Insights from the past: Invasion trajectory and niche trends of a global freshwater invader.

Freshwater ecosystems are invaded by a non-random selection of taxa, among which crayfish stand out with successful examples worldwide. Species distribution models (SDMs) have been used to detect suitable areas for invasive species and predict their potential distributions. However, these prediction exercises assume the stability of realized environmental niches, which is uncertain during invasion. Worldwide evaluations involving cosmopolitan invaders may be particularly useful but have seldom been considered. Focusing on the successful invasion history of the red swamp crayfish, Procambarus clarkii, we assessed its geographic expansion and niche trends over time. Based on global occurrences from 1854 to 2022, multiple sequential SDMs have been implemented based on a set of bioclimatic variables. The environmental suitability for each period was projected through to the next period(s) using an ensemble procedure of commonly used SDM algorithms. As the records of the species are known, it was possible to check whether the modelling projections were concordant with the observed expansion of red swamp crayfish at a global scale. This also permitted analysis of its realized niche, and its dynamics, during different expansion phases. SDM maps based on past species records showed concordance with the known crayfish distributions and yielded similar spatial patterns with outputs overperforming random combinations of cells in term of suitability. The results also reflect the stability of the species niche, which despite some expansions during the invasion process, changed little in terms of main position in functional space over time. SDMs developed in the early stages of invasion provide useful insights but also tend to underpredict the potential range compared to models that were built for later stages. Our approach can be easily transferable to other well-documented taxa and represents valuable evidence for validating the use of SDMs, considering a highly dynamic world where biogeographical barriers are often bypassed.

AQUA-GAPS/MONET-Derived Concentrations and Trends of PAHs and Polycyclic Musks across Global Waters.

Polycyclic aromatic hydrocarbons (PAHs), released from petrogenic, pyrogenic or diagenetic sources (degradation of wood materials), are of global concern due to their adverse effects, and potential for long-range transport. While dissolved PAHs have been frequently reported in the literature, there has been no consistent approach of sampling across water bodies. Passive samplers from the AQUA/GAPS-MONET initiative were deployed at 46 sites (28 marine and 18 freshwater), and analyzed for 28 PAHs and six polycyclic musks (PCMs) centrally. Freely dissolved PAH concentrations were dominated by phenanthrene (mean concentration 1500 pg L-1; median 530 pg L-1) and other low molecular weight compounds. Greatest concentrations of phenanthrene, fluoranthene, and pyrene were typically from the same sites, mostly in Europe and North America. Of the PCMs, only galaxolide (72% of samples) and tonalide (61%) were regularly detected, and were significantly cross-correlated. Benchmarking of PAHs relative to penta- and hexachlorobenzene confirmed that the most remote sites (Arctic, Antarctic, and mountain lakes) displayed below average PAH concentrations. Concentrations of 11 of 28 PAHs, galaxolide and tonalide were positively correlated (P < 0.05) with population density within a radius of 5 km of the sampling site. Characteristic PAH ratios gave conflicting results, likely reflecting multiple PAH sources and postemission changes.

Triclosan Dioxygenase: A Novel Two-component Rieske Nonheme Iron Ring-hydroxylating Dioxygenase Initiates Triclosan Degradation.

The emerging contaminant triclosan (TCS) is widely distributed both in surface water and in wastewater and poses a threat to aquatic organisms and human health due to its resistance to degradation. The dioxygenase enzyme TcsAB has been speculated to perform the initial degradation of TCS, but its precise catalytic mechanism remains unclear. In this study, the function of TcsAB was elucidated using multiple biochemical and molecular biology methods. Escherichia coli BL21(DE3) heterologously expressing tcsAB from Sphingomonas sp. RD1 converted TCS to 2,4-dichlorophenol. TcsAB belongs to the group IA family of two-component Rieske nonheme iron ring-hydroxylating dioxygenases. The highest amino acid identity of TcsA and the large subunits of other dioxygenases in the same family was only 35.50%, indicating that TcsAB is a novel dioxygenase. Mutagenesis of residues near the substrate binding pocket decreased the TCS-degrading activity and narrowed the substrate spectrum, except for the TcsAF343A mutant. A meta-analysis of 1492 samples from wastewater treatment systems worldwide revealed that tcsA genes are widely distributed. This study is the first to report that the TCS-specific dioxygenase TcsAB is responsible for the initial degradation of TCS. Studying the microbial degradation mechanism of TCS is crucial for removing this pollutant from the environment.

Epidemiology, molecular characterization, and drug resistance of IncHI5 plasmids from Enterobacteriaceae.

The increasingly frequent occurence of IncHI5 plasmids has attracted worldwide attention. The aim of this study was to perform an in-depth bioinformatics analysis to determine the genetic characteristics and global distribution of all IncHI5 plasmids. The geographic distribution and epidemiology of all IncHI5 plasmids from GenBank were analyzed based on relevant literature reports and background information from the National Center for Biotechnology Information (NCBI). Detailed annotation of antibiotic resistance genes was performed. A total of 65 IncHI5 plasmid genomes were collected in GenBank. All IncHI5 plasmids were carried by Enterobacteriaceae, of which Klebsiella pneumoniae accounted for the largest proportion (50%, 33/65). The host bacterium of IncHI5 plasmids was mainly isolated from Homo Sapiens (81%, 53/65). All strains carrying IncHI5 plasmids were mainly distributed in China (83%, 54/65). Evolutionary analysis can divide IncHI5 plasmids into two groups, namely Groups I/II, of which Group II was more widely distributed worldwide. This study showed that Enterobacteriaceae, especially Klebsiella, was the main host for IncHI5 plasmid. Almost all IncHI5 plasmids carried multiple types of antibiotic resistance genes, related to Tn1696 or Tn6535. The IncHI5 plasmids should be of continuing interest as good repositories for antibiotic resistance genes.

The enigmatic Placozoa part 1: Exploring evolutionary controversies and poor ecological knowledge.

The placozoan Trichoplax adhaerens is a tiny hairy plate and more simply organized than any other living metazoan. After its original description by F.E. Schulze in 1883, it attracted attention as a potential model for the ancestral state of metazoan organization, the "Urmetazoon". Trichoplax lacks any kind of symmetry, organs, nerve cells, muscle cells, basal lamina, and extracellular matrix. Furthermore, the placozoan genome is the smallest (not secondarily reduced) genome of all metazoan genomes. It harbors a remarkably rich diversity of genes and has been considered the best living surrogate for a metazoan ancestor genome. The phylum Placozoa presently harbors three formally described species, while several dozen "cryptic" species are yet awaiting their description. The phylogenetic position of placozoans has recently become a contested arena for modern phylogenetic analyses and view-driven claims. Trichoplax offers unique prospects for understanding the minimal requirements of metazoan animal organization and their corresponding malfunctions.

Remote Sensing Monitoring and Assessment of Global Vegetation Status and Changes during 2016-2020.

Vegetation plays a fundamental role within terrestrial ecosystems, serving as a cornerstone of their functionality. Presently, these crucial ecosystems face a myriad of threats, including deforestation, overgrazing, wildfires, and the impact of climate change. The implementation of remote sensing for monitoring the status and dynamics of vegetation ecosystems has emerged as an indispensable tool for advancing ecological research and effective resource management. This study takes a comprehensive approach by integrating ecosystem monitoring indicators and aligning them with the objectives of SDG15. We conducted a thorough analysis by leveraging global 500 m resolution products for vegetation Leaf Area Index (LAI) and land cover classification spanning the period from 2016 to 2020. This encompassed the calculation of annual average LAI, identification of anomalies, and evaluation of change rates, thereby enabling a comprehensive assessment of the global status and transformations occurring within major vegetation ecosystems. In 2020, a discernible rise in the annual Average LAI of major vegetation ecosystems on a global scale became evident when compared to data from 2016. Notably, the ecosystems demonstrating a slight increase in area constituted the largest proportion (34.23%), while those exhibiting a significant decrease were the least prevalent (6.09%). Within various regions, such as Eastern Europe, Central Africa, and South Asia, substantial increases in both forest ecosystem area and annual Average LAI were observed. Furthermore, Eastern Europe and Central America recorded significant expansions in both grassland ecosystem area and annual average LAI. Similarly, regions experiencing notable growth in both cropland ecosystem areas and annual average LAI encompassed Southern Africa, Northern Europe, and Eastern Africa.

