The Cocktail Effects on the Acute Cytotoxicity of Pesticides and Pharmaceuticals Frequently Detected in the Environment.

Xenobiotics never appear as single, isolated substances in the environment but instead as multi-component mixtures. However, our understanding of the ecotoxicology of mixtures is far from sufficient. In this study, three active pharmaceutical ingredients (carbamazepine, diclofenac, and ibuprofen) and three pesticides (S-metolachlor, terbuthylazine, and tebuconazole) from the most frequently detected emerging micropollutants were examined for their acute cytotoxicity, both individually and in combination, by bioluminescence inhibition in Aliivibrio fischeri (NRRL B-11177). Synergy, additive effects, and antagonism on cytotoxicity were determined using the combination index (CI) method. Additionally, PERMANOVA was performed to reveal the roles of these chemicals in binary, ternary, quaternary, quinary, and senary mixtures influencing the joint effects. Statistical analysis revealed a synergistic effect of diclofenac and carbamazepine, both individually and in combination within the mixtures. Diclofenac also exhibited synergy with S-metolachlor and when mixed with ibuprofen and S-metolachlor. S-metolachlor, whether alone or paired with ibuprofen or diclofenac, increased the toxicity at lower effective concentrations in the mixtures. Non-toxic terbuthylazine showed great toxicity-enhancing ability, especially at low concentrations. Several combinations displayed synergistic effects at environmentally relevant concentrations. The application of PERMANOVA was proven to be unique and successful in determining the roles of compounds in synergistic, additive, and antagonistic effects in mixtures at different effective concentrations.

Exploring health preference heterogeneity in the UK: Using the online elicitation of personal utility functions approach to construct EQ-5D-5L value functions on societal, group and individual level.

A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

Seasonal shift in gut microbiome diversity in wild Sichuan takin (Budorcas tibetanus) and environmental adaptation.

In this study, we investigated the change in microbiome composition of wild Sichuan takin (Budorcas tibetanus) during winter and spring and analyzed the physiological implications for such changes. Diversity analyses of the microbiome (average 15,091 high-quality reads per sample) in 24 fecal samples (15 from winter, 9 from spring) revealed that spring samples had higher species diversity and were compositionally different from winter samples (P < 0.05). Taxonomic composition analysis showed that the relative abundance increased in spring for Patescibacteria (2.7% vs. 0.9% in winter, P < 0.001) and Tenericutes (1.9% vs. 1% in winter, P < 0.05). Substantial increases in relative abundance of Ruminococcaceae and Micrococcaceae were identified in spring and winter, respectively. Mann-Whitney U and ANCOM identified seven differentially abundant genera: Enterococcus, Acetitomaculum, Blautia, Coprococcus 1, Lachnospiraceae UCG 008, Ruminococcus 2 and Ralstonia. All seven genera were significantly more abundant in spring (average 0.016-1.2%) than winter (average 0-0.16%), with the largest difference found in Ruminococcus (1.21% in spring vs. 0.16% in winter). The other six genera were undetectable in winter. Functional prediction and pathway analysis revealed that biosynthesis of cofactors (ko01240) had the highest gene count ratios in the winter, followed by the two-component system (ko02020). Seasonal variation affects the gut microbiomes in wild Sichuan takins, with winter associated with lower species diversity and spring with enrichment of cellulose-degrading genera and phytopathogens. Such changes were crucial in their adaptation to the environment, particularly the difference in food abundance.

A semiparametric model for between-subject attributes: Applications to beta-diversity of microbiome data.

The human microbiome plays an important role in our health and identifying factors associated with microbiome composition provides insights into inherent disease mechanisms. By amplifying and sequencing the marker genes in high-throughput sequencing, with highly similar sequences binned together, we obtain operational taxonomic units (OTUs) profiles for each subject. Due to the high-dimensionality and nonnormality features of the OTUs, the measure of diversity is introduced as a summarization at the microbial community level, including the distance-based beta-diversity between individuals. Analyses of such between-subject attributes are not amenable to the predominant within-subject-based statistical paradigm, such as t-tests and linear regression. In this paper, we propose a new approach to model beta-diversity as a response within a regression setting by utilizing the functional response models (FRMs), a class of semiparametric models for between- as well as within-subject attributes. The new approach not only addresses limitations of current methods for beta-diversity with cross-sectional data, but also provides a premise for extending the approach to longitudinal and other clustered data in the future. The proposed approach is illustrated with both real and simulated data.

Influence of environmental factors on biology and catch composition of Barbonymus schwanenfeldii in a tropical lake, northern Malaysia: implications for conservation planning.

Very little work has determined the relative importance of uncontrolled environmental factors for affecting fish biology, and how these might influence gillnet catches. This study addresses this deficit for an important Southeast Asian cyprinid (Barbonymus schwanenfeldii). Fish were caught monthly for 12 months using gillnets of three different mesh sizes, each of which was deployed in duplicate at the surface of one of three randomly selected sites in Lake Kenyir, Malaysia, concurrent with determining various environmental parameters and the abundance of phytoplankton (chlorophyll-a). Results indicated that growth co-efficient of B. schwanenfeldii was positively influenced by dissolved oxygen and negatively influenced by total inorganic nitrogen, whereas an opposite result was observed in case of the hepatosomatic index of fish. Water turbidity was a limiting factor only for small fish (mean total length: 15.74±1.10 cm). B. schwanenfeldii could best be caught during the period of high phytoplankton abundance or at the location of high phytoplankton density in the water. Water temperature negatively influenced the gillnet catches of the fish. The remaining environmental factors such as water depth, pH, and phosphate had a weak and insignificant influence (P >0.05) on the biology and gillnet catches of fish. The observed results can be very useful for the ecological monitoring and conservation plans for this species in relation to climate change. Furthermore, the utility of the similar data for other species would be useful not only for regional but also for international fishery by optimizing catches considering environmental conditions.

Transmission dynamics of an antimicrobial resistant Campylobacter jejuni lineage in New Zealand's commercial poultry network.

Understanding the relative contribution of different between-farm transmission pathways is essential in guiding recommendations for mitigating disease spread. This study investigated the association between contact pathways linking poultry farms in New Zealand and the genetic relatedness of antimicrobial resistant Campylobacter jejuni Sequence Type 6964 (ST-6964), with the aim of identifying the most likely contact pathways that contributed to its rapid spread across the industry. Whole-genome sequencing was performed on 167C. jejuni ST-6964 isolates sampled from across 30 New Zealand commercial poultry enterprises. The genetic relatedness between isolates was determined using whole genome multilocus sequence typing (wgMLST). Permutational multivariate analysis of variance and distance-based linear models were used to explore the strength of the relationship between pairwise genetic associations among the C. jejuni isolates and each of several pairwise distance matrices, indicating either the geographical distance between farms or the network distance of transportation vehicles. Overall, a significant association was found between the pairwise genetic relatedness of the C. jejuni isolates and the parent company, the road distance and the network distance of transporting feed vehicles. This result suggests that the transportation of feed within the commercial poultry industry as well as other local contacts between flocks, such as the movements of personnel, may have played a significant role in the spread of C. jejuni. However, further information on the historical contact patterns between farms is needed to fully characterise the risk of these pathways and to understand how they could be targeted to reduce the spread of C. jejuni.

Expertise- and Tempo-Related Performance Differences in Unimanual Drumming.

BACKGROUND: High-speed drumming requires precise control over the timing, velocity, and magnitude of striking movements. AIM: To examine effects of tempo and expertise on unaccented repetitive drumming performance using 3D motion capture. METHODS: Expert and amateur drummers performed unimanual, unaccented, repetitive drum strikes, using their dominant right hand, at five different tempi. Performance was examined with regard to timing variability, striking velocity variability, the ability to match the prescribed tempo, and additional variables. RESULTS: Permutated multivariate analysis of variance (PERMANOVA) revealed significant main effects of tempo (p < .001) and expertise (p <.001) on timing variability and striking velocity variability; low timing variability and low striking velocity variability were associated with low/medium tempo as well as with increased expertise. Individually, improved precision appeared across an optimum tempo range. Precision was poorest at maximum tempo (400 hits per minute) for precision variables. CONCLUSIONS: Expert drummers demonstrated greater precision and consistency than amateurs. Findings indicate an optimum tempo range that extends with increased expertise.

Aquatic Ecosystems of the Anthropocene: Limnology and Microbial Ecology of Mine Pit Lakes.

Mine pit lakes ('pit lakes') are new aquatic ecosystems of the Anthropocene. Potentially hundreds of meters deep, these lakes are prominent in the landscape and in the public consciousness. However, the ecology of pit lakes is underrepresented in the literature. The broad goal of this research was to determine the environmental drivers of pelagic microbe assemblages in Australian coal pit lakes. The overall experimental design was four lakes sampled three times, top and bottom, in 2019. Instrument chains were installed in lakes and measurements of in situ water quality and water samples for metals, metalloids, nutrients and microbe assemblage were collected. Lakes were monomictic and the timing of mixing was influenced by high rainfall events. Water quality and microbial assemblages varied significantly across space and time, and most taxa were rare. Lakes were moderately saline and circumneutral; Archeans were not prevalent. Richness also varied by catchment. Microbial assemblages correlated to environmental variables, and no one variable was consistently significant, spatially or temporally. Study lakes were dominated by 'core' taxa exhibiting temporal turnover likely driven by geography, water quality and interspecific competition, and the presence of water chemistry associated with an artificial aquifer likely influenced microbial community composition. Pit lakes are deceptively complex aquatic ecosystems that host equally complex pelagic microbial communities. This research established links between microbial assemblages and environmental variables in pit lakes and determined core communities; the first steps towards developing a monitoring program using microbes.

The Landscape of Microbial Composition and Associated Factors in Pancreatic Ductal Adenocarcinoma Using RNA-Seq Data.

Recent research studies on interrogation of the tumor microbiome (including bacteria, viruses, and fungi) have yielded important insights into the role of microbes in carcinogenesis, therapeutic responses, and resistance. Once thought to be a sterile organ, a number of studies have showed the presence of microbes within this organ in PDAC status. A microbiome-pancreas axis for PDAC (pancreatic ductal adenocarcinoma) carcinogenesis is proposed. However, the microbial composition of localized PDAC tissue is still unclear. The associations between microbiome and PDAC reported in previous studies were detected in an indirect way, which mostly used samples from stool, oral saliva, and intestinal samples. This study integrated 582 samples derived from PDAC tissues across four datasets and presented a landscape of tumor microbiome at the genus level in PDAC based on remining of RNA-Seq data. On average, there are hundreds of genera distributed in the PDAC tissue, and dozens of core microbiota were identified by PDAC tissue. The pan-microbiome of PDAC tissue was also estimated, which might surpass 2,500 genera. In addition, sampling sites (stroma vs. epithelium) and tissue source (human tissue vs. PDX) were found to have great effects on the microbial composition of PDAC tissue, but not the traditional risk factors (sex and age). It is the first study to systematically focus on exploring the microbial composition of PDAC tissue and is helpful to have a deep understanding of tumor microbiome. The identified specific taxa might be potential biomarkers for follow-up research studies.

Comparative metagenomic analysis of the vaginal microbiome in healthy women.

The composition of these vaginal microbiome has a significant impact on women's health. However, few studies have characterized the vaginal microbiome of healthy Chinese women using metagenomic sequencing. Here, we carried out a comparative metagenomic analysis to survey taxonomic, functional levels, and microbial communities' genome content in healthy women's vaginal microbiome. Overall, we observed a total of 111 species, including all dominant vaginal Lactobacillus species, such as L. iners, L. crispatus, L. gasseri, and L. jensenii. Unlike microbial taxa, several pathways were ubiquitous and prevalent across individuals, including adenosine ribonucleotides de novo biosynthesis and pyruvate fermentation to acetate and lactate II. Notably, our diversity analysis confirmed a significant difference in healthy women from different ethnic groups. Moreover, we binned vaginal assemblies into 62 high-quality genomes, including 9 L. iners, 7 A. vaginae, 5 L. jensenii, and 5 L. crispatus. We identified the pan and core genomes of L. iners and A. vaginae and revealed the genetic diversity. Primary differences between strains were the hypothetical genes and mobile element-like genes. Our results provide a framework for understanding the implications of the female reproductive tract's composition and functional potential and highlight the importance of genome-resolved metagenomic analysis to further understand the human vaginal microbiome.

