scholarly journals Indoor Microbiome: Quantification of Exposure and Association with Geographical Location, Meteorological Factors, and Land Use in France

2020 ◽  
Vol 8 (3) ◽  
pp. 341 ◽  
Author(s):  
Steffi Rocchi ◽  
Gabriel Reboux ◽  
Emeline Scherer ◽  
Audrey Laboissière ◽  
Cécile Zaros ◽  
...  
Keyword(s):  
Microbial Community ◽  
Spatial Scales ◽  
Geographical Location ◽  
Allergic Diseases ◽  
Spatial Description ◽  
Geographical Patterns ◽  
Cladosporium Sphaerospermum ◽  
Streptomyces Spp ◽  
Indoor Microbiome ◽  
Cryptococcus Spp

The indoor microbial community is a mixture of microorganisms resulting from outdoor ecosystems that seed the built environment. However, the biogeography of the indoor microbial community is still inadequately studied. Dust from more than 3000 dwellings across France was analyzed by qPCR using 17 targets: 10 molds, 3 bacteria groups, and 4 mites. Thus, the first spatial description of the main indoor microbial allergens on the French territory, in relation with biogeographical factors influencing the distribution of microorganisms, was realized in this study. Ten microorganisms out of 17 exhibited increasing abundance profiles across the country: Five microorganisms (Dermatophagoïdes pteronyssinus, Dermatophagoïdes spp., Streptomyces spp., Cladosporium sphaerospermum, Epicoccum nigrum) from northeast to southwest, two (Cryptococcus spp., Alternaria alternata) from northwest to southeast, Mycobacteria from east to west, Aspergillus fumigatus from south to north, and Penicillium chrysogenum from south to northeast. These geographical patterns were partly linked to climate and land cover. Multivariate analysis showed that composition of communities seemed to depend on landscapes, with species related to closed and rather cold and humid landscapes (forests, located in the northeast) and others to more open, hot, and dry landscapes (herbaceous and coastal regions, located in the west). This study highlights the importance of geographical location and outdoor factors that shape communities. In order to study the effect of microorganisms on human health (allergic diseases in particular), it is important to identify biogeographic factors that structure microbial communities on large spatial scales and to quantify the exposure with quantitative tools, such as the multi-qPCR approach.

scholarly journals Wavelet-based spatial comparison technique for analysing and evaluating two-dimensional geophysical model fields

2012 ◽  
Vol 5 (1) ◽  
pp. 223-230 ◽  
Author(s):  
S. Saux Picart ◽  
M. Butenschön ◽  
J. D. Shutler
Keyword(s):  
Satellite Data ◽  
Fishery Management ◽  
Numerical Models ◽  
Spatial Scales ◽  
Marine Ecosystem ◽  
Original Method ◽  
Precipitation Forecast ◽  
Spatial And Temporal Scales ◽  
Geographical Patterns ◽  
Marine Ecosystem Model

Abstract. Complex numerical models of the Earth's environment, based around 3-D or 4-D time and space domains are routinely used for applications including climate predictions, weather forecasts, fishery management and environmental impact assessments. Quantitatively assessing the ability of these models to accurately reproduce geographical patterns at a range of spatial and temporal scales has always been a difficult problem to address. However, this is crucial if we are to rely on these models for decision making. Satellite data are potentially the only observational dataset able to cover the large spatial domains analysed by many types of geophysical models. Consequently optical wavelength satellite data is beginning to be used to evaluate model hindcast fields of terrestrial and marine environments. However, these satellite data invariably contain regions of occluded or missing data due to clouds, further complicating or impacting on any comparisons with the model. This work builds on a published methodology, that evaluates precipitation forecast using radar observations based on predefined absolute thresholds. It allows model skill to be evaluated at a range of spatial scales and rain intensities. Here we extend the original method to allow its generic application to a range of continuous and discontinuous geophysical data fields, and therefore allowing its use with optical satellite data. This is achieved through two major improvements to the original method: (i) all thresholds are determined based on the statistical distribution of the input data, so no a priori knowledge about the model fields being analysed is required and (ii) occluded data can be analysed without impacting on the metric results. The method can be used to assess a model's ability to simulate geographical patterns over a range of spatial scales. We illustrate how the method provides a compact and concise way of visualising the degree of agreement between spatial features in two datasets. The application of the new method, its handling of bias and occlusion and the advantages of the novel method are demonstrated through the analysis of model fields from a marine ecosystem model.

