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This article discusses Conservation Units in the conservationist perspective, as instruments to protect nature, assuring the maintenance of Brazilian biodiversity and biomes, in order to build an ecologically balanced environment under the terms of the Federal Constitution of 1988. Through deductive method, exploratory, documental, and bibliographic research, and indirect analysis of Environmental Ministry and Environmental, Sustainable Development State Office data, it makes a legal-theoretical appreciation of the issue in Brazil. By looking at the Brazilian scenario, it notices that most part of the Conservation Units were created by the States and were focused, respectively, on Mata Atlântica, Cerrado, and the Amazon, and had sustainability as a legal-political fundament. The conjuncture of Goiás indicates that stating the Conservation Units existence is not enough, since more than half of Conservation Units lack landing regularization. Also, six out of twenty-five Conservation Units still do not have an Administrative Counsel. Twenty Conservation Units do not have a working plan, which, added to financial and staff difficulties may compromise the expected protection of nature. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This review is aimed at summarizing the current state of knowledge about the relationship between environmental exposure to the bioaerosol emitted by intensive livestock farming and changes in the microbiome of people living in livestock farm vicinity. The PubMed, Scopus and Web of Science databases were searched by crossing keywords from the following 3 groups: a) "livestock," "animal farms," "animal breeding"; b) "microbiome," "resistome"; c) "livestock vicinity," "farm vicinity," "neighborhoods and health" in 2010-2022. Literature screening did not reveal any paper related to the full microbiome composition in the population studied. In the study, the authors included 7 papers (5 from the Netherlands, 1 from the USA, and 1 from China). The studies confirmed the carriage of Staphylococcus aureus, including methicillin-resistant S. aureus (MRSA), livestockassociated MRSA (LA-MRSA MC398) and multidrug-resistant S. aureus (MDRSA) in the nasal microbiome of adults and children living within 500-2000 m from a livestock farm. Clostridium difficile, including LA-ribotype RT078 carriage, was detected in the intestinal microbiome of adults living within 500-1000 m. Extended-spectrum β-lactamase (ESBL) producing Enterobacteriaceae were confirmed in the intestinal microbiome of adults living within 500-6200 m. Knowledge on the composition of the microflora of people living in livestock farm vicinity is insufficient to conclude about changes in the microbiome caused by the environmental emission of bioaerosol. The carriage prevalence of the LA-bacteria, including both strains with antimicrobial resistance and antimicrobial resistance genes, confirms the presence of zoonotic bacteria in the human microflora in populations without occupational contact with animals. It cannot be ruled out that zoonotic bacteria, as a component of the microbiome, have a negative impact on people's health. Int J Occup Med Environ Health. 2024;37(2):138-52. [ABSTRACT FROM AUTHOR]

This study investigated the impact of tobacco exposure, specifically through heating and burning, on periodontopathogens in the subgingival microbiome among clinically healthy individuals and those diagnosed with periodontitis. The sample comprised 66 subjects (26–56 years, median 38 yrs; 64% females) classified as non-smokers, classic cigarette smokers, and tobacco heating system (THS) smokers (each N = 22). Full-mouth periodontal examination was performed, and 330 paper-point samples from periodontal pockets were collected. Next-generation sequencing of 16S rRNA genes was conducted to identify the composition of subgingival microbiome. Periodontitis prevalence among the groups was ranked as THS (41%) < non-smokers (44%) < cigarette smokers (68%), without statistically significant differences between the groups. The number of perio-pathogenic species was higher in subjects with periodontitis compared to those without (median 7 vs. 6 species; p = 0.005) but without significant differences between exposure groups: non-smokers (6) = smokers (6) < THS (6.5). When combining exposure and periodontal status, each smoker group had more perio-pathogenic species than non-smokers: non-smokers without periodontitis (5) < smokers without periodontitis (5.5) < THS without periodontitis (6); non-smokers with periodontitis (6.5) < THS with periodontitis (7) = smokers with periodontitis (7). Multiple linear regression indicated periodontitis as the sole predictor of perio-pathogenic species quantity, irrespective of the type of tobacco consumption, sex, age, or oral hygiene (R2 = 0.163; p = 0.005). In conclusion, the quantity of perio-pathogenic species in the subgingival microbiome was more influenced by periodontitis than by exposure to tobacco smoke, regardless of whether it was heated or burned. [ABSTRACT FROM AUTHOR]

Inland waters are among the most threatened biodiversity hotspots. Ponds located in alpine areas are experiencing more rapid and dramatic water temperature increases than any other biome. Despite their prevalence, alpine ponds and their biodiversity responses to climate change have been poorly explored, reflecting their small size and difficult access. To understand the effects of climate change on alpine pond biodiversity, we performed a comprehensive literature review for papers published since 1955. Through analysis of their geographic distribution, environmental features, and biodiversity values, we identified which environmental factors related to climate change would have direct or indirect effects on alpine pond biodiversity. We then synthesized this information to produce a conceptual model of the effects of climate change on alpine pond biodiversity. Increased water temperature, reduced hydroperiod, and loss of connectivity between alpine ponds were the main drivers of biodiversity geographic distribution, leading to predictable changes in spatial patterns of biodiversity. We identified three major research gaps that, if addressed, can guide conservation and restoration strategies for alpine ponds biodiversity in an uncertain future. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Health and disease are fundamentally influenced by microbial communities and their genes (the microbiome). An in-depth analysis of microbiome structure that enables the classification of individuals based on their health can be crucial in enhancing diagnostics and treatment strategies to improve the overall well-being of an individual. In this paper, we present a novel semi-supervised methodology known as Randomized Feature Selection based Latent Dirichlet Allocation (RFSLDA) to study the impact of the gut microbiome on a subject's health status. Since the data in our study consists of fuzzy health labels, which are self-reported, traditional supervised learning approaches may not be suitable. As a first step, based on the similarity between documents in text analysis and gut-microbiome data, we employ Latent Dirichlet Allocation (LDA), a topic modeling approach which uses microbiome counts as features to group subjects into relatively homogeneous clusters, without invoking any knowledge of observed health status (labels) of subjects. We then leverage information from the observed health status of subjects to associate these clusters with the most similar health status making it a semi-supervised approach. Finally, a feature selection technique is incorporated into the model to improve the overall classification performance. The proposed method provides a semi-supervised topic modelling approach that can help handle the high dimensionality of the microbiome data in association studies. Our experiments reveal that our semi-supervised classification algorithm is effective and efficient in terms of high classification accuracy compared to popular supervised learning approaches like SVM and multinomial logistic model. The RFSLDA framework is attractive because it (i) enhances clustering accuracy by identifying key bacteria types as indicators of health status, (ii) identifies key bacteria types within each group based on estimates of the proportion of bacteria types within the groups, and (iii) computes a measure of within-group similarity to identify highly similar subjects in terms of their health status. [ABSTRACT FROM AUTHOR]

Introduction: In our paper, we explored the impact of different anthropogenic stressors, namely, mussel farming, methane extraction platforms, and summer mass tourism, on the epipelagic microbiomes of the North- Western Adriatic Sea. Methods: By 16S rRNA gene sequencing, we provided the epipelagic microbiome layout from selected sites corresponding to each of the considered impacts. As an unimpacted reference, we used already published 16S rRNA sequencing data. Results: According to our findings, each one of the anthropogenic stressors resulted in a peculiar increase of specific epipelagic microbial components, including copiotrophic R-strategists and host-restricted bacteria, as well as some pathobiome components, the latter being detected exclusively in impacted sites. Particularly, potentially harmful pathogenic species such as Legionella impletisoli and Staphylococcus epidermidis have been detected in proximity to the mussel farms, and Escherichia coli and Campylobacter ureolyticus were present close to the methane extraction platform and at the summer mass tourism site, respectively. Particularly, C. ureolyticus is an emerging human gastrointestinal pathogen, capable of destroying intestinal microvilli. Discussion: In addition to providing evidence supporting the existence of recognizable and impact-driven fingerprints on the epipelagic marine microbiome peculiar to the different anthropogenic stressors, our findings also raise concern about the ecological relevance of the observed changes, in terms of possible loss of ecosystem services and also for the potential release of pathogenic microorganisms in the environment. [ABSTRACT FROM AUTHOR]

This paper analyzes the correlation between precipitation and deforestation and trends in the Brazilian Amazon Biome from 1985 to 2021 using rain gauge measurements. A total of 187 stations were selected after filtering time series with less than 10% of missing data. Deforestation data was acquired using the MapBiomas dataset. Results show that deforestation rates vary across different locations and may be influenced by various factors. The analysis also found significant negative correlations between precipitation and deforestation, with a range of − 0.49 to − 0.33, as well as significant positive correlations, with a range of 0.34 to 0.57. These findings underscore the importance of continued monitoring of precipitation patterns in the region and the urgent need for measures to mitigate deforestation, which is critical for the hydrological cycle of the region. The highest deforestation rates and values were found between latitude 0 and − 12.5, where the arc of deforestation lies. Additionally, this study found a significant negative correlation between precipitation patterns and deforestation, indicating that deforestation led to a reduction in rainfall in the region. [ABSTRACT FROM AUTHOR]

Purpose: Brazilian territory is divided into six biomes (Amazon, Atlantic Forest, Cerrado, Caatinga, Pantanal, and Pampa) that represent important global biodiversity hotspots. Research into soil science in these environments has increased in recent years, but a quantitative and qualitative mapping of research into the soils of Brazilian biomes has never been carried out. In this study, research on soil science in the Brazilian biomes were analyzed to map the evolution, scientific collaboration, current status, research trends and impact over the last 50 years (1972–2022). Methods: The database was obtained from the Core Collection of Web of Science. The data was quantitatively analyzed through descriptive statistics and linear regression using Microsoft Excel, and qualitatively using the bibliometric software VOSviewer. Results: A total of 11,231 papers were obtained. The results indicated a significant increase in soil science research across all biomes (polynomial growth), with greater emphasis for research in the Cerrado (R2 = 0.9361), Amazon (R2 = 0.9170) and Atlantic Forest (R2 = 0.9104) biomes. Soil science research in the Amazon accounted for 47.0% of the research conducted in all Brazilian biomes. While in the Amazon (38.8%), Atlantic Forest (34.8%), and Pantanal (36.7%), most of the research was related to environmental sciences and ecology, in the Cerrado (47.4%), Caatinga (58.2%), and Pampa biome (48.9%), research in the field of agriculture was more significant. For all biomes, except for the Caatinga (a dry climate biome), a significant participation of international researchers and institutions was evident in the overall publications. This demonstrates a lower global interest in soil science research in the Brazilian dry ecosystem. Conclusion: Soil science research in the Brazilian biomes is disproportionate, with greater interest in the soils of the larger forest biomes and less interest in the dry and flooded areas. The results of this study can be useful for the development of public policies, research and scientific collaboration aimed at soil conservation in Brazilian terrestrial biomes. [ABSTRACT FROM AUTHOR]

[Display omitted] The increasing availability of remote sensing imagery led to the emergence of numerous burned area mapping products and methodologies, thus, the necessity of spatial and temporally validating them. The main objective of this paper is to conduct a global analysis and comparison of MODIS and VIIRS active fire dates with dating provided by moderate resolution burned area mapping products. As reference burned area maps, we used the Burned Area Reference Database (BARD) to analyze and compare the performances of MODIS and VIIRS active fires. For 316 path-rows, we calculated the temporal gap between the dates of BARD pixels and those of the five nearest active fires. Olson terrestrial biomes were taken into account in the analysis of results. The agreement rates between the dates of burned areas and of active fires varied based on their geographical distance, fire size and biome. The highest agreement rates were observed for smaller distances (<500 m) and larger fires (>100 ha). Boreal and Mediterranean biomes exhibited the highest values of date percent agreement between burned area pixels and active fires, while the lowest values were found in biomes encompassed by grasslands and savannas. [ABSTRACT FROM AUTHOR]

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi‐arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long‐term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate–ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi‐arid biomes for the assessment of climate–ecosystem interactions that contribute to abrupt shifts. [ABSTRACT FROM AUTHOR]

The indiscriminate use of antimicrobials has led to the emergence of resistant bacteria, especially pathogenic strains of Escherichia coli , which are associated with diseases in animals and humans. The aim of the present study was to characterize E. coli isolates in calves with regards to the presence of virulence genes and investigate the resistance of the isolates to different antimicrobials. Between 2021 and 2023, 456 fecal samples were collected from calves in the Pantanal and Cerrado biomes of the state of Mato Grosso do Sul, Brazil. All samples were subjected to microbiological analysis and disc diffusion antibiogram testing. The polymerase chain reaction method was used to detect virulence genes. Bacterial growth was found in 451 of the 456 samples and biochemically identified as Escherichia coli. All 451 isolates (100 %) exhibited some phenotypic resistance to antimicrobials and 67.62 % exhibited multidrug resistance. The frequency of multidrug-resistant isolates in the Cerrado biome was significantly higher than that in the Pantanal biome (p = 0.0001). In the Cerrado , the most common pathotype was Shiga toxin-producing Escherichia coli (STEC) (28 %), followed by toxigenic Escherichia coli (ETEC) (11 %), enterohemorrhagic Escherichia coli (EHEC) (8 %) and enteropathogenic Escherichia coli (EPEC) (2 %). In most cases, the concomitant occurrence of pathotypes was more common, the most frequent of which were ETEC + STEC (33 %), ETEC + EHEC (15 %) and ETEC + EPEC (3 %). The STEC pathotype (30 %) was also found more frequently in the Pantanal , followed by EHEC (12 %), ETEC (9 %) and EPEC (6 %). The STEC pathotype had a significantly higher frequency of multidrug resistance (p = 0.0486) compared to the other pathotypes identified. The frequency of resistance was lower in strains from the Pantanal biome compared to those from the Cerrado biome. Although some factors are discussed in this paper, it is necessary to clarify the reasons for this difference and the possible impacts of these findings on both animal and human health in the region. • Multi-resistant bacteria in cattle in the Cerrado and Pantanal biomes of Brazil. • Antimicrobial multiresistance of E. coli pathotypes isolated from calf feces. • Domestic animals and humans, exchange of pathogens between different species. [ABSTRACT FROM AUTHOR]

