Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,157
datasets available to search
ShareScore release 0.9.0
Dataset results
1,157 results for “Limited data”
Figures 4-6 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Figures 4-6 Shape differences wireframes in PC1. Gray solid lines indicate C. tener (positive PC1 values) and black dotted lines indicate C. expulsus (negative PC1 values), see Fig. 3 for individual projections. (4) Differences between the mean shapes of C. tener and C. expulsus; (5) differences between the disparate shape of C. tener represented by CT 05 and C. expulsus represented by CE 09; (6) shape differences wireframes in PC2. Gray solid lines indicate the mean of shape of PC2 value and black dotted lines indicate specimen CT 02 (C. tener outlier).
Data for "Towards quantum gravity with neural networks: Solving quantum Hamilton constraints of 3d Euclidean gravity in the weak coupling limit"
<h2>1. Repository Information</h2> <p>This repository contains the data produced during the work discussed in in the paper "<a href="https://iopscience.iop.org/article/10.1088/1361-6382/ad7c14" target="_blank" rel="noopener">Towards quantum gravity with neural networks: Solving quantum Hamilton constraints of 3d Euclidean gravity in the weak coupling limit</a>". Please refer to this paper for more details on how the data was produced.</p> <p> </p> <h2>2. Citing</h2> <p>In addition to citing this repository, please also cite the paper mentioned above if you use the data. The citation is:</p> <p>Hanno Sahlmann and Waleed Sherif 2024 <em>Class. Quantum Grav.</em> <strong>41</strong> 215006</p> <p> </p> <h2>3. File Description</h2> <p>In this repository, you will find 4 general directories (here called parent directories):</p> <ol> <li>Ground Energy + Fluctuations</li> <li>Misc</li> <li>Quantum Constraint</li> <li>Volume</li> </ol> <p>Each of these directories correposnd to different data produced and discussed in the corresponding parts in the paper mentioned above (e.g. the directory "Ground Energy + Fluctuations" contains the data used in Table 1 and Table 2 in the paper while the "Volume" directory contains the data used in Section 4.3 of the paper).</p> <p>Some of these parent directories, which involve simulations solving constraints, contain within them several sub-directories (child directories) corresponding to different produced data. The raw data of the simulation can be found in a <code>.json</code> file inside the child directories.</p> <p> </p> <h2>4. Usage</h2> <h3>4.1 Raw Simulation Data</h3> <p>The <code>.json</code> files include the raw data produced during the study. These files can be easily accessed using a python script, as an example, by using:</p> <p><code>import json</code></p> <p><code>filePath = ...</code></p> <p><code>data = json.load(open(filePath))</code></p> <p>where <code>filePath</code> should hold the correct path to the local data once downloaded. Once loaded, the data is handled as a python <code>dict</code>.</p> <p> </p> <p>The dictionary will have <em>at least one</em> parent key called "Energy". The data in the "Energy" key corresponds to the data being minimised. The data in any other parent key correspond to operators which were being observed during the simulation. For example, in the data in the "Quantum Constraint" directory, some .json files will have multiple parent keys such as FG, H, HG, .... Each of these keys correspond to different operators which were observed during that simulation. Each parent key is yet another dictionary in itself. The structure of the dictionaries corresponding to any parent key are always the same and always include the keys:</p> <ul> <li>iters</li> <li>Mean</li> <li>Variance</li> <li>Sigma</li> <li>R_hat</li> <li>TauCorr</li> </ul> <p>Hence, to access the "Mean" values, you use <code>data["Energy"]["Mean"]</code> (or alternatively <code>data["FG"]["Mean"]</code> if you wish to observe the value of the F + G operator during the simulation). The data represents the values during a simulation of typically 500 iterations, hence, each of the keys mentioned above will correspond to an array of 500 items. The <code>iters</code> array includes merely the iteration number. The <code>Mean</code> array includes the value of the expectation value of the constraint at the corresponding iteration. The <code>Variance</code>, <code>Sigma</code>, <code>R_hat</code> and <code>TauCorr</code> includes the values of the variance and error in the expectation value at the given iteration as well as the split R-hat diagnostic and the time correlation also in the given iteration. </p> <p> </p> <h3>4.2 Variational State Data</h3> <p><em><strong>The files for the variational arrays are too large to be uploaded to a general repository hosting service. Therefore, they will be provided directly upon request in a direct download link. Please contact the author of the paper (Waleed Sherif, email: waleed.sherif@fau.de) for accessing the data. </strong></em></p> <p> </p> <h3>4.3 Fluctuation results</h3> <p>In some child directories, there will be a <code>.txt</code> file which includes the output of the calculation of the expectation value of some operators and their quantum fluctuations. These are only results, and not data, as the data can only be computed during the simulation.</p> <p> </p> <h2>4.4 Probabilities</h2> <p>The "Misc/Probabilities" directory contains <code>.npy</code> files which should be handled in the same manner as the variational states. These files correspond to the probability simulations conducted in section 4.4.4 in the paper.</p> <p> </p> <h2>5. Contact</h2> <p>Shall you have any unanswered questions regarding the usage of the data, please contact the author:</p> <p>Waleed Sherif</p> <p>email: waleed.sherif@fau.de</p> <p> </p> <h2>6. References</h2> <p>The data provided in this repository was produced using the <a href="https://github.com/netket" target="_blank" rel="noopener">NetKet</a>[1] package</p> <p>[1] <a href="https://doi.org/10.21468/SciPostPhysCodeb.7" target="_blank" rel="noopener">doi: 10.21468/SciPostPhysCodeb.7</a></p>
Data to: High tolerance to zinc but limited evidence for local adaptation in the aquatic plant species Lemna gibba/minor
<p>We measured <em>Lemna</em> growth in a reciprocal transplant experiment in a glasshouse where the four plant populations were grown in each of the environments, as well as in three different concentrations of Zn. We sampled chlorophyll-a as a proxy for algal biomass, and also measured total nitrogen and total organic carbon.</p> <p> </p> <p> </p>
Рис. 2. Схема распространения и мест встречи японского ужа на российском ΔаΛьнем Востоке: 1 — места встречи Αо 1985 г. (по Λитературным Αанным); 2 — места встречи посΛе 1985 г.; 3 — «КΛючевые ΛокаΛитеты» (см. в тексте); 4 — распространение хвойноширокоΛиственных и широкоΛиственных Λесов (по: КоΛесников 1969); 5 — граница распространения манчжурской фауны (по: Куренцов 1965) Fig. 2. Distribution map and finding localities of Hebius vibakari in the Russian Far East: 1 — findings before 1985 (according to the published data); 2 — findings after 1985; 3 — Key localities (see the text of the article); 4 — distribution of coniferous/broad-leaved and broad-leaved forests (see Kolesnikov 1969); 5 — limits of the Manchurian fauna (see Kurentsov 1965) in Особенности Распространения Японского Ужа Hebius Vibakari (H. Boie, 1826) (Colubridae: Natricinae) В Российской Части Ареаλа
Рис. 2. Схема распространения и мест встречи японского ужа на российском ΔаΛьнем Востоке: 1 — места встречи Αо 1985 г. (по Λитературным Αанным); 2 — места встречи посΛе 1985 г.; 3 — «КΛючевые ΛокаΛитеты» (см. в тексте); 4 — распространение хвойноширокоΛиственных и широкоΛиственных Λесов (по: КоΛесников 1969); 5 — граница распространения манчжурской фауны (по: Куренцов 1965) Fig. 2. Distribution map and finding localities of Hebius vibakari in the Russian Far East: 1 — findings before 1985 (according to the published data); 2 — findings after 1985; 3 — Key localities (see the text of the article); 4 — distribution of coniferous/broad-leaved and broad-leaved forests (see Kolesnikov 1969); 5 — limits of the Manchurian fauna (see Kurentsov 1965)
Scripts and data for: Increased host diversity limits bacterial generalism but may promote microbe-microbe interactions
