Find research datasets worth reusing

Intraspecific variation in mycorrhizal response is much larger than ecological literature suggests

Mycorrhizal response is the most common metric for characterizing how much benefit a plant derives from mycorrhizal symbiosis. Traditionally, ecologists have used these metrics to generalize benefit from mycorrhizal symbiosis in plant species, ignoring the potential for plant intraspecific trait variation to alter the outcome of the mutualism. In order for mean trait values to be useful as a functional trait to describe a species, as has been attempted for mycorrhizal response traits, interspecific variation must be much larger than intraspecific variation. While the variation among species has been extensively studied with respect to mycorrhizal response traits, variation within species has rarely been examined. We conducted a systematic review and analyzed how much variation for mycorrhizal growth and nutrient response typically exists within a plant species. We assessed 26 publications that included 56 individual studies testing mycorrhizal response in at least five genotypes of a plant species, and we found that intraspecific trait variation for mycorrhizal response was generally very large and highly variable depending on study design. The difference between the highest and lowest growth response in a study ranged from 10% to 350% across studies, and 37 of the studies included species for which both positive and negative growth responses to mycorrhizae were observed across different genotypes. Phosphorus concentration and content were measured in 15 studies and variation was similar to variation in growth responses. We also found that plant genotype was just as important for predicting mycorrhizal response as the effects of fungal inoculant identity. Our analysis highlights not only the potential importance of intraspecific trait variation for mycorrhizal response but also the lack of research that has been done on the scale of this variation in plant species. Including intraspecific variation in research on the interactions between plants and their symbionts can increase our understanding of plant coexistence and ecological stability.

Oviposition and olfactometry response of codling moth (Cydia pomonella) to quince (Cydonia oblonga) cultivars

Behavioral data of codling moth (Cydia pomonella) mated females and larvae against quince (Cydonia oblonga) cultivars in laboratory assays.

Biomechanics of the Finger Pad in Response to Torsion

This dataset was used in the paper "Biomechanics of the Finger Pad in Response to Torsion".  The paper was not published at the time of dataset upload and no DOI was attributed to it yet. A preprint is available on bioRxiv, https://doi.org/10.1101/2022.11.07.515186. We refer the reader to this publication for detailed methods. In brief, we have made public : - The raw forces and platform kinematics files. - 1DxTime variables extracted from the videos such as displayed in our Fig. 2A. - 1D summary variables over trials (for example the angle at full slip for each trial).

Identification of the atmospheric water sources and pathways responsible for the East Asian summer monsoon rainfall

era_hydro_easm_jul2013_*.csv.gz: These three files are the raw output from the TRACMASS trajectory model. They stored positions of each trajectory at the start (ini file), during run (run file) and at the end (out file) during July 2013 and has been used for generating Figure 1. mask.nc: The basin definition in Figure 1 was plotted using this netcdf file. ep_traj_*.gz: The four zip files corresponds to four summer months (June, July, August, and September) and used to plot Figure 2. ep_traj_basins_*.gz: The four zip files corresponds to four summer months (June, July, August, and September) and used to plot Figure 3. quantification.gz: These files were used for quantification provided in Figure 4 and Figure 8. traj_pathways_*.gz: The two zip files (one for the South Indian Ocean, SIO and another for the Pacific Ocean, PAC) were used to generate Figure 5. traj_rt.gz:  The residence time of atmospheric waters in Figure 6 was created using the files in this zip. traj_age_*.gz: The two zip files (one for the South Indian Ocean, SIO and another for the Pacific Ocean, PAC) were used to generate Figure 7.

opencc-by-4.0Dec 2021View details →

Multi-Omic Approach Associates Blood Methylome with Bronchodilator Drug Response in Pediatric Asthma: Summary statistics

We conducted an epigenome-wide association study of bronchodilator drug response (BDR) in a discovery and validation design. The discovery phase was focused on 221 African American children with asthma. The association between DNA methylation and BDR was conducted using the limma package correcting for age, sex, ancestry, and tissue heterogeneity. Summary statistics include the output from toptable limma function and CpG annotation (based on Illumina EPIC Manifest file v 1.0 B4) organized in the following columns: <ul> <li>Probe: Probe ID</li> <li>Chr: chromosome</li> <li>Pos: genomic position based on GRCh37/hg19</li> <li>Gene: Gene annotation based on Illumina EPIC Manifest file v 1.0 B4</li> <li>logFC: estimate of the log2-fold-change corresponding to the effect or contrast</li> <li>SE: standard error</li> <li>AveExpr: average log2-expression for the probe over all arrays and channels</li> <li>t: moderated t-statistic</li> <li>P.value: raw p-value</li> <li>FDR: adjusted p-value by false discovery rate</li> <li>B: log-odds that the gene is differentially expressed</li> <li>Problem: Flagged potentially problematic probes</li> </ul>