The maternal pregnancy microbiome (including genitourinary and gut) has been linked to important pregnancy/birth and later childhood health outcomes. However, such sampling as part of large population cohort studies is logistically and financially challenging. Many countries routinely collect vaginal or vaginal-rectal swabs in late pregnancy for Group B Streptococcus (GBS) screening, but their utility for population-based research is still unclear. As part of planning for the Generation Victoria population-based cohort study beginning in pregnancy, we assessed the utility and reliability of residual clinical GBS vaginal/vaginal-rectal swabs for generating late pregnancy microbiome data. We carried out a two-phased pilot study. Phase one assessed the level of microbial diversity apparent in 'residual' clinical vaginal/vaginal-rectal swabs post clinical testing and storage for 7–10 days at 4 °C (routine clinical practice). Phase two directly assessed the impact of storage time and temperature on the microbial composition of vaginal/vaginal-rectal swabs collected specifically for research purposes. The microbiota composition in the 'residual' clinical swabs aligned with published studies. The 'research' swabs, stored at 4 °C for up to ten days, showed minimal changes in microbiota profile, compared to swabs examined on the day of collection. In contrast, significant variation in diversity was seen in swabs stored at room temperature for up to 48 h. Residual clinical material from swabs collected primarily for GBS screening in late pregnancy represent a reliable and abundant source of material for assessing the late pregnancy maternal microbiome for research purposes. This represents a low-burden opportunity for population-representative pregnancy studies to assess the potential of late pregnancy microbiome for prediction and understanding maternal and child health outcomes. [ABSTRACT FROM AUTHOR]

Understanding the large-scale pattern of soil microbial carbon use efficiency (CUE) and its temperature sensitivity (CUET) is critical for understanding soil carbon–climate feedback. We used the 18O-H2O tracer method to quantify CUE and CUET along a north-south forest transect. Climate was the primary factor that affected CUE and CUET, predominantly through direct pathways, then by altering soil properties, carbon fractions, microbial structure and functions. Negative CUET (CUE decreases with measuring temperature) in cold forests (mean annual temperature lower than 10 °C) and positive CUET (CUE increases with measuring temperature) in warm forests (mean annual temperature greater than 10 °C) suggest that microbial CUE optimally operates at their adapted temperature. Overall, the plasticity of microbial CUE and its temperature sensitivity alter the feedback of soil carbon to climate warming; that is, a climate-adaptive microbial community has the capacity to reduce carbon loss from soil matrices under corresponding favorable climate conditions. The climate-dependency of microbial carbon use efficiency thermal sensitivity is demonstrated in a forest transect experiment, with implications for soil carbon feedbacks to climate warming. [ABSTRACT FROM AUTHOR]

Background: Scavenging indigenous village chickens play a vital role in sub-Saharan Africa, sustaining the livelihood of millions of farmers. These chickens are exposed to vastly different environments and feeds compared to commercial chickens. In this study, we analysed the caecal microbiota of 243 Ethiopian village chickens living in different altitude-dependent agro-ecologies. Results: Differences in bacterial diversity were significantly correlated with differences in specific climate factors, topsoil characteristics, and supplemental diets provided by farmers. Microbiota clustered into three enterotypes, with one particularly enriched at high altitudes. We assembled 9977 taxonomically and functionally diverse metagenome-assembled genomes. The vast majority of these were not found in a dataset of previously published chicken microbes or in the Genome Taxonomy Database. Conclusions: The wide functional and taxonomic diversity of these microbes highlights their importance in the local adaptation of indigenous poultry, and the significant impacts of environmental factors on the microbiota argue for further discoveries in other agro-ecologies. EEwR8PKafK2-LVnkA2-YG- Video Abstract [ABSTRACT FROM AUTHOR]

Background: In gut ecosystems, there is a complex interplay of biotic and abiotic interactions that decide the overall fitness of an individual. Divulging the microbe-microbe and microbe-host interactions may lead to better strategies in disease management, as microbes rarely act in isolation. Network inference for microbial communities is often a challenging task limited by both analytical assumptions as well as experimental approaches. Even after the network topologies are obtained, identification of important nodes within the context of underlying disease aetiology remains a convoluted task. We therefore present a network perspective on complex interactions in gut microbial profiles of individuals who have multiple sclerosis with and without Mycobacterium avium subspecies paratuberculosis (MAP) infection. Our exposé is guided by recent advancements in network-wide statistical measures that identify the keystone nodes. We have utilised several centrality measures, including a recently published metric, Integrated View of Influence (IVI), that is robust against biases. Results: The ecological networks were generated on microbial abundance data (n = 69 samples) utilising 16 S rRNA amplification. Using SPIEC-EASI, a sparse inverse covariance estimation approach, we have obtained networks separately for MAP positive (+), MAP negative (-) and healthy controls (as a baseline). Using IVI metric, we identified top 20 keystone nodes and regressed them against covariates of interest using a generalised linear latent variable model. Our analyses suggest Eisenbergiella to be of pivotal importance in MS irrespective of MAP infection. For MAP + cohort, Pyarmidobacter, and Peptoclostridium were predominately the most influential genera, also hinting at an infection model similar to those observed in Inflammatory Bowel Diseases (IBDs). In MAP- cohort, on the other hand, Coprostanoligenes group was the most influential genera that reduces cholesterol and supports the intestinal barrier. Conclusions: The identification of keystone nodes, their co-occurrences, and associations with the exposome (meta data) advances our understanding of biological interactions through which MAP infection shapes the microbiome in MS individuals, suggesting the link to the inflammatory process of IBDs. The associations presented in this study may lead to development of improved diagnostics and effective vaccines for the management of the disease. [ABSTRACT FROM AUTHOR]