<p>Research Overview: In this project, we compared cloacal microbiome communities from reptiles from six localities that spanned a gradient in host taxonomic diversity. We found that diversity of the bacterial communities was relatively stable across locations, but that host-specific taxa were overrepresented in high host diversity communities. ASVs in high host diversity communities were more likely to have strong interactions with other bacterial lineages across multiple hosts. Host generalist bacteria were more likely to be from a generalist phylum.</p> <p>Methodology: We used a 16S rRNA metabarcoding approach to quantify bacterial community diversity. We processed the output fastq files using qiime2, and processed the output files using the qiime2R package. We performed our analyses in R. Processed input files and scripts are described below. </p>
considered that it was present. Due to the lack of recent data and the limited information sup- plied by previous authors for Angolan specimens, the presence of L. viridis in Angola is questionable. MAP 74. Distribution of Leptopelis viridis in Angola. in Diversity and Distribution of the Amphibians and Terrestrial Reptiles of Angola Atlas of Historical and Bibliographic Records (1840-2017)
considered that it was present. Due to the lack of recent data and the limited information sup- plied by previous authors for Angolan specimens, the presence of L. viridis in Angola is questionable. MAP 74. Distribution of Leptopelis viridis in Angola.
Supporting data and results for manuscript: "Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches"
Open the record for dataset details and reuse information.
Data from: Sign epistasis limits evolutionary trade-offs at the confluence of single- and multi-carbon metabolism in Methylobacterium extorquens AM1
Adaptation of one set of traits is often accompanied by attenuation of traits important in other selective environments, leading to fitness trade-offs. The mechanisms that either promote or prevent the emergence of trade-offs remain largely unknown, and are difficult to discern in most systems. Here, we investigate the basis of trade-offs that emerged during experimental evolution of Methylobacterium extorquens AM1 to distinct growth substrates. After 1500 generations of adaptation to a multi-carbon substrate, succinate (S), many lineages had lost the ability to use one-carbon compounds such as methanol (M), generating a mixture of M+ and M− evolved phenotypes. We show that trade-offs in M− strains consistently arise via antagonistic pleiotropy through recurrent selection for loss-of-function mutations to ftfL (formate-tetrahydrofolate ligase), which improved growth on S while simultaneously eliminating growth on M. But if loss of FtfL was beneficial, why were M trade-offs not found in all populations? We discovered that eliminating FtfL was not universally beneficial on S, as it was neutral or even deleterious in certain evolved lineages that remained M+. This suggests that sign epistasis with earlier arising mutations prevented the emergence of mutations that drove trade-offs through antagonistic pleiotropy, limiting the evolution of metabolic specialists in some populations.
Data from: Horizontal and vertical movements of Caribbean reef sharks (Carcharhinus perezi): conservation implications of limited migration in a marine sanctuary
Despite the ecological and economic importance of the Caribbean reef shark (Carcharhinus perezi), little data exist regarding the movements and habitat use of this predator across its range. We deployed 11 pop-up satellite archival tags on Caribbean reef sharks captured in the northeast Exuma Sound, The Bahamas, to assess their horizontal and vertical movements throughout the water column. Sharks showed high site fidelity to The Bahamas suggesting Bahamian subpopulations remain protected within the Bahamian Shark Sanctuary. Depth data indicate that Caribbean reef sharks spent a significant proportion (72–91%) of their time above 50 m in narrow vertical depth bands, which varied considerably on an individual basis. This may be indicative of high site fidelity to specific bathymetric features. Animals exhibited three broadly categorized sporadic off-bank excursions (more than 50 m excursions) down to a depth of 436.1 m, which were more frequent during the night. These deeper excursions during night may be indicative of foraging in relation to prey on mesophotic reefs, as well as diel-vertically migrating prey from the deeper meso- and bathypelagic zones. These vertical movements suggest that Caribbean reef sharks can be significant vectors of ecosystem connectivity further warranting holistic multi-system management and conservation approaches.
