Phenotypic and Genotypic Characteristics of Members of the Genus Streptobacillus

The genus Streptobacillus (S.) remained monotypic for almost 90 years until two new species were recently described. The type species, S. moniliformis, is one of the two etiological agents of rat bite fever, an under-diagnosed, worldwide occurring zoonosis. In a polyphasic approach field isolates and reference strains of S. moniliformis, S. hongkongensis, S. felis as well as divergent isolates were characterized by comparison of molecular data (n = 29) and from the majority also by their physiological as well as proteomic properties (n = 22). Based on growth-independent physiological profiling using VITEK2-compact, API ZYM and the Micronaut system fastidious growth-related difficulties could be overcome and streptobacilli could definitively be typed despite generally few differences. While differing in their isolation sites and dates, S. moniliformis isolates were found to possess almost identical spectra in matrix-assisted laser desorption ionization-time of flight mass spectrometry and Fourier transform infrared spectroscopy. Spectroscopic methods facilitated differentiation of S. moniliformis, S. hongkongensis and S. felis as well as one divergent isolate. Sequencing of 16S rRNA gene as well as functional genes groEL, recA and gyrB revealed only little intraspecific variability, but generally proved suitable for interspecies discrimination between all three taxa and two groups of divergent isolates.Hessian Ministry for the Environment, Climate Change, Agriculture and Consumer Protection (HMUKLV)Hessian Ministry for the Environment, Climate Change, Agriculture and Consumer Protection (HMUKLV

3D-surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semi-supervised deep learning

Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nm range and strong contrast for membranous structures without requirement for labeling or chemical fixation. The short acquisition time and the relatively large volumes acquired allow for fast acquisition of large amounts of tomographic image data. Segmentation of these data into accessible features is a necessary step in gaining biologically relevant information from cryo-soft X-ray tomograms. However, manual image segmentation still requires several orders of magnitude more time than data acquisition. To address this challenge, we have here developed an end-to-end automated 3D-segmentation pipeline based on semi-supervised deep learning. Our approach is suitable for high-throughput analysis of large amounts of tomographic data, while being robust when faced with limited manual annotations and variations in the tomographic conditions. We validate our approach by extracting three-dimensional information on cellular ultrastructure and by quantifying nanoscopic morphological parameters of filopodia in mammalian cells

Variability in the carbon isotopic composition of foliage carbon pools (soluble carbohydrates, waxes) and respiration fluxes in southeastern U.S. pine forests

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): G02009, doi:10.1029/2011JG001867.We measured the δ13C of assimilated carbon (foliage organic matter (δCOM), soluble carbohydrates (δCSC), and waxes (δCW)) and respiratory carbon (foliage (δCFR), soil (δCSR) and ecosystem 13CO2 (δCER)) for two years at adjacent ecosystems in the southeastern U.S.: a regenerated 32 m tall mature Pinus palustris forest, and a mid-rotation 13 m tall Pinus elliottii stand. Carbon pools and foliage respiration in P. palustris were isotopically enriched by 2‰ relative to P. elliottii. Despite this enrichment, mean δCER values of the two sites were nearly identical. No temporal trends were apparent in δCSC, δCFR, δCSR and δCER. In contrast, δCOM and δCW at both sites declined by approximately 2‰ over the study. This appears to reflect the adjustment in the δ13C of carbon storage reserves used for biosynthesis as the trees recovered from a severe drought prior to our study. Unexpectedly, the rate of δ13C decrease in the secondary C32–36 n-alkanoic acid wax molecular cluster was twice that observed for δCOM and the predominant C22–26 compound cluster, and provides new evidence for parallel but separate wax chain elongation systems utilizing different carbon precursor pools in these species. δCFR and δCER were consistently enriched relative to assimilated carbon but, in contrast to previous studies, showed limited variations in response to changes in vapor pressure deficit (D). This limited variability in respiratory fluxes and δCSC may be due to the shallow water table as well as the deep taproots of pines, which limit fluctuations in photosynthetic discrimination arising from changes in D.This work was supported by a NSF grants DEB-0343604, DEB-0344562 and DEB-0552202, and DOE grant DE-FC02-06ER64156/06-SC-NICCR-1063.2012-10-1

Global transpiration data from sap flow measurements: The SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.This research was supported by the Minis-terio de Economía y Competitividad (grant no. CGL2014-55883-JIN), the Ministerio de Ciencia e Innovación (grant no. RTI2018-095297-J-I00), the Ministerio de Ciencia e Innovación (grant no. CAS16/00207), the Agència de Gestió d’Ajuts Universitaris i de Recerca (grant no. SGR1001), the Alexander von Humboldt-Stiftung (Humboldt Research Fellowship for Experienced Researchers (RP)), and the Institució Catalana de Recerca i Estudis Avançats (Academia Award (JMV)). Víctor Flo was supported by the doctoral fellowship FPU15/03939 (MECD, Spain)

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications