This study applied artificial intelligence algorithms to the time-series forecasting of meteorological variables associated with nocturnal drainage flows. Using observations from the Stable Atmospheric Variability And Transport (SAVANT) field campaign as the source data, a baseline dataset was constructed by extracting a core set of variables. These variables are output varibles. the XGBoost models were subsequently developed and integrated with SHAP (SHapley Additive exPlanations) to quantify feature importance. Based on the resulting SHAP rankings, additional variables beyond the core were selected from the original dataset to construct additional data sets. Then six deep learning models were compared with the baseline and additional datasets. Prior to the experiments, the raw data were preprocessed and resampled to a uniform 5-minute temporal resolution. In this study, the multivariate time series forecasting task is defined as follows: a continuous $\mathbf{1 4}$-hour observation sequence (168 time steps at 5 -minute resolution) serves as input to predict the subsequent 6 time steps (30 minutes of future meteorological evolution). This forecast horizon closely matches operational requirements for short-term atmospheric prediction. Results indicate that the optimal forecasting performance was achieved using only the baseline dataset, whereas the inclusion of non-baseline variables reduced predictive accuracy. Among the six models, MTGNN achieved the lowest MSE, while Crossformer yielded the lowest MAE. The superior performance demonstrated by MTGNN and Crossformer suggests that future research can further investigate hybrid architectures integrating graph structure modeling and attention mechanisms, and provide novel insights and approaches for improving meteorological forecasting performance through additional fusion experiments.

The alkaline phosphatase (phoD) gene-encoding bacterial communities (phoD-harbouring communities, hereafter) play crucial roles in organic phosphorus (Po) mineralisation across global terrestrial ecosystems. However, their geographic distribution and driving factors remain unclear, largely due to the mosaic temperature and humidity patterns and the lack of comprehensive high-resolution sampling data across the Qinghai-Tibet Plateau. We addressed this gap using amplicon sequencing techniques and analyses of soil properties as well as plant biomass. Plant biomass, soil organic carbon (C), Po content, C:P ratio, alkaline phosphatase (ALP) activity, and the richness and abundance of key soil phoD-harbouring taxa were higher in warmer, more humid regions, such as the southeastern plateau than the northeastern plateau, while soil pH followed an inverse trend. Soil pH and Po content emerged as the key factors shaping the geographic distribution of phoD-harbouring communities. Acidic soils were associated with higher C:P ratios, community richness, ALP activity, and Po content than alkaline soils. Our findings suggest that warmer, more humid regions promote soil acidification, which in turn drive changes in phoD-harbouring communities, enhance ALP activity, and stimulate Po mineralisation. This study provides new insights into the geographic distribution of phoD-harbouring communities and their role in Po mineralisation across the Qinghai-Tibet Plateau.

Terrain slopes with and without upslope large surface roughness impact downstream shear‐generated turbulence differently in the nighttime stable boundary layer (SBL). These differences can be identified through variations in the relationship between turbulence and wind speed at a given height, known as the HOckey STick (HOST) transition, as compared to the HOST relationship over flat terrain. The transport of cold surface air from elevated uniform terrain reduces downstream air temperature not much air stratification. As terrain slope rises, the increasing cold and heavy air enhances downstream hydrostatic imbalance, resulting in increasing turbulence for a given wind speed. That is, the rate of turbulence increase with wind speed from downslope flow is independent of terrain slope. Upslope large surface roughness elements enhance vertical turbulent mixing, elevating cold surface air from the terrain. Horizontal transport of this elevated, cold, turbulent air layer reduces the downstream upper warm air temperature. Benefiting from the progressive reduction of downstream stable stratification with increasing height in the SBL, wind shear can effectively generate strong turbulence. In addition to the turbulence enhancement from the cold downslope flow, the rate of turbulence increase with wind speed is elevated. This study demonstrates key physical mechanisms for turbulence generation captured by the HOST relationship. It also highlights the influence of terrain features on these mechanisms through deviations from the HOST relationship over flat terrain.

