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188 results for “Microbial diversity”
Fig. 5 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 5 | Biological and life history drivers of mucosal microbiota in diverse sampling of marine fish from Southern California. a Multivariate analysis of biological and life history parameters evaluated using unweighted and weighted normalized UniFrac distances. Statistical significance (PERMANOVA p = 0.001) indicated by yellow blocks (left) and effect size (right). All samples compared together (all) along with individual sample types (gill, skin, midgut, hindgut). b Impact of trophic level on similarity between midgut and hindgut (within a species) (linear model:p p value, mslope,dottedlinesare 95% confidence interval). F-Stat test statistic used in PERMANOVA analysis, all row names in a are metadata column names used in the analysis, MG midgut, HG hindgut, Gen. Weighted UniFrac generalized weighted UniFrac.
Fig. 6 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 6 | Evidence forphylosymbiosis across fishbody sites. Effectof evolutionary distance (low divergence time indicates a short branch length or similar fish species) of all fish compared to a skin unweighted UniFrac distance, b gill generalized weighted UniFrac distance, c hindgut generalized weighted UniFrac distance. Comparisons performed using Mantel test with multiple testing by FDR. Divergence time between fish species calculated using timetree.org. Gen. Weighted UniFrac generalized weighted UniFrac.
Fig. 3 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 3 | Alpha diversity and biomass comparisons across ecological and biolo- gical gradients in marine fish. Comparison of microbial diversity a "Chao1", b "Faith's Phylogenetic Diversity", c "Shannon", or d microbial biomassacrossbody site (gill, skin, midgut, and hindgut). Distributions in "red" are median with inter- quartile range. Statistical differences determined using non-parametric testing Kruskal–Wallistest with 0.05 FDR Benjamini–Hochberg. Further testing computed for each unique body site for a variety of biological and ecological metadata categories. Metadata whichis e categorical istestedusing Kruskal–Wallis f whereas numeric metadata tested using Spearmancorrelation. Onlysignificant associations are represented in e (Kruskal–Wallis p <0.05) and f (Spearman p <0.05). KW or KW stat "H" test statistic from Kruskal–Wallis test, MG midgut, HG hindgut, Faith PD Faith's Phylogenetic Diversity metric, GI:TL gastrointestinal length to fish total length "ratio", TL total length of fish.
Fig. 4 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 4 | Associations between fishmass and collection location as measuredby and d distance from shore with gill microbial biomass. e Comparison of fish mass distancefrom shorewith fishgill microbialbiomassand alphadiversity. Subset and f distancefromshorewithalpha diversitymetrics (Chao1).g Comparison of fish of fish from EPO and Atlantic (n = 54) collected from ocean (excludes bay and mass and h distance from shore with alpha diversity metric: Faith's PD. estuary samples) and from the neritic zone (<200 m depth). a Correlation matrix c–h (Confidenceintervalsof 95% aredisplayedasdotted lines). habita- between sample metadata where values are rho and significance indicated by t_act_collection refers to the metadata column name from where this habitat clas- *p <0.05, **p <0.01, ***p <0.001, ****p <0.0001 (Spearmancorrelation). sification can be found…, SZsurf zone, RIT rocky intertidal, RST rocky subtidal, IS b Comparison of gill microbial biomass (log cells per gram) across habitat types inner shelf, KBRF kelp bed rocky reef, MDRF mid depth rocky reef, CP coastal from which the fish were collected. Distribution is in median and interquartile pelagic, P pelagic. Mass_g_log = log 10 (mass of the fish in grams), dis- range. Statistical differences determined using non-parametric testing tance_from_shore_m_log = log 10 (distance from nearest point on shore in meters Kruskal–Wallistest with 0.05 FDRBenjamini–Hochberg. c Comparison of fish mass from where the fish was caught).
Fig. 2 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 2 | Limit of detection, sample exclusion, and microbial biomassestimation for FMP101 dataset. a Application of KatharoSeq formula to calculate limit of detection of microbiota platesusing the Bacillus/Paracoccus mock community (1150 reads at 90%). b Limit of detection based on cell counts of Bacillus/ Paracoccus mock community (~16 cells into extraction at 90%). c Model fit of the log(sequencing read counts) of positive extraction controls vs. the log cell counts of those positive extraction controls (empirically determined using plate counts. The linear regression of the line is indicative of the quality of method to estimate microbial biomass from sequencing read counts. Con- fidenceintervalsof 95% aredisplayedas dottedlines. Thismethodissimilar to a qPCR curvewherethe log (Ct) would beequivalent to the log(read counts).This equation is then used to estimate the number of "microbial density" of the existing samples which is then further normalized by the volume of the DNA extraction,biomass of materialgoinginto theextraction and finallynormalized to at estimated microbial cells per gram of tissue. d Community analysis comparison and validation of compositionality of controls of twosets of mock community controls (section 1 = Bacillus/Paracoccus mock community; section 2 = zymo mock community). Putative contaminant g__Geobacillus identified (presentin 93% of negatives and higherrelative abundance ascompared to positives and samples). e Number of samples successful across the four body sites collected from the broad fish microbiota dataset. QC quality control, g__ refers to a genus of bacteria, HM mock homemade mock or human made mixture of bacteria to use as a control whereas zymo mock = mock microbial community created by a company "Zymo".