Temperature variability and metabolic adaptation in terrestrial and aquatic ectotherms.

Thermodynamics is a major factor determining rates of energy expenditure, rates of biochemical dynamics, and ultimately the biological and ecological processes linked with resilience to global warming in ectothermic organisms. Nonetheless, whether ectothermic organisms exhibit general adaptive metabolic responses to cope with worldwide variation in thermal conditions has remained as an open question. Here we combine a model comparison approach with a global dataset of standard metabolic rates (SMR), including 1,160 measurements across 788 species of aquatic invertebrates, insects, fishes, amphibians and reptiles, to investigate the association between metabolic rates and environmental temperatures in their respective habitats. Our analyses suggest that variation in SMR after removing allometric and thermodynamic effects is best explained by the temperature range encountered across seasons, which always provided a better fit than the average temperature for the hottest and coldest month and mean annual temperatures. This pattern was consistent across taxonomic groups and robust to sensitivity analyses. Nonetheless, aquatic and terrestrial lineages responded differently to seasonality, with SMR declining - 6.8% °C-1 of thermal range across seasons in aquatic organisms and increasing 2.8% °C-1 in terrestrial organisms. These responses may reflect alternative strategies to mitigate the impact of increments in warmer temperatures on energy expenditure, either by means of metabolic reduction in thermally homogeneous water bodies or effective behavioral thermoregulation to exploit temperature heterogeneity on land.

A PES framework coupling socioeconomic and ecosystem dynamics from a sustainable development perspective.

Payments for ecosystem services (PES) are becoming a global ecological protection strategy used to promote sustainable social and economic development. However, the current PES research and applications are often local and one-sided. The lack of a unified framework for PES results in a high policy cost and low ecological and social benefits. A large number of local PES experiences need to be comprehensively analyzed to construct a unified PES framework, which can provide support for the implementation and optimization of nature conservation policy in different regions of the world. Here, we combined natural language processing methods to analyze 1919 global studies on PES. We obtained the topics and spatiotemporal distributions of PES, as well as the compensation modes of hotspot ecosystem services in 114 countries worldwide. PES have been studied in 80% of the world (excluding Antarctica), but the research topics and distributions are very uneven. We found a disconnection between PES socioeconomic strategies and knowledge of natural ecosystem dynamics. Therefore, the knowledge and experience of PES must be exchanged globally, and PES need to be further integrated with the sustainable development goal (SDG) framework. We propose a PES framework that couples socioeconomic and ecosystem dynamics and be oriented toward sustainable development to make comprehensive management decisions. On this basis, a consistent PES solution may be provided for future theoretical research and implementation strategies of conservation.

Global material flow analysis of end-of-life of lithium nickel manganese cobalt oxide batteries from battery electric vehicles.

The global market for battery electric vehicles (BEVs) is continuously increasing which results in higher material demand for the production of Li-ion batteries (LIBs). Therefore, the end of life (EOL) of batteries must be handled properly through reusing or recycling to minimize the supply chain issues in future LIBs. This study analyses the global distribution of EOL lithium nickel manganese cobalt (NMC) oxide batteries from BEVs. The Stanford estimation model is used, assuming that the lifespan of NMC batteries follows a Weibull distribution. The global sales data of NMC batteries from 2009 to 2018 were collected and the sales data from 2019 to 2030 were estimated based on historical trends and BEV development plans in the top 10 countries for BEV sales. The result shows a view of EOL NMC batteries worldwide. In 2038, China, South Korea and the United States (US) will be the three leading countries in the recovery of NMC battery materials. An overall global flow of NMC battery materials (aluminium, copper, manganese, steel, lithium and graphite/carbon) was also predicted in this research. This study estimated the waste potential of NMC battery materials specifically in the top 10 countries and also in other countries. Finally, the economic value estimation results for recovered materials indicated that copper, aluminium and manganese will have cumulative economic values of 7.9, 4.4 and 3.9 billion US dollars in 2038, respectively. As this study considers the different specific energy of NMC batteries in the coming years due to technological advancement, the findings can provide a more realistic insight into the future demand for NMC battery materials. This study reveals that a high number of EOL NMC batteries will be accumulated in 2038 in several countries. Therefore, large-scale recycling infrastructures should be set up to improve the efficiency of the recovery of battery materials.

Spatiotemporal analysis of the morbidity of global Omicron from November 2021 to February 2022.

The Omicron variant was first reported to the World Health Organization (WHO) from South Africa on November 24, 2021; this variant is spreading rapidly worldwide. No study has conducted a spatiotemporal analysis of the morbidity of Omicron infection at the country level; hence, to explore the spatial transmission of the Omicron variant among the 220 countries worldwide, we aimed to the analyze its spatial autocorrelation and to conduct a multiple linear regression to investigate the underlying factors associated with the pandemic. This study was an ecological study. Data on the number of confirmed cases were extracted from the WHO website. The spatiotemporal characteristic was described in a thematic map. The Global Moran Index (Moran's I) was used to detect the spatial autocorrelation, while the local indicators of spatial association (LISA) were used to analyze the local spatial correlation characteristics. The joinpoint regression model was used to explore the change in the trend of the Omicron incidence over time. The association between the morbidity of Omicron and influencing factors were analyzed using multiple linear regression. This study was an ecological study. Data on the number of confirmed cases were extracted from the WHO website. The spatiotemporal characteristic was described in a thematic map. The Global Moran Index (Moran's I) was used to detect the spatial autocorrelation, while the LISA were used to analyze the local spatial correlation characteristics. The joinpoint regression model was used to explore the change in the trend of the Omicron incidence over time. The association between the morbidity of Omicron and influencing factors were analyzed using multiple linear regression. The value of Moran's I was positive (Moran's I = 0.061, Z-score = 3.772, p = 0.007), indicating a spatial correlation of the morbidity of Omicron at the country level. From November 26, 2021 to February 26, 2022; the morbidity showed obvious spatial clustering. Hotspot clustering was observed mostly in Europe (locations in High-High category: 24). Coldspot clustering was observed mostly in Africa and Asia (locations in Low-Low category: 32). The result of joinpoint regression showed an increasing trend from December 21, 2021 to January 26, 2022. Results of the multiple linear regression analysis demonstrated that the morbidity of Omicron was strongly positively correlated with income support (coefficient = 1.905, 95% confidence interval [CI]: 1.354-2.456, p < 0.001) and strongly negatively correlated with close public transport (coefficient = -1.591, 95% CI: -2.461 to -0.721, p = 0.001). Omicron outbreaks exhibited spatial clustering at the country level worldwide; the countries with higher disease morbidity could impact the other countries that are surrounded by and close to it. The locations with High-High clustering category, which referred to the countries with higher disease morbidity, were mainly observed in Europe, and its adjoining country also showed high spatial clustering. The morbidity of Omicron increased from December 21, 2021 to January 26, 2022. The higher morbidity of Omicron was associated with the economic and policy interventions implemented; hence, to deal with the epidemic, the prevention and control measures should be strengthened in all aspects.

Flavonoids are promising safe therapy against COVID-19.

Flavonoids are a class of phenolic natural products, well-identified in traditional and modern medicines in the treatment of several diseases including viral infection. Flavonoids showed potential inhibitory activity against coronaviruses including the current pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and designated as COVID-19. Here, we have collected all data related to the potential inhibitory mechanisms of flavonoids against SARS-CoV-2 infection and their significant immunomodulatory activities. The data were mapped and compared to elect major flavonoids with a promising role in the current pandemic. Further, we have linked the global existence of flavonoids in medicinal plants and their role in protection against COVID-19. Computational analysis predicted that flavonoids can exhibit potential inhibitory activity against SARS-CoV-2 by binding to essential viral targets required in virus entry and/ or replication. Flavonoids also showed excellent immunomodulatory and anti-inflammatory activities including the inhibition of various inflammatory cytokines. Further, flavonoids showed significant ability to reduce the exacerbation of COVID-19 in the case of obesity via promoting lipids metabolism. Moreover, flavonoids exhibit a high safety profile, suitable bioavailability, and no significant adverse effects. For instance, plants rich in flavonoids are globally distributed and can offer great protection from COVID-19. The data described in this study strongly highlighted that flavonoids particularly quercetin and luteolin can exhibit promising multi-target activity against SARS-CoV-2, which promote their use in the current and expected future outbreaks. Therefore, a regimen of flavonoid-rich plants can be recommended to supplement a sufficient amount of flavonoids for the protection and treatment from SARS-CoV-2 infection.

Age and spatial distribution of the world's oldest trees.

Extremely old trees have important roles in providing insights about historical climatic events and supporting cultural values. Yet there has been limited work on the global distribution and conservation of these trees. We extracted information on 197,855 tree cores at 4,854 sites, and combined it with other tree age data from a further 156 sites, to determine the age of the world's oldest trees and quantify the factors influencing their global distribution. We found that extremely old trees >1,000 years are rare. Among 30 individual trees that exceeded 2,000 years old, 27 occurred in high mountains. Our model suggests that many of the existing oldest trees occur in high-elevation, cold and arid mountains with limited human disturbance. This pattern is markedly different from that of the tallest trees, which are more likely to occur in more mesic and productive locations. Global warming and expansion of human activities may induce rapid population declines of extremely old trees. New strategies, including targeted establishment of conservation reserves in remote regions, especially those in western Table 1 parts of China and USA, are required to protect these trees. This article is protected by copyright. All rights reserved.

Coupled Aerobic Methane Oxidation and Arsenate Reduction Contributes to Soil-Arsenic Mobilization in Agricultural Fields.

Microbial oxidation of organic compounds can promote arsenic release by reducing soil-associated arsenate to the more mobile form arsenite. While anaerobic oxidation of methane has been demonstrated to reduce arsenate, it remains elusive whether and to what extent aerobic methane oxidation (aeMO) can contribute to reductive arsenic mobilization. To fill this knowledge gap, we performed incubations of both microbial laboratory cultures and soil samples from arsenic-contaminated agricultural fields in China. Incubations with laboratory cultures showed that aeMO could couple to arsenate reduction, wherein the former bioprocess was carried out by aerobic methanotrophs and the latter by a non-methanotrophic bacterium belonging to a novel and uncultivated representative of Burkholderiaceae. Metagenomic analyses combined with metabolite measurements suggested that formate served as the interspecies electron carrier linking aeMO to arsenate reduction. Such coupled bioprocesses also take place in the real world, supported by a similar stoichiometry and gene activity in the incubations with natural paddy soils, and contribute up to 76.2% of soil-arsenic mobilization into pore waters in the top layer of the soils where oxygen was present. Overall, this study reveals a previously overlooked yet significant contribution of aeMO to reductive arsenic mobilization.

Global distribution of treatment resistance gene markers for leishmaniasis.

BACKGROUND: Pentavalent antimonials (Sb(V)) such as meglumine antimoniate (Glucantime®) and sodium stibogluconate (Pentostam®) are used as first-line treatments for leishmaniasis, either alone or in combination with second-line drugs such as amphotericin B (Amp B), miltefosine (MIL), methotrexate (MTX), or cryotherapy. Therapeutic aspects of these drugs are now challenged because of clinical resistance worldwide. METHODS: We reviewedthe recent original studies were assessed by searching in electronic databases such as Scopus, Pubmed, Embase, and Web of Science. RESULTS: Studies on molecular biomarkers involved in drug resistance are essential for monitoring the disease. We reviewed genes and mechanisms of resistance to leishmaniasis, and the geographical distribution of these biomarkers in each country has also been thoroughly investigated. CONCLUSION: Due to the emergence of resistant genes mainly in anthroponotic Leishmania species such as L. donovani and L. tropica, as the causative agents of ACL and AVL, respectively, selection of an appropriate treatment modality is essential. Physicians should be aware of the presence of such resistance for the selection of proper treatment modalities in endemic countries.

Infection rates, species diversity, and distribution of zoonotic Babesia parasites in ticks: a global systematic review and meta-analysis.

Zoonotic Babesia species are emerging public health threats globally, and are the cause of a mild to severe malaria-like disease which may be life threatening in immunocompromised individuals. In this study, we determine the global infection rate, distribution, and the diversity of zoonotic Babesia species in tick vectors using a systematic review and meta-analysis. We used the random-effects model to pool data and determined quality of individual studies using the Joanna Briggs Institute critical appraisal instrument for prevalence studies, heterogeneity using Cochran's Q test, and across study bias using Egger's regression test. Herein, we reported a 2.16% (3915/175345, 95% CI: 1.76-2.66) global infection rate of zoonotic Babesia species (B. divergens, B. microti, and B. venatorum) in tick vectors across 36 countries and 4 continents. Sub-group infection rates ranged between 0.65% (95% CI: 0.09-4.49) and 3.70% (95% CI: 2.61-5.21). B. microti was the most prevalent (1.79%, 95% CI: 1.38-2.31) species reported in ticks, while Ixodes scapularis recorded the highest infection rate (3.92%, 95% CI: 2.55-5.99). Larvae 4.18% (95% CI: 2.15-7.97) and females 4.08% (95% CI: 2.56-6.43) were the tick stage and sex with the highest infection rates. The presence of B. divergens, B. microti, and B. venatorum in tick vectors as revealed by the present study suggests possible risk of transmission of these pathogens to humans, especially occupationally exposed population. The control of tick vectors through chemical and biological methods as well as the use of repellants and appropriate clothing by occupationally exposed population are suggested to curtail the epidemiologic, economic, and public health threats associated with this emerging public health crisis.

Paradigms of actinorhizal symbiosis under the regime of global climatic changes: New insights and perspectives.

Nitrogen occurs as inert and inaccessible dinitrogen gaseous form (N2 ) in the atmosphere. Biological nitrogen fixation is a chief process that makes this dinitrogen (N2 ) accessible and bioavailable in the form of ammonium (NH4 + ) ions. The key organisms to fix nitrogen are certain prokaryotes, called diazotrophs either in the free-living form or establishing significant mutual relationships with a variety of plants. On such examples is ~95-100 MY old incomparable symbiosis between dicotyledonous trees and a unique actinobacterial diazotroph in diverse ecosystems. In this association, the root of the certain dicotyledonous tree (~25 genera and 225 species) belonging to three different taxonomic orders, Fagales, Cucurbitales, and Rosales (FaCuRo) known as actinorhizal trees can host a diazotroph, Frankia of order Frankiales. Frankia is gram-positive, branched, filamentous, sporulating, and free-living soil actinobacterium. It resides in the specialized, multilobed, and coralloid organs (lateral roots but without caps), the root nodules of actinorhizal tress. This review aims to provide systematic information on the distribution and the phylogenetic diversity of hosts from FaCuRo and their micro-endosymbionts (Frankia spp.), colonization mechanisms, and signaling pathways. We also aim to provide details on developmental and physiological imperatives for gene regulation and functional genomics of symbiosis, phenomenal restoration ecology, influences of contemporary global climatic changes, and anthropogenic impacts on plant-Frankia interactions for the functioning of ecosystems and the biosphere.

Seasonal spatial dynamics of butterfly migration.

Understanding the seasonal movements of migratory species underpins ecological studies. Several hundred butterfly species show migratory behaviour, yet the spatial pattern of these migrations is poorly understood. We developed climatic niche models for 405 migratory butterfly species globally to estimate patterns of seasonal movement and the distribution of seasonal habitat suitability. We found strong seasonal variation in habitat suitability for most migratory butterflies with >75% of pixels within their distributions showing seasonal switching in predicted occupancy for 85% of species. The greatest rate of seasonal switching occurred in the tropics. Several species showed extreme range fluctuations between seasons, exceeding 10-fold for 53 species (13%) and more than 100-fold for nine species (2%), suggesting that such species may be at elevated extinction risk. Our results can be used to search for the ecological processes that underpin migration in insects, as well as to design conservation interventions for declining migratory insects.

Global Diversity and Biogeography of the Zostera marina Mycobiome.

