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Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the cycling of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of relative abundance of soil fungi versus bacteria could drive striking differences in carbon decomposition and soil organic matter formation between different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial ecosystems has prevented the inclusion of relative abundance of soil fungi versus bacteria and the associated processes in global biogeochemical models. Here, we used a global-scale dataset of >3000 distinct observations of abundance of soil fungi versus bacteria in the surface topsoil (up to 15 cm) to generate the first quantitative and high-spatial-resolution (1 km 2) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high-latitude environments with large soil carbon stocks. There was a strong nonlinear response of fungal dominance to the environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi dominated in regions with low MAT and NPP and bacteria dominated in regions with high MAT and NPP, thus representing slow vs. fast soil energy channels, respectively, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios. Raw datasets and global maps generated in this study are available at 10.6084/m9.figshare.19556419 (Yu, 2022). [ABSTRACT FROM AUTHOR]

The article offers information about class of signaling components, the so-called G-protein coupled receptor (GPCR)-bigrams in eukaryotic microorganisms oomycetes. Topics discussed include ways in which plant pathogenic oomycetes like Phytophthora infestans causes enormous yield losses in crop plants; animal pathogenic oomycetes; and process of cellular signaling in oomycetes.

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large‐scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass‐loss rates and stabilization factors of plant‐derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy‐to‐degrade components accumulate during early‐stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass‐loss rates and stabilization, notably in colder locations. Using TBI improved mass‐loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early‐stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models. [ABSTRACT FROM AUTHOR]

The article explores the use of large language models (LLMs) in scientific research, highlighting their potential benefits and limitations. It provides examples of how LLMs can assist in various scientific tasks, such as summarizing documents and improving writing. However, it also acknowledges the need for fact-checking and the potential biases in training data. The authors emphasize the importance of adhering to ethical guidelines and journal policies when using LLMs. While LLMs can be valuable tools, caution should be exercised in their use. [Extracted from the article]

Over the past decade, the use of future climate projections from the coupled model intercomparison project (CMIP) has become central in biodiversity science. Pre‐packaged datasets containing future projections of the widely used bioclimatic variables, for different times and socio‐economic pathways, have contributed immensely to the study of climate change implications for biodiversity. However, these datasets lack the flexibility to obtain projections to other target years, and the use of raw data requires coding and spatial information systems expertise. The Python tool, 'chelsa‐cmip6', developed by Karger et al., provides the flexibility needed by allowing users to generate bioclimatic variables for the time of their choice provided the selected general circulation model and socioeconomic pathway combination exists. This is a fantastic step forward in bringing flexibility to the use of climate datasets in biodiversity and will allow for more widespread use of data provided by CMIP6. We hope it also will prompt the development of more user‐friendly tools for the study of the effects of climate change on biodiversity. [ABSTRACT FROM AUTHOR]

Combating climate change requires unified action across all sectors of society. However, this collective action is precluded by the ‘consensus gap’ between scientific knowledge and public opinion. Here, we test the extent to which the iconic cities around the world are likely to shift in response to climate change. By analyzing city pairs for 520 major cities of the world, we test if their climate in 2050 will resemble more closely to their own current climate conditions or to the current conditions of other cities in different bioclimatic regions. Even under an optimistic climate scenario (RCP 4.5), we found that 77% of future cities are very likely to experience a climate that is closer to that of another existing city than to its own current climate. In addition, 22% of cities will experience climate conditions that are not currently experienced by any existing major cities. As a general trend, we found that all the cities tend to shift towards the sub-tropics, with cities from the Northern hemisphere shifting to warmer conditions, on average ~1000 km south (velocity ~20 km.year-1), and cities from the tropics shifting to drier conditions. We notably predict that Madrid’s climate in 2050 will resemble Marrakech’s climate today, Stockholm will resemble Budapest, London to Barcelona, Moscow to Sofia, Seattle to San Francisco, Tokyo to Changsha. Our approach illustrates how complex climate data can be packaged to provide tangible information. The global assessment of city analogues can facilitate the understanding of climate change at a global level but also help land managers and city planners to visualize the climate futures of their respective cities, which can facilitate effective decision-making in response to on-going climate change. [ABSTRACT FROM AUTHOR]

