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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 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.)

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.)

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]

Major biogeographic and taxonomic biases are recurrent in biological surveys, including fragmentation studies. Detecting biases and subsequent gaps is crucial to steer future research and suitable conservation policies. We evaluated biogeographic and fragmentation-related biases on antbirds and non-flying small mammals in Brazil, two oversampled and vulnerable taxonomic groups, by surveying papers in the Scielo and the Web of Science. We found 566 articles published from 1945 to 2018, including 55 and 43 fragmentation studies for antbirds and small mammals, respectively. Considering the species richness for each group across the Brazilian biomes, the number of publications for small mammals tended to disproportionately increase while increasing richness. The Atlantic Forest, the most degraded and densely populated biome, contained the highest number of publications. However, the Amazon included a disproportionately high number of papers considering its low population density. Conversely, non-forest biomes such as the Caatinga, Pampa and Pantanal were mostly overlooked. Our results show that research effort for small mammals and antbirds in Brazil is biogeographically biased. We call future research to consider more studies across non-forest biomes and vast unexplored areas within forest biomes to overcome major knowledge gaps on diversity, distribution and ecology of antbirds and small mammals in Brazil. [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]

This paper introduces a relatively simple method for recovering global fields of near-surface net available energy (the sum of the sensible and latent heat flux or the difference between the net radiation and surface heat accumulation) using satellite visible and infrared products derived from the AIRS (Atmospheric Infrared Sounder) and MODIS (MOderate Resolution Imaging Spectroradiometer) platforms. The method focuses on first specifying net surface radiation by considering its various shortwave and longwave components. This was then used in a surface energy balance equation in conjunction with satellite day-night surface temperature difference to derive 12 h discrete time estimates of surface, system heat capacity and heat accumulation, leading directly to retrieval for surface net available energy. Both net radiation and net available energy estimates were evaluated against ground truth data taken from 30 terrestrial tower sites affiliated to the FLUXNET network covering 7 different biome classes. This revealed a relatively good agreement between the satellite and tower data, with a pooled root mean square deviation of 98 and 72Wm-2 for net radiation and net available energy, respectively, although both quantities were underestimated by approximately 25 and 10%, respectively relative to the tower observations. Analysis of the individual shortwave and longwave components of the net radiation revealed the downwelling shortwave radiation to be the main source of this systematic underestimation. [ABSTRACT FROM AUTHOR]

Phenology is essential to our understanding of biogeochemical cycles and the climate system. We develop a global mechanistic model of leaf phenology based on the hypothesis that phenology is a strategy for optimal carbon gain at the canopy level so that trees adjust leaf gains and losses in response to environmental factors such as light, temperature and soil moisture, to achieve maximum carbon assimilation. We fit this model to five years of satellite observations of leaf area index (LAI) using a Bayesian fitting algorithm. We show that our model is able to reproduce phenological patterns for all vegetation types and use it to explore variations in growing season length and the climate factors that limit leaf growth for different biomes. Phenology in wet tropical areas is limited by leaf age physiological constraints while at higher latitude leaf seasonality is limited by low temperature and light availability. Leaf growth in grassland regions is limited by water availability but often in combination with other factors. This model will advance the current understanding of phenology for ecosystem carbon models and our ability to predict future phenological behaviour. [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]

Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes defined by environmental envelopes incorporating 4 criteria: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl), ice fraction, and maximum mixed layer depth (maxMLD) on a one-by-one degree grid (doi:10.1594/PANGAEA.828650). By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the gridcells that do not change biome assignment across the 13 years of the time-varying biomes. These ocean biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function. [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]

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]

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedback to elevated atmospheric carbon dioxide (CO2) in the warmer future world. We examined seven biome models with climate projections forced by four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify uncertainty in global SOC stock projections from global and regional perspectives. Our simulations showed that SOC stocks among the biome models varied from 1090 to 2650 PgC even in historical periods (ca. 2000). In a higher forcing scenario (RCP8.5), inconsistent estimates of impact on the total SOC (2099-2000) were obtained from different model simulations, ranging from a net sink of 347 PgC to a net source of 122 PgC. In all models, the elevated atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 PgC by the end of the 21st century. Using time-series data of total global SOC estimated by biome biome model, we statistically analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (▵ T and ▵ P respectively) in each biome model using a state-space model. This analysis suggests that ▵ T explained global SOC stock changes in most models with a resolution of 1-2° C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 PgCyr-1 to 3.53 PgCyr-1 among the biome models. On the other hand, ▵ P had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the changes in SOC estimated by the biome models, especially in boreal to arctic regions. Our study revealed considerable climate change impact uncertainty in SOC decomposition among biome models. Further research is required to improve our understanding and ability to estimate biospheric feedback through SOC-relevant processes as well as vegetation processes. [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]

For most of the 20th century, the hypothesis was accepted that Madagascar's extensive grass‐dominated ecosystems were of anthropogenic origin, carved out of pristine forests after a mere two millennia of human settlement. We tested an alternative hypothesis that these C4 grassy ecosystems were part of the general Late Miocene expansion of tropical grassy biomes, using diverse data from published sources (Bond et al. 2008). Joseph and Seymour (2021) criticised this paper, which they see as seminal to subsequent studies on the grasslands. Here we respond to their critique of our study. We also briefly note diverse studies since 2008 pointing to the ancient origin of Madagascar's C4 grasses and the ecosystems they dominate. We conclude with key research needs that will help promote open‐minded research on these long neglected grassy biomes. The answers would be of considerable scientific and public interest but may also contribute to enlightened management of forest/grassland mosaics. [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]

This paper described an experimental study for treating salt containing wastewater with a bench-scale SBBR (sequencing batch biofilm reactor). By gradually increasing salinity of the wastewater, the activated sludge of high salt-tolerance was acclimatized, and the treatment test of simulated salt wastewater was carried out with wastewater samples of five sorts of salinity: 0 g/L, 8 g/L, 16 g/L, 24 g/L and 32 g/L. The experimental results showed that with the increase of salinity gradient, the efficiencies of removing NH4+-N, COD and TP decreased notably: in case where salinity was 32 g/L, and compared with salinity of 0 g/L, NH4+-N declined from 98% to 84%; COD from 98% to 73%; and TP from 97% to 47%. Additionally, the microbial activity, which was characterized by SOUR (specific consumption rate) and DHA (dehydrogenase activity) of biofilm, increased on condition of salinity being below 8 g/L, while decreased when salinity was up to greater than 8 g/L. Salinity made it possible to increase the content of extracellular polymer (EPS) in biofilms from 26.15 mg/g SS to 216.27 mg/g SS, among which polysaccharide (PS) content of TB-EPS grew most, and the increase of EPS could improve the resistance of microorganisms to salinity and the cells' protective effectiveness. It was found that under different salinity conditions there were growing three largest dominant phyla: actinomycetes, proteomycetes and patella bacteria in the biofilms, and the average relative abundance remained between 72% and 83%, among which the relative abundance of actinomycetes increased significantly with the increase of salinity, and the relative abundance of variant phylum decreased with the increase of salinity; the relative abundance of Kineosphaera, Micropruina and TM7a increased rapidly with the increase of salinity, and on the condition of salinity being up to 32 g/L, they became the three biggest dominant genera. To sum up, from the perspective of microbial community characteristics, the effects of increasing salinity on the structure and diversity of microbial communities were explored, the results could provide a theoretical basis for the further study on COD, NH4+-N and TP removal mechanisms of SBBR systems under high salinity stress. [ABSTRACT FROM AUTHOR]

Habitat loss, fragmentation and invasive species are the major causes of biodiversity loss. In the Atlantic Forest, Callithrix aurita is threatened by habitat modification and the invasion of Callithrix jacchus. We evaluated how landscape variables and a local one, the distance to the roads, influence the presence of the native and invasive species within the distribution range of the native. For that, we retrieved data on the presence of C. aurita and C. jacchus from published papers. Comparing species, C. aurita occurs in higher altitudes and lesser urbanized areas than C. jacchus. In presence modeling, the probability of presence of the native C. aurita was higher within deforested landscapes with intense road traffic, while the presence of the invasive species, C. jacchus, was increased in urbanized areas, mostly in non-mountainous terrain, confirming its generalist habits. If such results are not related to biased detectability, C. aurita are living in suboptimal areas, and probably should be more affected by the presence of invasive species. These opposite characteristics of the species highlighted some regions in which conservation measures should be guided, where C. aurita is probably more present and the negative influence of C. jacchus is still limited. [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]

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]