Thaumarchaeota are predominant in oligotrophic habitats such as deserts and arid soils, but their adaptations to these arid conditions are not well understood. In this study, we assembled 23 Thaumarchaeota genomes from arid and semi-arid soils collected from the Inner Mongolia Steppe and the Qinghai-Tibet Plateau. Using a comparative genomics approach, integrated with 614 Thaumarchaeota genomes from public databases, we identified the traits and evolutionary forces that contribute to their adaptations to aridity. Our results showed that the newly assembled genomes represent an early diverging group within the lineage of ammonia-oxidising Thaumarchaeota. While the genomic functions previously identified in arid soil lineages were conserved across terrestrial, shallow-ocean and deep-ocean lineages, several traits likely contribute to Thaumarchaeota's adaptation to aridity. These include chlorite dismutase, arsenate reductase, V-type ATPase and genes dealing with oxidative stresses. The acquisition and loss of traits at the last common ancestor of arid soil lineages may have facilitated the specialisation of Thaumarchaeota in arid soils. Additionally, the acquisition of unique adaptive traits, such as a urea transporter, Ca2+:H+ antiporter, mannosyl-3-phosphoglycerate synthase and phosphatase, DNA end-binding protein Ku and phage shock protein A, further distinguishes arid soil Thaumarchaeota. This study provides evidence for the adaptations of Thaumarchaeota to arid soil, enhancing our understanding of the nitrogen and carbon cycling driven by Thaumarchaeota in drylands.

Desertification-control policies have been applied in the Mu Us Desert since the 1950s. The landscape there is characterized by patches of shrub plants and well-developed lichen and moss crusts, some covered by shrub canopies and some in interspace soils. Little is known about how shrub cover and biocrusts shape soil fungal community structure in this ecosystem. Using high-throughput amplicon sequencing, the effects of biocrust types and shrub cover on soil fungal communities were analyzed. The results showed that biocrust types were more important than shrub cover in affecting soil properties and shaping soil fungal communities. Among all the measured soil properties, significant effects of shrub cover on soil pH and available P were observed. Biocrust types had significant effects on soil total organic carbon, C:N, and C:P ratios. Fungal taxa relating to plant pathogens and formation of lichens, (e.g., the Eurotiomycetes and Dothideomycetes and the of genera Endocarpon and Knufia) were dominant across biocrust types and shrub cover. Furthermore, although relative abundances of dominant fungal taxa were statistically similar among microhabitats, abundances of lichenized and pathogenic fungi differed significantly among biocrust types, with the former showing higher abundances in lichen crusts, and the latter exhibiting higher abundances in moss crosts. Soil total nitrogen and C:N were correlated with fungal community structure. Our results highligh the dominant role of biocrust types over shrub cover in shaping soil fungal communities in the Mu Us Desert. With the succession from lichen to moss crusts, increasing N limitation (soil TOC:TN ratio) may drive higher abundances of pathogenic fungi in lichen crusts and fewer lichenized fungi in moss crusts.

Increases in temperature and precipitation have continually occurred in the past few decades, both globally and in China, which have probably impacted the dynamics of net methane (CH4) emissions by regulating soil CH4 oxidization. An alpine ecosystem is quite sensitive to climate changes, but how these two climatic factors regulate the community of soil aerobic methane-oxidizing bacteria (aMOB) remains elusive in such an ecosystem because of the lack of high-resolution soil sampling datasets. Here, we employed a hybrid approach of gridded field surveys and random forest prediction to discern the above question in the Qinghai-Tibetan Plateau (QTP). Results indicated that type Ic aMOBs exhibited a preference for drier, colder areas, while type IIa, TUSC-like and RA21-like aMOBs probably occurred in wetter and relatively warmer areas. There were no remarkable shifts in alpha-diversity and bacterial community compositions from the driest and coldest regions to moderate ones, while the alpha-diversity decreased and community compositions changed substantially from moderate arid and cold areas to wetter, relatively warmer ones. These trends were mainly regulated by soil pH, a potentially secondary effect shaped by the interactions of mean annual precipitation (MAP) and temperature (MAT) and an aridity index (AI) in the QTP. A slight decline in soil pH from the driest and coldest areas to moderate ones might regulate aMOB diversity and community structure by the stochastic extinction of individuals adapted to a higher pH and the unstable colonization of individuals preferring a moderate pH. A great decline in soil pH from the moderate arid, cold to wetter, relatively warmer areas might lead to the deterministic exclusion of species with a high pH adaptability and the stable colonization of species preferring the acidic habitat. This study implies that soil acidification probably induces aMOB diversity loss and species turnover in the arid, cold areas of the QTP under climatic warming and wetting, shedding a new light on projecting the impact of climate changes on an alpine ecosystem's structure and function on unprecedented spatial scales.

