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Copyright of Revista Caatinga is the property of Revista Caatinga 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.)

Malaria is the most important vector-borne disease in the world and a challenge for control programs. In Brazil, 99% of cases occur in the Amazon region. In the extra-Amazonian region, a non-endemic area, epidemiological surveillance focuses on imported malaria and on autochthonous outbreaks, including cases with mild symptoms and low parasitemia acquired in the Atlantic Forest biome. In this scenario, cases are likely to be underreported, since submicroscopic parasitemias are not detected by thick blood smear, considered the reference test. Molecular tests are more sensitive, detecting asymptomatic individuals and mixed infections. The aim of this study was to propose a more efficient alternative to detect asymptomatic individuals living in areas of low malaria endemicity, as they are reservoirs of Plasmodium that maintain transmission locally. In total, 955 blood samples from residents of 16 municipalities with autochthonous malaria outbreaks in the Sao Paulo State were analyzed; 371 samples were collected in EDTA tubes and 584 in filter paper. All samples were initially screened by a genus-specific qPCR targeting ssrRNA genes (limit of detection of 1 parasite/µL). Then, positive samples were subjected to a nested PCR targeting ssrRNA and dihydrofolate reductase-thymidylate synthase genes (limit of detection of 10 parasites/µL) to determine Plasmodium species. The results showed a statistically significant difference (K = 0.049; p < 0.0001) between microscopy positivity (6.9%) and qPCR (22.9%) for EDTA-blood samples. Conversely, for samples collected in filter paper, no statistical difference was observed, with 2.6% positivity by thick blood smear and 3.1% for qPCR (K = 0.036; p = 0.7). Samples positive by qPCR were assayed by a species-specific nested PCR that was in turn positive in 26% of samples (16 P. vivax and 4 P. malariae). The results showed that molecular protocols applied to blood samples from residents in areas with autochthonous transmission of malaria were useful to detect asymptomatic patients who act as a source of transmission. The results showed that the genus-specific qPCR was useful for screening positives, with the subsequent identification of species by nested PCR. Additional improvements, such as standardization of blood plotting on filter paper and a more sensitive protocol for species determination, are essential. The qPCR-based algorithm for screening positives followed by nested PCR will contribute to more efficient control of malaria transmission, offering faster and more sensitive tools to detect asymptomatic Plasmodium reservoirs. [ABSTRACT FROM AUTHOR]

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]

The Caatinga is an exclusively Brazilian biome, and is the largest and most biodiverse Seasonal Tropical Dry Forest in the world. Despite that, the mammalian fauna, especially small mammals, is the least studied of all Brazilian biomes. In order to fill gaps and provide detailed information on small mammals (Didelphimorphia, Rodentia) in the Caatinga biome, we compiled reliable records focusing on richness, composition and some biometric data. These records came from mammal collections, papers, theses, books, and unpublished data, prioritizing records with vouchers housed in scientific collections. We compiled a total of 3133 records from 816 locations, resulting in a richness of 47 native species (12 marsupials and 35 rodents, plus three exotic rodents, Rattus rattus, Rattus norvegicus, and Mus musculus). This dataset includes records of three new species for the biome and its transition zone: the rodents Calomys mattevii, Holochilus oxe, and Nectomys squamipes. Of the total number of records, 1808 (57.71%) are from consulting activities, 95 (3.03%) are from zoonoses studies and 104 (3.32%) are from the National Plague Service (SNP). All nine Brazilian states with territory in the Caatinga have sampling data for small mammals, but the number of records and localities are unevenly distributed, with the state of Rio Grande do Norte having the lowest number of records and locations sampled. Our dataset is the first of its kind for the Caatinga biome and has considerable potential value for studies of habitat use, landscape ecology, macroecology, biogeography, and conservation. There are no copyright restrictions on the data. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Agroveterinarias is the property of Revista de Ciencias Agroveterinarias 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 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]