Fig. 1 in Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species
Fig. 1 | Samplingdesignof 116 speciesof marine fish. a Using ArcGIS todepictthe general area from which fish were sampled: black dots indicate the locations of the 101 unique species of marine fish sampled from the California Current Ecosystem in the Eastern Pacific Ocean primarily in the waters of San Diego CA. Red circles depict the locations of an additional 17 species of fish (15 unique species with 2 species duplicates) collected from the Western Atlantic primarily in the waters of New York. When multiple species of fish were caught in the same location, a single circle is used to indicate the location. b Fish were sampled across a gradient of depth and distances from shore. c Biometric measurements taken for nearly all fish include total length, fork length, mass, gape, and GI length. Various ratios from these lengths were also calculated. Microbiota samples from the gill were primarily whole tissue specimens from the entire left second gill arch or a section of the top middle and bottom of the entire filament. Skin mucus samples were taken by scraping using a razor blade. Midgut digesta material was collected from directly posterior of the stomach or if stomach was absent, the beginning of the GI tract. Hindgut digesta samples were taken from near the anus. Image from phylopic. MG midgut, HG hindgut, GI gastrointestinal tract, m meters.
Disentangling relationships between physiology, morphology, diet, and gut microbial diversity in American Kestrel nestlings
<p>Gut microbiota are increasingly recognized as important drivers of host health and fitness across vertebrate taxa. Given that gut microbial composition is directly influenced by the environment, gut microbiota may also serve as an eco-physiological mechanism connecting host ecology, such as diet, and physiology. Although gut microbiota have been well-studied in mammalian systems, little is known about how gut microbial diversity and composition impact morphological and physiological development in wild birds. Here, we characterized both diet and gut microbial diversity of free-living American kestrel (<em>Falco sparverius</em>) nestlings throughout development to test whether gut microbial diversity predicts host morphological and physiological traits in either contemporary or time-lagged manners. Gut microbial alpha diversity on day 21 of nestling development was positively correlated with diet alpha diversity representative of the majority of nestling development (days 5–20). Gut microbial alpha diversity early in development was negatively correlated with body mass in both contemporary and time-lagged manners. Gut microbial alpha diversity early in development was positively correlated with blood glucose later in development. As nestlings experience rapid growth demands in preparation to fledge, these time-lagged associations may indicate that gut microbial diversity at early critical developmental windows may determine the future trajectory of morphological and physiological traits underlying metabolism that ultimately impact fitness.</p>
Disentangling relationships between physiology, morphology, diet, and gut microbial diversity in American Kestrel nestlings
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Leaf-shelters facilitate the colonization of arthropods and enhance microbial diversity on plants
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Native plant diversity generates microbial legacies that either promote or suppress non-natives, depending on drought history
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Plant invasion has limited impact on soil microbial alpha-diversity : a meta-analysis
<p>Plant invasion has proved to be a significant driver of ecosystem change, and with increased probability of invasion due to globalization, agricultural practices and other anthropogenic causes, it is crucial to understand its impact across multiple trophic levels. With the strong linkages between above and belowground processes, the response of soil microorganisms to plant invasion is the next logical step in developing our conceptual understanding of this complex system. In our study, we utilized a meta-analytical approach to better understand the impacts of plant invasion on soil microbial diversity. We synthesized 70 independent studies with 23 unique invaders across multiple ecosystem types to search for generalizable trends in soil microbial a-diversity following invasion. When possible, soil nutrient metrics were also collected in an attempt to understand the contribution of nutrient status shifts on microbial a-diversity. Our results show plant invasion to have highly heterogenous and limited impacts on microbial a-diversity. When taken together, our study indicates soil microbial a-diversity to remain constant following invasion, contrary to the aboveground counter parts. As our results suggest a decoupling in patterns of below and aboveground diversity, future work is needed to examine the drivers of microbial diversity patterns following invasion.</p>
Data from: Diverse communities of bacteria and archaea flourished in Palaeoarchaean (3.5-3.3 Ga) microbial mats
