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Background Currently, much is unknown about the taxonomic diversity and the mechanisms of methane metabolism in the Florida Everglades ecosystem. The Loxahatchee National Wildlife Refuge is a section of the Florida Everglades that is almost entirely unstudied in regard to taxonomic profiling. This short report analyzes the metagenome of soil samples from this Refuge to investigate the predominant taxa, as well as the abundance of genes involved in environmentally significant metabolic pathways related to methane production (nitrogen fixation and dissimilatory sulfite reduction). Methods Shotgun metagenomic sequencing using the Illumina platform was performed on 17 soil samples from four different sites within the Loxahatchee National Wildlife Refuge, and underwent quality control, assembly, and annotation. The soil from each sample was tested for water content and concentrations of organic carbon and nitrogen. Results The three most common phyla of bacteria for every site were Actinobacteria, Acidobacteria, and Proteobacteria; however, there was variation in relative phylum composition. The most common phylum of Archaea was Euryarchaeota for all sites. Alpha and beta diversity analyses indicated significant congruity in taxonomic diversity in most samples from Sites 1, 3, and 4 and negligible congruity between Site 2 and the other sites. Shotgun metagenomic sequencing revealed the presence of biogeochemical biomarkers of particular interest (e.g., mrcA, nifH, and dsrB) within the samples. The normalized abundances of mcrA , nifH , and dsrB exhibited a positive correlation with nitrogen concentration and water content, and a negative correlation with organic carbon concentration. Conclusion This Everglades soil metagenomic study allowed examination of wetlands biological processes and showed expected correlations between measured organic constituents and prokaryotic gene frequency. Additionally, the taxonomic profile generated gives a basis for the diversity of prokaryotic microbial life throughout the Everglades.

Background: Currently, much is unknown about the taxonomic diversity and the mechanisms of methane metabolism in the Florida Everglades ecosystem. The Loxahatchee National Wildlife Refuge is a section of the Florida Everglades that is almost entirely unstudied in regard to taxonomic profiling. This short report analyzes the metagenome of soil samples from this Refuge to investigate the predominant taxa, as well as the abundance of genes involved in environmentally significant metabolic pathways related to methane production (nitrogen fixation and dissimilatory sulfite reduction). Methods: Shotgun metagenomic sequencing using the Illumina platform was performed on 17 soil samples from four different sites within the Loxahatchee National Wildlife Refuge, and underwent quality control, assembly, and annotation. The soil from each sample was tested for water content and concentrations of organic carbon and nitrogen. Results: The three most common phyla of bacteria for every site were Actinobacteria, Acidobacteria, and Proteobacteria; however, there was variation in relative phylum composition. The most common phylum of Archaea was Euryarchaeota for all sites. Alpha and beta diversity analyses indicated significant congruity in taxonomic diversity in most samples from Sites 1, 3, and 4 and negligible congruity between Site 2 and the other sites. Shotgun metagenomic sequencing revealed the presence of biogeochemical biomarkers of particular interest (e.g., mrcA, nifH, and dsrB) within the samples. The normalized abundances of mcrA, nifH, and dsrB exhibited a positive correlation with nitrogen concentration and water content, and a negative correlation with organic carbon concentration. Conclusion: This Everglades soil metagenomic study allowed examination of wetlands biological processes and showed expected correlations between measured organic constituents and prokaryotic gene frequency. Additionally, the taxonomic profile generated gives a basis for the diversity of prokaryotic microbial life throughout the Everglades.

Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.

Aim: The influence of soil properties on photosynthetic traits in higher plants is poorly quantified in comparison with that of climate. We address this situation by quantifying the unique and joint contributions to global leaf-trait variation from soils and climate. Location: Terrestrial ecosystems world-wide. Methods: Using a trait dataset comprising 1509 species from 288 sites, with climate and soil data derived from global datasets, we quantified the effects of 20 soil and 26 climate variables on light-saturated photosynthetic rate (Aarea) stomatal conductance (gs), leaf nitrogen and phosphorus (Narea and Parea) and specific leaf area (SLA) using mixed regression models and multivariate analyses. Results: Soil variables were stronger predictors of leaf traits than climatic variables, except for SLA. On average, Narea, Parea and Aarea increased and SLA decreased with increasing soil pH and with increasing site aridity. gs declined and Parea increased with soil available P (Pavail). Narea was unrelated to total soil N. Joint effects of soil and climate dominated over their unique effects on Narea and Parea, while unique effects of soils dominated for Aarea and gs. Path analysis indicated that variation in reflected the combined independent influences of Narea and gs, the former promoted by high pH and aridity and the latter by low Pavail. Main conclusions: Three environmental variables were key for explaining variation in leaf traits: soil pH and Pavail, and the climatic moisture index (the ratio of precipitation to potential evapotranspiration). Although the reliability of global soil datasets lags behind that of climate datasets, our results nonetheless provide compelling evidence that both can be jointly used in broad-scale analyses, and that effects uniquely attributable to soil properties are important determinants of leaf photosynthetic traits and rates. A significant future challenge is to better disentangle the covarying physiological, ecological and evolutionary mechanisms that underpin trait-environment relationships.