Nodules harboring nitrogen-fixing rhizobia are a well-known trait of legumes, but nodules also occur in other plant lineages, with rhizobia or the actinomycete Frankia as microsymbiont. It is generally assumed that nodulation evolved independently multiple times. However, molecular-genetic support for this hypothesis is lacking, as the genetic changes underlying nodule evolution remain elusive. We conducted genetic and comparative genomics studies by using Parasponia species (Cannabaceae), the only nonlegumes that can establish nitrogen-fixing nodules with rhizobium. Intergeneric crosses between Parasponia andersonii and its nonnodulating relative Trema tomentosa demonstrated that nodule organogenesis, but not intracellular infection, is a dominant genetic trait. Comparative transcriptomics of P. andersonii and the legume Medicago truncatula revealed utilization of at least 290 orthologous symbiosis genes in nodules. Among these are key genes that, in legumes, are essential for nodulation, including NODULE INCEPTION (NIN) and RHIZOBIUM-DIRECTED POLAR GROWTH (RPG). Comparative analysis of genomes from three Parasponia species and related nonnodulating plant species show evidence of parallel loss in nonnodulating species of putative orthologs of NIN, RPG, and NOD FACTOR PERCEPTION. Parallel loss of these symbiosis genes indicates that these nonnodulating lineages lost the potential to nodulate. Taken together, our results challenge the view that nodulation evolved in parallel and raises the possibility that nodulation originated ~100 Mya in a common ancestor of all nodulating plant species, but was subsequently lost in many descendant lineages. This will have profound implications for translational approaches aimed at engineering nitrogen-fixing nodules in crop plants. [ABSTRACT FROM AUTHOR]

• Contents of soil bacterial and fungal biomass were quantified across Europe. • Land use and climate jointly control soil bacterial and fungal biomass. • Soil agricultural use buffers the impact of harsh climate conditions on bacteria. • Soil texture, organic carbon and nitrogen are predictors of soil microbial biomass. • Soil microbial biomass was not influenced by crop type in croplands. Elucidating contents and drivers of soil bacterial and fungal biomass in contrasting land uses and climates at European scale is useful to define appropriate policies for the conservation of the ecosystem services that soil microorganisms provide. Here, we aimed to (i) quantify and compare bacterial and fungal biomass in 513 European soils collected from three different land uses (forests, grasslands, and croplands) and climates (arid, temperate, and cold) through analysis of fatty acid methyl esters; (ii) model the factors controlling soil bacterial and fungal biomass; and (iii) investigating levels of bacterial and fungal biomass in cropland soils cultivated with three important crop types in Europe: cereals, oil-producing crops, and orchards. Bacterial biomass decreased with land use in the following order: grasslands > croplands > forests and was found to be the highest in temperate environments. Similar patterns were found for biomass of Gram-positive and Gram-negative bacteria and Actinobacteria. Soil fungal biomass was greater in forests than in croplands and grasslands and was favoured by colder environments. The fungi to bacteria ratio (F/B) decreased as follows: forests > croplands > grasslands, with soils in colder climates showing greater F/B ratios in croplands and forests. Soil texture, soil organic carbon, and nitrogen were shown to directly drive bacterial and fungal biomass. The biomass of the different microbial groups was not influenced by the crop type when only croplands were considered. Fungi appear to be more susceptible to agricultural soil use than bacteria. Moreover, agricultural use of soil seems to buffer the effect of harsh climatic conditions on soil bacterial biomass. The present study improves our understanding of the combined effects of land use and climate on soil bacterial and fungal biomass across Europe. [ABSTRACT FROM AUTHOR]