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10,929 results for “Communities”
European river typologies fail to capture trends in diatom, fish, and macrophyte community composition
<p>This repository contains files related to the publication: "European river typologies fail to capture trends in diatom, fish, and macrophyte community composition".</p> <p> </p> <p> </p>
RSE-AUNZ community review: responses to steering committee survey
<p>These are the anonymous responses to the steering committee survey conducted for a review of the Research Software Engineers Australia and New Zealand (RSE-AUNZ) community. <a href="https://doi.org/10.5281/zenodo.8098001">Read the report</a>.<br> <br> This survey is one of 2 surveys conducted for the review, the other being a community survey. <a href="https://doi.org/10.5281/zenodo.8098070">Read the results</a>.</p>
Data and code for gmd-2023-113 "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast"
<p>Data and code for the paper "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast"</p> <p>includes: </p> <p>The model is Community Earth System Model (v1.2.1) (provided by www.cesm.ucar.edu)</p> <p>Data assimilation code is initially provided by Data Assimilation Research Testbed (DART) (https://dart.ucar.edu/), some modifications are made to enable parameter estimation function of ocean background vertical diffusivity coefficients. And the programs and scripts for deal with OISST and EN4 profiles are also developed.</p> <p>The parameter sensitivity experiment results are saved as <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/sensitive2008-2012.nc">sensitive2008-2012.nc</a> and <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/sensitive2008-2012salt.nc">sensitive2008-2012salt.nc</a> for temperature and salinity, respectively. And the python script to draw the results is </p> <p>The state estimation results are provided as <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/Temp_05-17.nc">Temp_05-17.nc</a> and <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/Temp_05-17.nc">Salt_05-17.nc</a> for temperature and salinity, respectively.</p> <p>The parameter estimation results are provided as <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/PE_Temp_05-17.nc">PE_Temp_05-17.nc</a> and <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/PE_Temp_05-17.nc">PE_Salt_05-17.nc</a> for temperature and salinity, respectively.</p> <p>the estimated paremeter ensemble is saved in <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/parameters.nc">parameters.nc</a></p> <p>the python script for comparing the SE and PE results is <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/plot_analysis.py">plot_analysis.py</a></p> <p>the nino3.4 indices computed by the forecast experiment is saved in <a href="https://zenodo.org/api/files/6e5b4bfa-61cf-44bc-8e15-e62fab467ea6/fcst_correlation.nc">fcst_correlation.nc</a></p> <p> </p>
Data from: Pathogen community composition and co-infection patterns in a wild community of rodents
<p><strong>ABSTRACT</strong></p> <p>Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors that may influence their distribution in the wild. Here, we describe the incidence and distribution patterns of a range of endemic and zoonotic pathogens circulating among rodent communities in northern France. The community sample consisted of 713 rodents, including 11 host species from diverse habitats. Rodents were screened for virus exposure (hantaviruses, cowpox virus, Lymphocytic choriomeningitis virus, Tick-borne encephalitis virus) using antibody assays. Bacterial communities were characterized using 16S rRNA amplicon sequencing of splenic samples. Multiple correspondence (MCA), regression and association screening (SCN) analyses were used to determine the degree to which extrinsic factors contributed to pathogen community structure, and to identify patterns of associations between pathogens within hosts. We found a rich diversity of bacterial genera, with 36 known or suspected to be pathogenic. We revealed that host species is the most important determinant of pathogen community composition, and that hosts that share habitats can have very different pathogen communities. Pathogen diversity and co-infection rates also vary among host species. Aggregation of pathogens responsible for zoonotic diseases suggests that some rodent species may be more important for transmission risk than others. Moreover we detected positive associations between several pathogens, including <em>Bartonella</em>, <em>Mycoplasma</em> species, Cowpox virus (CPXV) and hantaviruses, and these patterns were generally specific to particular host species. Altogether, our results suggest that host and pathogen specificity is the most important driver of pathogen community structure, and that interspecific pathogen-pathogen associations also depend on host species.