Host microbial communities (hereafter, the 'microbiome') are recognized as an important aspect of host health and are gaining attention as a useful biomarker to understand the ecology and demographics of wildlife populations. Several studies indicate that the microbiome may contribute to the adaptive capacity of animals to changing environments associated with increasing habitat fragmentation and rapid climate change. To this end, we investigated the gut microbiome of pronghorn (Antilocapra americana), an iconic species in an environment that is undergoing both climatic and anthropogenic change. The bacterial composition of the pronghorn gut microbiome has yet to be described in the literature, and thus our study provides important baseline information about this species. We used 16S rRNA amplicon sequencing of fecal samples to characterize the gut microbiome of pronghorn—a facultative sagebrush (Artemisia spp.) specialist in many regions where they occur in western North America. We collected fecal pellets from 159 captured female pronghorn from four herds in the Red Desert of Wyoming during winters of 2013 and 2014. We found small, but significant differences in diversity of the gut microbiome relative to study area, capture period, and body fat measurements. In addition, we found a difference in gut microbiome composition in pronghorn across two regions separated by Interstate 80. Results indicated that the fecal microbiome may be a potential biomarker for the spatial ecology of free-ranging ungulates. The core gut microbiome of these animals—including bacteria in the phyla Firmicutes (now Bacillota) and Bacteroidota—remained relatively stable across populations and biological metrics. These findings provide a baseline for the gut microbiome of pronghorn that could potentially be used as a target in monitoring health and population structure of pronghorn relative to habitat fragmentation, climate change, and management practices. [ABSTRACT FROM AUTHOR]

Copyright of Ostrich: The Journal of African Ornithology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ice-nucleating macromolecules (INMs) produced by plant pollen can nucleate ice at warm temperatures and may play an important role in weather- and climate-relevant cloud glaciation. INMs have also proved useful for mammalian cell and tissue model cryopreservation. The high ice nucleation (IN) activity of some INMs indicates an underlying biological function, either freezing tolerance or bioprecipitation-mediated dispersal. Here, using the largest study of pollen ice nucleation to date, we show that phylogenetic proximity, spermatophyte subdivision, primary growth biome, pollination season, primary pollination method, desiccation tolerance and native growth elevation do not account for the IN activity of INMs released from different plant species' pollen. The results suggest that these macromolecules are produced by plants for a purpose unrelated to ice nucleation and have an incidental ability to nucleate ice. This ability may have been adapted by some species for specific biological purposes, producing exceptional ice nucleators. Pollen INMs may be more active, widespread in nature, and diverse than previously thought. [ABSTRACT FROM AUTHOR]

The study of the water cycle in the forest at large scales, such as countries, is challenging due to the difficulty of correctly estimating forest water flows. Hydrological models can be coupled with extensive forest data sources, such as national forest inventories, to estimate the water flow of forests over large extents, but so far the studies conducted have not analysed the role of stand structure variables or the functional traits of the forest on predicted blue and green water flows in detail. In this study, we modelled the water balance of Spanish forests using stand structure and species data from forest inventories to understand the effects of climate, stand structure, and functional groups on blue water flows. We calculated blue water and green water flows and expressed them relative to received precipitation. Relative blue water flow was mainly concentrated in the wetter regions (Atlantic and alpine biomes) of Spain (around 25 %) in comparison with the Mediterranean biomes (10 %–20 %) and during the autumn–winter season. The leaf area index (LAI) of the forest stand is the most important predictor of relative blue water, exhibiting a negative effect until it reaches a plateau at higher levels (around 2.5–3). Deciduous forests showed a greater relative blue water flow than evergreen functional groups (25 %–35 % and 10 %–25 %, respectively) primarily due to leaf fall during the autumn–winter season. This study highlights how green water is decoupled from blue water; namely, blue water depends on winter and autumn precipitation, while green water depends on the spring and summer water demand and how the species' functional traits (deciduous vs. evergreen) can influence blue water production. [ABSTRACT FROM AUTHOR]

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding betweenmicrobiologists andmodelers/bioinformaticians, stemming froma lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored formicrobiologists, researchers newtomicrobiomemodeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling. [ABSTRACT FROM AUTHOR]

The microbiome constitutes a complex microbial ecology of interacting components that regulates important pathways in the host. Most microbial communities at various body sites tend to share common substructures of interactions, while also showing diversity related to the needs of the local environment. The aim of this paper is to develop a method for inferring both the common core and the differences in such microbiota systems. The approach combines two elements: (i) a random graph model generating networks across environments, and capturing potential relatedness at the structural level, with (ii) a Gaussian copula graphical model for the inference of environment-specific networks from multivariate microbial data. We propose a Bayesian approach for the joint inference of microbiota systems from metagenomic data for a number of body sites. The analysis of human microbiome data shows how the proposed random graphical model is able to capture varying levels of structural similarity across the different body sites and how this is supported by their taxonomical classification. Beyond a stable core, the inferred microbiome systems show interesting differences between the body sites, as well as interpretable relationships between various classes of microbes. [ABSTRACT FROM AUTHOR]

Background: Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, the latter of which then helps retrieve their function based on annotated gene products, mRNA, protein, and metabolites. Within the context of a specific hypothesis, additional modalities are often included, to give host-microbiome interaction. For example, in human-associated microbiome projects, it has become increasingly common to include host immunology through flow cytometry. Whilst there are plenty of software approaches available, some that utilize marker-based and assembly-based approaches, for downstream statistical analyses, there is still a dearth of statistical tools that help consolidate all such information in a single platform. By virtue of stringent computational requirements, the statistical workflow is often passive with limited visual exploration. Results: In this study, we have developed a Java-based statistical framework (https://github.com/KociOrges/cviewer) to explore shotgun metagenomics data, which integrates seamlessly with conventional pipelines and offers exploratory as well as hypothesis-driven analyses. The end product is a highly interactive toolkit with a multiple document interface, which makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant patterns. We have designed algorithms based on frequently used numerical ecology and machine learning principles, with value-driven from integrated omics tools which not only find correlations amongst different datasets but also provide discrimination based on case–control relationships. Conclusions: CViewer was used to analyse two distinct metagenomic datasets with varying complexities. These include a dietary intervention study to understand Crohn's disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean. Complete analyses of both studies in CViewer then provide very powerful mechanistic insights that corroborate with the published literature and demonstrate its full potential. EDLr-6-tH-9CdVCxoa6z_8 Video Abstract [ABSTRACT FROM AUTHOR]

