eight novel species, indicating unexplored diversity. While some nonpathogenic species have experienced a recent loss of a type III secretion system, specifically the hrp2 cluster, we observed an apparent lack of association of the hrp2 cluster with lifestyles of diverse species. We performed association analysis on a large data set of 337 Xanthomonas strains to explain how xanthomonads may have established association with the plants across the continuum of lifestyles from commensals to weak pathogens to pathogens. Presence of distinct transcriptional regulators, distinct nutrient utilization and assimilation genes, transcriptional regulators, and chemotaxis genes may explain lifestyle-specific adaptations of xanthomonads. [ABSTRACT FROM AUTHOR]

Microhabitat utilisation holds a pivotal role in shaping a species' ecological dynamics and stands as a crucial concern for effective conservation strategies. Despite its critical importance, microhabitat use has frequently been addressed as static, centering on microhabitat preference. Yet, a dynamic microhabitat use that allows individuals to adjust to fine-scale spatio-temporal prey fluctuations, becomes imperative for species thriving in challenging environments. High-elevation ecosystems, marked by brief growing seasons and distinct abiotic processes like snowmelt, winds, and solar radiation, feature an ephemeral distribution of key resources. To better understand species' strategies in coping with these rapidly changing environments, we delved into the foraging behaviour of the white-winged snowfinch Montifringilla nivalis, an emblematic high-elevation passerine. Through studying microhabitat preferences during breeding while assessing invertebrate prey availability, we unveiled a highly flexible microhabitat use process. Notably, snowfinches exhibited specific microhabitat preferences, favoring grass and melting snow margins, while also responding to local invertebrate availability. This behaviour was particularly evident in snow-associated microhabitats and less pronounced amid tall grass. Moreover, our investigation underscored snowfinches' fidelity to foraging sites, with over half located within 10 m of previous spots. This consistent use prevailed in snow-associated microhabitats and high-prey-density zones. These findings provide the first evidence of dynamic microhabitat use in high-elevation ecosystems and offer further insights into the crucial role of microhabitats for climate-sensitive species. They call for multi-faceted conservation strategies that go beyond identifying and protecting optimal thermal buffering areas in the face of global warming to also encompass locations hosting high invertebrate densities. [ABSTRACT FROM AUTHOR]

Viruses are major players in the biosphere, yet little is known about their dynamics and life strategies in alpine lakes, particularly those on the Tibetan Plateau. We investigated microbial abundance, viral dynamics, and viral life strategies in 10 high‐altitude Tibetan lakes and found that they harbor high levels of active viruses. Salinity was identified as a crucial factor influencing viral abundance, dynamics, as well as viral life strategies. Lytic and lysogenic viral productions in moderate‐ and high‐salinity lakes were significantly higher than those in freshwater lakes. A trade‐off between viral life strategies resulted in a switch from lysis to lysogeny in high‐salinity lakes. Virus‐mediated cell lysis and virus decay in sampled Tibetan lakes could release about 162.72 and 2.84 μg C L−1 d−1, respectively. These findings revealed the crucial role of viruses in the carbon cycle of Tibetan lakes, and a switch in viral life strategies may impact their contribution to the carbon cycle. The potential impact of salinity changes triggered by climate change on the carbon cycle in alpine lakes worldwide is highlighted. [ABSTRACT FROM AUTHOR]

Species interactions such as facilitation and competition play a crucial role in driving species range shifts. However, density dependence as a key feature of these processes has received little attention in both empirical and modelling studies. Herein, we used a novel, individual‐based treeline model informed by rich in situ observations to quantify the contribution of density‐dependent species interactions to alpine treeline dynamics, an iconic biome boundary recognized as an indicator of global warming. We found that competition and facilitation dominate in dense versus sparse vegetation scenarios respectively. The optimal balance between these two effects was identified at an intermediate vegetation thickness where the treeline elevation was the highest. Furthermore, treeline shift rates decreased sharply with vegetation thickness and the associated transition from positive to negative species interactions. We thus postulate that vegetation density must be considered when modelling species range dynamics to avoid inadequate predictions of its responses to climate warming. [ABSTRACT FROM AUTHOR]