Increased flash drought awareness in recent years has motivated the development of numerous indicators for monitoring, early warning, and assessment. The flash drought indicators can act as a complementary set of tools by which to inform flash drought response and management. However, the limitations of each indicator much be measured and communicated between research and practitioners to ensure effectiveness. The limitations of any flash drought indicator are better understood and overcome through assessment of indicator sensitivity and consistency; however, such assessment cannot assume any single indicator properly represents the flash drought “truth.” To better understand the current state of flash drought monitoring, this study presents an intercomparison of nine, widely used flash drought indicators. The indicators represent perspectives and processes that are known to drive flash drought, including evapotranspiration and evaporative demand, precipitation, and soil moisture. We find no single flash drought indicator consistently outperforms all others across the contiguous United States. We do find the evaporative demand- and evapotranspiration-driven indicators tend to lead precipitation- and soil moisture-based indicators in flash drought onset, but also tend to produce more flash drought events collectively. Overall, the regional and definition-specific variability in results supports the argument for a multi-indicator approach for flash drought monitoring, as advocated by recent studies. Furthermore, flash drought research—especially evaluation of historical and potential future changes in flash drought characteristics—should test multiple indicators, datasets, and methods for representing flash drought, and ideally employ a multi-indicator analysis framework over use of a single indicator from which to infer all flash drought information. Significance Statement Rapid onset or “flash” drought has been an increasing concern globally, with quickly intensifying impacts to agriculture, ecosystems, and water resources. Many tools and indicators have been developed to monitor and provide early warning for flash drought, ideally resulting in more time for effective mitigation and reduced impacts. However, there remains no widely accepted single method for defining, monitoring, and measuring flash drought, which means most indicators that are developed are compared with other individual indicators or conditions and impacts in one or two flash drought events. In this study, we measure the state of flash drought monitoring through an intercomparison of nine, widely used flash drought indicators that represent different aspects of flash drought. We find that no single flash drought indicator outperformed all others and suggest that a comprehensive flash drought monitor should leverage multiple, complementary indicators, datasets, and methods. Furthermore, we suggest flash drought research—especially that which reflects on historical or projected changes in flash drought characteristics—should seek multiple indicators, datasets, and methods for analyses, thereby reducing the potentially confounding effects of sensitivity to a single indicator.

The wide dispersion of glyphosate-resistant (GR) horseweed (Conyza canadensis (L.) Cronquist: synonym Erigeron canadensis L.) biotypes has been reported in agricultural fields in many states. GR traits may be transferred through seeds or pollen from fields with existing GR horseweed prevalence to surrounding fields. Understanding seed production and movement is essential when characterizing and predicting the spread of GR horseweed, yet a literature review indicates that there are no experimental data on dynamic (hourly) seed production and horizontal dispersion and deposition from horseweed. To obtain the dynamic data, two field experiments were performed, one in Illinois and one in Tennessee, USA in 2013 and 2014, respectively. Seed concentration and deposition along with atmospheric conditions were measured with samplers in the Illinois (184 m × 46 m, natural plants, density = 9.5 plants/m2) and Tennessee (6 m × 6 m, cultivated plants, density = 4 plants/m2) experimental fields and their surrounding areas along the downwind direction up to 1 km horizontally and 100 m vertically in the Illinois field and up to 32 m horizontally and 5 m vertically in the Tennessee field. The dynamic seed source strengths (emission rates) measured during two entire seed-shedding seasons were reported, ranging from 0 to 0.41 grains/plant/s for Illinois and ranging from 0 to 0.56 grains/plant/s for Tennessee. The average total seed production was an estimated 122,178 grains/plant for the duration of the Illinois experiment and 94,146 grains/plant for Tennessee. Seeds trapped by Rotorod samplers attached beneath two balloons in the Illinois field experiment were observed at heights of 80 to 100 m, indicating the possibility of long-distance transport. Normalized (by source data) seed deposition with distance followed a negative power exponential function. Seed emission and transport were affected mainly by wind speed. This study is the first to investigate dynamic horseweed seed emission, dispersion, and deposition for an entire seed-shedding season. The results will aid in the management of GR horseweed. The potential for regional effects of horseweed invasion may require all farmers to control horseweed in their individual fields.