Behavioral data for: A learning experience elicits sex-dependent neurogenomic responses in Bicyclus anynana butterflies

This is the behavioral data file that corresponds to the behavioral data reported in "A learning experience elicits sex-dependent neurogenomic responses in Bicyclus anyana butterflies" by D.A. Ernst, G.A. Agcaoili, A.N. Merrill, & E. L. Westerman, published in Molecular Ecology. It contains one spreadsheet, with all the behavioral data corresponding to the training, trainer, and naive butterflies utilized in the comparative brain and eye transcriptomics analyses conducted in the manuscript. In our study, we show that male and female B. anynana butterflies exhibit sexually dimorphic gene expression in the brain and eye during a learning event. We further identify genes that were associated with learning independent of sex and show that a number of genes known to influence wing pattern are also differentially expressed in the brain and eye during a mate choice learning event. The sexually dimorphic expression was not the result of baseline differences in activity levels, as males and females exhibited similar amounts of behavior during the training and naive experiences.

Data used in "Morphosedimentary Response of an Urban Beach System to Interannual Variability in Shorefast Ice Dynamics"

This dataset includes digital surface models (DSM) and orthomosaics of Tibbits Cove beach located along the St. Lawrence Fluvial Estuary (Québec, Canada). Surveys were conducted using a UAV before, during and after the 2021 and 2022 winter season. It also includes videos acquired with fixed cameras for these periods. For questions, please contact jean-francois.bernier@ggr.ulaval.ca.

Plant functional traits predict heterogeneous distributional shifts in response to climate change

Climate change is causing the rapid redistribution of vegetation as plant species move to track their climatic optima. Despite a global trend of upward movement in latitude and elevation, there is extensive heterogeneity among species and locations, with few emerging generalizations. Greater generalization may be achieved by considering multidimensional changes in species' distributions as well as incorporating ecologically relevant functional traits into studies of range shifts. To better understand how recent changes in climate are influencing the elevational distribution of plant species and how species' functional traits mediate distributional changes, we resampled a 2,438-meter elevation transect spanning a distance of 16 kilometers which encompasses desert scrub, pinyon-juniper woodland, chaparral, and coniferous forest plant communities. Over the last 42 years, total perennial cover and species' average cover increased at lower elevations and decreased at higher elevations while the average elevational leading-edge increased 116 m and the elevational rear edge decreased 84 m. Notably, these changes were mediated by species' functional traits, where species exhibiting more conservative traits (lower SLA, greater δ13C, larger seed mass) and taller height shifted upward in their leading-edge range limit, average elevation, and trailing edge range limit, while declining in abundance at the median and trailing edge of their range. Species possessing more acquisitive traits (higher SLA, lower δ13C, smaller seed mass) and shorter height shifted downward and increased in abundance at their trailing edge, with increases in their total range size. Our results provide clear evidence that heterogeneous range dynamics under recent climate change can be generalized by considering ecologically relevant plant functional traits, and how they respond to localized climate exposure. Further, by documenting changes across a steep ecological gradient comprising a large aridity gradient, we show divergent patterns for plants occupying contrasting positions along the global spectrum of plant form and function, which provides critical insight into how trait-mediated changes under increasing aridity will impact ecosystem functioning.

Data for: Local adaptation of switchgrass drives trait relations to yield and differential responses to climate and soil environments