The ongoing climate change on the Tibetan Plateau, leading to warming and precipitation anomalies, modifies phosphorus (P) cycling in alpine meadow soils. However, the interactions and cascading effects of warming and precipitation changes on the key "extracellular" and "intracellular" P cycling genes (PCGs) of bacteria are largely unknown for these P‐limited ecosystems. We used metagenomics to analyze the individual and combined effects of warming and altered precipitation on soil PCGs and P transformation in a manipulation experiment. Warming and increased precipitation raised Olsen‐P (bioavailable P, AP) by 13% and 20%, respectively, mainly caused by augmented hydrolysis of organic P compounds (NaOH‐Po). The decreased precipitation reduced soil AP by 5.3%. The richness and abundance of the PCGs' community in soils on the cold Tibetan plateau were more sensitive to warming than altered precipitation. The abundance of PCGs and P cycling processes decreased under the influence of individual climate change factors (i.e., warming and altered precipitation alone), except for the warming combined with increased precipitation. Pyruvate metabolism, phosphotransferase system, oxidative phosphorylation, and purine metabolism (all "intracellular" PCG) were closely correlated with P pools under climate change conditions. Specifically, warming recruited bacteria with the phoD and phoX genes, which encode enzymes responsible for phosphoester hydrolysis (extracellular P cycling), strongly accelerated organic P mineralization and so, directly impacted P bioavailability in alpine soil. The interactions between warming and altered precipitation profoundly influenced the PCGs' community and facilitated microbial adaptation to these environmental changes. Warming combined with increased precipitation compensated for the detrimental impacts of the individual climate change factors on PCGs. In conclusion, warming combined with rising precipitation has boosting effect on most P‐related functions, leading to the acceleration of P cycling within microbial cells and extracellularly, including mineralization and more available P release for microorganisms and plants in alpine soils. [ABSTRACT FROM AUTHOR]

Recreational activities often result in a spatial and/or temporal activity shift in wildlife. With the concurrent development of outdoor activities and increase in temperatures due to climate change, mountain species face increasing pressures in terms of managing their activity pattern to limit both risk exposure and thermal discomfort. Using more than 15 years of long-term GPS and activity sensor data, we investigated how female northern chamois, Rupicapra rupicapra rupicapra , adjust their summer circadian activity to spatiotemporal variation in both temperatures and hikers' presence. Chamois' behaviour was more affected by high temperatures than by hikers' presence. During the hottest days, they shifted their activity peak earlier in the morning, were more active at night and during activity peaks, less active during daytime and had longer morning and evening peaks compared to the coldest days. Yet, total daily activity was only slightly different during the hottest days compared to the coldest days. Conversely, hikers' disturbance had weak effects on activity levels and on the timing of activity peaks. This is especially true for temporal disturbance (weekdays versus weekends and public holidays), possibly because most weekdays in summer fell during school holidays. Only during the hottest conditions, the morning activity peak was shorter and the evening peak longer in females living in the most exposed areas compared to females living in the least exposed areas. One possible explanation for the overall low effect of hikers' disturbance may be that behavioural changes buffering animals from high temperatures and hikers' presence (e.g. moving away from trails) allow them to just marginally modify their activity pattern. In the context of ongoing socioenvironmental changes, it is critical to conserve habitats providing thermal refuges against summer heat and protection from disturbance to mitigate potential detrimental consequences. • Chamois shifted their activity peak earlier in the morning during the hottest days. • Activity increased at night and decreased during the day with high temperatures. • Chamois' crepuscular activity was higher during the hottest than the coldest days. • Spatiotemporal variation in hikers' presence had few effects on chamois' activity. • Females in the most disturbed areas shortened morning activity on the hottest days. [ABSTRACT FROM AUTHOR]

Meadows are the most important source of feed for extensive livestock farming in mountainous conditions, as well as providing many environmental services. The actual socioeconomic situation and climate change risk its conservation. That is why finding its optimal management is important. To do so, predictive models are a useful tool to determine the impact of different practices and estimate the consequences of future scenarios. Empirical models are a good analytical tool, but their applications in the future are limited. Dynamic models can better estimate the consequences of newer scenarios, but even if there are many dynamic models, their adaptation into grassland production estimation is scarce. This article reviews the most suitable predictive models for grass production in mountain meadows when data on agricultural management (mowing, grazing, fertilization) and forage value are available, considering the conservation of plant biodiversity. [ABSTRACT FROM AUTHOR]

The highly temporal variability of the hydrological response in Mediterranean areas affects the operation of hydropower systems, especially in run-of-river (RoR) plants located in mountainous areas. Here, the water flow regime strongly determines failure, defined as no operating days due to inflows below the minimum operating flow. A Bayesian dynamics stochastic model was developed with statistical modeling of both rainfall as the forcing agent and water inflows to the plants as the dependent variable using two approaches—parametric adjustments and non-parametric methods. Failure frequency analysis and its related operationality, along with their uncertainty associated with different time scales, were performed through 250 Monte Carlo stochastic replications of a 20-year period of daily rainfall. Finally, a scenario analysis was performed, including the effects of 3 and 30 days of water storage in a plant loading chamber to minimize the plant's dependence on the river's flow. The approach was applied to a mini-hydropower RoR plant in Poqueira (Southern Spain), located in a semi-arid Mediterranean alpine area. The results reveal that the influence of snow had greater operationality in the spring months when snowmelt was outstanding, with a 25% probability of having fewer than 2 days of failure in May and April, as opposed to 12 days in the winter months. Moreover, the effect of water storage was greater between June and November, when rainfall events are scarce, and snowmelt has almost finished with operationality levels of 0.04–0.74 for 15 days of failure without storage, which increased to 0.1–0.87 with 3 days of storage. The methodology proposed constitutes a simple and useful tool to assess uncertainty in the operationality of RoR plants in Mediterranean mountainous areas where rainfall constitutes the main source of uncertainty in river flows. [ABSTRACT FROM AUTHOR]