<p><span><span><span><span><span><span><span><span><span><span><span>Limited taxonomic classification is possible for Archaean microbial mats and this is a fundamental limitation in constraining early ecosystems. Applying Fourier Transform Infrared spectroscopy (FTIR), a powerful tool for identifying vibrational motions attributable to specific functional groups, we characterised fossilised biopolymers in 3.5-3.3 Ga microbial mats from the Barberton greenstone belt (South Africa). Microbial mats from four Palaeoarchaean horizons exhibit significant differences in taxonomically informative aliphatic contents, despite high aromaticity. This reflects precursor biological heterogeneity since all horizons show equally exceptional preservation and underwent similar grades of metamorphism. Low methylene to end-methyl (CH<sub>2</sub>/CH<sub>3</sub>) absorbance ratios in mats from the 3.472 Ga Middle Marker horizon signify short, highly branched <i>n</i>-alkanes interpreted as isoprenoid chains forming archaeal membranes. Mats from the 3.45 Ga Hooggenoeg Chert H5c, 3.334 Ga Footbridge Chert, and 3.33 Ga Josefsdal Chert exhibit higher CH<sub>2</sub>/CH<sub>3</sub>ratios suggesting longer, unbranched fatty acids from bacterial lipid precursors. Absorbance ratios of end-methyl to methylene (CH<sub>3</sub>/CH<sub>2</sub>) in Hooggenoeg, Josefsdal and Footbridge mats yield a range of values (0.20-0.80) suggesting mixed bacterial and archaeal architect communities based on comparison with modern examples. Higher (0.78-1.25) CH<sub>3</sub>/CH<sub>2</sub> ratios in the Middle Marker mats identify Archaea. This exceptional preservation reflects early, rapid silicification preventing the alteration of biogeochemical signals inherited from biomass. Since silicification commenced during the lifetime of the microbial mat, FTIR signals estimate the affinities of the architect community and may be used in the reconstruction of Archaean ecosystems. Together, these results show that Bacteria and Archaea flourished together in Earth's earliest ecosystems.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Functional diversity enhances, but exploitative traits reduce tree mixture effects on microbial biomass
1. Soil microorganisms play key roles in terrestrial biodiversity and ecosystem functions. Despite recent progress in elucidating the association between plant diversity and soil microorganisms, it remains unclear whether the functional properties of plant mixtures might alter this association. 2. We examined whether the effects of tree species mixtures on soil microbial biomass were impacted by the functional diversity (FD) and community-weighted-mean (CWM) of tree mixtures, by conducting a global meta-analysis involving 123 paired observations of tree mixtures and the corresponding monocultures from 38 studies in forests. 3. We found that the tree mixture effect on microbial biomass increased with the FD of specific leaf area (SLA), leaf N and P content, as well as the FD based on all of these traits plus leaf dry matter content. Meanwhile, the responses of microbial biomass to tree mixtures decreased with the CWM of SLA, leaf N, and P content. The effects of FD and CWM remained consistent, despite variable tree species richness, stand age and climatic factors. 4. Our results provide a new insight that the functional properties of plants may alter the magnitude of the association between plant diversity and soil microorganisms.
Environmental and biotic drivers of soil microbial β‐diversity across spatial and phylogenetic scales
<p>Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β-diversity) along ecological gradients. Here, we characterize soil microbial β-diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β-diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β-diversities with respect to plant β-diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β-diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β-diversities were mostly related to plant β-diversity, while bacterial β-diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β-diversities with plant β-diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β-diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early-evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today's microbial community structure.</p>
Soil microbial dataset, crop diversity experiment
<p>This is the dataset of the corresponding study : https://www.biorxiv.org/content/10.1101/2020.11.27.401224v1</p> <p> </p>
Data from: Do temperate tree species diversity and identity influence soil microbial community function and composition?
Studies of biodiversity-ecosystem function in treed ecosystems have generally focused on aboveground functions. The present study investigates inter-trophic links between tree diversity and soil microbial community function and composition.We examined how microbial communities in surface mineral soil responded to experimental gradients of tree species richness (SR), functional diversity (FD), community-weighted mean trait value (CWM) and tree identity. The site was a 4-yr-old common garden experiment near Montreal, Canada, consisting of deciduous and evergreen tree species mixtures. Microbial community composition, community-level physiological profiles (CLPP) and respiration were evaluated using phospholipid fatty acid (PLFA) analysis and the MicroRespTM system, respectively. The relationship between tree species richness and glucose induced respiration (GIR), basal respiration (BR), metabolic quotient (qCO2) followed a positive but saturating shape. Microbial communities associated with species mixtures were more active (basal respiration (BR)), with higher biomass (glucose induced respiration (GIR)), and used a greater number of carbon sources than monocultures. Communities associated with deciduous tree species used a greater number of carbon sources than those associated with evergreen species, suggesting a greater soil carbon storage capacity. There were no differences in microbial composition (PLFA) between monocultures and SR mixtures. The FD and the CWM of several functional traits affected both BR and GIR. In general, the CWM of traits had stronger effects than did FD, suggesting that certain traits of dominant species have more effect on ecosystem processes than does FD. Both the functions of GIR and BR were positively related to aboveground tree community productivity. Both tree diversity (SR) and identity (species and functional identity – leaf habit) affected soil microbial community respiration, biomass and composition. For the first time, we identified functional traits related to life history strategy, as well as root traits that influence another trophic level, soil microbial community function, via effects on BR and GIR.
Data from: Exceptional but vulnerable microbial diversity in coral reef animal surface microbiomes
<p>Coral reefs host hundreds of thousands of animal species that are increasingly threatened by anthropogenic disturbances. These animals host microbial communities at their surface, playing crucial roles for their fitness. However the diversity of such microbiomes is mostly described in a few coral species, and still poorly defined in other invertebrates and vertebrates. Given the diversity of animal microbiomes, and the diversity of host species inhabiting coral reefs, the contribution of such microbiomes to the total microbial diversity of coral reefs could be important, yet potentially vulnerable to the loss of animal species.</p> <p>Analysis of the surface microbiome from 74 taxa, including teleost fishes, hard and soft corals, crustaceans, echinoderms, bivalves and sponges, revealed that more than 90% of their prokaryotic phylogenetic diversity was specific and not recovered in surrounding plankton.</p> <p>Estimate of the total diversity associated to coral reef animal surface microbiomes reached up to 2.5% of current estimates of Earth prokaryotic diversity. Therefore, coral reef animal surfaces should be recognized as a hotspot of marine microbial diversity. Loss of the most vulnerable reef animals expected under present-day scenarios of reef degradation would induce an erosion of 28% of the prokaryotic richness, with unknown consequences on coral reef ecosystem functioning.</p>
The effects of temperature and dispersal on species diversity in natural microbial metacommunities
<p>Dispersal is key for maintaining biodiversity at local- and regional scales in metacommunities. However, little is known about the combined effects of dispersal and climate change on biodiversity. Theory predicts that alpha-diversity is maximized at intermediate dispersal rates, resulting in a hump-shaped diversity-dispersal relationship. This relationship is predicted to flatten when competition increases. We anticipate that this same flattening will occur with increased temperature because, in the rising part of the temperature performance curve, interspecific competition is predicted to increase. We explored this question using aquatic communities of <i>Sarracenia purpurea</i> from early- and late-successional stages, in which we simulated four levels of dispersal and four temperature scenarios. With increased dispersal, the hump shape was observed consistently in late successional communities, but only in higher temperature treatments in early succession. Increased temperature did not flatten the hump-shape relationship, but decreased the level of alpha- and gamma-diversity. Interestingly, higher temperatures negatively impacted small-bodied species. These metacommunity-level extinctions likely relaxed interspecific competition, which could explain the absence of flattening of the diversity-dispersal relationship. Our findings suggest that climate change will cause extinctions both at local- and global- scales and emphasize the importance of intermediate levels of dispersal as an insurance for local diversity.</p>
Drivers and mechanisms that contribute to microbial β-diversity patterns and range sizes in mountains across a climatic variability gradient
<p>Microbial communities are highly diverse, yet the mechanisms underlying microbial community assembly are not well understood. Janzen's mountain passes hypothesis proposed that climatic barriers and dispersal limitation shape communities to a greater extent in mountains with lower climatic variability and overlap, permitting higher levels of species coexistence. Here, we investigate changes in microbial community dissimilarities, distributional range sizes and ecological processes along elevational gradients in three montane ecosystems representing a climatic variability gradient. We found that climate, climatic variability and spatial distance play dominating roles in affecting microbial β-diversity patterns and range sizes along elevational gradients. Janzen's mountain passes hypothesis can be applied for microbial community assembly: mountains with lower climatic variability and higher climatic difference between elevations exhibited higher β-diversity, higher endemism, lower range sizes, and steeper distance-decay trends. However, microbial communities experience clear climate-driven limited range sizes and dispersal processes and show typical endemic patterns in all mountain ecosystems. Our results emphasize the importance of dispersal and climatic niche processes in shaping montane biodiversity. As a result, changes in climate may significantly impact soil biodiversity in montane ecosystems by altering the effects of dispersal limitation and climatic variability on bacterial and fungal community composition along elevational gradients.</p>
Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors - raw data
<p>Dataset for the study</p> <p><strong><span>Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors</span></strong></p> <ol> <li>environmental variables of the research plots</li> <li>vascular plant species composition of the research plots</li> <li>mcirobial activity on the research plots</li> <li>CLPP profiles of the research plots</li> </ol>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.