This paper describes the validation of the SimSphere SVAT model conducted at different ecosystem types in the USA and Australia. Specific focus was given to examining the models' ability in predicting Shortwave Incoming Solar Radiation (Rg), Net Radiation (Rnet), Latent Heat (LE), Sensible Heat (H), Air Temperature at 1.3m (Tair 1.3m) and Air Temperature at 50m (Tair 50m). Model predictions were compared against corresponding in situ measurements acquired for a total of 72 selected days of the year 2011 obtained from 8 sites belonging to the AmeriFlux (USA) and OzFlux (Australia) monitoring networks. Selected sites were representative of a variety of environmental, biome and climatic conditions, to allow for the inclusion of contrasting conditions in the model evaluation. The application of the model confirmed its high capability in representing the multifarious and complex interactions of the Earth system. Comparisons showed a good agreement between modelled and measured fluxes, especially for the days with smoothed daily flux trends. A good to excellent agreement between the model predictions and the in situ measurements was reported, particularly so for the LE, H, Tair 1.3m and Tair 50m parameters (RMSD= 39.47, 55.06 Wm-2, 3.23, 3.77°C respectively). A systematic underestimation of Rg and Rnet (RMSD=67.83, 58.69 Wm-2, MBE= 67.83, 58.69 Wm-2 respectively) was also found. Highest simulation accuracies were obtained for the open woodland savannah and mulga woodland sites for most of the compared parameters. Very high values of the Nash-Sutcliffe efficiency index were also reported for all parameters ranging from 0.720 to 0.998, suggesting a very good model representation of the observations. To our knowledge, this study presents the first comprehensive validation of Sim- Sphere, particularly so in USA and Australian ecosystem types. Findings are important and timely, given the rapidly expanding use of this model worldwide both as an educational and research tool. This includes ongoing research by different Space Agencies examining its synergistic use with Earth Observation data towards the development of global operational products. [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]

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models. [ABSTRACT FROM AUTHOR]

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]

Savanna ecosystems are one of the most dominant and complex terrestrial biomes that derives from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static, but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of 6 TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit, but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP, and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange, rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe this study is the first to assess how well TBMs simulate savanna ecosystems, and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies. [ABSTRACT FROM AUTHOR]

Microorganisms are an important source of compounds that are pharmaceutically active, both as leads and as scaffolds for synthesis. Often, interesting chemistry is uncovered by exploring new biomes, of which the Chilean Atacama Desert is a prime example. This paper describes the isolation and structural characterisation, using HR-LCMS and 1D and 2D NMR, of a new compound belonging to a family of compounds called radstrictins. The compound was isolated from a fungus, that had itself been isolated from a soil sample from the Atacama Desert. The compound was tested against pathogenic strains associated with bovine mastitis, but was found to be devoid of antimicrobial activity. [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]

Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to Net Ecosystem Exchange in many biomes, even the most complex Dynamic Vegetation Models (DVMs) embedded in General Circulation Models contain poor representations of fire behaviour and dynamics such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected Component Labeling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the results are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its Fire Return Interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model (point model); the fire regime is described by large scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals) are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the evolution of land cover, biomass and Net Ecosystem Exchange after a fire. [ABSTRACT FROM AUTHOR]

Despite the overall extension of the Amazon Basin (approximately 6,000,000 km 2 ),which encompasses such a complex ecosystem and territories belonging to seven different nations, it is worth mentioning that environmental assessments related to changes in land use and land cover (LULC) in this region are often conducted respecting geopolitical boundaries associated with each country or taking into account the so-called Amazon biome. With the purpose of prospecting the intricate and hidden hydrological patterns, we undertake an in-depth evaluation of the water balance along the 2001–2021 time span across the whole basin, whose behavior depends on the features deriving from the metamorphoses in land use and land cover. To accomplish that task, the influence of the components of the water balance, namely rainfall and evapotranspiration, jointly with the terrestrial topographic mapping, are examined to investigate the interactions among the physical mechanisms that make up the hydrological cycle and the corresponding physical hydrological processes triggered by deforestation and reforestation in the region. More specifically, the modeling approach was rigorously designed to also consider, separately or not, Negro, Solimões, Madeira, Tapajós and Xingu hydrographic sub-basins, which are the most important ones of the Amazon Basin. The results highlight that in the southern region of the Amazon, specifically within the Madeira river sub-basin, the lowest forest coverage is observed (56.0%), whereas in the northern Negro river sub-basin, the most notable forest coverage is observed (85.0%). The most preserved forest areas, such as the Negro and Solimões river sub-basins, with percentages of 81.9% and 74.2%, respectively, have higher annual rates of precipitation and evapotranspiration over time. On the other hand, regions that suffered the most intense deforestation along the time period studied, such as the Madeira, Tapajós and Xingu sub-basins, have lower annual rates of precipitation and evapotranspiration, with preservation percentages of 54.6%, 62.6% and 70.7%, respectively. As the pace of deforestation slowed between 2003 and 2013, annual precipitation rates increased by 12.0%, while evapotranspiration decreased by 2.0%. The hydrological findings of this paper highlight th predominant role of the forest in the context of the global water balance of the Amazon Basin and the potential to also produce distinct impacts within different parts of the basin in terms of having more or less rainfall and evapotranspiration. In addition, those variabilities in the hydrological operational components and mechanisms due to changes in land cover and land use also reveal the potential impacts that could be expected in the surrounding areas, closer or farther, notably beyond the limits of the Amazon Basin. [ABSTRACT FROM AUTHOR]

Upper Palaeolithic archaeological sites in the Basque Country have been excavated for over a century. They have yielded a rich palaeoenvironmental record with zoological and botanical remains that have been obtained in stratigraphic series dated precisely by radiocarbon. This information reveals cyclical environmental changes from climates similar to today to drier and extremely cold conditions, when species in current boreal biomes and others now extinct but with similar ecological preferences were present in the region. Moreover, the archaeological sites have provided high-resolution information about the resilience mechanisms of the communities of our own human species. This information allows us to increase the corpus of palaeoclimate data regarding the Marine Isotopic Stage (MIS) 2 and MIS 3 for a critical region within the human population of Eurasia. The aim of this paper is to show how an extraordinary capacity for adaptation to drastic climate changes Upper Palaeolithic hunter–gatherer societies displayed, even though their subsistence depended on biotic resources that alter rapidly. [ABSTRACT FROM AUTHOR]

Global change models predict that high-latitude boreal forests will become increasingly susceptible to fire activity as climate warms, possibly causing a positive feedback to warming through fire-driven emissions of CO into the atmosphere. However, fire-climate feedbacks depend on forest regrowth and carbon (C) accumulation over the post-fire successional interval, which is influenced by nitrogen (N) availability. To improve our understanding of post-fire C and N accumulation patterns in boreal forests, we evaluated above- and belowground C and N pools within 70 stands throughout interior Alaska, a region predicted to undergo a shift in canopy dominance as fire severity increases. Stands represented gradients in age and successional trajectory, from black spruce ( Picea mariana) self-replacement to species replacement by deciduous species of trembling aspen ( Populus tremuloides) and Alaska paper birch ( Betula neoalaskana). Stands undergoing deciduous trajectories stored proportionally more of their C and N in aboveground stemwood and had 5-7 times faster rates of aboveground net primary productivity of trees compared to stands undergoing a black spruce trajectory, which stored more of their C and N in the soil organic layer (SOL), a thick layer of mostly undecomposed mosses. Thus, as successional trajectories shift, total C and N pool sizes will remain relatively unchanged, but there will be a trade-off in pool location and a potential increase in C and N longevity due to decreased flammability and decomposition rates of deciduous stemwood. Despite often warmer, drier conditions in deciduous compared to black spruce stands, deciduous stemwood has a C:N around 10 times higher than the black spruce SOL and often remains standing for many years with reduced exposure to fungal decomposers. Thus, a fire-driven shift in successional trajectories could cause a negative feedback to climate warming because of increased pool longevity in deciduous trajectories. [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]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias 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.)