The alkaline phosphatase-harboring community (the phoD community hereafter) plays an important role in organic P mineralization. Here, we comparatively studied the biogeographical patterns of abundant and rare phoD subcommunities and their roles in mediating soil phosphatase (ALP) activity and available P content in three representative steppe regions in China, namely the Inner Mongolian Plateau, the Loess Plateau, and the Qinghai-Tibetan Plateau. The results indicated that soil ALP activity, available P content, soil and microbial biomass C:P, N:P ratios varied significantly among steppe regions. Significant differences in diversity, metabolic energy and assembly processes were observed between abundant and rare phoD subcommunities. First, richness of the rare taxa was significantly higher than that of the abundant subcommunities. Second, testing of metabolic theory of ecology showed that rare subcommunities had a higher metabolic activation energy than the abundant taxa. Thirdly, deterministic other than stochastic processes dominated in the community assembly of both subcommunities. Soil pH was the key environmental determinant in community assembly processes for both subcommunities. The relationships among P-cycling parameters and between these parameters and phoD diversity were scale-dependent. The phylogenetic beta diversity of the rare phoD taxa had higher correlations with P-cycling parameters than that with the abundant taxa. More rare than abundant genera were significantly correlated with P limitation and ALP activity at different spatial scales. The rare Frankia was the key genus detecting P limitation, producing ALP and enhancing soil available P in Qinghai-Tibet.

Gene flow from genetically modified (GM) plants is concerning because of its ecological risks. In modeling studies, these risks may be reduced by altering crop management while taking environmental conditions into account. Gene flow modeling should consider many field aspects, both biological and physical. For example, empirical statistical models deduced from experimental data simulate gene flow well only under limited conditions (similar to experimental conditions). Mechanistic models, however, offer a potentially greater predictive ability. Gene flow models from GM crops to non-GM crops are used to simulate field conditions and minimize the adventitious presence of transgenes to meet certain threshold levels. These models can be adapted to simulate gene flow from GM crops to crop wild relatives using parameters of sexual compatibility and growth characteristics of the wild plants. Currently, modeling gene flow from herbicide-resistant weeds has become very important in light of the increased application of herbicides and widely evolved resistance in weeds.

Microbial species have different niche breadth, leading to distinct habitat ranges. Specialists have narrow niche breadth and high habitat specificity in comparison with the generalists, which possess extensive habitat ranges. Since specialists have low probabilities to occur in various habitats at a specific spatio-temporal scale, communities with different ratios of specialists and generalists may exhibit different species co-occurrence patterns and functional characteristics. However, it is still not clear how the assemblages of specialists and generalists can affect microbial co-occurrence and functional potential at a large biogeographical scale. In this study, we explored the relationship between microbial habitat specificity and the co-occurrence patterns of prokaryotic communities in Chinese wetland soils and the contribution of functional profiles to this relationship. We first identified some specialists and generalists which hold significant roles in the co-occurrence network. Then, we found that communities with more specialists have more simple co-occurrence patterns (fewer linkages in network) than those with more generalists. Soil electrical conductivity was the most significant abiotic factor in structuring this relationship. The biological mechanisms that contribute to this relationship were closely associated with functional differences of taxa. With the increase of specialists in communities, aerobic ammonia oxidation and cellulolysis guilds decreased, and photoautotrophy and sulfate/sulfide respiration populations increased. Furthermore, the abundances of metabolic pathways altered along with the abiotic gradients (e.g., conductivity and pH), including carbohydrate degradation, fermentation, inorganic nutrient metabolism and stress resistance-related pathways. Especially, there were higher abundances of metabolism-related pathways in communities with more specialists compared to those with more generalists. Functional differences at traits, genes, and metabolic pathways reflected the characteristics of microbial co-occurrence patterns and biogeochemical cycles of habitats. In summary, microbial habitat-specificity can modulate the co-occurrence patterns of prokaryotic communities along the environmental gradients in wetland soils. Our findings provide a mechanistic understanding on how microbial niche breadth can affect microbial co-occurrence in wetland soils.

