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3,339 results for “heterogeneities”
Companion data of Detection, Evaluation and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters
<p>This is the companion data repository for the paper entitled <strong>Detection, Evaluation, and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters</strong> 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>.</p>
Heterogeneous evolution of sex chromosomes in the torrent frog genus Amolops
<p>In sharp contrast with birds and mammals, sex chromosomes have been described as homomorphic in cold-blooded vertebrates. This sex-chromosome homomorphy has been suggested to result from high turnovers when they are often observed across deeply diverged clades. However, little is known about the tempo and mode of sex chromosome evolution among most closely related species. Here, we examine patterns of sex chromosome evolution among nine species of the torrent frog genus <em>Amolops</em>. Through the analysis of male and female GBS and RAD-seq from 182 individuals and of PCR verification for 176 individuals, we identify signatures of sex chromosomes involving two pairs of chromosomes. We find that the sex-chromosome homomorphy results from both turnover and X–Y recombination in the <em>Amolops</em> species, simultaneously exhibiting heterogeneous evolution on homologous and non-homologous sex chromosomes. The lower turnover rate of non-homologous sex chromosomes exists in these torrent frogs, whereas the ongoing X–Y recombination in homologous sex chromosomes would act as an indispensable force to prevent the sex chromosomes from differentiations. </p>
Heterogeneity of RNA editing in mesothelioma and how RNA editing enzyme ADAR2 affects mesothelioma cell growth, response to chemotherapy and tumor microenvironment
<p>Raw data supporting the manuscript</p>
Linked selection, differential introgression and recombination rate variation promote heterogeneous divergence in a pair of yellow croakers
<p><span>Understanding the mechanisms underlying heterogeneous genomic divergence is of particular interest in evolutionary biology. Highly differentiated genomic regions, known as genomic islands, often evolve between diverging lineages. These genomic islands may be related to selection promoting adaptation or reproductive isolation. Based on whole genome assembly and genome-wide RAD sequencing in a pair of yellow croakers (genus: <em>Larimichthys</em>), we investigated the evolutionary processes shaping genomic landscapes of divergence. Demographic modelling indicated that the two species diverged following a secondary contact scenario, where differential introgression and linked selection were suggested to be involved in heterogeneous genomic divergence. We identified reduced recombination rate in genomic islands and a relatively good conservation of both genetic diversity and recombination landscapes between species, which highlight the roles of linked selection and recombination rate variation in promoting heterogeneous divergence in the common ancestral lineage of the two species. In addition, we found a positive correlation between differentiation (F<sub>ST</sub>) and absolute sequence divergence (<em>D</em><sub>xy</sub>), and elevated </span><span><span><em>D</em><sub>xy</sub></span> in genomic islands, which were different from the patterns under linked selection. Restricted gene flow in highly differentiated regions has likely remodeled the landscape of heterogeneous genomic divergence. Moreover, genomic islands showed little evidence of overlapping within and between species, implying that high gene flow and divergent selection when colonizing new habitats have reshaped the patterns of intraspecific divergence. This study highlights that highly differentiated genomic regions can also be from linked selection and variation of recombination rate, and thus are not necessarily related to speciation islands or local adaptation. </span></p>
Dataset to "Defining the pressures of a fluid in a nanoporous, heterogeneous medium"
<p>This is the dataset presented in the article "Defining the pressures of a fluid in a nanoporous, heterogeneous medium" [1].</p> <ol> <li>https://www.frontiersin.org/articles/10.3389/fphy.2022.866577/full</li> </ol>
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>
Data for: (Epi)genomic adaptation driven by fine geographical scale environmental heterogeneity after recent biological invasions