Motivation: High-throughput sequencing technology facilitates the quantitative analysis of microbial communities, improving the capacity to investigate the associations between the human microbiome and diseases. Our primary motivating application is to explore the association between gut microbes and obesity. The complex characteristics of microbiome data, including high dimensionality, zero inflation, and over-dispersion, pose new statistical challenges for downstream analysis. Results: We propose a GLM-based zero-inflated generalized Poisson factor analysis (GZIGPFA) model to analyze microbiome data with complex characteristics. The GZIGPFA model is based on a zero-inflated generalized Poisson (ZIGP) distribution for modeling microbiome count data. A link function between the generalized Poisson rate and the probability of excess zeros is established within the generalized linear model (GLM) framework. The latent parameters of the GZIGPFA model constitute a low-rank matrix comprising a low-dimensional score matrix and a loading matrix. An alternating maximum likelihood algorithm is employed to estimate the unknown parameters, and cross-validation is utilized to determine the rank of the model in this study. The proposed GZIGPFA model demonstrates superior performance and advantages through comprehensive simulation studies and real data applications. [ABSTRACT FROM AUTHOR]

Non-genetic sources of phenotypic variation, such as the epigenome and the microbiome, could be important contributors to adaptive variation for species with low genetic diversity. However, little is known about the complex interaction between these factors and the genetic diversity of the host, particularly in wild populations. Here, we examine the skin microbiome composition of two closely-related mangrove killifish species with different mating systems (self-fertilising and outcrossing) under sympatric and allopatric conditions. This allows us to partition the influence of the genotype and the environment on their microbiome and (previously described) epigenetic profiles. We find the diversity and community composition of the skin microbiome are strongly shaped by the environment and, to a lesser extent, by species-specific influences. Heterozygosity and microbiome alpha diversity, but not epigenetic variation, are associated with the fluctuating asymmetry of traits related to performance (vision) and behaviour (aggression). Our study identifies that a proportion of the epigenetic diversity and microbiome differentiation is unrelated to genetic variation, and we find evidence for an associative relationship between microbiome and epigenetic diversity in these wild populations. This suggests that both mechanisms could potentially contribute to variation in species with low genetic diversity. Species with low genetic diversity have limited capacity to adapt to environmental change. This study finds that the skin microbiome and non-genetic (epigenetic) modifications of the DNA represent additional sources of variation that could help low diversity fish survive environmental challenges. [ABSTRACT FROM AUTHOR]

Microbial communities often exhibit more than one possible stable composition for the same set of external conditions. In the human microbiome, these persistent changes in species composition and abundance are associated with health and disease states, but the drivers of these alternative stable states remain unclear. Here we experimentally demonstrate that a cross-kingdom community, composed of six species relevant to the respiratory tract, displays four alternative stable states each dominated by a different species. In pairwise coculture, we observe widespread bistability among species pairs, providing a natural origin for the multistability of the full community. In contrast with the common association between bistability and antagonism, experiments reveal many positive interactions within and between community members. We find that multiple species display cooperative growth, and modeling predicts that this could drive the observed multistability within the community as well as non-canonical pairwise outcomes. A biochemical screening reveals that glutamate either reduces or eliminates cooperativity in the growth of several species, and we confirm that such supplementation reduces the extent of bistability across pairs and reduces multistability in the full community. Our findings provide a mechanistic explanation of how cooperative growth rather than competitive interactions can underlie multistability in microbial communities. This study explores alternative stable states in microbial communities. Focusing on a respiratory tract community of 6 species, the authors identified four distinct stable states that are predicted to be driven by cooperative growth. The findings contrast with the common association between competitive interactions and multistability in microbial communities. [ABSTRACT FROM AUTHOR]

Horse owners and veterinarians report that from the age of 15, their horses can lose body condition and be more susceptible to diseases. Large intestinal microbiome changes may be involved. Indeed, microbiota is crucial for maintaining the condition and health of herbivores by converting fibres into nutrients. This study aimed to compare the faecal microbiome in horses aged from 6 to 30 years old (yo), living in the same environment and consuming the same diet, in order to assess whether the parameters changed linearly with age and whether there was a pivotal age category. Fifty horses were selected from the same environment and distributed across four age categories: 6–10 (n = 12), 11–15 (n = 11), 16–20 (n = 13), and 21–30 (n = 14) yo. All horses had no digestive problems, had teeth suitable for consuming their feed, and were up to date with their vaccination and deworming programmes. After three weeks of constant diet (ad libitum hay and 860 g of concentrate per day), one faecal sample per horse was collected on the same day. The bacterial communities' richness and intra-sample diversity were negatively correlated with age. There was a new distribution of non-beneficial and beneficial taxa, particularly in the 21–30 yo category. Although the faecal concentration of short-chain fatty acids remained stable, the acetate proportion was negatively correlated with age while it was the opposite for the proportions of butyrate, valerate, and iso-valerate. Additionally, the faecal pH was negatively correlated with age. Differences were more pronounced when comparing the 6–10 yo and 21–30 yo categories. The values of the parameters studied became more dispersed from the 16–20 yo category onwards, which appeared as a transitional moment, as it did not differ significantly from the younger and older categories for most of these parameters. Our data suggest that the microbiome changes with age. By highlighting the pivotal age of 16–20, this gives the opportunity to intervene before individuals reach extremes that could lead to pathological conditions. [ABSTRACT FROM AUTHOR]

Local biodiversity can help students develop conservation attitudes regarding biodiversity. However, studies reveal students' preferences regarding exotic than local biodiversity. Therefore, more research can permit an improved understanding of the reasons for their interest in these organisms. This research aimed to investigate São Paulo state (Brazil) students' interests and perceptions about their local biodiversity and understand how teaching materials present this topic. A Likert-type questionnaire and semi-structured interviews were used to collect data regarding students' interests and perceptions. Textbooks and handouts analysis included counting quoted living beings and verifying their occurrence in local biomes using open-access datasets. Results showed that the students were less interested in local biodiversity than global biodiversity. They further expressed little knowledge about local biomes and their biodiversity. Teaching materials mostly name living beings that exist in Brazil. However, they offer few explicit examples of them in students' biome. Furthermore, regional teaching materials must deal with more contextualisation. Results from our study support previous research that suggests students need more than proximity to local biodiversity to be aware of it. Therefore, we recommend developing teaching materials focusing on local biodiversity, with follow-up studies examining their impact on student awareness of local biodiversity. [ABSTRACT FROM AUTHOR]

Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections. Plain Language Summary: Climate change has caused substantial vegetation growth that was detected by satellite observations ("greening") over northern permafrost regions. However, the consequences or feedbacks of vegetation greening remain largely unknown, hindering the understanding of near‐surface thermal dynamics and bringing considerable uncertainty in model projections. Here we aimed to decipher the biophysical impact of permafrost greening on the summer surface offset (SSO), which is an indicator of permafrost degradation. We found latitude‐ and biome‐dependent patterns of SSO changes and divergent responses of SSO to greening. Increases in satellite‐observed leaf area index lead to higher SSO in relatively cold and wet areas but lower SSO in warm‐dry regions. Biophysical mechanisms associated with surface albedo, evapotranspiration, and SM can help explain various effects of greening on SSO. Our results highlight greening feedbacks on the thermal dynamics of permafrost with climate warming, calling for the improvement of current projections. Key Points: Vegetation greening impacts the thermal dynamics of permafrost surfaceBiophysical effects of greening on surface offset could be related to surface albedo, evapotranspiration, and soil moisture [ABSTRACT FROM AUTHOR]

Microorganisms are a valuable source of pharmaceutically active chemicals, serving as scaffolds for synthesis as well as lead structures. Investigating novel biomes frequently yields intriguing chemistry; the Atacama Desert in Chile is one such example. This study reports the isolation of a new reduced anthracycline-related compound from the Atacama Desert-derived bacterium Saccharothrix S26. Structural characterisation was achieved by one-dimensional and two-dimensional NMR, HR-LCMS, and X-ray crystallography. The compound was tested against the ESKAPE pathogens, bovine mastitis-related pathogens, and the fungal strain Cryptococcus neoformans, but no antimicrobial activity was observed. [ABSTRACT FROM AUTHOR]

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks. Alternative stable states in forests have implications for the biosphere. Here, the authors combine forest biodiversity observations and simulations revealing that leaf types across temperate regions of the NH follow a bimodal distribution suggesting signatures of alternative forest states. [ABSTRACT FROM AUTHOR]

The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change. This study maps global tree composition in forests and assesses the impacts of historical forest cover loss and climate change. The results highlight the need for preserving the remaining large forest biomes, while regenerating degraded forests in a way that provides resilience against climate change. [ABSTRACT FROM AUTHOR]

Comparing the abundance of microbial communities between different groups or obtained under different experimental conditions using count sequence data is a challenging task due to various issues such as inflated zero counts, overdispersion, and non-normality. Several methods and procedures based on counts, their transformation and compositionality have been proposed in the literature to detect differentially abundant species in datasets containing hundreds to thousands of microbial species. Despite efforts to address the large numbers of zeros present in microbiome datasets, even after careful data preprocessing, the performance of existing methods is impaired by the presence of inflated zero counts and group-wise structured zeros (i.e. all zero counts in a group). We propose and validate using extensive simulations an approach combining two differential abundance testing methods, namely DESeq2-ZINBWaVE and DESeq2, to address the issues of zero-inflation and group-wise structured zeros, respectively. This combined approach was subsequently successfully applied to two plant microbiome datasets that revealed a number of taxa as interesting candidates for further experimental validation. [ABSTRACT FROM AUTHOR]

Carbohydrate reserves play a vital role in plant survival during periods of negative carbon balance. Under a carbon-limited scenario, we expect a trade-offs between carbon allocation to growth, reserves, and defense. A resulting hypothesis is that carbon allocation to reserves exhibits a coordinated variation with functional traits associated with the 'fast-slow' plant economics spectrum. We tested the relationship between non-structural carbohydrates (NSC) of tree organs and functional traits using 61 angiosperm tree species from temperate and tropical forests with phylogenetic hierarchical Bayesian models. Our results provide evidence that NSC concentrations in stems and branches are decoupled from plant functional traits. while those in roots are weakly coupled with plant functional traits. In contrast, we found that variation between NSC concentrations in leaves and the fast-slow trait spectrum was coordinated, as species with higher leaf NSC had trait values associated with resource conservative species, such as lower SLA, leaf N, and leaf P. We also detected a small effect of leaf habit on the variation of NSC concentrations in branches and roots. Efforts to predict the response of ecosystems to global change will need to integrate a suite of plant traits, such as NSC concentrations in woody organs, that are independent of the 'fast-slow' plant economics spectrum and that capture how species respond to a broad range of global change drivers. [ABSTRACT FROM AUTHOR]

Background: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris. Results: The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study. Conclusion: Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity. [ABSTRACT FROM AUTHOR]

Millions of years of co-evolution between animals and their associated microbial communities have shaped and diversified the nature of their relationship. Studies continue to reveal new layers of complexity in host–microbe interactions, the fate of which depends on a variety of different factors, ranging from neutral processes and environmental factors to local dynamics. Research is increasingly integrating ecosystem-based approaches, metagenomics and mathematical modelling to disentangle the individual contribution of ecological factors to microbiome evolution. Within this framework, host factors are known to be among the dominant drivers of microbiome composition in different animal species. However, the extent to which they shape microbiome assembly and evolution remains unclear. In this review, we summarize our understanding of how host factors drive microbial communities and how these dynamics are conserved and vary across taxa. We conclude by outlining key avenues for research and highlight the need for implementation of and key modifications to existing theory to fully capture the dynamics of host-associated microbiomes. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'. [ABSTRACT FROM AUTHOR]

Background: Soil microbial communities are difficult to measure and critical to soil processes. The bulk soil microbiome is highly diverse and spatially heterogeneous, which can make it difficult to detect and monitor the responses of microbial communities to differences or changes in management, such as different crop rotations in agricultural research. Sampling a subset of actively growing microbes should promote monitoring how soil microbial communities respond to management by reducing the variation contributed by high microbial spatial and temporal heterogeneity and less active microbes. We tested an in-growth bag method using sterilized soil in root-excluding mesh, "sterile sentinels," for the capacity to differentiate between crop rotations. We assessed the utility of different incubation times and compared colonized sentinels to concurrently sampled bulk soils for the statistical power to differentiate microbial community composition in low and high diversity crop rotations. We paired this method with Oxford Nanopore MinION sequencing to assess sterile sentinels as a standardized, fast turn-around monitoring method. Results: Compared to bulk soil, sentinels provided greater statistical power to distinguish between crop rotations for bacterial communities and equivalent power for fungal communities. The incubation time did not affect the statistical power to detect treatment differences in community composition, although longer incubation time increased total biomass. Bulk and sentinel soil samples contained shared and unique microbial taxa that were differentially abundant between crop rotations. Conclusions: Overall, compared to bulk soils, the sentinels captured taxa with copiotrophic or ruderal traits, and plant-associated taxa. The sentinels show promise as a sensitive, scalable method to monitor soil microbial communities and provide information complementary to traditional soil sampling. [ABSTRACT FROM AUTHOR]

Peropteryx leucoptera is a widespread species in the Neotropics but with a disjunct distribution in Northern South America and a separated population in the Atlantic Forest of Northeastern Brazil. Here we present new records of this species for Northeastern Brazil, the first records for the Caatinga biome and for the states of Bahia and Rondônia. These new records represent a major range extension and establishes a new southern limit of occurrence for the species. We also examined and provide measurements of other specimens and present an updated map with the distribution of P. leucoptera in South America. [ABSTRACT FROM AUTHOR]