Primary biological aerosol particles (PBAP) encompass many particle types that are derived from several biological kingdoms. These aerosol particles can be composed of both whole living units such as pollen, bacteria, and fungi, as well as from mechanically formed particles, such as plant debris. They constitute a significant proportion of the overall atmospheric particle load and have been linked with adverse health issues and climatic effects on the environment. Traditional methods for their analysis have focused on the direct capture of PBAP before subsequent laboratory analysis. These analysis types have generally relied on direct optical microscopy or incubation on agar plates, followed by time-consuming microbiological investigation. In an effort to address some of these deficits, real-time fluorescence monitors have come to prominence in the analysis of PBAP. These instruments offer significant advantages over traditional methods, including the measurement of concentrations, as well as the potential to simultaneously identify individual analyte particles in real-time. Due to the automated nature of these measurements, large data sets can be collected and analyzed with relative ease. This review seeks to highlight and discuss the extensive literature pertaining to the most commonly used commercially available real-time fluorescence monitors (WIBS, UV-APS and BioScout). It discusses the instruments operating principles, their limitations and advantages, and the various environments in which they have been deployed. The review provides a detailed examination of the ambient fluorescent aerosol particle concentration profiles that are obtained by these studies, along with the various strategies adopted by researchers to analyze the substantial data sets the instruments generate. Finally, a brief reflection is presented on the role that future instrumentation may provide in revolutionizing this area of atmospheric research.

Plant species show considerable leaf trait variability that should be accounted for in dynamic global vegetation models (DGVMs). In particular, differences in the acclimation of leaf traits during periods more and less favourable to growth have rarely been examined. We conducted a field study of leaf trait variation at seven sites spanning a range of climates and latitudes across the Australian continent; 80 native plant species were included. We measured key traits associated with leaf structure, chemistry and metabolism during the favourable and unfavourable growing seasons. Leaf traits differed widely in the degree of seasonal variation displayed. Leaf mass per unit area (Ma) showed none. At the other extreme, seasonal variation accounted for nearly a third of total variability in dark respiration (Rdark). At the non‐tropical sites, carboxylation capacity (Vcmax) at the prevailing growth temperature was typically higher in summer than in winter. When Vcmax was normalized to a common reference temperature (25°C), however, the opposite pattern was observed for about 30% of the species. This suggests that metabolic acclimation is possible, but far from universal. Intraspecific variation—combining measurements of individual plants repeated at contrasting seasons, different leaves from the same individual, and multiple conspecific plants at a given site—dominated total variation for leaf metabolic traits Vcmax and Rdark. By contrast, site location was the major source of variation (53%) for Ma. Interspecific trait variation ranged from only 13% of total variation for Vcmax up to 43% for nitrogen content per unit leaf area. These findings do not support a common practice in DGVMs of assigning fixed leaf trait values to plant functional types. Trait‐based models should allow for interspecific differences, together with spatial and temporal plasticity in leaf structural, chemical and metabolic traits. A plain language summary is available for this article. Plain Language Summary

Elevated atmospheric CO₂ concentration (eCO₂) has the potential to increase vegetation carbon storage if increased net primary production causes increased long‐lived biomass. Model predictions of eCO₂ effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free‐air CO₂ enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO₂ effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO₂ effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

Abstract David Schindler and his colleagues pioneered studies in the 1970s on the role of phosphorus in stimulating cyanobacterial blooms in North American lakes. Our understanding of the nuances of phosphorus utilization by cyanobacteria has evolved since that time. We review the phosphorus utilization strategies used by cyanobacteria, such as use of organic forms, alternation between passive and active uptake, and luxury storage. While many aspects of physiological responses to phosphorus of cyanobacteria have been measured, our understanding of the critical processes that drive species diversity, adaptation and competition remains limited. We identify persistent critical knowledge gaps, particularly on the adaptation of cyanobacteria to low nutrient concentrations. We propose that traditional discipline-specific studies be adapted and expanded to encompass innovative new methodologies and take advantage of interdisciplinary opportunities among physiologists, molecular biologists, and modellers, to advance our understanding and prediction of toxic cyanobacteria, and ultimately to mitigate the occurrence of blooms. This review advocates for interdisciplinary research on cell physiology, molecular biology, and ecological modelling to improve predictions of cyanobacterial blooms in response to variability in phosphorus supply rates in situ.

Jeffrey Trent, David Huntsman and colleagues identify the SWI/SNF chromatin-remodeling gene SMARCA4 as commonly mutated in small cell carcinoma of the ovary, hypercalcemic type (SCCOHT). Their results implicate SMARCA4 as a crucial factor in the oncogenesis of SCCOHT, a rare but highly malignant cancer. Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 69% (9/13) of SCCOHT cases in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis.