Find research datasets worth reusing

opencc-by-4.0Nov 2021View details →

Code and data for 'Bacillus subtilis histidine kinase KinC activates biofilm formation by controlling heterogeneity of single-cell responses'

Code and data used in the paper 'Bacillus subtilis histidine  kinase KinC activates biofilm formation by controlling heterogeneity of single-cell responses'  https://doi.org/10.1128/mBio.01694-21

Mutation and methylation data for study: Assessment of the molecular heterogeneity of E-cadherin expression in invasive lobular breast cancer

Processed mutation data and DNA methylation beta values published with this study.

Data, code, and manual for analysis of image heterogeneity in mass spectrometric imaging.

This upload contains all replication material for "The software for interactive evaluation of mass spectrometric imaging heterogeneity" (forthcoming). Authors: E.S. Zhvansky, E.V. Zhdanova, M.S. Belenikin, M.A. Shamraeva, S.V. Silkin, K.V. Bocharov, A.A. Sorokin. Code, manual, and data are located within Interactive_CSMM.zip. Code is written MATLAB R2019b and Python 3.5.2. Please find the README.md for code using and the code to replicate the main findings of the paper described below: <ul> <li>imzml2mat.py in conversion directory for file conversion.</li> <li>CSMM.m for application start.</li> <li>40TopL,10TopR,30BottomL,20BottomR-centroid.mat - data in conversion/Data directory for reproducing the results.</li> <li>User_manual.pdf - manual.</li> <li>mp4 files - screencasts.</li> </ul>

Representing surface heterogeneity in land-atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime - E3SM SCM data and code

This dataset contains post-processed E3SM single-column model output and code used to produce the figures in the manuscript that we are targeting Geoscientific Model Development to submit.

Raw data for "Condensates in RNA repeat sequences are heterogeneously organized and exhibit reptation dynamics"

This is the raw data for the paper "Condensates in RNA repeat sequences are heterogeneously organized and exhibit reptation dynamics". There are 5 directories. Three correspond to the CAG repeats with different length (20, 31 and 47). The "scramble47" directory stores data for the scrambled sequence. "Electrostatics" has data for the electrostatics run (see details in Extended Data Fig. 9). Each directory of CAG contains multiple sub-directories corresponding to different concentrations.

opencc-zeroDec 2021View details →

Data from: Landscape heterogeneity filters functional traits of rice arthropods in tropical agroecosystems

Biological control services of agroecosystems depend on the functional diversity of species traits. However, the relationship between arthropod traits and landscape heterogeneity is still poorly understood, especially in tropical rice agroecosystems which harbour a high diversity of often specialized species. We investigated how landscape heterogeneity, measured by three metrics of landscape composition and configuration, influenced body size, functional group composition, dispersal ability and vertical distribution of rice-arthropods in the Philippines. We found that landscape composition and configuration acted to filter arthropod traits in tropical rice agroecosystems. Landscape diversity and rice habitat fragmentation were the two main gradients influencing rice-arthropod traits, indicating that different rice-arthropods have distinct habitat requirements. Whereas small parasitoids and species mostly present in the rice-canopy were favoured in landscapes with high compositional heterogeneity, predators and medium-sized species occupying the base of the rice plant, including planthoppers, mostly occurred in highly fragmented rice habitats. We demonstrate the importance of landscape heterogeneity as an ecological filter for rice-arthropods, identifying how the different components of landscape heterogeneity selected for or against specific functional traits. However, the contrasting effects of landscape parameters on different groups of natural enemies indicate that not all beneficial rice-arthropods can be promoted at the same time when using a single land management strategy. Increasing compositional heterogeneity in rice landscapes can promote parasitoids but may also negatively affect predators. Future research should focus on identifying trade-offs between fragmented rice habitats and structurally diverse landscapes to maximize the presence of multiple groups of beneficial arthropods.

opencc-by-4.0Jan 2022View details →

Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors - Scripts & Source data

Source data and scripts to reproduce the figures that are part of the publication "Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors". Journal of Cell Science (2022) 135, jcs259685, DOI: 10.1242/jcs.259685   An earlier version of this work is published as a preprint: "Heterogeneity and dynamics of ERK and Akt activation by G protein-coupled receptors depend on the activated heterotrimeric G proteins", DOI: <a href="https://doi.org/10.1101/2021.07.27.453948">10.1101/2021.07.27.453948</a>

opencc-by-4.0Feb 2022View details →

Data sets for 'Mechanical Compliance of Individual Fractures in a Heterogeneous Rock Mass from Production-type Full-waveform Sonic Data', submitted to JGR: Solid Earth

Synthetic and field FWS data sets are supplied for validation of proposed methods for compliance estimation of individual fractures. Each zip contains ‘ReadMe.txt ‘, which illustrates the files and corresponding parameters. More details about the setup in the submitted paper ‘Mechanical Compliance of Individual Fractures in a Heterogeneous Rock Mass from Production-type Full-waveform Sonic Data’.

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-zeroNov 2022View details →

Data from: Sharing detection heterogeneity information among species in community models of occupancy and abundance can strengthen inference

1. The estimation of abundance and distribution and factors governing patterns in these parameters is central to the field of ecology. The continued development of hierarchical models that best utilize available information to inform these processes is a key goal of quantitative ecologists. However, much remains to be learned about simultaneously modeling true abundance, presence, and trajectories of ecological communities. 2. Simultaneous modeling of the population dynamics of multiple species provides an interesting mechanism to examine patterns in community processes and, as we emphasize herein, to improve species-specific estimates by leveraging detection information among species. Here we demonstrate a simple but effective approach to share information about observation parameters among species in hierarchical community abundance and occupancy models, where we use shared random effects among species to account for spatiotemporal heterogeneity in detection probability. 3. We demonstrate the efficacy of our modeling approach using simulated abundance data, where we recover well our simulated parameters using N-mixture models. Our approach substantially increases precision in estimates of abundance compared to models that do not share detection information among species. We then expand this model, and apply it to repeated detection/non-detection data collected on six species of tits (Paridae) breeding at 119 1 km2 sampling sites across a P. montanus hybrid zone in northern Switzerland (2004-2020). We find strong impacts of forest cover and elevation on population persistence and colonisation in all species. We also demonstrate evidence for interspecific competition on population persistence and colonization probabilities, where the presence of marsh tits reduces population persistence and colonisation probability of sympatric willow tits, potentially decreasing gene flow among willow tit subspecies. 4. While conceptually simple, our results have important implications for the future modeling of population abundance, colonization, persistence, and trajectories in community frameworks. We suggest potential extensions of our modeling in this paper, and discuss how leveraging data from multiple species can improve model performance and sharpen ecological inference.

opencc-zeroMay 2022View details →

Data from: The importance of population heterogeneities in detecting social learning as the foundation of animal cultural transmission

High levels of within-population behavioural variation can have drastic demographic consequences, thus changing the evolutionary fate of populations. A major source of within-population heterogeneity is personality. Nonetheless, it is still relatively rarely accounted for in social learning studies that constitute the most basic process of cultural transmission. Here, we perform in female mosquitofish (Gambusia holbrooki) a social learning experiment in the context of mate choice, a situation called mate copying, and for which there is strong evidence that it can lead to the emergence of persistent traditions of preferring a given male phenotype. When accounting for the global tendency of females to prefer lager males but ignoring differences in personality we detected no evidence for mate copying. However, when accounting for the bold-shy dichotomy, we found that bold females did not show any evidence for mate copying, while shy females showed significant amounts of mate copying. This illustrates how the presence of variation in personality can hamper our capacity to detect mate copying. We conclude that mate copying may be more widespread than we thought because many studies ignored the presence of within-population heterogeneities.

opencc-zeroOct 2022View details →

Data from: Individual heterogeneity in fitness in a long-lived herbivore

Heterogeneity in the intrinsic quality and nutritional condition of individuals affects reproductive success and consequently fitness. Black brant (Branta bernicla nigricans) are long-lived, migratory, specialist herbivores. Long migratory pathways and short summer breeding seasons constrain the time and energy available for reproduction, thus magnifying life-history trade-offs. These constraints, combined with long lifespans and trade-offs between current and future reproductive value, provide a model system to examine the role of individual heterogeneity in driving life-history strategies and individual heterogeneity in fitness. We used hierarchical Bayesian models to examine reproductive trade-offs, modeling the relationships between within-year measures of reproductive energy allocation and among-year demographic rates of individual females breeding on the Yukon-Kuskokwim Delta, Alaska using capture-recapture and reproductive data from 1988 to 2014. We generally found that annual survival tended to be buffered against variation in reproductive investment, while breeding probability varied considerably over the range of clutch size-laying date combinations. We provide evidence for relationships between breeding probability and clutch size, breeding probability and nest initiation date, and an interaction between clutch size and initiation date. Average lifetime clutch size also had a weak positive relationship with apparent survival probability. Our results support the use of demographic buffering strategies for black brant. These results also indirectly suggest associations among environmental conditions during growth, fitness, and energy allocation, highlighting the effects of early growth conditions on individual heterogeneity, and subsequently, lifetime reproductive investment.

opencc-zeroJun 2022View details →

Data from: Neurotransmitter content heterogeneity within an interneuron class shapes inhibitory transmission at a central synapse

Neurotransmitter content is deemed the most basic defining criterion for neuronal classes, contrasting with the intercellular heterogeneity of many other molecular and functional features. Here we show, in the adult mouse brain, that neurotransmitter content variegation within a neuronal class is a component of its functional heterogeneity. Most Golgi cells (GoCs), the well-defined class of cerebellar interneurons inhibiting granule cells (GrCs), contain cytosolic glycine, accumulated by the neuronal transporter GlyT2, and GABA in various proportions. To assess the functional consequence of this neurotransmitter variation, we paired GrCs recordings with optogenetic stimulations of single GoCs, which preserve the intracellular transmitter mixture. We show that the strength and decay kinetics of GrCs IPSCs, which are entirely mediated by GABAA receptors are negatively correlated to the presynaptic expression of GlyT2 by GoCs. We isolate a slow spillover component of GrCs inhibition that is also affected by the expression of GlyT2, leading to a 56 % decrease in relative charge. Acute manipulations of cytosolic GABA and glycine supply recapitulate the modulation of IPSC charge, supporting the hypothesis that presynaptic loading of glycine negatively impact the GABAergic transmission in mixed interneurons through a competition for vesicular filling. Our results suggest that heterogeneity of neurotransmitter supply within the GoC class may provide a presynaptic mechanism to tune the gain of the stereotypic granular layer microcircuit, thereby expanding the realm of possible dynamic behavior.

opencc-by-4.0Mar 2022View details →

Data from: Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass in heterogenous landscapes

Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest aboveground biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering -- that is, excluding returns from LiDAR point clouds based on simple height thresholds -- is a common practice meant to improve the 'signal' content of LiDAR returns by preventing ground returns from masking useful information about tree size and condition contained within canopy returns. However, ground returns may be helpful for making accurate aboveground biomass predictions in heterogeneous landscapes that include a patchy mosaic of vegetation heights and land cover types.     In this paper, we applied several ground noise filtering thresholds while mapping forest AGB across New York State (USA), a heterogenous landscape composed of both contiguously forested and highly fragmented areas with mixed land cover types. We fit random forest models to predictor sets derived from each filtering intensity threshold and compared model accuracies, paying attention to how changes in accuracy correlated with landscape structure. We observed that removing ground noise via any height threshold systematically biases many of the LiDAR-derived variables used in AGB modeling, with mean correlation (Spearman's $\rho$) between variables increasing from 0.183 to 0.266. We found that that ground noise filtering yields models of forest AGB with lower accuracy than models trained using predictors derived from unfiltered point clouds, with RMSE increasing by up to 2.2 Mg ha^-1^ statewide. Although we only modeled AGB for forest cover types, models fit to predictors derived from filtered point clouds performed worse as landscape heterogeneity (as measured by patch density and edge density) increased, suggesting ground returns are particularly useful when modeling edge forests. Our results suggest that ground filtering should be a carefully considered decision when mapping forest AGB, particularly when mapping heterogeneous and highly fragmented landscapes, as ground returns are more likely to represent useful 'signal' than extraneous 'noise' in these cases.

opencc-zeroJul 2022View details →

Data from: Large trees and forest heterogeneity facilitate prey capture by California spotted owls

Predators are among the most threatened animal groups globally, with prey declines contributing to their endangerment. However, assessments of the habitat conditions that influence the successful capture of different prey species are rare, especially for small, cryptic predators. Accordingly, most predator conservation plans are based on the relative importance of habitats inferred from coarse-scale <a name="_Hlk99628060"></a>studies that do not consider habitat features contributing to hunting success, which can vary among prey species. To address this limitation, we integrated high-resolution GPS tracking and nest video monitoring to characterize habitat features at prey capture locations during the nestling provisioning stage for the Spotted Owl (Strix occidentalis) a small, cryptic predator that has been at the center of a decades-long forest management conflict in western North America. When all prey species were considered collectively, males provisioning nests tended to capture prey: (i) in areas with more large-tree forest, (ii) in areas with more medium trees/medium canopy forest, and (iii) at edges between conifer and hardwood forests. However, when we considered the owl's two key prey species separately, males captured woodrats (Neotoma fuscipes) and Humboldt flying squirrels (Glaucomys oregonensis) in areas with markedly different habitat features. Our study provides clarity for forest management in mixed-ownership landscapes because different prey species achieve high densities in different habitat types. Specifically, our results suggest that promoting large trees, increasing forest heterogeneity, and creating canopy gaps in forests with medium trees/high canopy cover could benefit Spotted Owls and their prey, which has the ancillary benefit of enhancing forest resilience. Combining high-resolution GPS tagging with video-based information on prey deliveries to breeding sites can strengthen conservation planning for small predators by more rigorously defining those habitat features that are associated with successful prey acquisition.

opencc-zeroAug 2022View details →

Detecting and reducing heterogeneity of error in acoustic classification: Data

<ol> <li>Passive acoustic monitoring can be an effective method for monitoring species, allowing the assembly of large audio datasets, removing logistical constraints in data collection, and reducing anthropogenic monitoring disturbances. However, the analysis of large acoustic datasets is challenging, and fully automated machine-learning processes are rarely developed or implemented in ecological field studies. One of the greatest uncertainties hindering the development of these methods is spatial generalisability – can an algorithm trained on data from one place be used elsewhere?</li> <li>We demonstrate that heterogeneity of error across space is a problem that could go undetected using common classification accuracy metrics. Secondly, we develop a method to assess the extent of heterogeneity of error in a random forest classification model for six Amazonian bird species. Finally, we propose two complementary ways to reduce heterogeneity of error, by (i) accounting for it in the thresholding process and (ii) using a secondary classifier that uses contextual data.</li> <li>We found that using a thresholding approach that accounted for heterogeneity of precision error reduced the coefficient of variation of the precision score from a mean of 0.61±0.17 (SD) to 0.41±0.25 in comparison to the initial classification with threshold selection based on F-score. The use of a secondary, contextual classification with thresholding selection accounting for heterogeneity of precision reduced it further still, to 0.16±0.13, and was significantly lower than the initial classification in all but one species. Mean average precision scores increased, from 0.66±0.4 for the initial classification, to 0.95±0.19, a significant improvement for all species.</li> <li>We recommend assessing - and if necessary correcting for - heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.</li> </ol>

opencc-by-4.0Jul 2021View details →

Companion data of Exploiting system level heterogeneity to improve the performance of a GeoStatistics multi-phase task-based application

This is the companion data repository for the paper entitled Exploiting system level heterogeneity to improve the performance of a GeoStatistics multi-phase task-based application by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted for publication in the <a href="https://oaciss.uoregon.edu/icpp21/">ICPP 2021</a>.

opencc-by-4.0Jul 2020View details →

Companion data for Communication-Aware Load Balancing of the LU Factorization over Heterogeneous Clusters

This is the companion data repository for the paper entitled Communication-Aware Load Balancing of the LU Factorization over Heterogeneous Clusters by Lucas Leandro Nesi, Lucas Mello Schnorr, and Arnaud Legrand. The manuscript has been accepted in the <a href="https://icpads2020.comp.polyu.edu.hk/">ICPADS 2020</a>.

opencc-by-4.0Aug 2020View details →

Companion data of Detection, Evaluation and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters

This is the companion data repository for the paper entitled Detection, Evaluation, and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters by Lucas Leandro Nesi and Lucas Mello Schnorr. The manuscript has been accepted for publication in the <a href="http://wscad.sbc.org.br/current/index.html">WSCAD 2020</a>.