The knowledge of the physiological aspects of Caatinga's vegetal species is extremely important for preserving this biome, which suffers with human impacts, mainly to select propagation methods. Erythrina velutina is a Brazilian tree, generally found in Caatinga, with medical and forestry potential. The objective of this paper was to determine the best soaking period in gibberellin solution to achieve the highest germination and to evaluate the internal anatomy by digital microtomography of E. velutina seeds. The design was completely randomized and consisted of eight treatments: 1, 3, 6, 12, 24 and 48 h of soaking, scarified seeds and the control with no-scarified seeds. Digital microtomography was efficient in describing the anatomy of the seeds and distinguishing their tissues. There was no significant difference between the treatments at different soaking times, as the gibberellic acid did not influence the germination; only the control presented a lower germination percentage, differing from the other treatments. The study presents evidence that E. velutina seeds do not require the exogenous use of gibberellic acid, but only the scarification process. In addition, the use of digital microtomography can be useful in understanding the anatomy of seeds, especially forest species, which can contribute to the future studies of other plant species. [ABSTRACT FROM AUTHOR]

The long-horned caddisfly genus Notalina Mosely, 1936 contains 27 species divided into two subgenera. The Neotropical N. (Neonotalina) Holzenthal, 1986 occurs exclusively in South America. Its species are organized into two species groups, brasiliana and roraima. Nine species have been recorded so far in Brazil, mainly distributed in the Cerrado and Atlantic Forest biomes of Southeast Region, and only one species has been recorded from the Central-West and Northeast Regions. In this paper a new species of N. (Neonotalina) is described and illustrated based on adult males from two protected and preserved areas in the Cerrado biome of Brazil. Notalina (Neonotalina) ralphi sp. nov. belongs to the brasiliana species group and can be recognized mainly by the morphology of the preanal appendages and segment X. New distributional records are provided for N. (Neonotalina) brasiliana Holzenthal, 1986. Additionally, a key to identify males of the ten species in the brasiliana species group is provided. [ABSTRACT FROM AUTHOR]

Host-parasite associations are driven by complex ecological interactions that can be influenced by the parasite, the host, and the climatic conditions. Knowledge about the structures of hostparasite interaction networks is still incipient and studies mainly focused on the infracommunity levels. So, we conducted a systematic review using full-text articles to understand the relation between Brazilian small mammals and protozoan infections besides identify their functional roles in the network. We identified 4527 potentially relevant references and finally included 41 papers and considered 42 species of small mammals and 13 species of the protozoan. We found nonspecificity of this relationship, with a modular network that is nestedness with low specialization values with most of the parasite and hosts occupying ultraperipheral or peripheral roles. Didelphids were homogeneously distributed among all modules, reinforcing the ancient relationship between this clade and the protozoan clade to spread infections. We also identify an isolated relation between the rodent O. cleberi and T. dionisii, a common bat protozoan highlighting that the environment and features of the parasites and hosts make these relationships more complex, and understanding these relationships can help to understand the dynamics of many infectious diseases. [ABSTRACT FROM AUTHOR]

The first county along the Yellow river, Madoi is the key region of the state natural protective source regions of Yangtze River, Lantsang River and Yellow River, its eco-environment and function in widespread attention. In support of the hardware and software system, based on GIS and remote sensing technology, this paper combined field investigation and laboratory analysis. Around 1990, 2000 and 2010, ten-phase remote sensing images are interpreted, and it is continuously monitored that Madoi wetlands have changed in the 20 years. Using wetland interpretation results and the area of the wetland types transfer matrix, it evaluates the changes of wetland area in the 20 years. With the meteorological and statistical data, this paper discussed the reason of the wetland changing in recent 20 years. The results of remote sensing monitoring and field investigation show that the overall trend of the wetland area changing increased after the first reducing in three times. In the first 10 years, swamp changes were the largest, followed by lakes and rivers; in the next 10 years, lake changes were the largest, followed by swamps and rivers. Natural factors which resulted in wetland changes of Madoi are climate changes, the permafrost environment changes, rodent rampant; man-made factors are overgrazing, irrational mining, fishing, hunting and development of tourism. [ABSTRACT FROM AUTHOR]

Copyright of Questiones Publicitarias is the property of Universitat Autonoma de Barcelona 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.)