Harvesting of crops in a weakly sloping Midwestern field during the Stable Atmospheric Variability and Transport (SAVANT) observation campaign allowed for a systematic investigation of the influence of surface roughness and static stability magnitude on the applicability of the Monin–Obukhov similarity (MOST) and hockey-stick transition (HOST) theories during stable boundary layer periods. We analyze momentum flux and turbulent velocity scale V TKE in three regimes, defined using the gradient Richardson number Ri and flux Richardson number Ri f as regime 1 (0 < Ri ≤ 0.1 and 0 < Ri f ≤ 0.1), regime 2 (0.1 < Ri ≤ 0.23 and 0.1 < Ri f ≤ 0.23), and regime 3 (both Ri and Ri f > 0.23). After harvest, in regime 1, stability varied from near-neutral to weakly stable and both MOST and HOST were applicable to estimate the momentum fluxes and V TKE as a function of mean wind speed. In regime 2, the momentum flux deviated from the MOST linear relationship as stability increased. In regimes 1 and 2, a HOST-defined threshold wind speed V s was identified beyond which V TKE increased linearly with wind speed at a rate of 0.26 for all observation heights. Below this threshold wind speed, V TKE behaved independent of mean wind and observation heights. Alternatively, for preharvest periods, MOST was applicable in regimes 1 and 2 for all heights and HOST was applicable with reduced V s for heights above the crop layer. Regime 3 during pre- and postharvest consisted of strongly stable periods and very weak to weak winds, where MOST was found to be invalid and V TKE remained low and independent of wind speed. The results suggest that roughness due to crops enhances the turbulence generation at lower wind speeds.

Soil microbiota increase their fitness to local habitats by adjusting their life history strategies. Yet, how such adjustments drive their ecological adaptations in xeric grasslands remains elusive. In this study, shifts in the traits that potentially represent microbial life history strategies were studied along two aridity gradients with different climates using metagenomic and trait-based approaches. The results indicated that resource acquisition (e.g., higher activities of β-d-glucosidase and N-acetyl-β-d-glucosidase, higher degradation rates of cellulose and chitin, as well as genes involved in cell motility, biodegradation, transportation and competition) and growth yield (e.g., higher biomass and respiration) strategies were depleted at higher aridity. However, maintenance of cellular and high growth potential (e.g., higher metabolic quotients and genes related to DNA replication, transcription, translation, central carbon metabolism and biosynthesis) and stress tolerance (e.g., genes involved in DNA damage repair, cation transportation, sporulation and osmolyte biosynthesis) strategies were enriched at higher aridity. This implied that microbiota have lower growth yields but are probably well primed for rapid responses to pulses of rainfall in more arid soils, whereas those in less arid soils may have stronger resource acquisition and growth yield abilities. By integrating a large amount of evidence from taxonomic, metagenomic, genomic and biochemical investigations, this study demonstrates that the ecological adaptations of soil microbiota to aridity made by adjusting and optimizing their life history strategies are universal in xeric grasslands and provides an underlying mechanistic understanding of soil microbial responses to climate changes.

Aim: The contemporary coexistence theory suggests that species pool, environmental filtering, dispersal assembly processes, ecological drift and biotic interactions collectively determine the beta-diversity of communities. However, we know little about the biogeographical patterns of the beta-diversity of microbial communities harbouring the alkaline phosphatase phoD gene (phoD communities, hereafter) and whether these mechanisms are all-important in shaping phoD communities' beta-diversity in natural steppe ecosystems. Location: Northern Hemisphere steppes. Time period: July to August 2018. Major taxa studied: Alkaline phosphatase (phoD gene) encoding community. Methods: Using the high throughput amplicon sequencing method, soil phoD communities were comparatively studied along three representative regions of the Northern Hemisphere steppes, namely the Qinghai-Tibetan Plateau, Inner Mongolian Plateau and the Loess Plateau. Each region harbours three types of steppes (habitats): meadow, typical and desert steppes. Results: We observed significantly higher phoD beta-diversity in the Qinghai-Tibetan than in the Loess and Inner Mongolian Plateaus and significantly lower beta-diversity in the typical steppes than in other steppe types. The decay rates of phoD beta-diversity with geographical distance varied in different steppe regions and types. The phoD beta-diversity was not significantly influenced by species pool; instead, environmental filtering, dispersal assembly processes, ecological drift and biotic interactions jointly shaped the beta-diversity patterns. The beta-deviation variations (beta-diversity excluding the effects of species pool) were influenced by spatial and environmental factors and biotic interactions, among which soil pH was the key environmental determinant. The soil pH driving beta-diversity mechanism was steppe region and habitat specific. Main conclusions: The biogeographical patterns of phoD beta-diversity were mainly driven by local community assembly processes in the Northern Hemisphere steppes.