In the 1990s and 2000s, soybean farming grew sharply, particularly in states located in Brazil's mid-west region. To curb deforestation, the Federal Government implemented command and control policies and, at the same time, soy-buying companies and Civil Society Organizations implemented the Soy Moratorium. This paper focused on the major role of these initiatives in decreasing soybean farming in areas deforested after 2006 and their importance in achieving this result. We considered rich database deforestation, and soybean planted area based on highly detailed remote sensing images, combined with explanatory variables of different sources, forming a panel data of 287 municipalities over 8 years. Spatial panel data models are implemented to avoid any spatial correlation problems and to analyze relationships through regional units and time. The results confirm that lower deforestation rates in the biome laid the foundation for reducing soybean farming in the Amazon biome. However, since 2008, when the Soy Moratorium was launched, there was a structural decline in this relationship that was decisive for a decoupling of soybean farming from deforestation. Therefore, government programs to reduce deforestation made room for a new environment for agricultural expansion in line with Brazilian law and environmental commitments. The Soy Moratorium reinforced this new order, and this production chain became a case study on public and private governance, given its importance in reducing soybean farming in deforested areas after the cut-off date. These public and private effects stress the importance of coordinated actions to achieve efficient results, especially in a large social and environmentally complex region as the Brazilian Amazon, to halt biodiversity degradation and increase participation in value added markets. [ABSTRACT FROM AUTHOR]

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[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 forests of South Africa and the neighbouring countries, including Lesotho, eSwatini, Namibia, Botswana, Zimbabwe, and Mozambique (south of the Zambezi River), were mapped and classified according to the global system of biomes. The new four-tier hierarchical biome system suggested in this paper includes zonobiome, global biome, continental biome (all recognised earlier), and regional biome – a novel biome category. The existing spatial coverages of the forests were revised and considerably improved, both in terms of forest-patch coverage and mapping precision. Southern Africa is home to three zonal forest types, namely Subtropical Forests (Zonobiome I), Tropical Dry Forest (TDF; Zonobiome II) and Afrotemperate Forests (Zonobiome X). These three biomes are characterised by unique bioclimatic envelopes. Five, two, and eight regional biomes, respectively, have been recognised within these zonal biomes. Recognition of the Zonobiome I and the global biome Tropical Dry Forests in southern Africa is novel and expands our knowledge of the biome structure of African biotic communities. The system of the azonal regional biomes is also new and comprehensively covers the variability of the azonal helobiomes (riparian woodlands and swamp forests), mangroves, and azonal coastal forests. In total, 11 azonal regional biomes have been recognised in the study area. The forest biomes in southern Africa were captured in our electronic map in the form of more than 60 000 polygons, covering 42 416 km2 (1.27% of the study area). No less than 83% of these forests occur in the territory of southern Mozambique. Abbreviations: for the abbreviation of the biome units, see Table 1; CE: centre of endemism; IOCB: Indian Ocean Coastal Belt; MBSA: the area of the Map of Biomes of Southern Africa; VegMap2006 and VegMap2018: Vegetation Map of South Africa, Lesotho and Swaziland (as released in respective years); for the meaning of the codes of the biome units see Table 1, and for the meaning of the abbreviations of climatic characteristics see Appendix S1 [ABSTRACT FROM AUTHOR]

The resource‐use hypothesis, proposed by E.S. Vrba, states that habitat fragmentation caused by climatic oscillations would affect particularly biome specialists (species inhabiting only one biome), which might show higher speciation and extinction rates than biome generalists. If true, lineages would accumulate biome‐specialist species. This effect would be particularly exacerbated for biomes located at the periphery of the global climatic conditions, namely, biomes that have high/low precipitation and high/low temperature such as rainforest (warm‐humid), desert (warm‐dry), steppe (cold‐dry) and tundra (cold‐humid). Here, we test these hypotheses in swallowtail butterflies, a clade with more than 570 species, covering all the continents but Antarctica, and all climatic conditions. Swallowtail butterflies are among the most studied insects, and they are a model group for evolutionary biology and ecology studies. Continental macroecological rules are normally tested using vertebrates, this means that there are fewer examples exploring terrestrial invertebrate patterns at global scale. Here, we compiled a large Geographic Information System database on swallowtail butterflies' distribution maps and used the most complete time‐calibrated phylogeny to quantify diversification rates (DRs). In this paper, we aim to answer the following questions: (1) Are there more biome‐specialist swallowtail butterflies than biome generalists? (2) Is DR related to biome specialization? (3) If so, do swallowtail butterflies inhabiting extreme biomes show higher DRs? (4) What is the effect of species distribution area? Our results showed that swallowtail family presents a great number of biome specialists which showed substantially higher DRs compared to generalists. We also found that biome specialists are unevenly distributed across biomes. Overall, our results are consistent with the resource‐use hypothesis, species climatic niche and biome fragmentation as key factors promoting isolation. [ABSTRACT FROM AUTHOR]

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007–2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov–Smirnov test, the corrected Akaike criterion AICc, the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28–32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. [ABSTRACT FROM AUTHOR]

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]