scholarly journals Consistent predictors of microbial community composition across scales in grasslands reveal low context-dependency

2021 ◽  
Author(s):  
Dajana Radujković ◽  
Sara Vicca ◽  
Margaretha van Rooyen ◽  
Peter Wilfahrt ◽  
Leslie Brown ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Spatial Scales ◽  
Regional Scale ◽  
Microbial Community Composition ◽  
Soil Microbial Communities ◽  
Plant Productivity ◽  
Context Dependency ◽  
Fungal Community Composition ◽  
Soil Microbial

Environmental circumstances shaping soil microbial communities have been studied extensively, but due to disparate study designs it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 sampled across regional plant productivity gradients) to examine i) if the same abiotic or biotic factors predict both large- and regional-scale patterns in bacterial and fungal community composition, and ii) if microbial community composition differs consistently with regional plant productivity (low vs high) across different sites. We found that there is high congruence between predictors of microbial community composition across spatial scales; bacteria were predominantly associated with soil properties and fungi with plant community composition. Moreover, there was a microbial community signal that clearly distinguished high and low productivity soils that was shared across worldwide distributed grasslands suggesting that microbial assemblages vary predictably depending on grassland productivity.

Spatio-temporal Patterns of the Precipitation Response to Aerosol Perturbations from an Energetic Perspective

2020 ◽  
Author(s):  
Shipeng Zhang ◽  
Philip Stier ◽  
Duncan Watson-Parris ◽  
Guy Dagan
Keyword(s):  
Energy Transport ◽  
Spatial Scales ◽  
Heat Fluxes ◽  
Radiative Cooling ◽  
Regional Patterns ◽  
Geographical Patterns ◽  
Clear Sky ◽  
Spatio Temporal ◽  
Absorbing Aerosols ◽  
Global Mean

<p>Absorbing and non-absorbing aerosols have distinct effects on both global-mean and regional precipitation. Local changes of precipitation in response to aerosol perturbations are more complex than global-mean changes, which are strongly constrained by global energy budget. This work examines the changes of atmospheric energetic budget terms to study effects of large perturbations in black carbon (BC) and sulphate (SUL) on precipitation. Both cases show decrease of global-mean precipitation but with different geographical patterns. Decreased atmospheric radiative cooling contributes to the majority of decreased global-mean precipitation. It is caused by increased aerosols absorption in BC case but decreased cooling from clean-clear sky (without clouds and aerosols) in SUL case. Fast responses, which are independent of changes in sea surface temperature (SST), dominate the precipitation changes in the BC case, not only for global mean but also for regional patterns. Slow responses, which are mediated by changes in SST, dominate the precipitation responses in SUL case, both globally and regionally.</p><p> </p><p>Relationships between temporal responses of local precipitation and diabatic cooling and precipitation are also examined for both BC and SUL perturbations. Both cases show remarkable similar pattern of correlations despite of essentially different patterns of changes in precipitation and diabatic cooling. Strong positive correlations are found over mid-latitude land and this is mainly due to the changes from surface sensible heat fluxes. Negative correlations are found over tropical oceans, mainly contributed by (longwave) radiative cooling from clouds and clean-clear sky. Further analysis shows this similarity is caused by the natural variability which is independent from external forcing. It indicates that the temporal relationship between changes in local precipitation and diabatic cooling is forcer-independent. This correlation is examined as a function of increasing spatial scales, which demonstrates the scale at which the dominating energetic term on regional precipitation shifts from energy transport to atmospheric diabatic cooling.</p>

scholarly journals Defining marine microbial biomes from environmental and dispersal filtered metapopulations

2017 ◽  
Author(s):  
Markus V. Lindh
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Microbial Community Structure ◽  
Spatial Scales ◽  
Dispersal Limitation ◽  
Global Ocean ◽  
Microbial Populations ◽  
Microbial Biogeography ◽  
Metapopulation Theory ◽  
Mock Communities

SummaryEnergy and matter fluxes essential for all life1 are modulated by spatial and temporal shifts in microbial community structure resulting from environmental and dispersal filtering2,3, emphasizing the continued need to characterize microbial biogeography4,5. Yet, application of metapopulation theory, traditionally used in general ecology for understanding shifts in biogeographical patterns among macroorganisms, has not been tested extensively for defining marine microbial populations filtered by environmental conditions and dispersal limitation at global ocean scales. Here we show, from applying metapopulation theory on two major global ocean datasets6,7, that microbial populations exhibit core- and satellite distributions with cosmopolitan compared to geographically restricted distributions of populations. We found significant bimodal occupancy-frequency patterns (the different number of species occupying different number of patches) at varying spatial scales, where shifts from bimodal to unimodal patterns indicated environmental and dispersal filtering. Such bimodal occupancy-frequency patterns were validated in Longhurst’s classical biogeographical framework and in silico where observed bimodal patterns often aligned with specific biomes and provinces described by Longhurst and where found to be non-random in randomized datasets and mock communities. Taken together, our results show that application of metapopulation theory provides a framework for determining distinct microbial biomes maintained by environmental and dispersal filtering.

Fine-scale diversity patterns in belowground microbial communities are consistent across kingdoms

2019 ◽  
Vol 95 (6) ◽  
Author(s):  
Anders Bjørnsgaard Aas ◽  
Carrie J Andrew ◽  
Rakel Blaalid ◽  
Unni Vik ◽  
Håvard Kauserud ◽  
...  
Keyword(s):  
Microbial Community ◽  
Spatial Structure ◽  
Community Assembly ◽  
High Throughput Sequencing ◽  
Spatial Scales ◽  
Microbial Community Composition ◽  
Diversity Patterns ◽  
Bistorta Vivipara ◽  
Adjacent Soil ◽  
Bacteria And Fungi

ABSTRACT The belowground environment is heterogeneous and complex at fine spatial scales. Physical structures, biotic components and abiotic conditions create a patchwork mosaic of potential niches for microbes. Questions remain about mechanisms and patterns of community assembly belowground, including: Do fungal and bacterial communities assemble differently? How do microbes reach the roots of host plants? Within a 4 m2 plot in alpine vegetation, high throughput sequencing of the 16S (bacteria) and ITS1 (fungal) ribosomal RNA genes was used to characterise microbial community composition in roots and adjacent soil of a viviparous host plant (Bistorta vivipara). At fine spatial scales, beta-diversity patterns in belowground bacterial and fungal communities were consistent, although compositional change was greater in bacteria than fungi. Spatial structure and distance-decay relationships were also similar for bacteria and fungi, with significant spatial structure detected at <50 cm among root- but not soil-associated microbes. Recruitment of root microbes from the soil community appeared limited at this sampling and sequencing depth. Possible explanations for this include recruitment from low-abundance populations of soil microbes, active recruitment from neighbouring plants and/or vertical transmission of symbionts to new clones, suggesting varied methods of microbial community assembly for viviparous plants. Our results suggest that even at relatively small spatial scales, deterministic processes play a significant role in belowground microbial community structure and assembly.

Extraordinary variation in a simple song: No geographical patterns in initial phrase variation of the Yellowhammer, a passerine with pronounced dialects

The Auk ◽  
2019 ◽  
Vol 136 (4) ◽  
Author(s):  
Sharina J van Boheemen ◽  
Lucie Diblíková ◽  
Jana Bílková ◽  
Adam Petrusek ◽  
Tereza Petrusková
Keyword(s):  
Spatial Scales ◽  
Song Learning ◽  
Reproductive Barriers ◽  
Central European Country ◽  
Model Species ◽  
Central European ◽  
Geographical Patterns ◽  
Emberiza Citrinella ◽  
Behavioral Studies ◽  
Song Acquisition

Abstract Geographical variation of birdsong is used to study various topics from cultural evolution to mechanisms responsible for reproductive barriers or song acquisition. In species with pronounced dialects, however, patterns of variation in non-dialect parts of the song are usually overlooked. We focused on the individually variable initial phrase of the song of the Yellowhammer (Emberiza citrinella), a common Palearctic passerine which became a model species for dialect research. We used a quantitative method to compare the similarity of initial phrases from the repertoires of 237 males recorded at different spatial scales in a central European country covering all main dialect types. We hypothesized that patterns of initial phrase sharing and/or phrase similarity are affected by dialect boundaries and geographical proximity (i.e. that birds from the same dialect regions use more similar phrases or share them more often). Contrary to our expectations, initial phrase variation seems unrelated to dialects, as we did not find higher similarity either among recordings from the same dialect areas or among those from the same locality. Interestingly, despite the immense variability of phrase types detected (only 16% of 368 detected initial phrase types were shared between at least 2 males), a relatively high proportion of males (45%) was involved in sharing, and males using the same initial phrase were located anywhere from tens of meters to hundreds of kilometers apart. The patterns of variation suggest that precise copying during song learning as well as improvisation play important roles in forming individual repertoires in the Yellowhammer. Our data also confirm previous indications that the repertoires of Yellowhammer males (i.e. the composition of initial phrases) are individually unique and temporally stable. This makes the species a good candidate for individual acoustic monitoring, useful for detailed population or behavioral studies without the need for physical capture and marking of males.