Methane oxidation driven by aerobic methanotrophs plays a critical role in the alleviation of global warming. Yet, we still know little about the assembly mechanisms of methanotrophic communities and the corresponding drivers in mountain soils. Here, we comprehensively investigated methanotrophic bacteria along an elevational gradient (1800-4100 m) in Mount Gongga, China. Our results indicated that previously unrecognized AOB-rel methanotrophs predominated in mountain forest soils, and they showed distinct phylogenetic differentiation and pH preferences (pH 5.9-7.2 and pH 4.7-5.6 for AOB-rel subclade 1 and 2, respectively). Soil pH, temperature and precipitation primarily shaped methanotrophic communities. The community assembly of aerobic methanotrophs was governed mainly by deterministic processes. Our findings also implied that more acidic soils contained less phylogenetically clustered methanotrophic communities, and more neutral soils harbored more phylogenetically clustered communities. This study is the first to illustrate the significant role of soil pH in the assembly of aerobic methanotrophic communities and reinforce the importance of AOB-rel methanotrophs in atmospheric methane oxidation process in mountain forest soils.

Freshwater nitrogen (N) pollution is a significant sustainability concern in agriculture. In the U.S. Midwest, large precipitation events during winter and spring are a major driver of N losses. Uncertainty about the fate of applied N early in the growing season can prompt farmers to make additional N applications, increasing the risk of environmental N losses. New tools are needed to provide real-time estimates of soil inorganic N status for corn (Zea mays L.) production, especially considering projected increases in precipitation and N losses due to climate change. In this study, we describe the initial stages of developing an online tool for tracking soil N, which included, (i) implementing a network of field trials to monitor changes in soil N concentration during the winter and early growing season, (ii) calibrating and validating a process-based model for soil and crop N cycling, and (iii) developing a user-friendly and publicly available online decision support tool that could potentially assist N fertilizer management. The online tool can estimate real-time soil N availability by simulating corn growth, crop N uptake, soil organic matter mineralization, and N losses from assimilated soil data (from USDA gSSURGO soil database), hourly weather data (from National Weather Service Real-Time Mesoscale Analysis), and user-entered crop management information that is readily available for farmers. The assimilated data have a resolution of 2.5 km. Given limitations in prediction accuracy, however, we acknowledge that further work is needed to improve model performance, which is also critical for enabling adoption by potential users, such as agricultural producers, fertilizer industry, and researchers. We discuss the strengths and limitations of attempting to provide rapid and cost-effective estimates of soil N availability to support in-season N management decisions, specifically related to the need for supplemental N application. If barriers to adoption are overcome to facilitate broader use by farmers, such tools could balance the need for ensuring sufficient soil N supply while decreasing the risk of N losses, and helping increase N use efficiency, reduce pollution, and increase profits.

Plant-associated fungal communities play a vital role in plant adaptations, physiological functions, and productivity. Therefore, it is important to reveal the mechanisms driving the assembly of these communities. Yet it is still not fully understood how community assembly and structure differentiate in plant compartments, growth seasons, and varieties at large geographic distances. In this study, we analyzed bulk soil and plant-associated fungal communities of five wheat varieties across two growth stages in three biogeographic sites with distances of about 324, 534, or 800 km apart between any two locations. Our results indicated that the fungal community varied primarily across the sample types (leaf endosphere, root endosphere, rhizosphere, and bulk soil), followed by growth stage. Compared with the regreening stage, lower α-diversity and more dominance by abundant species in the fungal community were observed in wheat-associated compartments (four sample types except for bulk soil) at the heading stage. Additionally, within each wheat-associated compartment across every growth stage, location had stronger effects on fungal community assembly than the wheat variety. The effects of variety on fungal community assembly were location specific as were the growth-stage patterns of varietal effects on leaf endosphere and rhizosphere fungal communities. We further detected a less diverse but abundant core fungal taxa that could be grouped into three clusters associated mainly with location. This study characterized the interplay effects between plant selection (compartment, growth stage, variety) and environment (location) on wheat-associated mycobiomes by determining drivers of fungal community assembly and core fungal taxa in field conditions. • Fungal community assembly was mainly shaped by sample type and growth stage • A lower diversity and more abundant core fungal taxa were shown at heading stage • Location had stronger effects on fungal community assembly than variety

Biological soil crusts (biocrusts) are essential for ecosystem functioning, especially in drylands. However, we lack the knowledge of how ecosystem multifunctionality (EMF) responds to the development of biocrusts and the key factors mediating EMF during biocrust succession. In this study, we tested a series of essential ecosystem functions of the biocrust system and calculated a weighted EMF index, a processes-based EMFprocesses index, and a resource storage and availability based EMFpools index. Sequencing of the 16S rRNA gene and ITS gene was used to test differences in the community compositions of 16S rRNA gene-based organisms and ITS gene-based fungi in different biocrust stages. Results showed that the changing patterns and driving factors of all the three multifunctionality indices were similar. Later developed biocrust stages exhibited higher values of all three EMF indices. The 16S rRNA gene-based diversity reduced with biocrust succession. Biodiversity-EMF relationships varied when considering different biocrust stages and organisms. Across all biocrust stages, significantly negative relationships existed between the EMF indices and 16S rRNA based a-diversity, whereas positive relationships occurred between the EMF indices and both 16S rRNA and ITS gene-based beta-diversity. Further analyses indicated that the increasing relative abundance of non-cyanobacterial photosynthetic organisms (represented by chloroplast sequences and lichenized fungi) was the key predictor of all three EMF indices during biocrust succession. Specifically, these organisms were Streptophyta, Chlorophyta and Bacillariophyta and lichenized fungi, e.g., Verrucaria, Caloplaca and Aspicilia. This study provided a mechanistic understanding of how biological compositions and diversity drive EMF with biocrust development.

•Deterministic processes dominate methanotrophic community assembly.•Heterogeneous selection is a main process shaping methanotrophic community.•Key factors controlling methanotrophic communities are scale-dependent.

Pollen-mediated gene flow (PMGF) refers to the transfer of genetic information (alleles) from one plant to another compatible plant. With the evolution of herbicide-resistant (HR) weeds, PMGF plays an important role in the transfer of resistance alleles from HR to susceptible weeds; however, little attention is given to this topic. The objective of this work was to review reproductive biology, PMGF studies, and interspecific hybridization, as well as potential for herbicide resistance alleles to transfer in the economically important broadleaf weeds including common lambsquarters, giant ragweed, horseweed, kochia, Palmer amaranth, and waterhemp. The PMGF studies involving these species reveal that transfer of herbicide resistance alleles routinely occurs under field conditions and is influenced by several factors, such as reproductive biology, environment, and production practices. Interspecific hybridization studies within Amaranthus and Ambrosia spp. show that herbicide resistance allele transfer is possible between species of the same genus but at relatively low levels. The widespread occurrence of HR weed populations and high genetic diversity is at least partly due to PMGF, particularly in dioecious species such as Palmer amaranth and waterhemp compared with monoecious species such as common lambsquarters and horseweed. Prolific pollen production in giant ragweed contributes to PMGF. Kochia, a wind-pollinated species can efficiently disseminate herbicide resistance alleles via both PMGF and tumbleweed seed dispersal, resulting in widespread occurrence of multiple HR kochia populations. The findings from this review verify that intra- and interspecific gene flow can occur and, even at a low rate, could contribute to the rapid spread of herbicide resistance alleles. More research is needed to determine the role of PMGF in transferring multiple herbicide resistance alleles at the landscape level.