Spatial patterns of bacteria show that members of higher taxa share ecological characteristics

Affiche, résuméWhether bacteria display spatial patterns of distribution and at which level of taxonomic organization such patterns can be observed are central questions in microbial ecology. Here we investigated how the total and relative abundances of eight bacterial taxa at the phylum or class level were spatially distributed in a pasture by using quantitative PCR and geostatistical modelling. The distributions of the relative abundance of most taxa varied by a factor of 2.520136.5 and displayed strong spatial patterns at the field scale. These spatial patterns were taxon-specific and correlated to soil properties, which indicates that members of a bacterial clade defined at high taxonomical levels shared specific ecological traits in the pasture. Ecologically meaningful assemblages of bacteria at the phylum or class level in the environment provides evidence that deep branching patterns of the 16S rRNA bacterial tree are actually mirrored in nature

Environmental Assessment of Soil for Monitoring: Volume IIb Survey of National Networks

The ENVASSO Project (Contract 022713) was funded 2006-8, under the European Commission 6th Framework Programme of Research, with the objective of defining and documenting a soil monitoring system appropriate for soil protection at continental level. The ENVASSO Consortium, comprising 37 partners drawn from 25 EU Member States, reviewed almost 300 soil indicators, identified existing soil inventories and monitoring programmes in the Member States, designed and programmed a database management system to capture, store and supply soil profile data, and drafted procedures and protocols appropriate for inclusion in a European soil monitoring network of sites that are geo-referenced and at which a qualified sampling process is or could be conducted. This volume (IIb), a Survey of National Networks, is the second of two reports that together constitute the most comprehensive study to date of the soil inventory and monitoring activities in the European Union. It contains comprehensive fact sheets for each national network, listing the purpose, sampling strategy adopted, analytical methods used and the number of monitoring sites.JRC.H.7-Climate Risk Managemen

Spatial patterns of bacteria show that members of higher taxa share ecological characteristics

Affiche, résuméWhether bacteria display spatial patterns of distribution and at which level of taxonomic organisation such patterns can be observed are central questions in microbial ecology. Here we investigated how the total and relative abundances of eight bacterial taxa at the phylum or class level were spatially distributed in a pasture by using quantitative PCR. Geostatistical modelling was used to analyse the spatial patterns of the taxa distributions. To test whether the spatial distributions of the different taxa were related to soil heterogeneity, we performed exploratory analyses of relationships between abundance of the bacterial taxa and key soil properties. The distributions of the relative abundance of most taxa varied by a factor of 2.5 to 6.5 and displayed strong spatial patterns at the field scale with autocorrelation ranging between 2 to 37 m. These spatial patterns were taxon-specific and correlated to soil properties, which indicates that members of a bacterial clade defined at high taxonomical levels shared specific ecological traits in the pasture. Overall, the present study showed spatial patterns of distribution of bacteria both at the meter scale and at high taxonomical levels of organisation. Such spatial patterns allow comprehensive observations and predictions of bacterial occurrence in nature, hence helping in the generation of hypotheses concerning the mechanisms generating and maintaining bacterial diversity. The taxa-specific spatial patterns observed here suggest that, in a given environment, ecological traits are shared at high taxonomic levels within the domain Bacteria. This is a piece of evidence that the 16S rRNA gene tree divisions are not only based on evolutionary theory, but also have an ecological reality

Future C loss in mid-latitude mineral soils: climate change exceeds land use mitigation potential in France

Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO2 emissions will be crucial to prevent further loss of carbon from our soils

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils

Satellite Imagery to Map Topsoil Organic Carbon Content over Cultivated Areas: An Overview

There is a need to update soil maps and monitor soil organic carbon (SOC) in the upper horizons or plough layer for enabling decision support and land management, while complying with several policies, especially those favoring soil carbon storage. This review paper is dedicated to the satellite-based spectral approaches for SOC assessment that have been achieved from several satellite sensors, study scales and geographical contexts in the past decade. Most approaches relying on pure spectral models have been carried out since 2019 and have dealt with temperate croplands in Europe, China and North America at the scale of small regions, of some hundreds of km(2): dry combustion and wet oxidation were the analytical determination methods used for 50% and 35% of the satellite-derived SOC studies, for which measured topsoil SOC contents mainly referred to mineral soils, typically cambisols and luvisols and to a lesser extent, regosols, leptosols, stagnosols and chernozems, with annual cropping systems with a SOC value of similar to 15 g.kg(-1) and a range of 30 g.kg(-1) in median. Most satellite-derived SOC spectral prediction models used limited preprocessing and were based on bare soil pixel retrieval after Normalized Difference Vegetation Index (NDVI) thresholding. About one third of these models used partial least squares regression (PLSR), while another third used random forest (RF), and the remaining included machine learning methods such as support vector machine (SVM). We did not find any studies either on deep learning methods or on all-performance evaluations and uncertainty analysis of spatial model predictions. Nevertheless, the literature examined here identifies satellite-based spectral information, especially derived under bare soil conditions, as an interesting approach that deserves further investigations. Future research includes considering the simultaneous analysis of imagery acquired at several dates i.e., temporal mosaicking, testing the influence of possible disturbing factors and mitigating their effects fusing mixed models incorporating non-spectral ancillary information

Environmental Assessment of Soil for Monitoring Volume I: Indicators & Criteria

The ENVASSO Project (Contract 022713) was funded 2006-8, under the European Commission 6th Framework Programme of Research, with the objective of defining and documenting a soil monitoring system appropriate for soil protection at continental level. The ENVASSO Consortium, comprising 37 partners drawn from 25 EU Member States, reviewed soil indicators, identified existing soil inventories and monitoring programmes in the Member States, designed and programmed a database management system to capture, store and supply soil profile data, and drafted procedures and protocols appropriate for inclusion in a European soil monitoring network of sites that are geo-referenced and at which a qualified sampling process is or could be conducted. Volume I, one of six describing the results of the ENVASSO Project, identifies 290 potential indicators relating to 188 key issues for the following nine threats to soil: erosion, organic matter decline, contamination, sealing, compaction, loss of biodiversity, salinisation, landslides and desertification. Sixty candidate indicators that address 27 key issues, covering all these threats, were selected on the basis of their thematic relevance, policy relevance and data availability. Baseline and threshold values are presented and detailed Fact Sheets describe three priority indicators for each soil threat.JRC.DDG.H.7-Land management and natural hazard