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248 results for “Multiscale”
Multiscale drivers of carabid beetle (Coleoptera: Carabidae) assemblages in small European woodlands
<p><strong>Aim </strong>The spatiotemporal connectivity of forest patches in lowland agricultural landscapes and their age matter to explain current biodiversity patterns across regional as well as biogeographical extents, to the point that it exceeds the contribution of macroclimate for plant diversity in the understory of temperate forests. Whether this holds true for other taxonomic groups remains largely unknown. Yet, it has important consequences for ecosystem functioning and the delivery of ecosystem services. Focusing on carabid beetle assemblages, we assessed the relative importance of macroclimatic, landscape, and patch attributes on driving local species richness (-diversity) and species dissimilarity between patches (-diversity).</p> <p><strong>Location</strong> Deciduous forest patches in seven regions along a 2,100-km long latitudinal gradient across the European temperate forest biome, from southern France to central Sweden.</p> <p><strong>Methods</strong> We sampled 221 forest patches in two 55-km landscape windows with contrasting management intensities. Carabid beetles were classified into four habitat-preference guilds: forest-specialist, forest-generalist, eurytopic, and open-habitat species. We quantified the multi-level environmental influence using mixed-effects models and variation partitioning analysis.</p> <p><strong>Results</strong> We found that both - and -diversity were primarily determined by macroclimate, acting as a large-scale ecological filter on carabid assemblages among regions. Forest-patch conditions, including biotic and abiotic heterogeneity as well as patch age (but not patch size), increased -diversity of forest species. Landscape management intensity weakly influenced -diversity of forest species, but increased the number of non-forest species in forest patches. Beta-diversity of non-forest species increased with patch heterogeneity and decreased with landscape management intensity.</p> <p><strong>Main conclusions</strong> Our results highlight the leading role of broad macroclimatic gradients over local and landscape factors in determining the composition of local carabid communities, thereby shedding light on macroecological patterns of arthropod assemblages. This study emphasizes the urgent need for preserving ancient forest patches embedded in agricultural landscapes, even the small and weakly connected ones.</p>
Data from: Bringing multivariate support to multiscale codependence analysis: assessing the drivers of community structure across spatial scales
1. Multiscale codependence analysis (MCA) quantifies the joint spatial distribution of a pair of variables in order to provide a spatially-explicit assessment of their relationships to one another. For the sake of simplicity, the original definition of MCA only considered a single response variable (e.g. a single species). However, that definition would limit the application of MCA when many response variables are studied jointly, for example when one wants to study the effect of the environment on the spatial organisation of a multi-species community in an explicit manner. 2. In the present paper, we generalize MCA to multiple response variables. We conducted a simulation study to assess the statistical properties (i.e. type I error rate and statistical power) of multivariate MCA (mMCA) and found that it had honest type I error rate and sufficient statistical power for practical purposes, even with modest sample sizes. We also exemplified mMCA by applying it to two ecological data sets. 3. The simulation study confirmed the adequacy of mMCA from a statistical standpoint: it has honest type I error rates and sufficient power to be useful in practice. Using mMCA, we were able to detect variation in fish community structure along the Doubs River (in France), which was associated with large spatial structures in the variation of physical and chemical variables related to water quality. Also, mMCA usefully described the spatial variation of an Oribatid mite community structure associated with a gradient of water content superimposed on various smaller-scale spatial features associated with vegetation cover in the peat blanket surrounding Lac Geai (in Québec, Canada). 4. In addition to demonstrating the soundness of mMCA in theory and practice, we further discuss the strengths and assumptions of mMCA and describe other potential scenarios where it would be helpful to biologists interested in assessing influence of environmental conditions on community structure in a spatially-explicit way.
Mapping multiscale breeding bird species distributions across the United States and evaluating their conservation applications
<p>Species distribution models are vital to management decisions that require understanding habitat use patterns, particularly for species of conservation concern. However, the production of distribution maps for individual species is often hampered by data scarcity, and existing species maps are rarely spatially validated due to limited occurrence data. Furthermore, community-level maps based on stacked species distribution models lack important community assemblage information (e.g., competitive exclusion) relevant to conservation. Thus, multispecies, guild, or community models are often used in conservation practice instead. To address these limitations, we aimed to generate fine-scale, spatially-continuous, nationwide maps for species represented in the North American Breeding Bird Survey (BBS) between 1992-2019. We generated ensemble models for each species at three spatial resolutions – 0.5, 2.5, and 5 km – across the conterminous United States. We also compared species richness patterns from stacked single-species models with those of 19 functional guilds developed using the same data to assess the similarity between predictions. We successfully modeled 192 bird species at 5-km resolution, 160 species at 2.5-km resolution, and 80 species at 0.5-km resolution. However, the species we could model represent only 28-56% of species found in the conterminous US BBS surveys across resolutions owing to data limitations. We found stacked maps and guild maps generally had high correlations across resolutions (median = 84%), but spatial agreement varied regionally by resolution and was most pronounced between the East and West at the 5-km resolution. The spatial differences between our stacked maps and guild maps illustrate the importance of spatial validation in conservation planning. Overall, our species maps are useful for single-species conservation and can support fine-scale decision-making across the United States, and can also support community-level conservation when used in tandem with guild maps. However, there are still data scarcity issues for many species of conservation concern when using the BBS for single-species models.</p>
A multiscale theory for spreading and migration of adhesion-reinforced mesenchymal cells
<p>We present a chemomechanical whole-cell theory for the spreading and migration dynamics of mesenchymal cells that can actively reinforce their adhesion to an underlying viscoelastic substrate as a function of its stiffness. Our multiscale model couples the adhesion reinforcement effect at the subcellular scale with the nonlinear mechanics of the nucleus-cytoskeletal network complex at the cellular scale to explain the concurrent monotonic area-stiffness and non-monotonic speed-stiffness relationships observed in experiments: We consider that large cell spreading on stiff substrates flattens the nucleus, increasing the viscous drag force on it. The resulting force balance dictates a reduction in the migration speed on stiff substrates. We also reproduce the experimental influence of the substrate viscosity on the cell spreading area and migration speed by elucidating how the viscosity may either maintain adhesion reinforcement or prevent it depending on the substrate stiffness. Additionally, our model captures the experimental directed migration behavior of the adhesion-reinforced cells along a stiffness gradient, known as durotaxis, as well as up or down a viscosity gradient (viscotaxis or anti-viscotaxis), the cell moving towards an optimal viscosity in either case. Overall, our theory explains the intertwined mechanics of the cell spreading, migration speed and direction in the presence of the molecular adhesion reinforcement mechanism. </p>
The ReaxFF MD simulation code for the "Mechanistic Investigation of Thermal Plasma Gasification of Polytetrafluoroethylene via Multiscale Simulation Coupled with Experimental Confirmation""
<p>This repository contains the implementation for ReaxFF MD simulation method described in the paper "Mechanistic Investigation of Thermal Plasma Gasification of Polytetrafluoroethylene via Multiscale Simulation Coupled with Experimental Confirmation".</p>
HIDRA simulations and post-processing scripts for JGR: SP manuscript: characterization of N+ abundances in the terrestrial polar wind using the multiscale atmosphere-geospace environment
<div> <div> <div> <p>The High-latitude Ionosphere Dynamics for Research Applications (HIDRA) model is part of the Multiscale Atmosphere-Geospace Environment (MAGE) model under development by the Center for Geospace Storms (CGS) NASA DRIVE Science Center. This study employs HIDRA to simulate upflows of H+, He+, O+, and N+ ions, with a particular focus on the relative N+ concentrations, production and loss mechanisms, and thermal upflow drivers as functions of season, solar activity, and magnetospheric convection. The simulation results demonstrate that N+ densities typically exceed He+ densities, N+ densities are typically ∼ 10% O+ densities, and N+ concentrations at quiet-time are approximately 50-100% of N+ concentrations during storm-time. Furthermore, the N+ and O+ upflow fluxes show similar trends with variations in magnetospheric driving. The inclusion of ion-neutral chemical reactions involving metastable atoms is shown to have significant effects on N+ production rates. With this metastable chemistry included, the simulated ion density profiles compare favorably with satellite measurements from Atmosphere Explorer C (AE-C) and Orbiting Geophysical Observatory 6 (OGO-6).</p> </div> </div> </div>
Mesolithic Plant Processing Unveiled: Multiscale Use-Wear Analysis of the Ground Stone Tools from Vlasac (Serbia)
<p>This repository contains the raw data and code to reproduce the analyses presented in the paper "Mesolithic Plant Processing Unveiled: Multiscale Use-Wear Analysis of the Ground Stone Tools from Vlasac (Serbia)" by Zupancich et al.</p> <p>The repositiory includes:</p> <ul> <li>CSV files containing the raw data of:</li> <li>3D surface measurement of experimental and archaeological ground stone tools</li> <li>Use wear spatial distribution</li> <li>Ground stone tools techno-morphological data</li> <li>HTML files of the code utilised to perform the analyses</li> </ul>
Pole Reversals and Delta Q Dynamics: A MEFI-Based Multiscale Analysis
<p>This study examines the phenomena of geomagnetic pole reversals through the Modified Einstein</p> <p>Field Interaction (MEFI) framework. By exploring Delta Q stabilization, resonance deviations, and</p> <p>their global impacts, the study demonstrates MEFI's potential as a universal model. This journal</p> <p>entry provides visual evidence and simulations to highlight the quantum, geophysical, and societal</p> <p>effects of pole reversals, underscoring MEFI?s predictive power.</p>
Dataset for modeling of a multiscale human cerebrovasculature
<p>The dataset contains cerebrovascular structures for image-based model and mathematical model to replicate results in a forthcoming paper (PLoS Comput Biol 16(6): e1007943. https://doi.org/10.1371/journal.pcbi.1007943).</p> <p>Data formats: We assume the data will be visualized in ParaView (Kitware Inc, New York, USA).</p> <p>vtp: line edges including additive information (radius, order, level, etc.)/ surface elements including additive information (vascular subregion ID)</p> <p>ply: triangular polygons</p> <p>vti: volume data in a 3-D cubic domain</p> <p>(DAT: values written in a text format)</p> <p>code: fortran programs for running and analyzing the cerebral vasculatures</p>
Automating Computational Chemistry in Multiscale Catalysis Electronic Data Compendium
<p>Electronic data compendium containing supplemental datasets and figures, primarily detailing lateral interactions and adlayer properties at catalytic surfaces.</p> <p>Part of the physical print of the thesis "Automating Computational Chemistry in Multiscale Catalysis" by B. Klumpers.</p>
Data supplement for "Multiscale perspective on wetting on switchable substrates: mapping between microscopic and mesoscopic models"
<p>Data set and python code to recreate the figures of "Multiscale perspective on wetting on switchable substrates: mapping between microscopic and mesoscopic models". Additionally, it includes the oomph-lib Code to reproduce the data for the simulations in the mesoscopic thin-film model.</p>
Data from: Towards a better ecological understanding of metacommunity stability: A multiscale framework to disentangle population variability and synchrony effects
<p>1. Despite great progress in our understanding of the mechanisms governing ecosystem stability in local communities, we still lack knowledge at a larger spatial scale. Studying the stability of metacommunities requires assessing the temporal stability and synchrony of populations across space and organizational levels. Previous attempts to disentangle these effects have provided limited ecological interpretations, and conceptual improvements are needed to identify the underlying ecological processes.</p> <p>2. We propose an extended framework aiming at disentangling simultaneously the relative effects of population stability and different types of synchronies on metacommunity stability. We adapted previous methods of decomposing stability into a new set of indices associated with clearer ecological hypotheses. Particularly, we provide synchrony indices that are not affected by statistical properties of the metacommunity but focus on species responses to environment, demography, and interactions. We applied this framework to a unique dataset describing the sorted biomass of individual plant populations, across 12 communities of a species-rich meadow, and for 16 years. The communities were sampled in different treatments of fertilization and dominant removal to evaluate the effect of environmental heterogeneity on stability.</p> <p>3. We found higher stability at a larger spatial scale, mainly due to statistical averaging (portfolio effect). The variability of individual populations was an important determinant of the stability of the whole metacommunity. Consistent with the hypothesis of a common response to environmental conditions, we found that the fluctuations of populations were mostly synchronized (within and between species) at a large spatial scale and tended to destabilize the metacommunity. On the other hand, opposite fluctuations (anti-synchrony) between populations occurred at the local scale, probably due to local species interactions.</p> <p>4. Synthesis Our framework appears as a powerful tool to test how ecological processes occurring simultaneously at different spatial and organizational scales affect the stability of metacommunities. This study advances our ecological understanding of the processes underlying the stability of species-rich environments. --</p>
Dataset for the manuscript: Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages.
<p>Dataset for the manuscript:</p> <p>Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages. preprint, bioRxiv, 2022. DOI: 10.1101/2022.05.06.490883</p> <p>Each zip file contains the raw computational data (as a gzip compressed tarball), YAML input files, as well as Python plotting scripts. The Python plotting scripts have dependencies on the packages: <em>tarfile</em>, <em>multiprocessing</em>, <em>numpy</em>, <em>scipy</em>, and <em>matplotlib</em>. Note that the Python plotting scripts plot directly from the gzip compressed tarballs.</p> <p>The corresponding code can be found on GitHub: https://github.com/Ruth-Bowness-Group/CAModel</p>
Multiscale light-sheet organoid imaging framework
<p>These two files correspond to the data associated with the light-sheet recordings and time-course recordings utilized for the manuscript entitled "Multiscale light-sheet organoid imaging framework".<br> If access to the imaging data is needed, (which in total comprises of ~700 GB), please contact Prisca Liberali (prisca.liberali@fmi.ch) for more information.</p>
High-quality video file for Doekes, H.M. and Hermsen, R, "Multiscale selection in spatially structured populations" (2022)
<p>High-quality version of supplementary movie 1 as published with:</p> <p>Doekes, H.M. and Hermsen, R, "Multiscale selection in spatially structured populations" (to be submitted, 2022)</p>
Data for the paper "Bridging scales in a multiscale pattern-forming system""
<p>Raw data used for Fig. 2 of the paper "Bridging scales in a multiscale pattern-forming system" by Laeschkir Würthner et al.</p>
Competitive control of multiscale aquifer heterogeneity on solute transport in an alluvial aquifer
<p>Here, we provide the dataset for the publication "<strong>Competitive control of multiscale aquifer heterogeneity on solute transport</strong> <strong>in an alluvial aquifer</strong>" submitted to Journal of Hydrology for peer-review.</p>
Streamflow Prediction in Human-Regulated Catchments Using Multiscale LSTM Modeling with Anthropogenic Similarities
<p>These codes are used in the paper entitled"Streamflow Prediction in Human-Regulated Catchments Using Multiscale LSTM Modeling with Anthropogenic Similarities" which is submitted to the Journal of Water Resources Research. The code for the differentiable parameter learning (DPL) model can be downloaded at https://doi.org/10.5281/zenodo.7091334. The code for LSTM to reproduce our analysis is available at <a href="https://github.com/neuralhydrology/neuralhydrology">https://github.com/neuralhydrology/neuralhydrology</a>. The SWORD database utilized in our study can be accessed at https://zenodo.org/records/10013982. The geometric dataset of the global river attribute information for every river reach, the values of all pressure indicators (DOF, DOR,SED, USE, RDD and URB) and the values for the CSI are available at https://doi.org/10.6084/m9.figshare.7688801.</p>
A Machine Learning Approach for Multiscale Modeling of Biological Tissues, Companion Dataset
<p>This dataset includes the response of a Delaunay fiber network to various deformation gradients. The dataset is in adios2 format and includes stress, strain, strain energy, stiffness, and the applied deformation gradients.</p> <p>This also includes the pytorch implementation of our neural network.</p>
Multiscale Bayesian Simulations Reveal Functional Chromatin Condensation of Gene Loci
<p>Chromatin, the complex assembly of DNA and associated proteins, plays a pivotal role in orchestrating various genomic functions. To aid our understanding of the principles underlying chromatin organization, we introduce Hi-C metainference, a Bayesian approach that integrates Hi-C contact frequencies into multiscale prior models of chromatin. This approach combines both bottom-up (the physics-based prior) and top-down (the data-driven posterior) strategies to characterize the 3D organization of a target genomic locus. We first demonstrate the capability of this method to accurately reconstruct the structural ensemble and the dynamics of a system from contact information. We then apply the approach to investigate the Sox2, Pou5f1, and Nanog loci of mouse embryonic stem cells using a bottom-up chromatin model at 1kb resolution. We observe that the studied loci are conformationally heterogeneous and organized as crumpled globules, favoring contacts between distant enhancers and promoters. Using nucleosome-resolution simulations, we then reveal how the Nanog gene is functionally organized across the multiple scales of chromatin. At the local level, we identify diverse tetranucleosome folding motifs with a characteristic distribution along the genome, predominantly open at cis-regulatory elements and compact in between. At the larger scale, we find that enhancer-promoter contacts are driven by the transient condensation of chromatin into compact domains stabilized by extensive inter-nucleosome interactions. Overall, this work highlights the condensed, but dynamic nature of chromatin in vivo, contributing to a deeper understanding of gene structure-function relationships.</p>
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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.