<p><span>Elucidating processes and mechanisms involved in rapid local adaptation to varied environments is a poorly understood but crucial component in management of invasive species. Recent studies have proposed that genetic and epigenetic variation could both contribute to ecological adaptation, yet it remains unclear on the interplay between these two components underpinning rapid adaptation in wild animal populations. To assess their respective contributions to local adaptation, we explored epigenomic and genomic responses to environmental heterogeneity in eight recently colonized ascidian (<em>Ciona intestinalis</em>) populations at a relatively fine geographical scale. Based on MethylRADseq data, we detected strong patterns of local environment-driven DNA methylation divergence among populations, significant epigenetic isolation by environment (IBE), and a large number of local environment-associated epigenetic loci. Meanwhile, multiple genetic analyses based on single nucleotide polymorphisms (SNPs) showed genomic footprints of </span><span>divergent selection</span><span>. </span><span>In addition, for five genetically similar populations, we detected significant methylation divergence and local environment-driven methylation patterns, indicating strong effects of local environments on epigenetic variation. From a functional perspective, a majority of functional genes, gene ontology (GO) terms, and biological pathways were largely specific to one of these two types of variation, suggesting partial independence between epigenetic and genetic adaptation. The methylation quantitative trait loci (mQTL) analysis showed that the genetic variation explained only 18.67% of methylation variation, further confirming the autonomous relationship between these two types of variation. Altogether, we highlight the complementary interplay of genetic and epigenetic variation involved in local adaptation, which may jointly promote populations' rapid adaptive capacity and successful invasions in different environments. The findings here provide valuable insights into interactions between invaders and local environments to allow invasive species to rapidly spread, thus contributing to better prediction of invasion success and development of management strategies.</span></p>
Design principles a heterogeneously catalyzed autothermal reactor with enhanced heat and mass transfer for hydrogen production
<p><strong>Design principles a</strong> <strong>heterogeneously catalyzed autothermal reactor with enhanced heat and mass transfer for hydrogen production</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>Catalysis, in chemistry, is the modification of the rate of a chemical reaction, usually an acceleration, by addition of a substance not consumed during the reaction. The rates of chemical reactions, that is, the velocities at which they occur, depend upon a number of factors, including the chemical nature of the reacting species and the external conditions to which they are exposed. A particular phenomenon associated with the rates of chemical reactions that is of great theoretical and practical interest is catalysis, the acceleration of chemical reactions by substances not consumed in the reactions themselves, substances known as catalysts. The study of catalysis is of interest theoretically because of what it reveals about the fundamental nature of chemical reactions; in practice, the study of catalysis is important because many industrial processes depend upon catalysts for their success. In a catalyzed reaction, the catalyst generally enters into chemical combination with the reactants but is ultimately regenerated, so the amount of catalyst remains unchanged. Since the catalyst is not consumed, each catalyst molecule may induce the transformation of many molecules of reactants. For an active catalyst, the number of molecules transformed per minute by one molecule of catalyst may be as large as several million. Where a given substance or a combination of substances undergoes two or more simultaneous reactions that yield different products, the distribution of products may be influenced by the use of a catalyst that selectively accelerates one reaction relative to the other(s). By choosing the appropriate catalyst, a particular reaction can be made to occur to the extent of practically excluding another. Many important applications of catalysis are based on selectivity of this kind.</p> <p>Streamwise distance (millimeters), Reforming channel centerline temperature (degrees kelvin)</p> <p>0 373</p> <p>0.00025 373.048742</p> <p>0.0005 373.2382942</p> <p>0.00075 373.7354626</p> <p>0.001 374.7081362</p> <p>0.00125 376.2548823</p> <p>0.0015 378.3951976</p> <p>0.00175 381.0814232</p> <p>0.002 384.2247405</p> <p>0.00225 387.7222496</p> <p>0.0025 391.465635</p> <p>0.00275 395.3617454</p> <p>0.003 399.3347598</p> <p>0.00325 403.3218552</p> <p>0.0035 407.2775391</p> <p>0.00375 411.1628179</p> <p>0.004 414.9538621</p> <p>0.00425 418.6311751</p> <p>0.0045 422.1828419</p> <p>0.00475 425.6012807</p> <p>0.005 428.8821587</p> <p>0.00525 432.025476</p> <p>0.0055 435.0312325</p> <p>0.00575 437.9015946</p> <p>0.006 440.6398117</p> <p>0.00625 443.2502165</p> <p>0.0065 445.7371415</p> <p>0.00675 448.1049195</p> <p>0.007 450.3600492</p> <p>0.00725 452.5057803</p> <p>0.0075 454.5475284</p> <p>0.00775 456.4896262</p> <p>0.008 458.3374895</p> <p>0.00825 460.0954509</p> <p>0.0085 461.7689261</p> <p>0.00875 463.3600816</p> <p>0.009 464.874333</p> <p>0.00925 466.3149298</p> <p>0.0095 467.6862047</p> <p>0.00975 468.9924902</p> <p>0.01 470.2348696</p> <p>0.01025 471.4176754</p> <p>0.0105 472.5441571</p> <p>0.01075 473.6175642</p> <p>0.011 474.6389798</p> <p>0.01125 475.6138198</p> <p>0.0115 476.5431672</p> <p>0.01175 477.4302716</p> <p>0.012 478.276216</p> <p>0.01225 479.0831669</p> <p>0.0125 479.8543736</p> <p>0.01275 480.5909193</p> <p>0.013 481.2938872</p> <p>0.01325 481.9665268</p> <p>0.0135 482.6099212</p> <p>0.01375 483.2251535</p> <p>0.014 483.8143901</p> <p>0.01425 484.377631</p> <p>0.0145 484.9170424</p> <p>0.01475 485.4347907</p> <p>0.015 485.930876</p> <p>0.01525 486.4063812</p> <p>0.0155 486.8623897</p> <p>0.01575 487.3010677</p> <p>0.016 487.721332</p> <p>0.01625 488.1264322</p> <p>0.0165 488.515285</p> <p>0.01675 488.8889736</p> <p>0.017 489.2496644</p> <p>0.01725 489.5962742</p> <p>0.0175 489.9309692</p> <p>0.01775 490.2526664</p> <p>0.018 490.5646152</p> <p>0.01825 490.8646493</p> <p>0.0185 491.1560181</p> <p>0.01875 491.4365554</p> <p>0.019 491.7073443</p> <p>0.01925 491.970551</p> <p>0.0195 492.2250926</p> <p>0.01975 492.472052</p> <p>0.02 492.7114294</p> <p>0.02025 492.9432247</p> <p>0.0205 493.1696042</p> <p>0.02075 493.3884016</p> <p>0.021 493.6017832</p> <p>0.02125 493.8086659</p> <p>0.0215 494.0101329</p> <p>0.02175 494.2072672</p> <p>0.022 494.3989857</p> <p>0.02225 494.5863716</p> <p>0.0225 494.7683417</p> <p>0.02275 494.9470624</p> <p>0.023 495.1214504</p> <p>0.02325 495.2915058</p> <p>0.0235 495.4583118</p> <p>0.02375 495.6218682</p> <p>0.024 495.7810921</p> <p>0.02425 495.9381497</p> <p>0.0245 496.0919577</p> <p>0.02475 496.2425163</p> <p>0.025 496.3898255</p> <p>0.02525 496.5360515</p> <p>0.0255 496.679028</p> <p>0.02575 496.8187551</p> <p>0.026 496.9563158</p> <p>0.02625 497.0927934</p> <p>0.0265 497.2260215</p> <p>0.02675 497.3570834</p> <p>0.027 497.4859789</p> <p>0.02725 497.6137912</p> <p>0.0275 497.7383541</p> <p>0.02775 497.8618338</p> <p>0.028 497.9831472</p> <p>0.02825 498.1033775</p> <p>0.0285 498.2203583</p> <p>0.02875 498.3362559</p> <p>0.029 498.4499873</p> <p>0.02925 498.5637186</p> <p>0.0295 498.6666184</p> <p>0.02975 498.796597</p> <p>0.03 498.88</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Heterogeneous Collaborative Aerial Manipulation
<p>The video shows the final experiments for heterogeneous collaborative aerial manipulation using two hexacopters with different manipulation capabilities and system properties.</p> <p>An exponentially stable controller is used on each vehicle such that the system consistently converges to the required setpoints, both on a free and locked manipulator scenarios. </p> <p>Experiments show that the controller can effectively transport a load using two different agents, with two different manipulation capabilities, to perform the task and still be robust to external unmodeled disturbances.</p>
Data from: Associations between developmental stability, canalization and phenotypic plasticity in plants with temporally heterogeneous environmental experience
<p>We subjected eight plant species to a first round of alternating inundation and drought vs. constantly moderate water treatments and a second round of water conditions. Fluctuating asymmetry (FA), intra- and inter-individual variations (CV<sub>intra</sub> and CV<sub>inter</sub>), and plasticity in traits were measured and correlations between variables were calculated for each species. Early temporally heterogeneous experience decreased the leaf size of half of the species, but had complex effects on leaf fluctuating asymmetry (FA) and inter-individual variation (CV<sub>inter</sub>) in traits immediately or in late conditions, with little effects on intra-individual variation (CV<sub>intra</sub>). There were several positive correlations between FA and CV<sub>inter</sub>, while there were correlations between CV<sub>inter</sub> and plasticity in early treatments, but negative ones in late treatments.</p>
A heterogenous mantle and crustal structure formed during the early differentiation of Mars
<p>Highly siderophile element abundances and Os isotopes of nakhlite and chassignite meteorites demonstrate that they represent a comagmatic suite from Mars. Nakhlites experienced variable assimilation of >2 Ga altered high Re/Os basaltic crust. This basaltic crust is distinct from the ancient crust represented by meteorites Allan Hills 84001, or impact-contaminated Northwest Africa 7034/7533. Nakhlites and chassignites that did not experience crustal assimilation were extracted from a depleted lithospheric mantle distinct from the deep plume source of depleted shergottites. The comagmatic origin for nakhlites and chassignites demonstrates a layered martian interior comprising ancient enriched basaltic crust derived from trace element-rich shallow magma ocean cumulates, a variably metasomatized mantle lithosphere, and a trace element-depleted deep mantle sampled by plume magmatism.</p>
Supplemental Data for the Journal Article Entitled The mechanistic origins of heterogeneous void growth during ductile failure accepted for publication by Acta Materialia
<p>This repository contains the Supplemental Data for the Journal Article Entitled The mechanistic origins of heterogeneous void growth during ductile failure accepted for publication by Acta Materialia.</p> <p>Authors: M.W. Vaughan<sup>a</sup>, H. Lim<sup>a</sup>, B. Pham<sup>a</sup>, R. Seede<sup>a</sup>, A. T. Polonsky<sup> a</sup>, K. Johnson<sup> a</sup>, P. J. Noell<sup>a,*</sup></p> <p>a: Sandia National Laboratories, Albuquerque, NM 87123</p> <p>Each folder contains a ReadMe.txt describing the files and their organization within each folder. </p> <p><br>Acknowledgements:<br><span>This work was supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The views expressed in the article do not necessarily represent the views of the U.S. DOE or the United States Government. </span></p>
Dataset: Phytoplankton Cell-States: multiparameter lifetime flow monitoring reveals cellular heterogeneity
<h1>Dataset for Multiparameter-based photosynthetic state transitions of single phytoplankton cells data.</h1> <h2>Creating environment</h2> <p>yaml and spec file are provided of the conda environment used. Most packages are typical, with the key exception of fretbursts</p> <p>A custom/development version of fretbursts was used, which contains support for more flexible photon selection (Ph_sel) objects, necessary for the larger parameter space. This version is in the polarization branch of harripd fork of fretbursts. The simple route to install is </p> <p><code>pip install git+https://https://github.com/harripd/FRETBursts@polarization</code></p> <p>however, if you want to ensure the exact same version is installed use:</p> <p><code>pip install git+https://github.com/harripd/FRETBursts@12a5168</code></p> <h2>Data organization</h2> <p>All zip files are meant to be unziped into the same destination folder (ie if a file is in a folder in the zip file, it should be in a subfolder inside the shared highest level folder, but if two files inside different zip folders are in the root of their respective zip files, they should be places in the same folder when all files are unzipped.</p> <p>After unzipping everything your folder for this article should contain the following items (normal text indicates file, <strong>bold text indicates folder</strong>).</p> <ol> <li>Flow_PhytoCellStates_figures.ipynb</li> <li><strong>mpAlgae</strong></li> <li><strong>figures</strong></li> <li>20230905_cyanoWH8102_diurnal</li> <li>20230707_cyanolightjump</li> <li>20230609_ppurp</li> <li>20230724_redalgaelightjump</li> <li>20231211_pmicans_6umol_diurnal</li> <li><strong>20231217_pmicans_6umol_lightjump</strong></li> <li><strong>20231019_WH8102_imaging</strong></li> <li><strong>bulk_cyano_lightjump</strong></li> <li>synWH8102_di_REPO_20230905.hdf5</li> <li>synWH8102_di_REPO_20230905.csv</li> <li>synWH8102_lj_REPO_20230707.hdf5</li> <li>synWH8102_lj_REPO_20230707.csv</li> <li>ppurp_di_REPO_20230609.hdf5</li> <li>ppurp_di_REPO_20230609.csv</li> <li>ppurp_lj_REPO_20230724.hdf5</li> <li>ppurp_lj_REPO_20230724.csv</li> <li>pmicans_di_REPO_20231211.hdf5</li> <li>pmicans_di_REPO_20231211.csv</li> <li>ppurp_lj_REPO_20230724.hdf5</li> <li>ppurp_lj_REPO_20230724.csv</li> </ol> <p>Flow_API_all.ipynb (item 1) is the jupyter notebook that analyses the data and produces the figures. It relies on having mpAlgae (item 2) in the same folder, as it contains the underlying code that adapts FRETBurts to work with the cell based data, adding functionality to combine multiple data files into one experiment, dynamic gating of data, storing calculated values to disk, which also reduces the memory requirements of the system, as well as a number of advanced plotting functions. Flow_API_all.ipynb also expects a figures folder (item 3) to exist so that it can save the produced figures. It also expects items 4-9 to exist, as those folder names are recorded as where the different raw data sets are stored. Even numbered items 12-22 (all items 12-23 that are hdf5 files) are produced by Flow_API_all.ipynb, and are where processed values of burst search are stored. the mpAlgae api makes it so that if these files are present, burst search is skipped, and instead loaded from these result files. Thus if you desire to examine the data, you only need the top level hdf5 files. These files also save results of histogram fittings, so that results can be loaded instead of recalculatd. </p> <p>The csv files are export of calculated parameters to csv format. Note that these are ungated, and thus proper gating must be implemented if plots are to be recapitulated from these files, this is done so that alternative gating strategies can also be explored.</p> <p> </p>
Data from: The two environmental drivers of thermoregulatory costs: Interactions between thermal mean and heterogeneity influence thermoregulation
<p>Ectotherms often thermoregulate behaviourally within variable thermal environments in their attempts to acquire optimal body temperatures. Thermoregulation accrues benefits, but also incurs costs, which are crucial for understanding thermoregulatory behaviour. Costs of thermoregulating are influenced by two key attributes of the thermal environment – heterogeneity of thermal microhabitats and the deviation of the mean temperature from an animal's preferred temperature. However, empirical research has rarely distinguished between these two drivers of thermoregulatory costs or examined them concurrently.</p> <p>Our experiment used a novel thermoregulatory arena to examine the independent and interactive effects of the two environmental drivers of costs of thermoregulation on the thermoregulatory behaviour of a small ectotherm, the jacky dragon (<em>Amphibolurus muricatus</em>).</p> <p>Following previous theory we predicted that i) thermoregulation would be higher in environments with greater thermal heterogeneity (body temperatures closer to preferred temperatures, higher thermoregulatory accuracy, and higher effectiveness of thermoregulation); and ii) changes in thermoregulation as a function of mean environmental temperatures would differ depending on thermal heterogeneity.</p> <p>We found support for our prediction that these two environmental attributes had an interactive effect on thermoregulation, but not for our prediction that thermal heterogeneity would impact thermoregulation independently. Individuals in highly heterogeneous environments maintained greater thermoregulatory accuracy compared with those in less heterogeneous environments as the mean environment increasingly deviated from the preferred temperature range.</p> <p>The results emphasise the crucial conceptual distinction between thermal mean and heterogeneity as drivers of thermoregulatory costs and how this distinction underpins variation in the thermal behaviour of ectotherms.</p>
Datasets accompanying "Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing"
<p>Datasets include two seurat objects: one with all unfiltered cells and raw expression data (seu_unfiltered.rds) and one dataset with normalised expression and latest annotations (differentiation_object_latest.rds). Additionally, a single-cell object containing post-(py)SCENIC analysis is added (ipsc_scenic.h5ad).</p>
Forest structure and heterogeneity increase diversity and alter the composition of host-parasitoid networks
<p>Antagonistic host-parasitoid interactions can be quantified using bipartite and meta networks, which have the potential to reveal how habitat structural elements relate to this important ecosystem function. Here, we analysed the host-parasitoid interactions of cavity-nesting bees and wasps, as well as their abundance, diversity, and species richness with forest structural elements from 127 forest research plots in southwestern Germany. We found that parasitoid abundance, diversity, and species richness all increase with host abundance, a potential mediator between parasitoids and forest structure. Both parasitoid abundance and diversity increased with stand structural complexity, possibly mediated by the abundance of hosts. Additionally, parasitoid abundance increased with increasing standing deadwood and herb cover. The bipartite networks of host-parasitoid interactions showed higher connectance with increasing standing deadwood, herb cover, and host abundance. Analyses of interactions within the host-parasitoid metanetwork revealed that increasing host abundance and decreasing canopy cover diversify the suites of interactions present at the plot level. These results demonstrate that forest structural elements can improve the stability and resilience of host-parasitoid networks by promoting parasitoids and diversifying interactions in ecological networks.</p>
Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes
<p><strong>Supplemental files contain all necessary datasets to reproduce the analysis and figures in "Calibration of variant effect predictors on genome-wide data masks heterogeneous performance across genes" Code and additional files can be found at https://github.com/FowlerLab/VEP-calibrations</strong></p>
Distinct oral-associated gastric microbiota and Helicobacter pylori communities for spatial microbial heterogeneity in gastric cancer
<p><span>STROBE Statement—Checklist of items that should be included in reports of <strong><em>case-control studies</em></strong> </span></p>
Fluid flow drives phenotypic heterogeneity in bacterial growth and adhesion on surfaces
<p>Raw data for the study reported by Hubert et al., Nature Communications 2024 (accepted).</p> <p>Each of the 4 folders within the archive, denoted 'Ulow', 'Low', 'Med', and 'High' contains 3 sets of raw experimental data, each corresponding to an experiment performed in the 'Ulow', 'Low', 'Med', and 'High' shear stress regime, in accordance with the folders' names.</p> <p>Each of these data sets is bundled into a single .avi video, consisting of raw images recorded at a 1/60 Hz acquisition frequency (i.e., 1 image per minute).</p> <p>The folder 'Supplementary_Software'contains Matlab and Python scripts used to treat the raw data, with a raw data sample. The file 'HOWTO_use_the_scripts.txt' explains how to use the scripts.</p> <p>Except for this HOWTO file, the files inside the various subfolders of folder 'Supplementary_Software' are not listed in the file tree below. Only the subfolders are listed.</p> <p>./<br>├── README_data_sets_and_treatment_scripts.txt (this file)<br>├── Ulow/<br> | ├── Ulow_set1.avi<br> | ├── Ulow_set2.avi<br> | └── Ulow_set3.avi<br>├── Low/<br> | ├── Low_set1.avi<br> | ├── Low_set2.avi<br> | └── Low_set3.avi<br>├── Med/<br> | ├── Med_set1.avi<br> | ├── Med_set2.avi<br> | └── Med_set3.avi<br>└── High/<br> | ├── High_set1.avi<br> | ├── High_set2.avi<br> | └── High_set3.avi<br>└── Supplementary_Software/<br> ├── HOWTO_use_the_scripts.txt<br> ├── step1_matlab/ <br> | ├── Pos0_100_every_1000/ <br> | ├── matlab_image_processing/ <br> | ├── images_treated_20201120_220854/ <br> | └── Outputs/<br> └── step2_python/<br> └── Outputs/</p> <p> </p> <p> </p>
Fungi and deadwood diversity: A test of the area-heterogeneity trade-off hypothesis
<p>Environmental heterogeneity is one of the most fundamental drivers of species diversity. For decades, ecologists have suggested that heterogeneity-diversity relationships are generally positive. But today, a greater variety of heterogeneity-diversity relationships is discussed. In this study, we contrasted two hypotheses for wood-inhabiting fungi: The classical heterogeneity-diversity hypothesis, that predicts positive relationships due to an increase in niche dimensionality with increasing heterogeneity. And the more recently stated area-heterogeneity trade-off hypothesis, that predicts a unimodal pattern due to an inherent trade-off between the number of occupied niches and the effective area per species. It allows positive and negative relationships only as special cases.</p> <p>We sampled 3,715 deadwood objects on 135 plots along a forest structure gradient in the Black Forest, Germany, and recorded 284 wood-inhabiting fungal species. To assess heterogeneity of deadwood structures, we calculated two multidimensional structural diversity indices: Structural richness was used as a measure of available niche space, and structural divergence as a measure of multivariate variance within that niche space. Those indices were then related to species richness estimates for rare, common, and dominant species, using the framework of Hill numbers.</p> <p>We found a linear, positive effect of structural richness and a unimodal effect for structural divergence on estimated species diversity. Structural richness, but not structural divergence was strongly correlated with the number of sampled deadwood objects. No clear differences between the responses of rare, common, and dominant species to the two heterogeneity gradients were found. We also estimated the mean abundance as proxy for mean population size, which decreased significantly with structural richness, but was non-significantly related to structural divergence.</p> <p><em>Synthesis: </em>In general, the results of this study suggest a unimodal heterogeneity-diversity relationship for deadwood-inhabiting fungi, and are thereby in line with the area-heterogeneity trade-off hypothesis. Thus, the negative effect of heterogeneity should lead to lower species richness and higher risk of stochastic extinctions at high levels of heterogeneity. However, as deadwood amount and deadwood diversity are often strongly correlated, we argue that the positive effect of resource availability on species richness may mask the negative effect of structural heterogeneity in some cases.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.