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308 results for “fungal community”
Mycorrhizal fungal communities identified from seedlings planted in the Taylor, Dalton, and Boundary fire complexes which burned in 2004
This dataset contains the operational taxonomic unit table and taxonomic assignments for fungi that were associated with the roots of seedlings planted into the 2004 burn sites. There were 458 seedlings from 22 of the 32 established intensive sites (Johnstone and Hollingsworth 2019) consistenting of black spruce, white spruce, aspen, and lodgepole pine.
Hubbard Brook Experimental Forest: Soil Fungal Communities, 2021-2023
Sporocarp (fungal fruiting body) observational data and fungal eDNA data extracted from soil samples collected primarily by Farrar Ransom in the summers of 2021, 2022, and 2023. Also included: detailed site metadata, soil moisture measurements, sample processing metadata, and R code used in publication analysis. Data are still being uploaded as of January 2026. The majority of these data were collected in study plots established around 2016 by Dr. Elizabeth Studer for her dissertation work. This factorial study design consists of approximately 60 plots on two hydropedological soil types beneath four canopy tree species. The four tree species we considered were white ash (Fraxinus americana), sugar maple (Acer saccharum), American beech (Fagus grandifolia), and yellow birch (Betula alleghaniensis). Some of these plots are now part of the ongoing Ash Protection Experiment. The following data tables and other entities were used in the analysis for the publication: Unique soil fungal communities are associated with disappearing ash trees in a northern temperate hardwood forest. Site_Metadata; eDNA_Abun_Table; eDNA_Taxa_Metadata; eDNA_Extraction_Metadata; iNext_Format_eDNA; Sporocarp_Count_Table; Sporocarp_Prop_Table; Soil_Moisture_Measurements; PCR_Plate_Gel_Photos; FR_DADA2_PlusFilter_CodePub; FR_eDNA_CodePub; FR_Sporocarp_CodePub; These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Tree-Associated Fungal and Bacterial Communities at Harvard Forest 2021
Cities are investing in tree-planting initiatives to protect their citizens from climate change-related heat and pollution exposure, yet Boston’s street trees are growing nearly four times as fast and dying twice as young as Massachusetts’ rural forest trees. Our research aims to characterize the belowground variables and microbial community composition that might explain the differences in growth and mortality rates observed between urban and rural trees. In 2021, soil, leaf, and root samples were taken from 25 trees in Harvard Forest to use as a rural comparison to Boston’s street trees and trees in other forests along an urban-to-rural gradient from Boston into Western Massachusetts. At each tree, three 12” deep, 2.4-centimeter radius soil cores were taken within the drip line, and soil cores were divided into the top 6” and lower 6” of soil. Fine roots were picked from each soil core. Six leaf samples were taken from the mid-canopy of each tree, where possible. Soil variables including temperature, moisture, percent organic matter, soluble nitrogen availability, bulk density, and root biomass were measured. Thus far, we have found that urban trees have fewer roots than Harvard Forest trees (F1,252) = 10.88, p = 0.0011), and that urban trees establish more root biomass deeper into the soil than Harvard Forest trees (p = 4.84e-5).
Effects of factorial nitrogen, phosphorus, and potassium with micronutrient addition and Host Community on Fungal Endophyte Diversity at Cedar Creek Ecosystem Reserve, Minnesota, USA, 2014
The microbes contained within free-living organisms can alter host growth, reproduction, and interactions with the environment. In turn, processes occurring at larger scales determine the local biotic and abiotic environment of each host that may affect the diversity and composition of the microbiome community. Here, we examine variation in the diversity and composition of the foliar fungal microbiome in the grass host, Andropogon gerardii, across a factorial nitrogen, phosphorus, and potassium addition experiment in Minnesota, USA. We found limited evidence of direct effects of nutrients on endophyte diversity. Instead, the effects of nutrients on endophyte diversity appeared to be mediated by accumulation of plant litter and plant diversity loss. Specifically, nitrogen addition is associated with a 40% decrease in plant diversity and an 11% decrease in endophyte richness. Although nitrogen, phosphorus, and potassium addition increased aboveground live biomass and decreased relative Andropogon cover, endophyte diversity did not covary with live plant biomass or Andropogon cover. Our results suggest that fungal endophyte diversity within this focal host is determined in part by the diversity of the surrounding plant community and its potential impact on immigrant propagules and dispersal dynamics. Our results suggest that elemental nutrients reduce endophyte diversity indirectly via impacts on the local plant community, not direct response to nutrient addition.
Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs
<p>Datasets describing the fungal species diversity, microbial density and acidity of French sourdoughs, phenotypic variation of Kazachstania bulderi and Kazachstania humilis strains as well as the diversity of bread-making practices of 40 bakers and farmers-bakers.The data were collected, analyzed, and reported within the following publication :</p> <p>Elisa Michel, Estelle Masson, Sandrine Bubbendorf, Léocadie Lapicque, Thibault Nidelet, Diego Segond, Stéphane Guézenec, Thérèse Marlin, Hugo deVillers, Olivier Rué, Bernard Onno, Judith Legrand, Delphine Sicard and the participating bakers: <strong>Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs</strong>. PCI Evol. Biol.</p> <p> </p>
Data from: Shift of bacterial and fungal communities upon soil amelioration is driven by carbon degradability of organic amendments
<p>Microbial communities of bacteria and fungi have been analyzed in soil. Agricultural soil was amended with different organic amendments including straw, compost, biogas residues, and biochar, and incubated in the lab. After 6 months, DNA extracted from soil samples was analyzed via Illumia MiSeq DNA sequencing (16S V3V4 for bacteria, ITS1 for fungi) to evaluate changes to the microbial community structure.</p> <p>For details, please see the respective publication (DOI: 10.1007/s44378-024-00012-5).</p>
Root-associated fungal communities exposed to experimental drought
Plant-associated fungi can ameliorate abiotic stress in their hosts, and changes in these fungal communities can alter plant productivity, species interactions, community structure and ecosystem processes. We investigated the response of root-associated fungi to experimental drought (66% reduction in growing season precipitation) across six North American grassland ecosystem types to determine how extreme drought alters root-associated fungi, and understand what abiotic factors influence root fungal community composition across grassland ecosystems. Next generation sequencing of the fungal ITS2 region demonstrated that drought primarily re-ordered fungal species’ relative abundances within host plant species, with different fungal responses depending on host identity. Grass species that declined more under drought trended toward less community re-ordering of root fungi than species less sensitive to drought. Host identity and grassland ecosystem type defined the magnitude of drought effects on community composition, diversity, and root colonization, and the most important factor affecting fungal composition was plant species identity.
Dataset of fungal communities observed on decomposing pig carcasses in New Jersey
<p>This dataset contains estimated count data for fungal taxa identified using ITS metabarcoding collected from decomposing fetal pig carcasses placed in grasslands of New Jersey, USA.</p> <p>FungiPigDecomp_Data.csv is a file that contains the estimated count data at the level of taxonomic resolution possible for each replicate, at each stage of decomposition, across three body districts.</p> <p>FungiPigDecomp_Methods.docx is a summarized version of the sampling method relevant to interpreting the data.</p> <p>FungiPigDecomp_Descriptive.txt is a file describing the column headers in "FungiPigDecomp_Data.csv".</p>
ARISA fungal community profiles for each resprouting Betula nana shrub sampled in an observational study of post-fire mycorrhizal communities across a fire-severity gradient in the Anaktuvuk River Fire burn scar, 2010
The dataset contains fungal community data from a sampling campaign in 2009, two growing seasons after the Anaktuvuk River Fire. We used molecular tools, including ARISA and fungal ITS sequencing, to characterize the mycorrhizal communities on resprouting Betula nana shrubs across a fire-severity gradient. ARISA profiles are provided for each shrub sampled in the study.
Fungal community structure associated with seedlings that established post-fire and adjacent resprouting shrubs at Finger Mountain and Nome Creek, Alaska
This dataset contains characterizations of fungal community structure associated with seedlings that established after fire and adjacent resprouting shrubs. It also includes variables that describe proximity to the closest resprouting shrub, fire severity, vegetation, and substrate associated with seedlings and adjacent resprouting shrubs harvested at Finger Mountain and Nome Creek in 2009.
ARISA profiles for root-associated fungal communities associated with seedlings that established after fire and adjacent shrubs harvested at Finger Mountain and Nome Creek in 2009
This dataset contains the ARISA profiles of the root-associated fungal communities associated with seedlings that established after the 2004 fires and the closest resprouting shrub.
Accounting for environmental variation in co‐occurrence modelling reveals the importance of positive interactions in root‐associated fungal communities
<p>Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co-occurrences that are not constrained by the environmental conditions. In this study, we investigated co-occurrences among root-associated fungi, asking whether fungi co-occur more or less strongly than expected based on the environmental conditions and the host plant species examined. For this purpose, we generated molecular data on root-associated fungi of five plant species evenly sampled along an elevational gradient at a high Arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co-occurrences that could be explained by the environmental conditions and the host plant species, as well as those co-occurrences that remained unexplained and thus more likely reflect interactive associations. Our results indicate that positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co-occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root-associated fungi are predominantly positive.</p>
Data from: Fungal communities are important determinants of bacterial community composition in deadwood
<p>Fungal-bacterial interactions play a key role in the functioning of many ecosystems. Thus, understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. However, it is challenging to disentangle the mechanisms behind species associations from observed co-occurrence patterns and little is known about the directionality of such interactions. Here we apply joint species distribution modelling to high-throughput sequencing data on co-occurring fungal and bacterial communities in deadwood to ask whether fungal and bacterial co-occurrences result from shared habitat use (i.e. dead wood's properties), or whether there are fungal-bacterial interactive associations after habitat characteristics are taken into account. Moreover, we test the hypothesis that the interactions are mainly modulated through fungal communities influencing bacterial communities. For that, we quantified how much the predictive power of the joint species distribution models for bacterial and fungal community improved when accounting for the other community. Our results show that fungi and bacteria form tight association networks (i.e. some species pairs co-occur more frequently and other species pairs co-occur less frequently than expected by chance) in deadwood that include common (or opposite) responses to the environment, as well as (potentially) biotic interactions. Additionally, we show that information about the fungal occurrences and abundances increased the power to predict the bacterial abundances substantially, whereas information about the bacterial occurrences and abundances increased the power to predict the fungal abundances much less. Our results suggest that fungal communities may mainly affect bacteria in deadwood.</p> <p><b>Importance</b></p> <p>Understanding the interactive dynamics between fungal and bacterial communities is important to gain predictive knowledge on ecosystem functioning. However little is known about the mechanisms behind fungal-bacterial associations and the directionality of species interactions. Applying joint species distribution modelling to high throughput sequencing data on co-occurring fungal-bacterial communities in deadwood, we found evidence that non-random fungal-bacterial associations derive from shared habitat use, as well as (potentially) biotic interactions. Importantly,<i> </i>the combination of cross-validations and conditional cross-validations helped us to answer the question about the directionality of the biotic interactions, providing evidence that suggests that fungal communities may mainly affect bacteria in deadwood. Our modelling approach may help gaining insight into the directionality of interactions between different components of the microbiome in other environments.</p>
Simple attributes predict the value of plants as hosts to fungal and arthropod communities
Fungal and arthropod consumers constitute the vast majority of global terrestrial biodiversity. Yet, the link from richness and composition of producer (plant) communities to the richness of consumer communities is poorly understood. Fungal and arthropod species richness could be a simple function of producer species richness at a site. Alternatively, it could be a complex function of chemical and structural properties of the producer species making up communities. We used databases on plant-fungus and plant-arthropod trophic links to derive the richness of consumer biota per associated plant species (coined link score). We assessed how well link scores could be predicted by simple attributes of plant species. Next, we used a multi-taxon inventory of 130 sites, representing all major habitat types in a country (Denmark), to investigate whether link scores summed over plant species in communities (coined link sum) could outperform simple plant species richness as predictor of fungal and arthropod richness at the sites. We found plant species' link scores for both fungi and arthropods to be positively related to plant size, regional occupancy, nativeness and ectomycorrhizal status. Link-based indices generally improved the prediction of richness of fungal and arthropod communities. For fungal communities, both observed link sum (from databases) and predicted link sum (from plant attributes) had high predictive power, while plant richness alone had none. For arthropod communities, predictive performance varied between functional groups. For both fungi and arthropods, richness predictions were further improved by considering abiotic habitat conditions. Our results underline the importance of plants as niche space for the megadiverse groups of arthropods and fungi. The plant-attribute approach holds promise for predicting local and regional consumer richness in areas of the world lacking detailed plant-consumer databases.
Data from: Plant community stability is associated with a decoupling of prokaryote and fungal soil networks
<p>Data from the manuscript Plant community stability is associated with a decoupling of prokaryote and fungal soil networks: https://doi.org/10.1101/2022.06.21.496867</p>
Deciphering the interactions between plant species and their main fungal root pathogens in mixed grassland communities
<p>1. Plant diversity can reduce the risk of plant disease, but positive, and neutral effects have also been reported. These contrasting relationships suggest that plant community composition, rather than diversity per se, affects disease risk. Here, we investigated how diversity and composition of plant communities drive root-associated pathogen accumulation belowground.</p> <p>2. In a temperate grassland biodiversity experiment, containing 16 plant species (forbs and grasses), we determined the abundance of root-associated fungal pathogens in individual plant species growing in monocultures and in 4-species mixtures through Illumina MiSeq amplicon sequencing.</p> <p>3. In the plant monocultures, we identified three major fungal pathogens that differed in host range: <em>Paraphoma chrysanthemicola</em>, associated with roots of forb species of the Asteraceae family, <em>Slopeiomyces cylindrosporus</em>, associated with grass species, and <em>Rhizoctonia solani</em>, associated with multiple forb and grass species. In mixtures, there was no significant reduction in relative abundance of these pathogens in their host species as compared to monocultures. However, in mixtures, there was a significant increase in relative abundance of each pathogen in several non-host and host plant species. Across mixtures, plant community composition affected pathogen relative abundance in individual plant species. This effect was driven by the presence of a particular neighbouring plant species (depending on the pathogen), rather than functional group composition (i.e. grass/forb ratio) or averaged pathogen pressure (based on monocultures) of all neighbours. Specifically, the presence of neighbour host species <em>Achillea millefolium</em> significantly increased <em>P. chrysanthemicola</em>, but decreased <em>R. solani</em> relative abundance in several host and non-host plant species in mixtures.</p> <p>4. Synthesis: Our results indicate that interactions between different plant species – both host and non-hosts – and fungal pathogens underlie effects of plant diversity on root pathogen abundance. Non-host species may act as pathogen reservoirs in diverse plant communities, as they harboured certain pathogens in mixtures, but not in monocultures. Additionally, particular host species can strongly affect pathogen abundance in other (host and non-host) plant species in plant mixtures, suggesting clear effects of species identity in the diversity-disease relationship. Belowground disease risk thus depends on plant community composition rather than diversity per se, via specific interactions between plant species and their root-associated pathogens.</p>
Different facets of bacterial and fungal communities drive soil multifunctionality in grasslands spanning a 3,500 km transect
<p>1. Soil microbial communities are essential in regulating ecosystem functions and services. However, the importance of bacterial and fungal communities as predictors of multiple soil functions (i.e., soil multifunctionality) in grassland ecosystems has not been studied systematically.</p> <p>2. Here, we measured soil microbial diversity, community composition, biomass, and multiple soil functions of 41 sites in five grassland ecosystems spanning a 3,500 km northeast–southwest transect. The random forest algorithm was adopted to determine the importance of geographical location, climatic, altitude, edaphic, plant, and microbial predictors in driving a proxy of soil multifunctionality (seven soil functions in this study). Moreover, structural equation models (SEMs) were employed to examine the direct and indirect effects of those predictors on soil multifunctionality.</p> <p>3. Our results demonstrated that soil multifunctionality was positively driven by soil fungal diversity but not by bacterial diversity. Fungal phylogenetic diversity (presence of different evolutionary lineages) showed stronger positive relationships with soil multifunctionality than taxonomic diversity (richness of species). Dominant bacterial taxa, particularly of phyla Actinobacteria and Proteobacteria, were positively associated with soil multifunctionality, while none of the fungal taxa were found to regulate soil multifunctionality. Furthermore, both fungal and bacterial biomass had significant effects on soil multifunctionality, while the effect of microbial biomass was weaker than that of fungal diversity and bacterial taxa. Importantly, the direct positive effects of soil fungal diversity, dominant bacterial taxa, and fungal and bacterial biomass were maintained after accounting for multiple predictors in grassland ecosystems.</p> <p>4. This study provided strong empirical evidence that soil multifunctionality was driven by different facets of the bacterial and fungal communities in the grassland ecosystems. Our results also highlighted that any loss of fungal diversity, dominant bacterial taxa and microbial biomass might reduce soil multifunctionality, exacerbating ecosystem functions and services such as soil fertility, primary production, and climate mitigation in grassland ecosystems. </p>
Data and scripts for: Idiosyncratic responses to biotic and environmental filters in wood-inhabiting fungal communities
<p>These files include the data, the scripts, and the pipeline for bioinformatic analyses for reproducing the results presented in the manuscript "<em>Idiosyncratic responses to biotic and environmental filters in wood-inhabiting fungal communities</em>".</p> <p>Description of the files can be found from the README.docx file.</p>
Data and scripts for "The role of stochasticity in fungal community assembly – explaining apparent stochasticity with field experiments"
<p>The results presented in the manuscript “The role of stochasticity in fungal community assembly – explaining apparent stochasticity by field experiments” can be reproduced by the data and scripts provided in this repository.</p> <p>Concerning the analysis of observational data:</p> <p>· The file ObservationalData.RData includes all data: XData is the dataframe including the predictors, and t is the vector of responses (F. rosea occurrences).</p> <p>· The script O1_model_observational_data.R defines the models, fits the models, and computes model fits based on cross-validation. The results are saved into a file.</p> <p>· The script O2_show_results_observational_data.R loads the results saved by the previous script, and outputs the results reported in the manuscript.</p> <p>Concerning the analysis of experimental data:</p> <p>· The file ExperimentalData.RData includes all data: the dataframe meta includes the relevant predictors, otu.table the matrix of samples x OTU read counts, and the dataframe taxonomy the taxonomic placement of those OTUs.</p> <p>· The script E1_compute_model_based_ordinations.R precomputes the gllvm-ordinations needed both for the colonization success model as well as the community divergence model. The precomputed ordinations are saved into a file.</p> <p>· The script E2_model_colonization_success.R defines the colonization success model, fits the model, and computes model fit based on cross-validation. The results are saved into a file.</p> <p>· The script E3_show_colonization_model_results.R loads the results saved by the previous script, and outputs the results reported in the manuscript.</p> <p>· The script E4_model_community_divergence defines the community divergence model and fits the model. The results are saved into a file.</p> <p>· The script E5_show_community_divergence_model_results.R loads the results saved by the previous scripts, and outputs the results reported in the manuscript, including Table 1 and Figure 2.</p>
Species introductions cause phylogenetically structured successional pathways in natural wood-inhabiting fungal communities
<p>These files include the data and the scripts for reproducing the results presented in the manuscript "Species introductions cause phylogenetically structured successional pathways in natural wood-inhabiting fungal communities".</p> <p>Description of the files can be found from the README.docx file.</p>
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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.