Bright sunshine duration (BSD) data are required for simulating biomes using process-based vegetation models. However, monthly global paleoclimate datasets that can be used in paleo data--model comparisons do not necessarily contain BSD or radiation data. Considering the theoretical and practical aspects, the scheme of Yin, X. (1999) is here recommended to estimate monthly time series of relative BSD using only monthly climate and location data. As a case study for the Carpathian Region, the efficiency of both the original and a variant of that scheme is analysed in this paper. The alternative scheme has high applicability in paleoenvironmental studies. Comparison of the estimated and observed BSD data shows that from May to August, the value of relative root mean squared error in more than 90 percent of the study area does not exceed the threshold of 20 percent, indicating an excellent performance of the original estimation scheme. It is also found that though the magnitude of overestimation for the alternative algorithm is significant in the winter period, the proposed method performs similarly well in the growing season as the original. Furthermore, concerning modelling the distribution of biomes, simulation experiments are performed to assess the effects of modifying some configuration settings: (a) the generation of relative BSD data, and (b) the algorithm used to create quasi-daily weather data from the monthly values. Under both the recent humidity conditions of the study region and the spatial resolution of the climate dataset used, the results can be considered sufficiently robust, regardless of the configuration settings tested. Thus, using monthly temperature and precipitation climatologies, the spatial distribution of biomes can be properly simulated with the configuration settings proposed here. [ABSTRACT FROM AUTHOR]

Humic substances are an important soil quality indicator, influencing its physical-chemical and biological characteristics while directly affecting plant growth, through their biostimulant activity. To elucidate the role of humic substances in seedlings acclimation it's important to establish a relationship among the origin, the structural composition and their biological activity. The aim of the present paper is to characterize the soluble humic fractions extracted from soils of the Brazilian Cerrado biome with different levels of preservation, and to verify their biological activity on seedlings of the pioneer Cerrado native species Enterolobium contortisiliquum (Vell.) Morong. Humic and fulvic acids were isolated from preserved and degraded Cerrado areas. Humic compounds were characterized assessing total acidity, UV-VIS and IR spectra. Humic substances bioactivity was evaluated on E. contortisiliquum seedlings grown in Leonard pots, supplied with nutrient solution added with the optimal concentrations of humic and fulvic acids and their mix. Seedlings root structure, antioxidant enzymes activity and photosynthetic pigments contents were evaluated. The humic substances showed different chemical characteristics and bioactivity depending on sampling area. Mixed humic and fulvic acids showed higher efficacy, especially those coming from the preserved area. It is noteworthy that A) the type of management influences humic fraction chemical structure, well reflected in their biological activity B) E. contortisiliquum, shows a better response to humic substances coming from a well-established and stable canopy. [ABSTRACT FROM AUTHOR]

Temperature imposes a constraint on the rates and outcomes of ecological processes that determine community-and ecosystem-level patterns. The application of metabolic scaling theory has advanced our understanding of the influence of temperature on pattern and process in marine communities. Metabolic scaling theory uses the fundamental and ubiquitous patterns of temperature-dependent metabolism to predict how environmental temperature influences patterns and processes at higher levels of biological organization. Here, we outline some of these predictions to review recent advances and illustrate how scaling theory might be applied to new challenges. For example, warming can alter species interactions and food-web structure and can also reduce total animal biomass supportable by a given amount of primary production by increasing animal metabolism and energetic demand. Additionally, within a species, larval development is faster in warmer water, potentially influencing dispersal and other demographic processes like population connectivity and gene flow. These predictions can be extended further to address major questions in marine ecology, and present an opportunity for conceptual unification of marine ecological research across levels of biological organization. Drawing on work by ecologists and oceanographers over the last century, a metabolic scaling approach represents a promising way forward for applying ecological understanding to basic questions as well as conservation challenges. [ABSTRACT FROM AUTHOR]