Influences of environmental parameters and phytoplankton productivity on benthic invertebrates in a tropical oligotrophic lake, northern Malaysia.

Studies that associate environmental parameters with aquatic organisms in man-made lakes remain limited by accessibility and interest particularly in many Asian countries. With missed opportunities to monitor environmental transitions at Lake Kenyir, our knowledge of lake transition is restricted to the non-mixing shallow waters only. Triplicate monthly benthic invertebrate samples were collected concurrently with various environmental parameters at three locations (zones A-C) of Kenyir Lake, Malaysia. Our results affirmed that the northeast part of Lake Kenyir is oligotrophic. Abundance of phytoplankton, total suspended solids, phosphate, nitrite and nitrate drive the abundance of various groups of benthic invertebrates. All of these extrinsic variables (except phosphate) negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Polychaeta, Oligochaeta, Bivalvia, Gastropod, Isopoda and Copepod in all zones. Phosphate negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Oligochaeta, Bivalvia and Copepod. Its influences on the Polychaeta, Gastropod and Isopoda densities were zone-specific. Overall, seasons equally influenced the relationships between extrinsic and response variables in all zones. The results of this study are useful to evaluate the lake's environmental quality, in conservation and in similar projects involving environmental handling, monitoring and recovery.

Detecting silent stressors: Trace element effects on nutritional status of declining scoter ducks of Puget Sound, USA.

White-winged scoters (Melanitta fusca; WWSC) and surf scoters (M. perspicillata; SUSC) have declined by over 60% in recent decades. Identifying contributing factors from within a mosaic of sublethal, multiple stressors is challenging. In urbanized Puget Sound, Washington, USA where scoters winter, changes in prey availability explained only a portion of local declines, suggesting that other "silent stressors" such as sublethal contaminants might play a role. Past studies of pollutant effects on scoters used Fisherian statistics that often revealed few correlates; however, novel statistical approaches could detect and provide more insights about sublethal impacts. Our objectives were to (1) relate pollutant accumulation to health of the birds, and (2) compare permutational multivariate statistics with traditional approaches in identifying sublethal health effects. We collected scoters from three locations in Puget Sound in December 2005 and March 2006, and measured cadmium (Cd), mercury (Hg), and selenium (Se) levels in livers and kidneys. To assess impacts of low contaminants levels in tissues on nutritional status (whole-body mass, lipid, and protein; and triglycerides, ß-hydroxybutyrate, and uric acid in blood), we compared statistical methods. Permutational multivariate methods use Monte Carlo techniques to assess how an integrated matrix of physiological responses in each animal respond to contaminants. Univariate regressions revealed very few and inconsistent relationships. In contrast, multivariate models showed that liver Hg and Se explained 25% of the variance in nutritional status of white-winged scoters; and in surf scoters, Cd, Hg, and Se in tissues explained 14 to 27% of nutritional status depending on site. The influence of these factors equals other aspects of habitat such as foraging conditions. Our study indicates that permutational multivariate statistics can be a powerful tool for identifying sublethal contaminant associations that, with non-contaminant stressors, can influence nutritional status and thus, contribute to population dynamics.

Power of Microbiome Beta-Diversity Analyses Based on Standard Reference Samples.