</p> <p><strong>FILE DESCRIPTION:</strong></p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from spleen rodent samples</strong></p> <p>This ZIP file contains the FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each spleen rodent sample using the MiSeq platform. The 749 multiplexed PCR products were indexed using both forward and reverse indices. Information of the multiplexed samples (<em>n</em>=363 in replicate) and positive (<em>n</em>= 6) & negative controls (<em>n</em>= 17) is provided in the following XLSX file titled: 16S_raw_abundance_data.xlsx</p> <p>File name: <strong>MiSeq raw sequences of the V4 region 16S rRNA gene.zip</strong></p> <p><strong>Raw input and output files generated by the mothur program</strong></p> <p>This ZIP file contains all the input and output files generated during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>Raw input and output files generated by the mothur program.zip</strong></p> <p><strong>Log file generated by the mothur program</strong></p> <p>This TXT file contains is the history of all the command lines and parameters used during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>mothur.1428506786.logfile</strong></p> <p><strong>Raw abundance table of the 16v4 rRNA gene from spleen rodent samples before data filtering</strong></p> <p>This XLSX file contains the number of reads for each distinct Operational Taxonomic Unit (OTU) and each of the PCR products, including the 332 spleen rodent samples analyzed in the study and the negative & positive controls, sequenced in the MiSeq run before the data filtering. This file contains also the following information: Study_site, Study_year, Sample_habitat, Host_species, Host_age, Host_sex, PCR_ID and the taxonomic classification (Kingdom to Genus) of each OTU.</p> <p>File name: <strong>16S_raw_abundance_data.xlsx</strong></p> <p><strong>Occurrence table of the 16v4 rRNA gene from spleen rodent samples after data filtering</strong></p> <p>This XLSX file contains the occurrences (presence: 1 ; absence: 0) after data filtering of each putative pathogenic Operational Taxonomic Unit (OTU) for each of the 332 spleen rodent samples analyzed in the study.</p> <p>File name: <strong>16S_presence_absence_data.xlsx</strong></p> <p><strong>Statistical Analysis Scripts and Data File</strong></p> <p>This ZIP file contains the R scripts for performing statistical analyses reported in the main text and supplemental materials. There is one main file (Analyses.R), as well as two source scripts required for association screening analyses (SCN.txt and FctTestScreenENV.txt). It also includes an R-legible data file containing occurrences (presence: 1 ; absence: 0) for all pathogen exposure variables on which statistical analyses were conducted (PA_DATA.csv) for each of the 332 spleen rodent samples analyzed in the study. The column names for bacterial exposures correspond to the “Pathogen Code” given in the 16S_presence_absence_data.xlsx file.</p> <p>File name: <strong>Statistical Analysis Scripts and Data File.zip</strong></p>
The effect of a political crisis on performance of community- and state-managed forests in Madagascar
<p>Data associated with paper: "The effect of a political crisis on performance of community forests and protected areas in Madagascar"</p> <p>For code and selected tabular data outputs, also see: https://github.com/raenb0/madagascar</p> <p>Includes a number of files with raster (tif) data. All data is for Madagascar:</p> <p>⦁ for2000.tif is forest cover in the year 2000<br>⦁ for2000_0.tif is the same as above but contains 0 values instead of NA values (better for analysis)<br>⦁ defor_year_90m is annual deforestation as a proportion of each 90 m pixel that is deforested, values range from 0-1.</p> <p>data on all time-invariant covariates used for matching, including:<br>⦁ dist_cart (distance from cart tracks, meters)<br>⦁ dist_road (distance from roads, meters)<br>⦁ dist_urb (distance from villages, meters)<br>⦁ dist_urb (distance from urban centers, meters)<br>⦁ dist_vil (distance from villages, meters)<br>⦁ edge_05 (distance from forest edge in 2005, meters)<br>⦁ elev (elevation, meters)<br>⦁ q1_materials (index of self-reported development level, based on material assets)<br>⦁ rain (average precipitation 1970-2000, mm)<br>⦁ rice (rice suitability, 0 for unsuitable or 1 for suitable)<br>⦁ slope (slope, meters)<br>⦁ v7_security (self-reported indicator of security and risk of theft)<br>⦁ veg_type (vegetation type, 1= eastern humid forest, 2= western deciduous forest, 3 = southern dry spiny forest)</p> <p>time-variant covariates include (for years 2005-2020):<br>⦁ distance_year (distance from forest edge of each forest pixel, in meters, in each year)<br>⦁ drght_year (drought severity, Palmer Index Score)<br>⦁ pop_year (human population density, people per sq km)<br>⦁ precip_year (maximum accumulated precipitation, mm)<br>⦁ rice_av_year (annual average rice prices, in USD)<br>⦁ rice_sd_year (standard deviation of rice price, in USD)<br>⦁ temp_year (maximum annual temperature, degrees C)<br>⦁ wind_year (maximum annual windspeed, meters/sec)</p> <p>Shapefile polygons for Community Forest Managed areas (CFM) and protected areas administered by Madagascar National Parks can be requested from the corresponding author: ran63 (at) cornell (dot) edu</p> <p>Shapefile polygons for protected areas in Madagascar are available from the World Database of Protected Areas: https://www.protectedplanet.net/country/MDG</p>