Switchgrass, a potential biofuel crop, is a genetically diverse species with phenotypic plasticity enabling it to grow in a range of environments. Two primary divergent ecotypes, uplands and lowlands, exhibit trait combinations representative of acquisitive and conservative growth allocation strategies, respectively. Whether these ecotypes respond differently to various types of environmental drivers remains unclear but is crucial to understanding how switchgrass varieties will respond to climate change. We grew two upland, two lowland, and two intermediate/hybrid cultivars of switchgrass at three sites along a latitudinal gradient in the central United States. Over a 4-year period, we measured plant functional traits and biomass yields and evaluated genotype-by-environment (G´E) interaction effects by analyzing switchgrass responses to soil and climate variables. We found substantial evidence of G´E interactions on biomass yield, primarily due to deviations in the response of the southern lowland cultivar Alamo, which produced more biomass in hotter and drier environments relative to other cultivars. While lowland cultivars had the highest potential for yield, their yields were more variable year-to-year compared to other cultivars, suggesting greater sensitivity to environmental perturbations. Models comparing soil and climate principal components as explanatory variables revealed soil properties, especially nutrients, to be most effective at predicting switchgrass biomass yield. Also, conservative plant traits such as high stem mass and tiller height became increasingly positively associated with biomass yield at lower latitudes where the climate is hotter and drier, regardless of ecotype. Lowland cultivars, however, showed a greater predisposition to exhibit these conservative traits. These results suggest switchgrass trait allocation trade-offs that prioritize aboveground biomass production are more tightly associated in hot, dry environments and that lowland cultivars may exhibit a more specialist life strategy relative to other cultivars. Altogether, this research provides essential knowledge for improving the viability of switchgrass as a biofuel crop.

Global variation in nonstructural carbohydrate stores in response to climate

Woody plant species store nonstructural carbohydrates (NSCs) for many functions. While known to buffer against fluctuations in photosynthetic supply, such as at night, NSC stores are also thought to buffer against environmental extremes, such as drought or freezing temperatures by serving as either back-up energy reserves or osmolytes. However, a clear picture of how NSCs are shaped by climate is still lacking. Here, we update and leverage a unique global database of seasonal NSC storage measurements to examine whether maximum total NSC stores and the amount of soluble sugars are associated with clinal patterns in low temperatures or aridity, indicating they may confer a benefit under freezing or drought conditions. We examine patterns using the average climate at each study site and the unique climatic conditions at the time and place in which the sample was taken. Altogether, our results support the idea that NSC stores act as critical osmolytes. Soluble Sugars increase with both colder and drier conditions in aboveground tissues, indicating they can plastically increase a plants' tolerance of cold or arid conditions. However, maximum total NSCs increased, rather than decreased, with average site temperature and had no relationship to average site aridity. This result suggests that the total amount of NSCs that a plant stores may be more strongly determined by its capacity to assimilate carbon than by environmental stress. Thus, NSCs are unlikely to serve as reservoirs of energy. This study is the most comprehensive synthesis to date of global NSC variation in relation to climate and supports the idea that NSC stores likely serve as buffers against environmental stress. By clarifying their role in cold and drought tolerance, we improve our ability to predict plant response to environment.

opencc-by-4.0Jan 2023View details →

Processed CMIP6 data for "The climate response to the Mt Pinatubo eruption does not constrain climate sensitivity"

Processed CMIP6 output for Pauling et al. "The climate response to the Mt Pinatubo eruption does not constrain climate sensitivity" submitted to Geophysical Research Letters in 2023. Download this code repository: https://doi.org/10.5281/zenodo.7553024 and follow the instructions in the README to download data and reproduce the results of the paper.

Distinct responses and range shifts of lizards populations across an elevational gradient under climate change

Ongoing climate change has profoundly affected global biodiversity, but its impacts on populations across elevations remain understudied. Using a mechanistic niche model incorporating species traits, we predicted ecophysiological responses (activity times, oxygen consumption and evaporative water loss) for lizard populations at high-elevation (< 3600 m asl) and extra-high-elevation (> 3600 m asl) under recent (1970–2000) and future (2081–2100) climates. Compared with their high-elevation counterparts, lizards from extra-high-elevations are predicted to experience a greater increase in activity time and oxygen consumption but a similar increase in evaporative water loss. By integrating these ecophysiological traits into a hybrid species distribution model (HSDM), we were able to make the following predictions under two warming scenarios (SSP1-2.6, SSP5-8.5). By 2081–2100, we predict that lizards at both high- and extra-high-elevations will shift upslope; lizards at extra-high-elevations will gain more and lose less habitat than will their high-elevation congeners. We therefore advocate the conservation of high-elevation species in the context of climate change, especially for those populations living close to their lower elevational range limits. In addition, by comparing the results from HSDM and traditional species distribution models, we highlight the importance of considering intraspecific variation and local adaptation in physiological traits along elevational gradients when forecasting species' future distributions under climate change.