This paper summarizes knowledge on the Neogene-Quaternary terrestrial fossil record from the Middle Kura Basin accumulated over a century and aims to its integration into the current research. This fossil evidence is essential in understanding the evolution of the Eurasian biome, since this territory is located at the border of Eastern Mediterranean and Central Asian regions. The general biostratigraphic framework suggests existence of two major intervals of the terrestrial fossil record in the area, spanning ca. 10-7 Ma and ca. 3-1 Ma, and points to an important hiatus between the late Miocene and late Pliocene. General aspects of the paleogeographic history and fossil record suggest that the biogeographic role of the Middle Kura Basin has been changing over geological time from a refugium (Khersonian) to a full-fledged part of the Greco-Iranian province (Meotian-Pontian). The dynamic environmental changes during the Quaternary do not depict this territory as a refugium in its general sense. The greatest value of this fossil record is the potential to understand a detailed history of terrestrial life during demise of late Miocene Hominoidea in Eurasia and early Homo dispersal out of Africa. Late Miocene record of the Middle Kura Basin captures the latest stage of the Eastern Paratethys regression, and among other fossils counts the latest and the easternmost occurence of dryopithecine, Udabnopithecus garedziensis, while the almost uninterrupted fossil record of the late Pliocene-Early Pleistocene covers the time interval of the early human occupation of Caucasus and Eurasia. [ABSTRACT FROM AUTHOR]