Data from: Host diversity limits the evolution of parasite local adaptation
Specificity in the interactions between hosts and their parasites can lead to local adaptation. However, the degree of local adaptation is predicted to depend upon the diversity of resistance alleles within the host population; increasing host diversity should decrease mean parasite infectivity and hence reduce local adaptation. In this study, we empirically test this prediction using the highly specific interactions between bacteria with clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas) immunity and their bacteriophage. Bacteria acquire immunity to phage by incorporating a phage-derived spacer sequence into CRISPR loci on the host genome, and phage can escape the CRISPR-mediated immunity of a specific clone by mutating the targeted sequence. We found that high levels of CRISPR allele diversity that naturally evolve in host populations exposed to phage (because each bacterial clone captures a unique phage-derived sequence) prevents phage from becoming locally adapted. By manipulating the number of CRISPR alleles in the host population, we show that phage can become locally adapted to their bacterial hosts but only when CRISPR allele diversity is low.
Data from: Subtropical thermal variation supports persistence of corals but limits productivity of coral reefs
Concomitant to the decline of tropical corals caused by increasing global sea temperatures is the potential removal of barriers to species range expansions into subtropical and temperate habitats. In these habitats, species must tolerate lower annual mean temperature, wider annual temperature ranges, and lower minimum temperatures. To understand ecophysiological traits that will impact geographic range boundaries we monitored populations of five coral species within a marginal habitat and used a year of in situ measures to model thermal performance of vital host, symbiont, and holobiont physiology. Metabolic responses to temperature revealed two acclimatization strategies: peak productivity occurring at annual midpoint temperatures (4-6ºC lower than tropical counterparts), or at annual maxima. Modeled relationships between temperature and P:R were compared to a year of daily sub-tropical sea temperatures and revealed that the relatively short time spent at any one temperature, limited optimal performance of all strategies to approximately half the days of the year. Thus, while subtropical corals can adjust their physiology to persist through seasonal lows, seasonal variation seems to be the key factor limiting coral productivity. This constraint on rapid reef accretion within subtropical environments provides insight into the global distribution of future coral reefs and their ecosystem services.
Data from: Global biogeography of scaly tree ferns (Cyatheaceae): evidence for Gondwanan vicariance and limited transoceanic dispersal
Aim: Scaly tree ferns, Cyatheaceae, are a well-supported group of mostly tree-forming ferns found throughout the tropics, the subtropics and the south-temperate zone. Fossil evidence shows that the lineage originated in the Late Jurassic period. We reconstructed large-scale historical biogeographical patterns of Cyatheaceae and tested the hypothesis that some of the observed distribution patterns are in fact compatible, in time and space, with a vicariance scenario related to the break-up of Gondwana. Location: Tropics, subtropics and south-temperate areas of the world. Methods: The historical biogeography of Cyatheaceae was analysed in a maximum likelihood framework using Lagrange. The 78 ingroup taxa are representative of the geographical distribution of the entire family. The phylogenies that served as a basis for the analyses were obtained by Bayesian inference analyses of mainly previously published DNA sequence data using MrBayes. Lineage divergence dates were estimated in a Bayesian Markov chain Monte Carlo framework using beast. Results: Cyatheaceae originated in the Late Jurassic in either South America or Australasia. Following a range expansion, the ancestral distribution of the marginate-scaled clade included both these areas, whereas Sphaeropteris is reconstructed as having its origin only in Australasia. Within the marginate-scaled clade, reconstructions of early divergences are hampered by the unresolved relationships among the Alsophila, Cyathea and Gymnosphaera lineages. Nevertheless, it is clear that the occurrence of the Cyathea and Sphaeropteris lineages in South America may be related to vicariance, whereas transoceanic dispersal needs to be inferred for the range shifts seen in Alsophila and Gymnosphaera. Main conclusions: The evolutionary history of Cyatheaceae involves both Gondwanan vicariance scenarios as well as long-distance dispersal events. The number of transoceanic dispersals reconstructed for the family is rather few when compared with other fern lineages. We suggest that a causal relationship between reproductive mode (outcrossing) and dispersal limitations is the most plausible explanation for the pattern observed.