Data from: Functionally analogous body- and animacy-responsive areas in the dog (Canis familiaris) and human occipito-temporal lobe

Comparing the neural correlates of socio-cognitive skills across species provides insights into the evolution of the social brain and has revealed face- and body-sensitive regions in the primate temporal lobe. Although from a different lineage, dogs share convergent visuo-cognitive skills with humans and a temporal lobe which evolved independently in carnivores. We investigated the neural correlates of face and body perception in dogs (N = 15) and humans (N = 40) using functional MRI. Combining univariate and multivariate analysis approaches, we found functionally analogous occipito-temporal regions involved in the perception of animate entities and bodies in both species and face-sensitive regions in humans. Though unpredicted, we also observed neural representations of faces compared to inanimate objects, and dog compared to human bodies in dog olfactory regions. These findings shed light on the evolutionary foundations of human and dog social cognition and the predominant role of the temporal lobe. This data set contains: <ul> <li>raw functional neuroimaging data of N = 15 dogs</li> <li>structural scans of the same dogs incl. brain masks & skull-stripped versions</li> <li>files containing the condition names, onsets and durations for each dog and task run</li> <li>files containing the motion regressors incl. motion scrubbing for each dog and task run</li> </ul> Data of the comparative human neuroimaging sample will be made available by the first author upon reasonable request. Please also visit our Open Science Framework project site for detailed sample descriptives and group-level imaging data of both species (<a href="https://osf.io/kzcs2/">https://osf.io/kzcs2/</a>).

Dataset 2: The plant response to high CO2 levels is heritable and orchestrated by DNA methylation

This is a supporting dataset from the manuscript “The plant response to high CO2 levels is heritable and orchestrated by DNA methylation” by Panda et al. This dataset was used to study trans-generational growth responses to environments with contrasting CO2 levels. Raspberry Pi computers and cameras were used to image Arabidopsis thaliana wild-type (Columbia) and mutant (ago1-27, cmt2-7/cmt3-11t, ddm1-2, met1, pol IV, suvh4/suvh5/suvh6, and ubp1b) plants growing under ambient (450-500 ppm) and high (1000 ppm) CO2 conditions. Imaging was done hourly from overhead beginning on the 8th day after sowing and continued until the 25th day after sowing. Dataset 2 contains images of plants grown in the second round of the experiment under ambient and high CO2 conditions.

Dataset 1: The plant response to high CO2 levels is heritable and orchestrated by DNA methylation

This is a supporting dataset from the manuscript “The plant response to high CO2 levels is heritable and orchestrated by DNA methylation” by Panda et al. This dataset was used to study trans-generational growth responses to environments with contrasting CO2 levels. Raspberry Pi computers and cameras were used to image Arabidopsis thaliana wild-type (Columbia) and mutant (ago1-27, cmt2-7/cmt3-11t, ddm1-2, met1, pol IV, suvh4/suvh5/suvh6, and ubp1b) plants growing under ambient (450-500 ppm) and high (1000 ppm) CO2 conditions. Imaging was done hourly from overhead beginning on the 8th day after sowing and continued until the 25th day after sowing. Dataset 1 contains images of plants grown in the first round of the experiment under ambient and high CO2 conditions.

Dataset 3: The plant response to high CO2 levels is heritable and orchestrated by DNA methylation

This is a supporting dataset from the manuscript “The plant response to high CO2 levels is heritable and orchestrated by DNA methylation” by Panda et al. This dataset was used to study trans-generational growth responses to environments with contrasting CO2 levels. Raspberry Pi computers and cameras were used to image Arabidopsis thaliana wild-type (Columbia) and mutant (ago1-27, cmt2-7/cmt3-11t, ddm1-2, met1, pol IV, suvh4/suvh5/suvh6, and ubp1b) plants growing under ambient (450-500 ppm) and high (1000 ppm) CO2 conditions. Imaging was done hourly from overhead beginning on the 8th day after sowing and continued until the 25th day after sowing. Dataset 3 contains images of the plants grown in the third round of the experiment under ambient and high CO2 conditions. Plants were the progeny of plants from the first and second rounds.

Data for the manuscript named 'Altitude-dependence response near cusp region after solar wind variations'

Data for the manuscript named 'Altitude-dependence response near cusp region after solar wind variations 1) cluster data, observation from cluster mission 2) MAD6400_2001-10-12_tau1a_59.4@vhfa_041292, EISCAT radar data 3) OMNI: solar wind and IMF data 4) p_shell_5.7Re_011012 is thermal pressure at 5.7 Re-shell, which was carried out in real-time solar wind conditions during 08:30-10:00UT (real-time-density run) 5) p_shell_5.7Re_011012cd is thermal pressure at 5.7 Re-shell, which was carried out in real-time solar wind conditions except for solar wind density  during 08:30-10:00UT (no-density-increasing run)  “1_5.7Rshell_out.txt”time_latitude_out “1P_shell_5.7Re.csv”time_shell_5.7Re data range: MLT 08:00~16:00, latitude -90°~ -30°

Data and analysis of proteomic responses to hexokinase-II depletion in GAL80 and gal80Δ Saccharomyces cerevisiae with an engineered sesquiterpene-pathway

Dataset 1: <a href="https://zenodo.org/api/files/ece3309f-0ca2-4773-b2e3-b1c5c839faa4/GAL80_HXK2_Vs._dhxk2p_20200324_T2_004.xlsx">GAL80_HXK2_Vs._dhxk2p_20200324_T2_004.xlsx</a> The comparison between strain ILHA o128R+pJT9RFR (dHxk2p) and ILHA o401R+ pJT9RFR (HXK2) under the conditions with the addition of 1-Naphthaleneacetic acid and in the exponential growth phase and the ethanol growth phase.    Dataset 2: <a href="https://zenodo.org/api/files/ece3309f-0ca2-4773-b2e3-b1c5c839faa4/gal80%CE%94_HXK2_Vs._dhxk2p_20200219_T1_004.xlsx">gal80Δ_HXK2_Vs._dhxk2p_20200219_T1_004.xlsx</a> The comparison between strain ILHA NLD128-1 (dHxk2p) and ILHA NLD401 (HXK2) under the conditions with the addition of 1-Naphthaleneacetic acid and in the exponential growth phase (EXP) and the ethanol growth phase (ETH).

Data for Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in the antibiotic response

Data from simulations used to generate the figures in the paper Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in the antibiotic response. To reproduce analyses, extract colony_data.zip in the data folder after cloning the vivarium-ecoli repository. The extracted folder contains the following items: <ul> <li>sim_dfs: a folder containing the CSV files that represent a subset of the raw simulation data used for downstream analyses.</li> <li>glc_10000_fluxome.csv: Each row represents a reaction in central carbon metabolism (in same order as listed in validation/ecoli/flat/toya_2010_central_carbon_fluxes.tsv). Each column represents a single time point for a single cell in a baseline glucose simulation (seed 10000). Each value is a flux (mmol/L/hr). Provided as input to ecoli/analysis/centralCarbonMetabolism.py script to reproduce fluxome validation plot.</li> <li>glc_10000_proteome_avgs.csv: Each row represents a protein monomer (in same order as sim_data.translation.monomer_data["id"] where sim_data is reconstruction/sim_data/kb/validationData.cPickle). Each column represents a cell in a baseline glucose simulation (seed 10000). Each row represents a protein monomer. Each value represents the average count of a given protein monomer for a given cell. Provided as input to ecoli/analysis/proteinCountsValidation.py script to reproduce proteome validation plot.</li> <li>glc_10000_expressome.csv: Each column represents a gene (with the exception of the final two metadata columns: "Time" and "Agent ID"). Each row represents a specific cell (agent) at a specific time in a baseline glucose simulation (seed 10000). Each value represents the number of new RNA transcripts for a given gene in a given cell at a given time. Provided as input to ecoli/analysis/antibiotics_colony/subgen_gene_plots/count_subgen.py script to calculate number of sub-generational genes among all genes and antibiotic response genes.</li> <li>glc_10000_total_mrna.json: Mapping of agent IDs for all cells in a baseline glucose simulation (seed 10000) to their average total mRNA count. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. 2C,D.</li> <li>jenner_2013.csv: Data extracted from Fig. 2C of <a href="https://doi.org/10.1073/pnas.1216691110">10.1073/pnas.1216691110</a>. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. S6A.</li> <li>olson_2006.csv: Data extracted from Fig. 2D of <a href="https://doi.org/10.1128%2FAAC.01499-05">10.1128/AAC.01499-05</a>. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. S6A.</li> <li>lysis_ratios.csv: Data extracted from Fig. 2 of <a href="https://doi.org/10.1099/00221287-31-3-339">10.1099/00221287-31-3-339</a>. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. 4N.</li> </ul>