Citizen science can facilitate in‐depth learning for pupils and students, contribute to scientific research, and permit civic participation. Here, we describe the development of the transnational school‐based citizen science project Phenology of the North Calotte. Its primary goal is to introduce pupils (age 12–15; grades 7–10) in northern Norway, Russia, and Finland to the local and global challenges of climate change resulting in life cycle changes at different trophic and ecosystem levels in their backyards. Partnerships between regional scientists and staff from NIBIO Svanhovd, State nature reserves, national parks, and teachers and pupils from regional schools aim to engage pupils in project‐based learning. The project uses standardized protocols, translated into the different languages of participating schools. The phenological observations are centered around documenting clearly defined life cycle phases (e.g., first appearance of species, flowering, ripening, leaf yellowing, snow fall, and melt). The observations are collected either on paper and are subsequently submitted manually to an open‐source online database or submitted directly via a newly developed mobile app. In the long term, the database is anticipated to contribute to research studying changes in phenology at different trophic levels. In principle, guided school‐based citizen science projects have the potential to contribute to increased environmental awareness and education and thereby to transformative learning at the societal level while contributing to scientific progress of understudied biomes, like the northern taiga and (sub)arctic tundra. However, differences in school systems and funding insecurity for some schools have been major prohibiting factors for long‐term retention of pupils/schools in the program. Project‐based and multidisciplinary learning, although pedagogically desired, has been partially difficult to implement in participating schools, pointing to the need of structural changes in national school curricula and funding schemes as well as continuous offers for training and networking for teachers. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizal fungi (AMF—Glomeromycota) are a group of soil fungi with a widespread occurrence in terrestrial ecosystems where they play important roles that influence plant growth and ecosystem processes. The aim of this paper is to reveal AMF distribution in the Neotropics based on an extensive biogeography database with literature data from the last five decades. All four orders and 11 families were reported in the Neotropics. 221 species (69% of the total number of species for the phylum) were registered in the Neotropics pertaining to 37 genera. Acaulospora , Glomus , Scutellospora , and Funneliformis were the most speciose genera and represented by 47, 29, 15, and 13 species, respectively. Seventy-six species were originally described from Neotropics, which represents 24% of the total diversity of Glomeromycota. The most representative families were Gigasporaceae, Ambisporaceae, and Acaulosporaceae with 89%, 80%, and 79% of species within each family detected in the Neotropics, respectively. AMF were detected in 11 biomes and 52 ecological regions in 19 countries. Biomes with the largest number of species were Tropical and Subtropical Moist Forests (186 species), Tropical and Subtropical Dry Broadleaf forests (127 species), and Tropical and Subtropical Grasslands (124 species), and Jaccard's similarity among them was 53–57%. Mean annual temperature and precipitation were not correlated with total AMF species richness. The Neotropics biomes shelter a large amount of the total diversity of Glomeromycota and studies of occurrence of these fungi should be encouraged considering their importance in maintaining terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Organisms in polluted environments are typically exposed to a complex mixture of chemical contaminants. The great concern about the health of aquatic ecosystems has led to the increased use of biomarkers over the past years. The aim of this work was to review the papers published from 2000 to 2015, which used biomarkers to assess the health of aquatic ecosystems in Brazil. A research resulted in 99 eligible papers. More than 80% of studies were conducted in the states of São Paulo and Rio Grande do Sul. Approximately 63% of studies used fish as bioindicator, whereas the micronucleus test and biochemical analyses were the most used biomarkers. A multibiomarker approach was used by 60.6% of studies, while 39.4% used one single biomarker. Furthermore, 68% were field studies and more than 75% of these used control animals sampled at reference sites. A relationship between the biomarker responses and pollution was reported by 87% of studies; however, 43.4% of studies analyzed only one sampling period, limiting comparisons and comprehension about possible seasonal variations. This review evidenced some weak points in studies using biomarkers in Brazil, especially related to the lack of studies in two important biomes (the Pantanal and the Amazon Rainforest) and experimental designs (small sample size, sampling in one single period, use of one single biomarker). Thus, future studies should consider mainly the use of multiple biomarkers, greater sample size, seasonal sampling and water physicochemical parameters to better diagnose the health of aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Aerosols and primary biological aerosol particles (PBAPs) play an important role in regulating the global climate, but information summarizing the available knowledge is limited. Here, we present a systematic review of in situ studies performed in the last 35 years on aerosols–PBAPs in Brazil, with 212 studies encompassing 474 cases. The Amazon rainforest was the most studied biome, represented by 72% of cases, followed by the Atlantic Forest with 18%. Studies focusing the Amazon mostly investigated climate-related issues and aerosol physics, with less than 5% examining the biological identity of aerosols, whereas outside the Amazon, this number reached 16%. Whilst more than half of the cases within Amazon (55%) were held at seven sampling sites only, conclusions were mainly extrapolated to the entire biome. Contrarily, research beyond the Amazon has mostly addressed the temporal and biological characterisation of PBAPs, and not only is it scattered, but also scarce. Regarding sampling efforts, most cases (72%) had fewer than 100 days of sampling, and 60% of them spanned less than half a year of study. We argue that scientists should produce more detailed/complete assessments of aerosols–PBAPs in Brazil as a whole, particularly considering their biological identity, given their importance to global climate regulation. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

This paper analyses and compares a set of case studies on ecosystem services (ES) mapping and assessment with the purpose of formulating lessons learned and recommendations. Fourteen case studies were selected during the EU Horizon 2020 "Coordination and Support Action" ESMERALDA to represent different policy- and decision-making processes throughout the European Union, across a wide range of themes, biomes and scales. The analysis is based on a framework that addresses the key steps of an ES mapping and assessment process, namely policy questions, stakeholder identification and involvement, application of mapping and assessment methods, dissemination and communication and implementation. The analysis revealed that most case studies were policy-orientated or gave explicit suggestions for policy implementation in different contexts, including urban, rural and natural areas. Amongst the findings, the importance of starting stakeholder engagement early in the process was confirmed in order to generate interest and confidence in the project and to increase their willingness to cooperate. Concerning mapping and assessment methods, it was found that the integration of methods and results is essential for providing a comprehensive overview from different perspectives (e.g. social, economic). Finally, lessons learned for effective implementation of ES mapping and assessment results are presented and discussed. [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]

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]

Vegetation fires are an important process in the Earth system. Fire intensity locally impacts fuel consumption, damage to the vegetation, chemical composition of fire emissions and also how fires spread across landscapes. It has been observed that fire occurrence, defined as the frequency of active fires detected by the MODIS sensor, is related to intensity with a hump-shaped empirical relation, meaning that occurrence reaches a maximum at intermediate fire intensity. Raw burned area products obtained from remote sensing can not discriminate between ignition and propagation processes. To go beyond burned area and to test if fire size is driven by fire intensity at a global scale as expected from empirical fire spread models, we used the newly delivered global FRY database, which provides fire patch functional traits based on satellite observation, including fire patch size, and the fire radiative power measures from the MCD14ML dataset. This paper describes the varying relationships between fire size and fire radiative power across biomes at a global scale. We show that in most fire regions of the world defined by the GFED database, the linear relationship between fire radiative power and fire patch size saturates for a threshold of intermediate-intensity fires. The value of this threshold differs from one region to another and depends on vegetation type. In the most fire-prone savanna regions, once this threshold is reached, fire size decreases for the most intense fires, which mostly happen in the late fire season. According to the percolation theory, we suggest that the decrease in fire size for more intense late season fires is a consequence of the increasing fragmentation of fuel continuity throughout the fire season and suggest that landscape-scale feedbacks should be developed in global fire modules. [ABSTRACT FROM AUTHOR]

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This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published African pollen dataset and a global ecosystem classification scheme. To test the applicability of traditional and machine-learning based classification models for the task of biome prediction from high dimensional modern pollen data, we train a total of eight classification models, including Linear Discriminant Analysis, Logistic Regression, Naïve Bayes, K-Nearest Neighbors, Classification Decision Tree, Random Forest, Neural Network, and Support Vector Machine. The ability of each model to predict biomes from pollen data is statistically tested on an independent test set. The Random Forest classifier outperforms other models in its ability correctly classify biomes given pollen data. Out of the eight models, the Random Forest classifier scores highest on all of the metrics used for model evaluations and is able to predict four out of five biome classes to high degree of accuracy, including arid, montane, tropical and subtropical closed and open systems, e.g. forests and savanna/grassland. The model has the potential for accurate reconstructions of past biomes and awaits application to fossil pollen sequences. The Random Forest model may be used to investigate vegetation changes on both long and short time scales, e.g. during glacial and interglacial cycles, or more recent and abrupt climatic anomalies like the African Humid Period. Such applications may contribute to a better understanding of past shifts in vegetation cover and ultimately provide valuable information on drivers of climate change. [ABSTRACT FROM AUTHOR]

Stryphnodendron adstringens is a native species from Caatinga and Cerrado biomes. The chemical composition of species is variable and depends on the part of the tree, as well as on genetic and soil characteristics related to the origin of the population. This paper describes the influence of toposequence position of trees on the discrimination of wood and bark samples based on visible (VIS), near-infrared (NIR) and mid-infrared (MID) spectroscopy. A total of 28 trees were collected in the northern part of Cerrado State Park in the municipality of Jaguariaíva, Paraná state, Brazil, in different types of soil, at seven positions (0, 100, 200, 300, 400, 500 and 600 m) of the toposequence. The results showed the influence of the position of trees. The bark was classified as dark brown and the wood as rose-grey. VIS spectra was not efficient in sample discrimination. The Principal Component Analysis (PCA) of NIR spectra presented two groups that can be related to the the type of soil: (i) 0-300 m - Red-Yellow Latosol and Haplic Cambisol; (ii) 400-600 m - Red Latosol. MID infrared spectra of bark also showed the distinction of two previous groups; and analysis based on wood spectra of trees collected on 0-100m presented discrimination from other positions. [ABSTRACT FROM AUTHOR]