Data from: Plasmid carriage can limit bacteria-phage coevolution
Coevolution with bacteriophages is a major selective force shaping bacterial populations and communities. A variety of both environmental and genetic factors has been shown to influence the mode and tempo of bacteria–phage coevolution. Here, we test the effects that carriage of a large conjugative plasmid, pQBR103, had on antagonistic coevolution between the bacterium Pseudomonas fluorescens and its phage, SBW25ϕ2. Plasmid carriage limited bacteria–phage coevolution; bacteria evolved lower phage-resistance and phages evolved lower infectivity in plasmid-carrying compared with plasmid-free populations. These differences were not explained by effects of plasmid carriage on the costs of phage resistance mutations. Surprisingly, in the presence of phages, plasmid carriage resulted in the evolution of high frequencies of mucoid bacterial colonies. Mucoidy can provide weak partial resistance against SBW25ϕ2, which may have limited selection for qualitative resistance mutations in our experiments. Taken together, our results suggest that plasmids can have evolutionary consequences for bacteria that go beyond the direct phenotypic effects of their accessory gene cargo.
Data from: Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlations
Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited.
Data from: miR-9a modulates maintenance and ageing of Drosophila germline stem cells by limiting N-cadherin expression
Ageing is characterized by a decline in stem cell functionality leading to dampened tissue regeneration. While the expression of microRNAs across multiple species is markedly altered with age, the mechanism by which they govern stem cell-sustained tissue regeneration is unknown. We report that in the Drosophila testis, the conserved miR-9a is expressed in germline stem cells and its levels are significantly elevated during ageing. Transcriptome and functional analyses show that miR-9a directly regulates the expression of the adhesion molecule N-cadherin (N-cad). miR-9a null mutants maintain a higher number of stem cells even in the aged tissue. Remarkably, this rise fails to improve tissue regeneration and results in reduced male fertility. Similarly, overexpression of N-cad also results in elevated stem cell number and decreased regeneration. We propose that miR-9a downregulates N-cad to enable adequate detachment of stem cells toward differentiation, thus providing the necessary directionality toward terminal differentiation and spermatogenesis.
Data from: Genomic evidence that resource-based trade-offs limit host-range expansion in a seed beetle
Trade-offs have often been invoked to explain the evolution of ecological specialization. Phytophagous insects have been especially well studied, but there has been little evidence that resource-based trade-offs contribute to the evolution of host specialization in this group. Here, we combine experimental evolution and partial genome resequencing of replicate seed beetle selection lines to test the trade-off hypothesis and measure the repeatability of evolution. Bayesian estimates of selection coefficients suggest that rapid adaptation to a poor host (lentil) was mediated by standing genetic variation at multiple genetic loci and involved many of the same variants in replicate lines. Sublines that were then switched back to the ancestral host (mung bean) showed a more gradual and variable (less repeatable) loss of adaptation to lentil. We were able to obtain estimates of variance effective population sizes from genome-wide differences in allele frequencies within and between lines. These estimates were relatively large, which suggests that the contribution of genetic drift to the loss of adaptation following reversion was small. Instead, we find that some alleles that were favored on lentil were selected against during reversion on mung bean, consistent with the genetic trade-off hypothesis.
Data from: Re-examination of species limits in Aspergillus section Flavipedes using advanced species delimitation methods and description of four new species
<p><span>Since the last revision in 2015, the taxonomy of section <i>Flavipedes</i> evolved rapidly along with the availability of new species delimitation techniques. This study aims to re-evaluate the species boundaries of section <i>Flavipedes </i>members using modern delimitation methods applied to an extended set of strains (n=90) collected from various environments. The analysis used DNA sequences of three house-keeping genes (<i>benA</i>, <i>CaM</i>, <i>RPB2</i>) and consisted of two steps: application of several single-locus (GMYC, bGMYC, PTP, bPTP) and multi-locus (STACEY) species delimitation methods to sort the isolates into putative species, which were subsequently validated using DELINEATE software that was applied for the first time in fungal taxonomy. As a result, four new species are introduced, i.e. <i>A. alboluteus</i>, <i>A. alboviridis</i>, <i>A. inusitatus</i> and <i>A. lanuginosus</i>, and <i>A. capensis</i> is synonymized with <i>A. iizukae</i>. Phenotypic analyses were performed for the new species and their relatives and the results showed that the growth parameters at different temperatures and colonies characteristics were useful for differentiation of these taxa. The revised section harbors 18 species, most of them are known from soil. However, common species from the section are ecologically diverse, occurring in indoor environment (6 species), clinical samples (5 species), food and feed (4 species), droppings (4 species) and other less common substrates/environments. Due to the occurrence of section <i>Flavipedes</i> species in the clinical material/hospital environment, we also evaluated the susceptibility of 66 strains to six antifungals (Amphotericin B, Itraconazole, Posaconazole, Voriconazole, Isavuconazole, Terbinafine) using the reference EUCAST method. These results showed some potentially clinically relevant differences in susceptibility between species. For example, MICs higher than those observed for wild-type <i>A. fumigatus</i> were found for both triazoles and amphotericin B for <i>A. ardalensis, A. iizukae, </i>and<i> A. spelaeus</i> whereas <i>A. lanuginosus, A. luppiae, A. movilensis, A. neoflavipes, </i>and<i> A. olivimuriae</i> were comparable to or more susceptible as <i>A. fumigatus</i>. Finally, terbinafine was <i>in vitro</i> active against all species except <i>A. alboviridis</i>.</span></p>
Data from: The travel speeds of large animals are limited by their heat-dissipation capacities
<div> <h2>Purpose</h2> <p>This is an extension of the travel speed dataset published by Dyer et al. 2023 in PLOS Biology that includes additional metadata. Data follow the same aggregation to species level by grouping records across unique combinations of study and species while preserving variation across important categorical covariates (listed below). </p> </div> <div> <h2>Scripts</h2> <ul> <li><code>scripts/modelling/fit_model.R</code>: Fits mechanistic locomotion models to aggregated data using RStan. Plots predictions and outputs parameter estimates of competing models.</li> </ul> </div> <div> <h2>Data Columns</h2> <p>Each heading below describes a column of the travel speed dataset.</p> <p><strong>move_speed_ref</strong>: Unique reference number for each study reporting animal travel speed. The corresponding references are contained within the supplementary reference list file.</p> <p><strong>move_mass_ref</strong>: Unique reference number for each study reporting animal body mass. The corresponding references are contained within the supplementary reference list file.</p> <p><strong>scientific_name</strong>: Scientific name of the species according to the taxonomy of the Global Biodiversity Information Facility (accessed via GBIF.org during 2022). A small number of studies that report only the genus name or common name of the species are reported in our dataset as <em>Genus sp.</em> (e.g. <em>Gazella sp.</em>). One study, which estimated the travel speed and body mass of an unknown species of mouse via camera traps, is reported in our dataset as <em>Amazon mouse sp.</em></p> <p><strong>move_movement_mode</strong>: Categorical value indicating whether the reported travel speed corresponds to an animal engaged in flying, running, or swimming. This allows species to be accommodated that are capable of multi-modal locomotion (e.g. northern elephant seal, <em>Mirounga angustirostris</em>).</p> <p><strong>taxon_group</strong>: Categorical value indicating membership to one of eight animal groups (amphibian, arthropod, cnidarian, bird, fish, mammal, mollusc, reptile).