Bangladesh and northeast India are the most densely populated regions in the world where severe floods as a result of extreme rainfall events kill hundreds of people and cause socio‐economic losses regularly. Owing to local high topography, the moisture‐carrying monsoon winds converge near southeast Bangladesh (SEB) and northeast Bangladesh and India (NEBI), which produces significant extreme rainfall events from May to October. Using observed data, we find an increasing trend of 1‐day extreme event (>$$ > $$150 mm·$$ \cdotp $$day −1$$ {}^{-1} $$) frequency during 1950–2021. The extreme rainfall events quadrupled over western Meghalaya (affecting NEBI) and coastal SEB during this period. Composite analysis indicates that warm Bay of Bengal sea‐surface temperature intensifies the lower tropospheric moisture transport and flux through the low‐level jet (LLJ) to inland, where mountain‐forced moisture converges and precipitates as rainfall during extreme events. To understand the role of climate change, we use high‐resolution downscaled models from Coupled Model Intercomparison Project phase 6 (CMIP6). We find that the monsoon extreme event increase is ongoing and the region of quadrupled events further extends over the NEBI and SEB in the future (2050–2079) compared with historical simulations (1950–1979). A quadrupling of the intense daily moisture transport episodes due to increased LLJ instability, a northward shift of LLJ, and increased moisture contribute to the increased future extreme events. This dynamic process causes moisture to be transported to the NEBI from the southern Bay of Bengal, and the local thermodynamic response to climate change contributes to the increased extreme rainfall events. The CMIP6 projection indicates that more devastating flood‐causing extreme rainfall events will become more frequent in the future. [ABSTRACT FROM AUTHOR]

The Irano-Turanian region is one of the largest floristic regions in the world and harbors a high percentage of endemics, including cushion-like and dwarf-shrubby taxa. Onobrychis cornuta is an important cushion-forming element of the subalpine/alpine flora of the Irano-Turanian floristic region. To specify the genetic diversity among the populations of this species (including individuals of O. elymaitica), we employed nrDNA ITS and two noncoding regions of plastid DNA (rpl32-trnL(UAG) and trnT(UGU)-trnL(UAA)). The most striking feature of O. cornuta assemblages was the unexpectedly high nucleotide diversity in both the nDNA and cpDNA dataset. In the analyses of nuclear and plastid regions, 25 ribotypes and 42 haplotypes were found among 77 and 59 accessions, respectively, from Iran, Turkey, and Afghanistan. Network analysis of the datasets demonstrated geographic differentiation within the species. Phylogenetic analyses of all dataset retrieved O. cornuta as a non-monophyletic species due to the inclusion of O. elymaitica, comprising four distinct lineages. In addition, our analyses showed cytonuclear discordance between both nuclear and plastid topologies regarding the position of some O. cornuta individuals. The underlying causes of this inconsistency remain unclear. However, we speculate that chloroplast capture, incomplete lineage sorting, and introgression were the main reasons for this event. Furthermore, molecular dating analysis indicated that O. cornuta originated in the early Pliocene (around 4.8 Mya) and started to diversify throughout the Pliocene and in particular the Pleistocene. Moreover, O. elymaitica was reduced to a subspecific rank within the species. [ABSTRACT FROM AUTHOR]

This study addresses the understudied dynamics of mortality and recruitment in Tropical Mountain forests, critical determinants of forest structural processes and biomass turnover. We examine how these demographic processes change with elevation and varying degrees of forest recovery by utilizing two forest censuses (2015 and 2019) from 16 plots (0.36 ha) across a 600–3500 m asl elevation gradient in the Ecuadorian Andes. Employing multivariate PCA analyses, we characterize successional forest dynamics and explore relationships between demographic rates, elevation, and indicators of forest recovery using standard linear regression and generalized additive models (GAMs). Contrary to our hypothesis, mortality exhibits a unimodal response, peaking at mid-elevations, with no significant relationship to above-ground biomass productivity (AGBp). In our successional forests, dominance by fast-growing species alters expected patterns, leading to increased mortality rates and AGBp, particularly at low-mid elevations. Forest recovery emerges as a significant driver of mortality and the sole predictor of recruitment, especially across different recovery statuses. Although forest recovery doesn't impact mortality rates, it elucidates the identity of declining species in forests with varying recovery degrees. Our findings underscore that while forest recovery does not alter mortality rates, it provides critical insights into understanding which species are affected under varying recovery conditions. Recruitment, primarily driven by successional dynamics, exhibits higher rates in sites with less recovery. Furthermore, we demonstrate the utility of forest structure indicators, such as above-ground biomass, in inferring successional dynamics when the time since the last disturbance is unknown. The study emphasizes the importance of considering disturbances in comprehending the intricate interplay between the environment and forest dynamics in secondary forests. [ABSTRACT FROM AUTHOR]