Simple Summary: Clostridium perfringens is a commensal bacterium of humans and other animals that can become pathogenic, causing myonecrosis and enteric diseases. Previous studies have reported C. perfringens infection in several wild animals as well as its presence as a commensal, but its role in animals of the Amazon region is largely unknown. Thus, this study investigated the occurrence of C. perfringens in samples from wild mammals treated at the Wild Animals Sector of the Veterinary Hospital of the Federal University of Pará in the Amazon biome. The results demonstrate that C. perfringens type A was the only toxinotype isolated from mammals in the Amazon biome, demonstrating the importance of further studies on the topic in wild animals, their impacts and the diseases caused. The objective of this study was to evaluate the occurrence of Clostridium perfringens in stool samples and swabs collected from wild mammals in the Amazon biome. Sixty-five faecal and swab samples were collected in situ and ex situ from 16 species and three genera of wild mammals, some of which were in good health and some of which had diarrhoea. After pre-enrichment, the samples were plated on selective agar for C. perfringens. Characteristic colonies were subjected to multiplex PCR for the detection of genes encoding the main C. perfringens toxins (alpha, beta, epsilon, and iota toxin and enterotoxin). Among the 65 samples, 40 (61.5%) were positive for the gene encoding the alpha toxin and were classified as type A, 36 of which were asymptomatic animals and four were diarrheal. No other toxinotypes were found. The findings of this study suggest that C. perfringens type A is commonly found in mammal species of the Amazon biome. This seems to be the first study to identify C. perfringens type A in species such as B. variegatus (common ground sloth), C. didactylus (two-toed sloth), P. flavus (Jupará), T. tetradactyla (anteater), S. collinsi (squirrel monkey), S. niger (black marmoset), and S. apella (Guyana capuchin) and in the genus Didelphis sp. (opossum). [ABSTRACT FROM AUTHOR]

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design. [ABSTRACT FROM AUTHOR]

Transition from traditional high-fiber to Western diets in urbanizing communities of Sub-Saharan Africa is associated with increased risk of non-communicable diseases (NCD), exemplified by colorectal cancer (CRC) risk. To investigate how urbanization gives rise to microbial patterns that may be amenable by dietary intervention, we analyzed diet intake, fecal 16 S bacteriome, virome, and metabolome in a cross-sectional study in healthy rural and urban Xhosa people (South Africa). Urban Xhosa individuals had higher intakes of energy (urban: 3,578 ± 455; rural: 2,185 ± 179 kcal/d), fat and animal protein. This was associated with lower fecal bacteriome diversity and a shift from genera favoring degradation of complex carbohydrates (e.g., Prevotella) to taxa previously shown to be associated with bile acid metabolism and CRC. Urban Xhosa individuals had higher fecal levels of deoxycholic acid, shown to be associated with higher CRC risk, but similar short-chain fatty acid concentrations compared with rural individuals. Fecal virome composition was associated with distinct gut bacterial communities across urbanization, characterized by different dominant host bacteria (urban: Bacteriodota; rural: unassigned taxa) and variable correlation with fecal metabolites and dietary nutrients. Food and skin microbiota samples showed compositional differences along the urbanization gradient. Rural-urban dietary transition in South Africa is linked to major changes in the gut microbiome and metabolome. Further studies are needed to prove cause and identify whether restoration of specific components of the traditional diet will arrest the accelerating rise in NCDs in Sub-Saharan Africa. Here, the authors present a comparative analysis of the diet, microbiome and metabolome of rural and urban Xhosa people in South Africa, associating urban diets with higher abundances of pro-neoplastic microbial metabolites. [ABSTRACT FROM AUTHOR]

The ecological and genetic changes that underlie the evolution of host–microbe interactions remain elusive, primarily due to challenges in disentangling the variables that alter microbiome composition. To understand the impact of host habitat, host genetics, and evolutionary history on microbial community structure, we examined gut microbiomes of river‐ and three cave‐adapted morphotypes of the Mexican tetra, Astyanax mexicanus, in their natural environments and under controlled laboratory conditions. Field‐collected samples were dominated by very few taxa and showed considerable interindividual variation. We found that lab‐reared fish exhibited increased microbiome richness and distinct composition compared to their wild counterparts, underscoring the significant influence of habitat. Most notably, however, we found that morphotypes reared on the same diet throughout life developed distinct microbiomes suggesting that genetic loci resulting from cavefish evolution shape microbiome composition. We observed stable differences in Fusobacteriota abundance between morphotypes and demonstrated that this could be used as a trait for quantitative trait loci mapping to uncover the genetic basis of microbial community structure. [ABSTRACT FROM AUTHOR]

Accounting for the condensation of organic vapors along with water vapor (co-condensation) has been shown in adiabatic cloud parcel model (CPM) simulations to enhance the number of aerosol particles that activate to form cloud droplets. The boreal forest is an important source of biogenic organic vapors, but the role of these vapors in co-condensation has not been systematically investigated. In this work, the environmental conditions under which strong co-condensation-driven cloud droplet number enhancements would be expected over the boreal biome are identified. Recent measurement technology, specifically the Filter Inlet for Gases and AEROsols (FIGAERO) coupled to an iodide-adduct chemical ionization mass spectrometer (I-CIMS), is utilized to construct volatility distributions of the boreal atmospheric organics. Then, a suite of CPM simulations initialized with a comprehensive set of concurrent aerosol observations collected in the boreal forest of Finland during spring 2014 is performed. The degree to which co-condensation impacts droplet formation in the model is shown to be dependent on the initialization of temperature, relative humidity, updraft velocity, aerosol size distribution, organic vapor concentration, and the volatility distribution. The predicted median enhancements in cloud droplet number concentration (CDNC) due to accounting for the co-condensation of water and organics fall on average between 16 % and 22 %. This corresponds to activating particles 10–16 nm smaller in dry diameter that would otherwise remain as interstitial aerosol. The highest CDNC enhancements (Δ CDNC) are predicted in the presence of a nascent ultrafine aerosol mode with a geometric mean diameter of ∼ 40 nm and no clear Hoppel minimum, indicative of pristine environments with a source of ultrafine particles (e.g., via new particle formation processes). Such aerosol size distributions are observed 30 %–40 % of the time in the studied boreal forest environment in spring and fall when new particle formation frequency is the highest. To evaluate the frequencies with which such distributions are experienced by an Earth system model over the whole boreal biome, 5 years of UK Earth System Model (UKESM1) simulations are further used. The frequencies are substantially lower than those observed at the boreal forest measurement site (< 6 % of the time), and the positive values, peaking in spring, are modeled only over Fennoscandia and the western parts of Siberia. Overall, the similarities in the size distributions between observed and modeled (UKESM1) are limited, which would limit the ability of this model, or any model with a similar aerosol representation, to project the climate relevance of co-condensation over the boreal forest. For the critical aerosol size distribution regime, Δ CDNC is shown to be sensitive to the concentrations of semi-volatile and some intermediate-volatility organic compounds (SVOCs and IVOCs), especially when the overall particle surface area is low. The magnitudes of Δ CDNC remain less affected by the more volatile vapors such as formic acid and extremely low- and low-volatility organic compounds (ELVOCs and LVOCs). The reasons for this are that most volatile organic vapors condense inefficiently due to their high volatility below the cloud base, and the concentrations of LVOCs and ELVOCs are too low to gain significant concentrations of soluble mass to reduce the critical supersaturations enough for droplet activation to occur. A reduction in the critical supersaturation caused by organic condensation emerges as the main driver of the modeled Δ CDNC. The results highlight the potential significance of co-condensation in pristine boreal environments close to sources of fresh ultrafine particles. For accurate predictions of co-condensation effects on CDNC, also in larger-scale models, an accurate representation of the aerosol size distribution is critical. Further studies targeted at finding observational evidence and constraints for co-condensation in the field are encouraged. [ABSTRACT FROM AUTHOR]

