Find research datasets worth reusing

opencc-zeroFeb 2022View details →

Data from: Scale-dependence of landscape heterogeneity effects on plant invasions

Invasive alien species are amongst the most concerning threats to native biodiversity worldwide, and the level of landscape heterogeneity is considered to affect spatial patterns of their occurrence and spread. However, as previous studies on these associations report contrasting results, the role of landscape heterogeneity on its susceptibility to invasions remains poorly understood. Landscape heterogeneity is usually described by two measures: configuration and composition. Both measures may differently affect invasive species and these impacts may be additionally scale-dependent. Nevertheless, their relative contribution to invasion patterns is poorly known. We investigated the effect of two landscape heterogeneity components: configuration (edge density) and composition (number and evenness of land-cover types) measured at different spatial scales (from within 0.25 km to 5 km of the studied localities) on the local abundance of one of the most invasive alien plant species in Europe, the North American goldenrods (Solidago canadensis and S. gigantea). Using publicly available geospatial environmental data and a novel method based on remote analysis of Google Street View images, we collected and analyzed large dataset on goldenrod occurrence along 1347 roadside transects in agricultural landscapes of Poland. Both the compositional and configurational heterogeneity were positively associated with the local abundance of goldenrods, however the effect size of these relationships was dependent on spatial scale. While abundance-heterogeneity associations were most pronounced at the largest spatial scale for compositional heterogeneity, the pattern was the opposite for configurational heterogeneity. Landscape heterogeneity is a clear correlate of plant invasion potential, with occurrences of invasive plants generally higher in more heterogeneous landscapes. However, scale-dependence of this association means that researchers and practitioners may miss the association if only concentrating on a single spatial scale. While increasing heterogeneity of rural landscapes is widely introduced as a way to promote farmland biodiversity, we show that it may also support invasive plants and thus conflict with original goals of biodiversity-oriented strategies. Therefore, we suggest implementing regular management and eradication schemes in most heterogeneous landscapes. Finally, we demonstrate how remote analysis of plant invasions using existing imagery can advance our understanding of invasion biology.

opencc-by-4.0Feb 2022View details →

Dataset for "Size-dependence of Aerosol Iron Solubility in an Urban Atmosphere"

Online PM concentration/weather condition and offline aerosol composition data for the study of "size-dependence of aerosol iron solubility in an urban atmosphere".

opencc-by-4.0Sep 2020View details →

The Surface Composition of Amino Acid - Halide Salt Solutions is pH-Dependent

Set of raw data which has been used for the publication. In short, it's about how the pH of a mixed solution of an amino acid and an inorganic halogen salt impacts the surface propensity of the inorganic ions.

opencc-by-4.0Mar 2022View details →

Raw experimental data and matlab codes for the paper "State-dependent driving : A route to non-equilibrium stationary states"

Raw experimental data and matlab codes used for numerical simulation in the paper - "State-dependent driving : A route to non-equilibrium stationary states". The data and codes to generate figures 2, 3 and 5 are available in the folders named "Fig 2", "Fig 3" and "Fig 5" respectively.

opencc-by-4.0Mar 2022View details →

Data set for: History-dependent domain and skyrmion formation in 2D van der Waals magnet Fe3GeTe2

This data repository contains the experimental data utilised to produce the figures shown in History-dependent domain and skyrmion formation in 2D van der Waals magnet Fe3GeTe2, by M. T. Birch, L. Powalla, S. Wintz, O. Hovorka, K. Litzius, J. C. Loudon, L. A. Turnbull, V. Nehruji, K. Son, C. Bubeck, T. G. Rauch, M. Weigand, E. Goering, M. Burghard, G. Schütz. Experimental data analysis were performed using Python via Jupyter notebooks, utilising matplotlib, scipy, numpy and h5py libraries. Jupyter notebooks are provided to process some of the experimental data to form the figures shown in the paper. Data data is divided into folders: Characterisation_Data - contains EDX, TEM and AFM characterisation of the bulk FGT material and exfoliated flakes. Magnetometry_Data - Includes data files from the MPM3 magnetometry utilised to study the magnetisation of the bulk FGT crystal as a function of temperature and applied magnetic field. The two sub folders divide the files into data acquired with the field applied either parallel to the c axis (OOP - out of plane), or perpendicular to the c axis (IP - in plane). STXM_Data - Contains Scanning Transmission X-ray Microscopy data acquired at the MAXYMUS instrument at the BESSY II synchrotron, Berlin. The data is divided into sections acquired following different sample histories, as reported in the main paper: field sweep, field-cooled and zero-field cooled. Folders containing the extracted skyrmion sizes and stripe domain sizes are included, as well as Python notebooks for plotting Fig. 3, 4 and 5 of the main paper. Spectra_Data - Contains x-ray absorption spectra acquired on a bulk FGT crystal via total electron yield method (Bulk spectra), and spectra acquired on the exfoliated FGT flake by a transmission method (Flake Spectra). The accompanying jupyter notebook demonstrates the plotting and application of XMCD sum rules to the experimental data. LTEM_Data - Contains images acquired via Lorentz Transmission Electron Microscopy of an FGT flake, measured as a function of temperature and applied magnetic field at various tilt angles. Analysis_Scripts - Contains python notebook for plotting the magnetic phase diagrams, and plotting the thickness dependence estimation from the x-ray absorption spectra data. Meanfield_Simulations - Contains the raw output files of the simulations, the .h5 files, and Python notebook plotting scripts. Summary pdf files show the output of all simulation runs for the field sweep performed at each temperature.  The latest version of this Data Set can be found at the Zenodo DOI: 10.5281/zenodo.6346695 Any further requests for materials are welcome, send any inquiries to Max Birch at birch@is.mpg.de

opencc-by-4.0Mar 2022View details →

Data from: Net plant interactions are highly variable and weakly dependent on climate at the global scale

Data were collected from the literature. The dataset is a compilation of published studies. An ISI Web of Science search covering the time period from 1900 onwards was conducted to identify the publications on plant interactions. Each publication was individually reviewed, and the reference list was inspected to identify additional relevant publications. We collected a total 1,220 publications for data compilation. We built a global dataset of 10,502 pairs of plant interaction data.

opencc-zeroMar 2022View details →

Do natural enemies mediate conspecific negative distance- and density-dependence of trees? A meta-analysis of exclusion experiments

Conspecific negative distance- and density-dependence is believed to be one of the most important mechanisms controlling forest community assembly and species diversity globally. Plant pathogens, and insect and mammalian herbivores, are the most common natural enemy types that have been implicated in this phenomenon, but their general effects at different plant life stages are still unclear. Here, we conduct a meta-analysis of studies that involved robust manipulative experiments, using fungicides, insecticides, or exclosures, to assess the contributions of different natural enemy types to distance- and density-dependent effects at seed and seedling stages. We found that conspecific negative distance- and density-dependence was more common at the seedling stage. Only 30% of studies showed significant conspecific negative distance- and density-dependence. Among those studies, applying fungicides significantly reduced the effect of conspecific negative distance -dependent mortality. Excluding large mammals reduced the effect of conspecifics, but with only marginal significance (p < 0.1). Our study confirms that plant pathogens have a significant impact on distance -dependent mortality and suggests that the impacts of herbivores on seedlings have been understudied. At the seed stage, large and small mammals, respectively, appear to weaken and enhance negative conspecific distance-dependent mortality. Future research should identify specific agents of mortality, investigate the interactions among different enemy types, and assess how global change may affect natural enemies and thus influence the strength of conspecific distance- and density-dependence.

Raw data for Hancock-Cerutti et. al. "ER-lysosome lipid transfer protein VPS13C/PARK23 prevents aberrant mtDNA-dependent STING signaling"

Blot images and tabular data for Hancock-Cerutti et. al. "ER-lysosome lipid transfer protein VPS13C/PARK23 prevents aberrant mtDNA-dependent STING signaling"

Sequence-dependent model of genes with dual σ factor preference

Escherichia coli uses s factors to quickly control large gene cohorts during stress conditions. While most of its genes respond to a single s factor, approximately 5% of them have dual s factor preference. The most common are those responsive to both s70, which controls housekeeping genes, and s38, which activates genes during stationary growth and stresses. Using RNA-seq and flow-cytometry measurements, we show that 'σ70+38 genes' are nearly as upregulated in stationary growth as 'σ38 genes'. Moreover, we find a clear quantitative relationship between their promoter sequence and their response strength to changes in σ38 levels. We then propose and validate a sequence dependent model of σ70+38 genes, with dual sensitivity to s38 and s70, that is applicable in the exponential and stationary growth phases, as well in the transient period in between. We further propose a general model, applicable to other stresses and σ factor combinations. Given this, promoters controlling σ70+38 genes (and variants) could become important building blocks of synthetic circuits with predictable, sequence-dependent sensitivity to transitions between the exponential and stationary growth phases.

Long-term resilience of primary sex ratios in a species with temperature dependent sex determination after decades of climate warming

Species with environmental sex determination (ESD) have persisted through deep time, despite massive environmental perturbation in the geological record. Understanding how species with temperature-dependent sex determination (TSD), a type of ESD, persist through climate change is particularly timely given the current climate crisis, as highly biased sex ratios and extinction are predicted. Since 1982, we have studied primary sex ratios of a reptile with TSD (Chelydra serpentina). Primary sex ratios remained unchanged over time, despite warming in the environment. Resilience of the primary sex ratio occurred via a portfolio effect, realized through remarkable intra-annual variation in nest-level sex ratios, leading to a relatively consistent mean annual sex ratio. Intra-annual variation in nest-level sex ratios was related to variation in egg burial depth coupled with large clutch sizes, creating thermal gradients in the nest, and promoting mixed-sex clutches. Further, both locally and globally, sustained increases in nighttime air temperature contribute more to warming than increases in daily maximum temperature, but development rate was affected more strongly by maximum daily air temperature, conferring additional resilience to overall warming. Our study suggests that some TSD species may be resilient to warming and provides an example of how ESD may persist under environmental change.

Subarctic soil carbon losses after deforestation for agriculture depend on permafrost abundance - study data

Contains the dataset and R code used for the study "Subarctic soil carbon losses after deforestation for agriculture depend on permafrost abundance".

Data from: Condition-dependent immune function in a freshwater snail revealed by stable isotopes

Data are saved as a tab-delimited text file (data.txt). Each row represents one snail individual.   The file has the following columns: infection - trematode infection (0 = no, 1 = yes) PO_activity - PO-like activity of haemolymph antibacterial_activity - antibacterial activity of haemolymph shell_length - shell length (mm) faeces - amount of produced faeces (mg) d15N_faeces - δ15N value of faeces d13C_faeces - δ13C value of faeces C:N_faeces - C:N ration of faeces d15N_tissue - δ15N value of tissue d13C_tissue - δ13C value of tissue C:N_tissue - C:N ration of tissue

Eco-evolutionary dynamics modulate plant responses to global change depending on plant diversity and species identity

Global change has dramatic impacts on grassland diversity. However, little is known about how fast species can adapt to diversity loss and how this affects their responses to global change. Here, we performed a common garden experiment testing whether plant responses to global change are influenced by their selection history and the conditioning history of soil at different plant diversity levels. Using seeds of four grass species and soil samples from a 14-year-old biodiversity experiment, we grew the offspring of the plants either in their own soil or in soil of a different community, and exposed them either to drought, increased nitrogen input, or a combination of both. Under nitrogen addition, offspring of plants selected at high diversity produced more biomass than those selected at low diversity, while drought neutralized differences in biomass production. Moreover, under the influence of global change drivers, soil history, and to a lesser extent plant history, had species-specific effects on trait expression. Our results show that plant diversity modulates plant-soil interactions and growth strategies of plants, which in turn affects plant eco-evolutionary pathways. How this change affects species' response to global change and whether this can cause a feedback loop should be investigated in more detail in future studies.

In-vitro dataset for classification and regression of stenosis: dependence on heart rate, waveform and location

Background This data supplements the paper "Classification and regression of stenosis using an in-vitro pulse wave dataset: dependence on heart rate, waveform and location".  It was created at Technische Hochschule Mittelhessen (THM) in Germany and uploaded to Zenodo. Please cite the paper (<a href="https://doi.org/10.1016/j.compbiomed.2022.106224">https://doi.org/10.1016/j.compbiomed.2022.106224</a>) and the Zenodo doi when using this dataset. General description / Dataset structure Each mat-File describes a different measurement (details can be found in the paper). There are 17 pressure signals for different positions, one flow sensor close to the stenosis location and one monitor signal of the proportional valve use to control the input curve. Total duration of each signal is 60s with a sampling rate of 1000 Hz. Each mat-file contains a header structure with metadata and struct array for signals of each sensor. Signals in each mat-File are aligned with respect to a common time axis, but this is not guaranteed between different measurements/files. We did our best to make the beginnings end endings align as close as possible (by removing buffer artefacts and aligning the input signal of the monitor), however algorithms should not rely on a global time axis. This similar to patient measurements without an ekg, this does also not share a global time axis comparable among patients. The file format can either be loaded directly in Matlab or in Python with scipy's loadmat function. The data is structure first by stenosis "state" (or location) then by heart rate and then by heart waveform. The stenosis "states" can devided in 1 subset of 10 folders created for regression and 6 created for classification. Excerpt of the folder structure: <ul> <li>No Stenosis <ul> <li>HR 50 <ul> <li>WaveForm1.mat</li> <li>WaveForm2.mat</li> <li>...</li> </ul> </li> <li>HR 55 <ul> <li>...</li> </ul> </li> <li>...</li> </ul> </li> <li>Regression - Stenosis at Pos01 <ul> <li>HR 50 <ul> <li>...</li> </ul> </li> <li>...</li> </ul> </li> <li>...</li> </ul> The tools also available at this page help with traversing this folder structure and are available for Python and Matlab. Data Fields of each file <table> <caption>headerStruct</caption> <thead> <tr> <th scope="col">field</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>id</td> <td>internal database id</td> </tr> <tr> <td>name</td> <td>stenosis location</td> </tr> <tr> <td>rate</td> <td>sampling rate in Hz</td> </tr> <tr> <td>description</td> <td>definition of automatic parameter sweep range</td> </tr> <tr> <td>configuration</td> <td>concrete parameters of the trapezoidal input curve (offset and amplitude in mmHg, ascend times and descend times and smoothing window in a fraction the time period (1.2s))</td> </tr> </tbody> </table>   <table> <caption>signalStruct</caption> <thead> <tr> <th scope="col">field</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>nodeId</td> <td>corresponds to numbered nodes at which the sensor is placed, the corresponding location can be found in the technical paper describing the MACSim simulator (node numbering, not sensor numbers) or in the software SISCA in the example database.</td> </tr> <tr> <td>type</td> <td>'p' ... pressure or 'q' ... flow</td> </tr> <tr> <td>data</td> <td>double array, time series of each sensor,  unit mmHg for type 'p' and ml/s for type 'q'</td> </tr> <tr> <td>anatomicalPosition</td> <td>name of the corresponding anatomical position</td> </tr> </tbody> </table> Tools: This Tools should make it easier to load the dataset. The usage is documented in the respective code files. Code for the publication is available here: https://gitlab.com/agbernhard.lse.thm/publication_macsim_machinelearning

Data from: Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats

The repeatability of adaptive radiation is expected to be scale dependent, with determinism decreasing as greater spatial separation among "replicates" leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation -their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale-dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.

Resource-dependent investment in male sexual traits in a viviparous fish

Exaggerated and conspicuous sexually selected traits are often costly to produce and maintain. Costly traits are expected to show resource-dependent expression, since limited resources prevent animals from investing maximally in multiple traits simultaneously. However, there may be critical periods during an individual's life where the expression of traits is altered if resources are limited. Moreover, costly sexual traits may arise from sexual selection acting both before (pre-copulatory) and after mating (post-copulatory). Gaining a robust understanding of resource-dependent trait expression therefore requires an approach that examines both episodes of sexual selection following resource limitation during different times in an individual's life. Yet few studies have taken such an approach. Here, we examine how resource restriction influences a set of pre- and post-copulatory traits in male pygmy halfbeaks (Dermogenys collettei), which invest in sexual ornaments and routinely engage in male-male contests and sperm competition. Critically, we examined responses in males when resources were restricted during development and after reaching sexual maturity. Both pre- and post-copulatory traits are resource-dependent in male halfbeaks. Body size, beak size, courtship behavior, and testes size were reduced by diet restriction, while, unexpectedly, the restricted-diet group had a larger area of red color on the beak and fins after diet treatment. These patterns were generally consistent when resources were restricted during development and after reaching sexual maturity. The study reinforces the role of resource acquisition in maintaining variation among sexual traits.

opencc-by-4.0May 2022View details →

Data for: "Above and below ground trait coordination in tree seedlings depend on the most limiting resource: A test comparing a wet and a dry tropical forest in Mexico" by L. Sanaphre-Villanueva, F. Pineda-Garcia, W. Dattilo, L. F. Pinzon-Perez, A. Ricaño Rocha, H. Paz.

These data represent those published in “Above and below ground trait coordination in tree seedlings depend on the most limiting resource: A test comparing a wet and a dry tropical forest in Mexico” by L. Sanaphre-Villanueva, F. Pineda-Garcia, W. Dattilo, L. F. Pinzon-Perez, A. Ricaño Rocha, H. Paz. PeerJ. 2022.

opencc-zeroMay 2022View details →

Strong selective environments determine evolutionary outcome in time-dependent fitness seascapes

The impact of fitness landscape features on evolutionary outcomes has attracted considerable interest in recent decades. However, evolution often occurs under time-dependent selection in so-called fitness seascapes where the landscape is under flux. Fitness seascapes are an inherent feature of natural environments, where the landscape changes owing both to the intrinsic fitness consequences of previous adaptations and extrinsic changes in selected traits caused by new environments. The complexity of such seascapes may curb the predictability of evolution. However, empirical efforts to test this question utilising a comprehensive set of regimes are lacking. Here we employed an in vitro microbial model system to investigate differences in evolutionary outcomes between time-invariant and -dependent environments, including all possible temporal permutations, with three subinhibitory antimicrobials and a viral parasite (phage) as selective agents. Expectedly, time-invariant environments caused stronger directional selection for resistances compared to time-dependent environments. Intriguingly, however, multidrug resistance outcomes in both cases were largely driven by two strong selective agents (rifampicin and phage) out of four agents in total. These agents either caused cross-resistance or obscured the phenotypic effect of other resistance mutations, modulating the evolutionary outcome overall in time-invariant environments and as a function of exposure epoch in time-dependent environments. This suggests that identifying strong selective agents and their pleiotropic effects is critical for predicting evolution in fitness seascapes, with ramifications for evolutionarily informed strategies to mitigate drug resistance evolution.

opencc-zeroMay 2022View details →

Is negative density-dependent reproduction regulated by density-induced stress in root voles? Two field experiments

Density dependence in reproduction plays an important role in stabilising population dynamics via immediate negative feedback from population density to reproductive output. Although previous studies have shown that negative density-dependent reproduction is associated with strong spacing behaviour and social interaction between individuals, the proximal mechanism for generating negative density-dependent reproduction remains unclear. In this study, we investigated the effects of density-induced stress on reproduction in root voles. Enclosed Founder populations were established by introducing six (low density) and 30 (high density) adults per sex into per enclosure (four enclosures per density in total) during the breeding season from April to July 2012 and from May to August 2015. Faecal corticosterone metabolite (FCM) levels, reproductive traits (recruitment rate and the proportion of reproductively active indivuduals), and founder population numbers were measured following repeated live-trapping in both years. The number of founders was negatively associated with recruitment rates and the proportion of reproductively active indivuduals, displaying a negative density-dependent reproduction. FCM level was positively associated with the number of founders. The number of founder females directly affected the proportion of reproductive females , and directly and indirectly through their FCM levels affected the recruitment rate; the effect of the number of male founders on the proportion of reproductive males was mediated by their FCM level. Our results showed that density-induced stress negatively affected reproductive traits and that density-induced stress is one ecological factor generating negative density-dependent reproduction.