scholarly journals Identifying the core bacterial and fungal communities within four agricultural biobeds used for the treatment of pesticide rinsates

2018 ◽  
Author(s):  
Jordyn Bergsveinson ◽  
Benjamin J. Perry ◽  
Claudia Sheedy ◽  
Larry Braul ◽  
Sharon Reedyk ◽  
...  
Keyword(s):  
Microbial Community ◽  
Bacterial Diversity ◽  
Fungal Diversity ◽  
Microbial Community Composition ◽  
Geographical Location ◽  
Fungal Communities ◽  
List Type ◽  
Pesticide Application ◽  
Similar Treatment ◽  
Taxonomic Groups

AbstractBacterial and fungal communities of four pesticide rinsate treatment biobeds constructed in Alberta and Saskatchewan, Canada were profiled via high throughput DNA sequencing to assess the effect of biobed depth and pesticide application on microbial community composition. Biobeds differed in geographical location and biobed design, and composition of pesticide rinsates (including herbicides, fungicides, and insecticides). All biobeds achieved similar treatment efficacy and supported greater bacterial diversity relative to fungal diversity, yet selected for similar abundant bacterial orders of Actinomycetales, Acidobacteria, Rhizobiales, and Sphingobacteriales and fungal taxonomic groups of Dothideomycetes, Eurotiales, Hypocreales, and Sordariales. Biobeds differed in the presence of unique and differentiated genera and operational taxonomic units. Biobed depth did not uniformly impact the diversity and/or the microbial community structure. Overall, pesticide application increased bacterial diversity, but had limited effect on the more variable fungal diversity, therefore suggesting broader implication for the effect of applied fungicides on biobed fungal communities.HighlightsBiobeds support diverse bacterial and fungal communitiesSpecific “core” bacterial and fungal taxa are abundant in biobeds of different design and treatmentMicrobial diversity is not directly linked with pesticide type or diversity.

scholarly journals How sample heterogeneity can obscure the signal of microbial interactions

2019 ◽  
Author(s):  
David W. Armitage ◽  
Stuart E. Jones
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Species Interactions ◽  
Dynamic Models ◽  
Spatial Scales ◽  
Microbial Interactions ◽  
Vital Rates ◽  
Ecological Processes ◽  
Correlation Networks ◽  
Community Data

ABSTRACTMicrobial community data are commonly subjected to computational tools such as correlation networks, null models, and dynamic models, with the goal of identifying the ecological processes structuring microbial communities. Researchers applying these methods assume that the signs and magnitudes of species interactions and vital rates can be reliably parsed from observational data on species’ (relative) abundances. However, we contend that this assumption is violated when sample units contain any underlying spatial structure. Here, we show how three phenomena — Simpson’s paradox, context-dependence, and nonlinear averaging — can lead to erroneous conclusions about population parameters and species interactions when samples contain heterogeneous mixtures of populations or communities. At the root of this issue is the fundamental mismatch between the spatial scales of species interactions (micrometres) and those of typical microbial community samples (millimetres to centimetres). These issues can be overcome by measuring and accounting for spatial heterogeneity at very small scales, which will lead to more reliable inference of the ecological mechanisms structuring natural microbial communities.

scholarly journals Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

2021 ◽  
Vol 12 ◽  
Author(s):  
Lauren M. Lui ◽  
Erica L.-W. Majumder ◽  
Heidi J. Smith ◽  
Hans K. Carlson ◽  
Frederick von Netzer ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Microbial Ecology ◽  
High Throughput Sequencing ◽  
Spatial Scales ◽  
Data Types ◽  
Modeling Framework ◽  
Rapid Acquisition ◽  
Mechanistic Understanding ◽  
And Function

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

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