Seagrasses are marine flowering plants that provide critical ecosystem services in coastal environments worldwide. Marine fungi are often overlooked in microbiome and seagrass studies, despite terrestrial fungi having critical functional roles as decomposers, pathogens, or endophytes in global ecosystems. Here, we characterize the distribution of fungi associated with the seagrass Zostera marina, using leaves, roots, and rhizosphere sediment from 16 locations across its full biogeographic range. Using high-throughput sequencing of the ribosomal internal transcribed spacer (ITS) region and 18S rRNA gene, we first measured fungal community composition and diversity. We then tested hypotheses of neutral community assembly theory and the degree to which deviations suggested that amplicon sequence variants (ASVs) were plant selected or dispersal limited. Finally, we identified a core mycobiome and investigated the global distribution of differentially abundant ASVs. We found that the fungal community is significantly different between sites and that the leaf mycobiome follows a weak but significant pattern of distance decay in the Pacific Ocean. Generally, there was evidence for both deterministic and stochastic factors contributing to community assembly of the mycobiome, with most taxa assembling through stochastic processes. The Z. marina core leaf and root mycobiomes were dominated by unclassified Sordariomycetes spp., unclassified Chytridiomycota lineages (including Lobulomycetaceae spp.), unclassified Capnodiales spp., and Saccharomyces sp. It is clear from the many unclassified fungal ASVs and fungal functional guilds that knowledge of marine fungi is still rudimentary. Further studies characterizing seagrass-associated fungi are needed to understand the roles of these microorganisms generally and when associated with seagrasses. IMPORTANCE Fungi have important functional roles when associated with land plants, yet very little is known about the roles of fungi associated with marine plants, like seagrasses. In this study, we report the results of a global effort to characterize the fungi associated with the seagrass Zostera marina across its full biogeographic range. Although we defined a putative global core fungal community, it is apparent from the many fungal sequences and predicted functional guilds that had no matches to existing databases that general knowledge of seagrass-associated fungi and marine fungi is lacking. This work serves as an important foundational step toward future work investigating the functional ramifications of fungi in the marine ecosystem.

Predicting Heavy Metal Adsorption on Soil with Machine Learning and Mapping Global Distribution of Soil Adsorption Capacities.

Studying heavy metal adsorption on soil is important for understanding the fate of heavy metals and properly assessing the related environmental risks. Existing experimental methods and traditional models for quantifying adsorption, however, are time-consuming and ineffective. In this study, we developed machine learning models for the soil adsorption of six heavy metals (Cd(II), Cr(VI), Cu(II), Pb(II), Ni(II), and Zn(II)) using 4420 data points (1105 soils) extracted from 150 journal articles. After a comprehensive comparison, our results showed that the gradient boosting decision tree had the best performance for a combined model based on all the data. The Shapley additive explanation method was used to identify the feature importance and the effects of these features on the adsorption, based on which six independent models were developed for the six metals to achieve better model performance than the combined model. Using these independent models, the global distribution of heavy metal adsorption capacities on soils was predicted with known soil properties. Reversed models, including one combined model for all the six metals and six independent models, were also built using the same data sets to predict the heavy metal concentration in water when the adsorbed amount is known for a soil/sediment.

Tracking POPs in Global Air from the First 10 Years of the GAPS Network (2005 to 2014).

The Global Atmospheric Passive Sampling (GAPS) network, initiated in 2005 across 55 global sites, supports the global monitoring plan (GMP) of the Stockholm Convention on Persistent Organic Pollutants (POPs) by providing information on POP concentrations in air on a global scale. These data inform assessments of the long-range transport potential of POPs and the effectiveness evaluation of chemical regulation efforts, by observing changes in concentrations over time. Currently, measurements spanning 5-10 sampling years are available for 40 sites from the GAPS Network. This study was the first time that POP concentrations in air were reported on a global scale for an extended time period and the first to evaluate worldwide trends with an internally consistent sample set. For consistency between sampling years, site- and sample specific sampling rates were calculated with a new, public online model, which accounts for the effects of wind speed variability. Concentrations for legacy POPs in air between 2005 and 2014 show different trends for different organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs). The POPs discussed in this study were chosen due to being the most frequently detected, with detection at the majority of sites. PCB, endosulfan, and hexachlorocyclohexane (HCH) concentrations in air are decreasing at most sites. The global trends reflect global sources and recycling of HCH, ongoing emissions from old stockpiles for PCBs, and recent use restrictions for endosulfan. These chlorinated OCPs continue to present exposure threat to humans and ecosystems worldwide. Concentrations of other OCPs, such as chlordanes, heptachlor and dieldrin, are steady and/or declining slowly at the majority of sites, reflecting a transition from primary to secondary sources (i.e., re-emission from reservoirs where these POPs have accumulated historically) which now control ambient air burdens.