A simple method to analyze microbiome beta-diversity computes mean beta-diversity distances from a test sample to standard reference samples. We used reference stool and nasal samples from the Human Microbiome Project and regressed an outcome on mean distances (2 degrees-of-freedom (df) test) or additionally on squares and cross-product of mean distances (5-df test). We compared the power of 2-df and 5-df tests with the microbiome regression-based kernel association test (MiRKAT). In simulations, MiRKAT had moderately greater power than the 2-df test for discriminating skin versus saliva and skin versus nasal samples, but differences were negligible for skin versus stool and stool versus nasal samples. The 2-df test had slightly greater power than MiRKAT for Dirichlet multinomial samples. In associating body mass index with beta-diversity in stool samples from the American Gut Project, the 5-df test yielded smaller P values than MiRKAT for most taxonomic levels and beta-diversity measures. Unlike procedures like MiRKAT that are based on the beta-diversity matrix, mean distances to reference samples can be analyzed with standard statistical tools and shared or meta-analyzed without sharing primary DNA data. Our data indicate that standard reference tests have power comparable to MiRKAT's (and to permutational multivariate analysis of variance), but more simulations and applications are needed to confirm this.

Environmental DNA assessment of airborne plant and fungal seasonal diversity.

Environmental DNA (eDNA) metabarcoding and metagenomics analyses can improve taxonomic resolution in biodiversity studies. Only recently, these techniques have been applied in aerobiology, to target bacteria, fungi and plants in airborne samples. Here, we present a nine-month aerobiological study applying eDNA metabarcoding in which we analyzed simultaneously airborne diversity and variation of fungi and plants across five locations in North and Central Italy. We correlated species composition with the ecological characteristics of the sites and the seasons. The most abundant taxa among all sites and seasons were the fungal genera Cladosporium, Alternaria, and Epicoccum and the plant genera Brassica, Corylus, Cupressus and Linum, the latter being much more variable among sites. PERMANOVA and indicator species analyses showed that the plant diversity from air samples is significantly correlated with seasons, while that of fungi varied according to the interaction between seasons and sites. The results consolidate the performance of a new eDNA metabarcoding pipeline for the simultaneous amplification and analysis of airborne plant and fungal particles. They also highlight the promising complementarity of this approach with more traditional biomonitoring frameworks and routine reports of air quality provided by environmental agencies.

Seasonal factors driving biochemical biomarkers in two fish species from a subtropical reservoir in southern Brazil: An integrated approach.

Reservoirs are lentic man-made waterbodies resulting from river damming processes. Pollutants coming from adjacent areas can accumulate in the water and sediment of these modified freshwater environments. Fish are often found in reservoirs occupying several trophic niches. Biochemical biomarkers are early warning signals of environmental disturbance to an organism. It is essential to understand how pollutants, abiotic variables and biochemical biomarker responses behave throughout the seasons to implement biomonitoring programs. Loricariichthys anus and Geophagus brasiliensis were collected, and abiotic variables were seasonally measured for one year, at six sampling sites in Passo Real reservoir, in a subtropical region of Southern Brazil. Biochemical biomarkers were analyzed in four tissues of both fish species, as well as metal and pesticide concentrations in the reservoir's water and sediment. Redundancy analysis (RDA) was carried out to find the temporal relationship between biomarkers and environmental variables. RDA has clearly shown the separation of seasons for both species. Azoxystrobin, simazine and propoxur were the pesticides mostly contributing to the variation, whereas metals had lesser contribution to it. Seasonality appears to be the main factor explaining biomarkers' variability. PERMANOVA has confirmed the effect of temperature and dissolved oxygen on biomarkers of both fish species. Thus, it is hard to differentiate if the fluctuation in biomarkers' responses only reflects the normal state of organisms or it is a biological consequence from negative effects of fish exposure to several types of pollution (sewage, pesticides, and fertilizers) entering this aquatic system. In this study, to circumvent the seasonality issue on biomonitoring, the analysis of biomarkers on these fish should not be carried out in organs directly affected by temperature (such as liver and gills), or during reproduction periods (mainly in Spring).

Effect of stevia on the gut microbiota and glucose tolerance in a murine model of diet-induced obesity.

Artificial sweeteners have been shown to induce glucose intolerance by altering the gut microbiota; however, little is known about the effect of stevia. Here, we investigate whether stevia supplementation induces glucose intolerance by altering the gut microbiota in mice, hypothesizing that stevia would correct high fat diet-induced glucose intolerance and alter the gut microbiota. Mice were split into four treatment groups: low fat, high fat, high fat + saccharin and high fat + stevia. After 10 weeks of treatment, mice consuming a high fat diet (60% kcal from fat) developed glucose intolerance and gained more weight than mice consuming a low fat diet. Stevia supplementation did not impact body weight or glucose intolerance. Differences in species richness and relative abundances of several phyla were observed in low fat groups compared to high fat, stevia and saccharin. We identified two operational taxonomic groups that contributed to differences in beta-diversity between the stevia and saccharin groups: Lactococcus and Akkermansia in females and Lactococcus in males. Our results demonstrate that stevia does not rescue high fat diet-induced changes in glucose tolerance or the microbiota, and that stevia results in similar alterations to the gut microbiota as saccharin when administered in concordance with a high fat diet.

Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis.

The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples-namely, Operational Taxonomic Units; the newer Amplicon Sequence Variants; and a method commonly found in sequence analysis, minhash-are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through this analysis, we provide insights which would affect the decisions on the application of each method. Specifically, the presence of sequence read errors and variability in sequence read coverage deferentially affects these processing methods.

La densidad, riqueza y composición arbóreas definen parches detectados remotamente en una selva subperennifolia

Recientemente se ha abordado la delimitación de parches de vegetación a través de clasificaciones orientadas a objetos con datos multiespectrales. En esta investigación se presenta una propuesta de caracterización de selvas secundarias basada en matrices de semejanza de composición específica, estructura de la vegetación arbórea e índices de diversidad, partiendo de una clasificación orientada a objetos de imágenes multiespectrales. El área de estudio corresponde a una selva mediana subperennifolia con antecedente de aprovechamiento agrícola bajo el sistema de roza tumba y quema (Ac: hace 8-23 años), aprovechamiento forestal selectivo (Fs: hace 43-53 años), y aprovechamiento forestal selectivo e incendio forestal (Fc: hace 21-28 años). Se delinearon tres parches de vegetación de acuerdo al historial de uso, y se analizaron las diferencias entre las medias de las métricas de campo de cada parche con un análisis de varianza multivariado permutacional (P < 0.001). Con un modelo logístico multinomial se identificaron, de entre más de 20 covariables, la riqueza de especies, densidad de tallos por hectárea, y el primer eje de variación del ordenamiento NMDS de la composición específica, como los atributos de la vegetación más distintivos. El parche Fc, presenta los mayores valores en diversidad de Shannon-Wiener, riqueza de especies, y densidad de tallos mayores a 7.5 cm de diámetro. El Fs tiene los mayores promedios de biomasa, área basal y altura individual, y el Ac tiene los menores valores de todas las métricas anteriores. Las especies de mayor Índice de Valor de Importancia fueron: Ac; Bursera simaruba y Psidia psipula, Fs: Gymnanthes lucida y Manilkara zapota, Fc: G. lucida y B. simaruba.

A proposal for characterizing habitat of forests, obtained from an object-oriented classification of RapidEye multiespectral imagery, based on dissimilarity matrices of vegetation structure, species diversity and composition is presented. The study area is a forested landscape mosaic after slash and burn agriculture (Ac: 8-23 years ago), selective logging (Fs: 43-53 years ago), and selective logging and forest fire (Fc: 21-28 years ago). The site is located in the central part of Quintana Roo, México, where three vegetation patches were delineated according to remotely sensed multiespectral imagery. Mean differences between vegetation structure properties of each vegetation patch were obtained through a permutational multivariate analysis of variance (P < 0.001). Species richness, stem density per hectare, and the axis-1 scores of the non-metric multidimensional scaling ordination of specific composition were identified as the vegetation attributes more relevant to differentiate the vegetation patches by a multinomial logistic model. Fc vegetation patch is characterized by the greatest mean values on Shannon-Wiener index, species richness, and stem density. The Fs has the greatest mean values of canopy height, basal area, and biomass at 80 percentile, and the Ac vegetation patch has the lowest values of all mentioned metrics. The species with the greatest relative importance value were: Ac: Bursera simaruba and Psidia psipula, Fs: Gymnanthes lucida and Manilkara zapota, Fc: G. lucida and B. simaruba. The uncertainty associated with the metrics assessed by vegetation patch was smaller than the uncertainty of the whole area, because of the efficient variability aggregation of the field data. We conclude that multiespectral information is a reliable tool for distinguishing vegetation patches with specific features, as stem density, specific composition, and species richness.

Using permutational and multivariate statistics to understand inorganic well water chemistry and the occurrence of methane in groundwater, southeastern New Brunswick, Canada.

Concerns over possible impacts from the rapid expansion of unconventional oil and natural gas (ONG) resource development prompted a regional domestic well sampling program focusing on the Carboniferous Maritimes Basin bedrock in southeastern New Brunswick, Canada. This work applies recent developments in robust multivariate statistical methods to overcome issues with highly non-Gaussian data and support the development of a conceptual model for the regional groundwater chemistry and the occurrence of methane. Principal component analysis reveals that the redox-sensitive species, DO, NO3, Fe, Mn, methane, As and U are the most important parameters that differentiate the samples. Permutation-based MANOVA and ANOVA testing revealed that geology was more important than geographic location and topography in influencing groundwater composition. The statistical inferences are supported by chemistry trends observed in relation to road de-icing salt and other saline sources. However, source differentiation between Carboniferous brines, entrapped post-glacial marine water and modern seawater cannot be made. Furthermore, Cl:Br ratios lower than those of seawater or regional brines suggest an origin related to the diagenesis of organic-rich sediment and that the groundwater may be influenced by local low permeability units. Combined spatial, statistical and chemical analysis shows that, while trace or low levels of methane, <1 mg/L, are found ubiquitously throughout the Maritimes Basin, elevated concentrations, >1 mg/L, are associated with the Horton Group, consistent with it being the host and inferred source of ONG resources in the province. The highest methane concentrations (14-29 mg/L) were detected in the region with a complex history of cycles of uplift and erosion which, in some locations, resulted in the juxtaposition at the surface of the Horton Group with several other groups of the Maritimes Basin. It is thought that proximity to the Horton Group can lead to naturally high methane concentrations in non-ONG-bearing units.

Desiccation events change the microbial response to gradients of wastewater effluent pollution.

While wastewater treatment plant (WWTP) effluents have become increasingly recognized as a stressor for receiving rivers, their effects on river microbial communities remain elusive. Moreover, global change is increasing the frequency and duration of desiccation events in river networks, and we ignore how desiccation might influence the response of microbial communities to WWTP effluents. In this study, we evaluated the interaction between desiccation events and WWTP effluents under different dilution capacities. Specifically, we used artificial streams in a replicated regressional design, exposing first a section of the streams to a 7-day desiccation period and then the full stream to different levels of a realistic WWTP effluent dilution, from 0% to 100% of WWTP effluent proportion of the total stream flow. The microbial community response was assessed by means of high-throughput sequencing of 16S rRNA gene amplicons and quantitative PCR targeting ecologically-relevant microbial groups. Threshold Indicator Taxa Analysis (TITAN) was used, together with model fitting, to determine community thresholds and potential indicator taxa. Results show significant interactions between WWTP effluents and desiccation, particularly when sediment type is considered. Indicator taxa included members of Proteobacteria, Actinobacteria and Cyanobacteria, with abrupt changes in community structure at WWTP effluent proportion of the total flow above 50%, which is related to nutrient levels ranging 4.6-5.2 mg N-NO3-L-1, 0.21-0.32 mg P-PO43-L-1 and 7.09-9.00 mg DOC L-1. Our work indicates that situations where WWTP effluents account for >50% of the total river flow might risk of dramatic microbial community structure changes and should be avoided.