Background: The phyllosphere microbiome is crucial for plant health and ecosystem functioning. While host species play a determining role in shaping the phyllosphere microbiome, host trees of the same species that are subjected to different environmental conditions can still exhibit large degrees of variation in their microbiome diversity and composition. Whether these intra-specific variations in phyllosphere microbiome diversity and composition can be observed over the broader expanse of forest landscapes remains unclear. In this study, we aim to assess the variation in the top canopy phyllosphere bacterial communities between and within host tree species in the temperate European forests, focusing on Fagus sylvatica (European beech) and Picea abies (Norway spruce). Results: We profiled the bacterial diversity, composition, driving factors, and discriminant taxa in the top canopy phyllosphere of 211 trees in two temperate forests, Veluwe National Parks, the Netherlands and Bavarian Forest National Park, Germany. We found the bacterial communities were primarily shaped by host species, and large variation existed within beech and spruce. While we showed that there was a core microbiome in all tree species examined, community composition varied with elevation, tree diameter at breast height, and leaf-specific traits (e.g., chlorophyll and P content). These driving factors of bacterial community composition also correlated with the relative abundance of specific bacterial families. Conclusions: While our results underscored the importance of host species, we demonstrated a substantial range of variation in phyllosphere bacterial diversity and composition within a host species. Drivers of these variations have implications at both the individual host tree level, where the bacterial communities differed based on tree traits, and at the broader forest landscape level, where drivers like certain highly plastic leaf traits can potentially link forest canopy bacterial community variations to forest ecosystem processes. We eventually showed close associations between forest canopy phyllosphere bacterial communities and host trees exist, and the consistent patterns emerging from these associations are critical for host plant functioning. [ABSTRACT FROM AUTHOR]

Sustainable livestock production requires reducing competition for food and feed resources and increasing the utilization of food by-products in livestock feed. This study describes the establishment of an anaerobic batch culture model to simulate pig microbiota and evaluate the effects of a food by-product, wakame seaweed stalks, on ex vivo microbial communities. We selected one of the nine media to support the growth of a bacterial community most similar in composition and diversity to that observed in pig donor feces. Supplementation with wakame altered the microbial profile and short-chain fatty acid composition in the ex vivo model, and a similar trajectory was observed in the in vivo pig experimental validation. Notably, the presence of wakame increased the abundance of Lactobacillus species, which may have been due to cross-feeding with Bacteroides. These results suggest the potential of wakame as a livestock feed capable of modulating the pig microbiome. Collectively, this study highlights the ability to estimate the microbiome changes that occur when pigs are fed a specific feed using an ex vivo culture model. [ABSTRACT FROM AUTHOR]

Vine training and pruning are cultural strategies that can be deployed to manage grapevine trunk diseases (GTDs). Forty-year-old commercial vineyards in the Cognac region, France, trained to either Guyot-Arcure (severe pruning) or Guyot-Poussard (minimal pruning), were studied to determine how the two systems affected trunk disease symptomatology. Effects of pruning practices on the pathobiome and mycobiome of asymptomatic grapevines were also assessed, using culture-and amplicon-based Illumina sequencing approaches. The hypothesis examined was that severe pruning of Guyot-Arcure increases trunk diseases incidence and severity, and causes higher pathogen load and microbial diversity, compared to Guyot-Poussard. Numbers of symptomatic and asymptomatic vines for the two training systems were recorded over 3 years, including numbers of vines with esca foliar symptoms, and partially unproductive and dead vines. Six asymptomatic vines from each pruning method were selected, and culturing and sequencing data were obtained from 27 samples per vine. Fungi in the Phaeomoniellaceae, Togniniaceae, and Botryosphaeriaceae were the most frequently identified. The data indicated that severe pruning increased risk of pathogen infections, with Phaeomoniella chlamydospora, Phaeoacremonium minimum and Diplodia sp. being the most commonly identified fungi. Greater numbers of dead or dying vines were recorded in the severely pruned vineyard, indicating that this strategy shortens vine longevity. Results also showed that severe pruning increased endophytic microbial diversity, and that the pruning methods influenced mycobiome community composition. This knowledge will improve recommendations to growers for practical and cost-effective ways to manage GTDs. [ABSTRACT FROM AUTHOR]

The Climate-responsive Land Allocation model with carbon Storage and Harvests (CLASH) is a global, biophysical land-use model that can be embedded into integrated assessment models (IAMs). CLASH represents vegetation growth, terrestrial carbon stocks, and production from agriculture and forestry for different land uses in a changing climate. Connecting CLASH to an IAM would allow the consideration of terrestrial carbon stocks, agriculture and forestry in global climate policy analyses. All terrestrial ecosystems and their carbon dynamics are comprehensively described at a coarse resolution. Special emphasis is placed on representing the world's forests. Vegetation growth, soil carbon stocks, agricultural yields and natural disturbance frequencies react to changing climatic conditions, emulating the dynamic global vegetation model LPJ-GUESS. Land is divided into 10 biomes with six land-use classes (including forests and agricultural classes). Secondary forests are age structured. The timing of forest harvests affects forest carbon stocks, and, hence, carbon storage per forest area can be increased through forest management. In addition to secondary forests, CLASH also includes primary ecosystems, cropland and pastures. The comprehensive inclusion of all land-use classes and their main functions allows representing the global land-use competition. In this article, we present, calibrate and validate the model; demonstrate its use; and discuss how it can be integrated into IAMs. [ABSTRACT FROM AUTHOR]

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