Pseudonymised Dataset of the Characterising the IIIF and Linked Art communities survey
<p>This is the pseudonymised<em> </em>dataset of the survey titled "Characterising the IIIF and Linked Art communities" that was conducted between 24 March and 7 May 2023. The survey explored the socio-technical characteristics of two prevalent community-driven initiatives in the cultural heritage domain, namely the International Image Interoperability Framework (IIIF) as well as Linked Art. The survey was carried out as part of the PhD Thesis titled "Linked Open Usable Data for Cultural Heritage: Perspectives on Community Practices and Semantic Interoperability" (see <a href="https://phd.julsraemy.ch" target="_blank" rel="noopener">https://phd.julsraemy.ch</a>).</p> <p>The survey report is available at <a href="https://hal.science/hal-04162572">https://hal.science/hal-04162572</a></p> <p>The dedicated GitHub repository is available at: <a href="https://github.com/julsraemy/loud-socialfabrics/" target="_blank" rel="noopener">https://github.com/julsraemy/loud-socialfabrics/ </a></p>
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>
Supplementary Files for "Extinction debt and functional traits mediate community saturation over large spatiotemporal scales"
<p><strong>Supplementary Files for "Extinction debt and functional traits mediate community saturation over large spatiotemporal scales"</strong></p> <p><strong>Supplementary Tables:</strong></p> <p><strong>Supplementary Table S1.</strong> Species composition data of the 67 sites included herein from members of the Dipsadidae.</p> <p><strong>Supplementary Table S2.</strong> Scores for the Principal Component (PC) Axes corresponding to the PC analyses performed with the climatic variables of the sites included in this work.</p> <p><strong>Supplementary Table S3.</strong> Species composition data of the 67 sites included herein from species from families different from Dipsadidae.</p> <p><strong>Supplementary Table S4.</strong> Functional data corresponding to each of the species found in the 67 sites included in this work.</p> <p><strong>Supplementary Table S5.</strong> Functional data corresponding to each of the species from families different from Dipsadidae found in the 67 sites included in this work.</p> <p><strong>Supplementary Table S6.</strong> GenBank accession numbers of each of the sequences used for constructing the timetree used for this work.</p> <p><strong>Supplementary Table S7.</strong> Table indicating the areas inhabited by each of the species of the Dipsadidae included in the Bayesian timetree used for the ancestral area estimation performed herein.</p> <p><strong>References used for constructing Supplementary Tables S4 and S5</strong></p> <p> </p> <p><strong>Supplementary Figures:</strong></p> <p><strong>Supplementary Figure S1.</strong> Results of the ancestral estimations as recovered by ‘BioGeoBEARS’</p>
Data from: Butterflies are not a robust bioindicator for assessing pollinator communities, but floral resources offer a promising way forward
<p>Monitoring pollinators is crucial for the evaluation of biodiversity and potential pollination services. Yet, efficiently monitoring multiple taxa over large areas can be costly. An alternative approach is using simple species bioindicators that represent the entire pollinator community. One of the requirements of a good bioindicator is that it can be easily identified to lower taxonomic levels and be sensitive to changes in habitat. This is the case for butterflies, a taxon for which many countries have a country-wide long-term monitoring scheme. We tested whether butterfly diversity can be used to predict diversity of bees and hoverflies both spatially and temporally. We surveyed 42 transects of the Dutch Butterfly Monitoring Scheme in 2020, to record species richness and abundance of butterflies, bees and hoverflies. We also recorded flower area and richness in the pollinator transects. To test whether pollinators with similar functional traits are more closely correlated than the entire pollinator community, we categorized bee and butterfly species according to their diet breadth (polyphagous vs. non-polyphagous), nitrogen-affinity (nitrophobous vs. nitrophilous larval resources) and body size. We used the same methods to test for temporal correlations over seven years for one site in Spain. Butterfly richness was not spatially correlated with bee richness (Pearson's r = 0.13), nor were the two taxa temporally correlated (Pearson's r = 0.02). Interestingly, hoverfly richness was spatially correlated with butterfly richness (Pearson's r = 0.43) and with bee richness (Pearson's r = 0.36) in the Netherlands and, hence, hoverflies might be slightly more suitable as a bioindicator of pollinator diversity in this area. Abundance of all three taxa showed no significant inter-correlation, except for correlations between diet specialist bees and butterflies (Pearson's r = 0.39). Importantly, all three taxa were strongly correlated with flower richness, but they varied in their preferences for host plant families. This is in line with 75% of the plant-pollinator studies finding significant positive relations. For monitoring schemes to be effective in informing better pollinator conservation, they should expand to include bees and hoverflies as well as simple indicators of habitat quality such as floral resources.</p>