This study aims to quantify the spatial changes in farmland and model the efficiency of their use in mountainous territories, considering climate, topographical characteristics, and the development of exogenous geological processes. The main factors affecting land-use efficiency were assessed using qualitative and quantitative fact-finding, correlation analysis, and Geographic Information Systems tools. Accordingly, 14 major influencing factors were identified. A correlation and regression analysis was performed to resolve the modelling task. Using the correlation analysis methodology, the impact of each factor on the required indicator was quantified. The model developed shows that the land structure and production volume mainly influence land-use efficiency in agriculture. This finding fits well with pan-European studies. There is an annual trend towards more efficient use of farmland. In general, mountainous regions may provide high indicators of agricultural production under conditions of warm climate, sufficient moisture content, soil fertility and/or moderate fertilization, control of erosion processes, and predominance of low hypsometric heights. The developed model allows for optimizing the utilization of land resources, improving soil fertility and crop yields, and finding the right decisions for preventing the development of unfavourable processes. [ABSTRACT FROM AUTHOR]

Wind loads play an important role in the design and construction of long-span bridges, especially for that built in mountain valley, and wind characteristics in mountain terrain are still unclear. To further understand the wind characteristics at a bridge site in a mountain valley, large eddy simulations were employed to comprehensively study the wind characteristics at the bridge site in an L-shaped canyon. Different wind directions consisting of 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315° were considered, and the wind characteristics on the main girder and towers, as well as the flow field, were comprehensively investigated. The results indicate that the mean and fluctuating wind characteristics are significantly different from those specified in the relevant specifications, and it is inappropriate to apply the specifications directly to mountainous terrain. When wind flows along a channel, it leads to a large wind speed amplification factor, strong non-Gaussianity, and large kurtosis and skewness. The steeper the slope of the mountain, the stronger the non-Gaussianity of the fluctuating wind. The coherence function remains nearly unchanged when the distance between the two points is constant, regardless of the location. The wind characteristics at the main girder and towers are so different that they should be considered separately and taken into account in engineering practice. This study provides a reference for the wind-resistant design of bridges and structures built on mountainous terrains. [ABSTRACT FROM AUTHOR]

Questions: Climate change may have different effects on species richness depending on regional climates, soil types and the functional composition of local communities. Location: Subalpine belt of the Grandes Rousses (Alps) and Sancy mountain ranges (the Massif Central), France. Methods: We compared changes in species richness in response to recent climate change in communities from two mountain ranges subjected to contrasting environmental conditions, with a more continental climate and drier soils in the Alps than in the Massif Central. Vegetation composition of 189 and 157 plots was assessed in 1997 and 2017–2018 in the Alps and 1988–1989 and 2022 in the Massif Central, respectively. Five species traits (height, lateral spread, leaf area, specific leaf area and leaf dry matter content) were measured on 108 and 144 species, respectively. Changes in vegetation composition and species richness along spatial environmental gradients were analysed with correspondence analysis at the Sancy site and canonical correspondence analysis at the Alpe d'Huez site. Changes in functional composition across sites were analysed with principal components analysis. Changes in species richness with climate change were analysed with repeated‐measure ANOVAs. Results: In both mountain ranges summer temperatures increased and the hydric balance decreased over the past three decades, but snow cover duration decreased in the Alps only, whereas irradiance strongly increased in the Massif Central only. Functional composition was characterized by shorter and more conservative species in the Alps than in the Massif Central, which was dominated by tall exploitative species. Species richness overall decreased with climate change by ca 10% in the Alps but overall increased by ca 10% in the Massif Central. Species richness decreased in the Alps probably because of increasing competition induced by dwarf shrub encroachment due to decreasing snow cover duration, whereas species richness increased in the Massif Central probably due to increasing irradiance in a very nebulous climate. Conclusion: The opposite changes in species richness observed in the two mountain ranges with recent climate change were likely to be explained by their contrasting climate and soil conditions driving different functional compositions and diversity–environment relationships. [ABSTRACT FROM AUTHOR]