Supplementary Data for "Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results from a Community-Partnered Low-cost Sensor Deployment"
<p>These are the underlying data sets needed to build the kriging maps and calculate dissemination block cumulative hazard indices described in the paper. There are three data sets:</p> <ol> <li><strong>"Sampling location names and coordinates.csv"</strong>: locations and IDs of the low-cost sensors and the regulatory monitoring stations used in this work.<strong> [NOTE: </strong>latitudes and longitudes for the sensor deployments have been intentionally rounded to protect the location of volunteer sensor hosts.]</li> <li><strong>"Dissemination Block Populations.csv"</strong>: These are the relevant dissemination blocks in the study domain and their associated populations. This information was originally extracted from: https://censusmapper.ca/#13/49.2430/-123.1252</li> <li><strong>"Daily average concentrations by site and pollutant.csv"</strong>: This contains the PM2.5, NO2 and O3 daily averages for the entire study period across all low-cost sensor sites and regulatory monitoring stations. Refer to "Sampling location names and coordinates.csv" to parse the labels in this data set.</li> </ol> <p>There is also a sample code in Python to construct the kriging maps provided in 2 formats. <strong>[NOTE: </strong>we have intentionally excluded uploading the exact data sets imported by this code; our original data contains exact locations of sensor host volunteers and thus cannot be shared.]</p> <ol> <li><strong>"Jain et al - GeoHealth - Kriging Script.ipynb"</strong>: A Jupyter notebook script to import the data, build kriging maps, calculate CHIs, and export the data.</li> <li><strong>" Jain et al - GeoHealth - Kriging Script.pdf"</strong>: A PDF export of the Jupyter notebook so that you can read the Python scripts even if you are not a Jupyter notebooks user.</li> </ol>
Dataset Changes in structure and assembly of a species-rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial Pseudomonas in the wheat rhizosphere
<p>This dataset is related to the paper "<strong>Changes in structure and assembly of a species-rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial <em>Pseudomonas </em>in the wheat rhizosphere</strong>" (Garrido-Sanz et al., 2023, doi: 10.1186/s40168-023-01660-5) and contains the data obtained from bacterial competition asays and plant-growth measurements.</p> <p>Sequencing data used in this study has been deposited in the NCBI Sequence Read Archive (RSA) under the BioProject accession number <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA948847">PRJNA948847</a>.</p> <p>The R script used to analyze the data generated in the paper is available at <a href="https://github.com/dgarrs/Pprotegens_proliferation_NatComs">GitHub </a>and <a href="https://doi.org/10.5281/zenodo.8322086">Zenodo</a>.</p>
Datasets from the paper "Measuring the relationship between the use of typical Manosphere discourse and the engagement of a user with the pick-up artist community"
<p>Datasets from the paper "Measuring the relationship between the use of typical Manosphere discourse and the engagement of a user with the pick-up artist community", presented at the 24th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL).</p> <p>The dataset consists in 2 files:</p> <ul> <li>tweets.csv: This file contains the ids of the tweets and the user that published the tweet.</li> <li>df_users_seeds.csv: This file contains a table were the first field is the user id; the other columns indicate the seed number and if the user follows that seed (1) or not (0)</li> </ul>
Community Package VanGalen-Oetjen Dataset
<p>The Community package (<a href="https://github.com/SoloveyMaria/community">https://github.com/SoloveyMaria/community</a>) is an R package designed for the analysis of single-cell RNA sequencing data, specifically for inferring interactions between different cell types. The dataset provided here is compatible with the Community tool, allowing for direct utilization. </p><p>Both datasets VanGalen (<a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116256">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116256</a>) and Oetjen (<a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120221">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120221</a>) have undergone peer review and has ben published. It's important to note that the data in this repository has undergone batch correction and normalization, and the corresponding metadata has been appropriately adjusted (for detailed insights into the preprocessing steps, you can review the information provided at our paper repository: <a href="https://github.com/colomemaria/community-paper/tree/main/src/data_preprocessing">preprocessing</a>). This processed data serves as the input for the Community tool.</p>
Effects of freshwater salinization on a salt-naïve planktonic eukaryote community
Salinization of freshwater ecosystems is a widespread issue, but evidence of ecological effects on aquatic eukaryote communities remains scarce. We experimentally exposed naive planktonic communities of a north-temperate, freshwater lake to a gradient of chloride (Cl-) concentration (0.27-1400 mg Cl-.L-1) with in-situ mesocosms. Following six weeks of exposure, we measured changes in the diversity, composition, and abundance of eukaryotic 18S rRNA gene. Total phytoplankton biomass remained unchanged, but we observed a shift in dominant phytoplankton groups with elevated salt concentration, from Cryptophyta and Chlorophyta that dominated in lower chloride concentrations (<185 mg Cl-.L-1) to Ochrophyta that dominated at higher conductivity (>185 mg Cl-.L-1). Most zooplankton and rotifer taxa were sensitive to the salinity and disappeared at low chloride concentrations (<40 mg Cl-.L-1). While ciliates thrived at low chloride concentrations (<185 mg Cl-.L-1), fungal groups dominated at intermediate chloride concentrations (185 mg Cl-.L-1 to 640 mg Cl-.L-1), and only phytoplankton remained at the highest chloride concentrations (> 640 mg Cl-.L-1).
Soil microbial community composition (16S) data from a laboratory redox fluctuation experiment conducted with an Oxisol and Mollisol
To test the response of microbial communities to periodic oxygen limitation, we conducted a laboratory experiment where two contrasting soils (a rainforest Oxisol from Puerto Rico, and an Iowa cropland Mollisol) were incubated under headspace treatments where oxygen availability varied cyclically over time. Treatments consisted of 0, 2, 4, 8, or 12 d of anoxic conditions (dinitrogen headspace) followed by 4 d of oxic conditions (i.e., ambient oxygen concentrations), and these treatments were repeated for a total of 384 d. At 0, 48, and 384 days, DNA was extracted from replicates from each treatment for sequencing of 16S rRNA amplicons. Companion biogeochemical measurements from this experiment were published previously by Huang et al. (2021a,b). These data support the Hall et al. (2022) manuscript published in Frontiers in Microbiology.
Kelp forest fish communities environmental DNA samples from Santa Barbara Channel
The dataset in this package is the processed fish community structure inferred from 12S eDNA metabarcoding in the Santa Barbara Channel. 49 water samples were collected across 11 sites in 2017 and the taxa were identified to the highest resolution possible. The raw DNA sequence has been archived in the Sequence Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra) under the accession number PRJNA667508. This dataset is used to support manuscript: Lamy, T., Pitz, K.J., Chavez, F.P. et al. Environmental DNA reveals the fine-grained and hierarchical spatial structure of kelp forest fish communities. Sci Rep 11, 14439 (2021). https://doi.org/10.1038/s41598-021-93859-5
Long-term response of wetland plant communities to management intensity, grazing abandonment, and prescribed fire
Isolated, seasonal wetlands within agricultural landscapes are important ecosystems. However, they are currently experiencing direct and indirect effects of agricultural management surrounding them. Because wetlands provide important ecosystem services, it is crucial to determine how these factors affect ecological communities. Here, we studied the long-term effects of land use intensification, cattle grazing, prescribed fires, and their interactions on wetland plant diversity, community dynamics, and functional diversity. To do this, we used vegetation and trait data from a 14-year-old experiment on 40 seasonal wetlands located within semi-natural and intensively managed pastures in Florida. These wetlands were allocated different grazing and prescribed fire treatments (grazed vs. ungrazed; burned vs. unburned). Our results showed that wetlands within intensively managed pastures have lower native plant diversity, floristic quality, evenness, higher non-native species diversity, and exhibited the most resource-acquisitive traits. Wetlands embedded in intensively managed pastures were also characterized by lower species turnover over time. We found that 14 years of cattle exclusion reduced species diversity in both pasture management intensities and had no effect on floristic quality. Fenced wetlands exhibited lower functional diversity and experienced a higher rate of community change both due to an increase in tall, clonal, and palatable grasses. The effects of prescribed fires were often dependent on grazing treatment. For instance, prescribed fires increased functional diversity in fenced wetlands but not in grazed wetlands. Our study suggests that cattle exclusion and prescribed fires are not enough to restore wetlands in intensively managed pastures and further highlights the importance of not converting semi-natural pastures to intensively managed pastures. Our study also suggests that grazing levels applied in semi-natural pastures maintained high plant dive
Manipulating the hydroperiod affects plant and invertebrate communities in freshwater mesocosms, La Marque TX USA, 2019-2021
We used a mesocosm experiment with six flooding depths and seven drought durations, followed by seven months of recovery, to explore how freshwater wetlands typical of the Houston, Texas area would respond to different hydrological regimes that might occur if wetlands were drained in anticipation of a heavy rain that did not materialize, leading to a temporary period of little or no standing water. The experiment was conducted in 2019-2021. How quickly mesocosms dried out was a function of initial water depth, with mesocosms initially set with greater water depths (30 cm) taking on average 38 days to dry out. Individual plant species (14 were planted; 8 were common at the end of the recovery period) were affected drought length, flooding depth, or their interaction, with results varying among species. The composition of the plant community at the end of the drought period was strongly affected by drought length, and this effect persisted through seven months of recovery, with the 80- and 160-day drought treatments diverging most strongly from shorter drought treatments. Densities of mosquito larvae, snails and tadpoles were temporally variable, and affected more during the treatment period than after seven months of recovery. Our results indicate that managed wetlands in southeast Texas would be quite resilient to dry periods of up to 40 days in duration, especially if water was not completely drained at the beginning of the drought. In addition, some wetland species would persist in managed wetlands even if they experienced droughts of up to 160 days.
FRAME (FoRests Among Managed Ecosystems) – Plant community and seed bank composition in forests, Philadelphia metropolitan area, USA, 2017-2019
Our study objectives were to conduct a Rosa multiflora (multiflora rose) removal experiment in three forest sites experiencing different invasion intensities and to restore native plant biodiversity while preventing secondary invasion. The study was conducted in and around Newark, DE, from 2017-2019, and data collection is complete. We utilized three management strategies: invasive plant removal, removal followed by native seed addition, and removal plus native seed and mulched invasive stem addition. We investigated the similarity between seed bank species composition and existing vegetation before and after removal to assess the potential for passive restoration. Two seasons after removal, we found that simply removing rose increased native species richness, Native Floristic Quality Assessment (FQAIN), and native shrub abundance in our medium invasion site, and total species richness in our low and medium invasion sites. Compared to removal alone, native seed addition, with and without mulch addition, resulted in larger native and total species richness and FQAIN increases at all sites, larger increases in native shrub abundance and exotic species richness in our medium invasion site, and larger reductions in exotic and total shrub abundance in our low and medium invasion sites. Following removal, species similarity between seed bank and vegetation improved for all three sites. Our results indicate that removal of Rosa multiflora (multiflora rose) alone increased native plant biodiversity in the medium invasion scenario, but the seed bank may not provide a large native species pool. Additional management strategies lead to improved outcomes, especially in our most invaded forest, demonstrating the need to conduct multiple plant removal treatments across forests with varying site conditions and plant invasion intensity to improve management recommendations.
Genome size influences plant growth and biodiversity responses to nutrient fertilization in diverse grassland communities
Experiments comparing diploids with polyploids and in single grassland sites show that nitrogen and/or phosphorus availability influences plant growth and community composition dependent on genome size; specifically plants with larger genomes grow faster under nutrient enrichments relative to those with smaller genomes. However, it is unknown if these effects are specific to particular site localities with speciifc plant assemblages, climates, and historical contingencies. To determine the generality of genome size dependent growth responses to nitrogen and phosphorus fertilisation, we combined genome size and species abundance data from 27 coordinated grassland nutrient addition experiments in the Nutrient Network that occur in the Northern Hemisphere across a range of climates and grassland communities. We found that after nitrogen treatment, species with larger genomes generally increased more in cover compared to those with smaller genomes, potentially due to a release from nutrient limitation. Responses were strongest for C3 grasses and in less seasonal, low precipitation environments, indicating that genome size effects on water-use-efficiency modulates genome size-nutrient interactions. Cumulatively the data suggest that genome size is informative and improves predictions of species’ success in grassland communities.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.