</p> <p><strong>thermo_reg</strong>: Categorical value indicating thermoregulatory strategy, i.e. the contribution of metabolic heat production to the maintenance of core body temperature during rest:<br>- <strong>ectotherm</strong>: negligible contribution, body temperature matches ambient temperature<br>- <strong>mesotherm</strong>: weak contribution with partial thermal stability, as in tunas, lamnid sharks, and leatherback sea turtles<br>- <strong>endotherm</strong>: strong contribution with metabolic stability even when ambient temperatures are significantly below body temperature</p> <p><strong>move_medium</strong>: Categorical value indicating whether the animal’s travel speed was measured during locomotion within the terrestrial realm (air) or aquatic realm (water).</p> <p><strong>move_speed_method</strong>: Categorical value indicating whether travel speed was estimated directly (i.e. instantaneously via direct observation in real-time, animal-attached speedometer, or video recording) or indirectly from higher-resolution telemetry data (i.e. from changes in an animal’s spatial coordinates at intervals < 30 minutes apart).</p> <p><strong>move_study_condition</strong>: Categorical value indicating whether travel speed was estimated under natural field conditions or under a controlled laboratory setting such as within an aquarium or mesocosm. Travel speeds of the smallest animals (e.g. arthropods) can only feasibly be estimated within a controlled setting.</p> <p><strong>move_avgspeed_value</strong>: Categorical value indicating whether average travel speed was reported as a mean or median within the original study.</p> <p><strong>move_bodymass_kg</strong>: Continuous value indicating the average adult body mass (units: kilograms) of the species. In cases where the study’s reference numbers <code>move_speed_ref</code> and <code>move_mass_ref</code> differ, we referred to secondary literature sources to assign the average adult body mass of the species. In cases where only body length was given, we used published allometric equations to estimate the wet body mass.</p> <p><strong>move_avgspeed_ms</strong>: Continuous value indicating the average (geometric mean) travel speed (units: metres per second) of the species reported within the study.</p> <p><strong>move_speed_source</strong>: Categorical value indicating the sampling level at which travel speed measurements were reported within the study.<br>- <code>indv</code>: travel speed reported from an individual animal. - <code>avgs</code>: travel speed reported as an average (mean or median) across multiple individuals from the same species.</p> <p><strong>move_individuals_n</strong>: Integer value indicating the number of individual animals from which travel speed measurements were obtained within the study.</p> <p><strong>move_measurements_n</strong>: Integer value indicating the number of travel speed measurements taken across individuals within the study. This value can exceed <code>move_individuals_n</code> when repeated measurements were made from the same individuals.</p> <p><strong>move_ygeo_min</strong>: Continuous value indicating the minimum reported latitude (decimal degrees) of the study location(s).</p> <p><strong>move_ygeo_max</strong>: Continuous value indicating the maximum reported latitude (decimal degrees) of the study location(s).</p> <p><strong>move_xgeo_min</strong>: Continuous value indicating the minimum reported longitude (decimal degrees) of the study location(s).</p> <p><strong>move_xgeo_max</strong>: Continuous value indicating the maximum reported longitude (decimal degrees) of the study location(s).</p> <p><strong>move_date_min</strong>: Earliest reported date of data collection within the study (format: YYYY-MM-DD).</p> <p><strong>move_date_max</strong>: Latest reported date of data collection within the study (format: YYYY-MM-DD).</p> <p><strong>move_study_country</strong>: Country in which the study was conducted.</p> <p><strong>move_study_location</strong>: A description of the study location.</p> </div> <div> <h2>Version Notes</h2> <p>This updated version of the travel speed dataset extends the aggregated dataset published in <br>Dyer et al. 2023, PLOS Biology<strong> </strong>through the inclusion of additional metadata fields.<br>Metadata follow the same aggregation to species level by grouping records across unique combinations of study and species while preserving variation across important categorical covariates (listed above).</p> <div> <h3>Key Updates</h3> <ul> <li><strong>Added spatial metadata</strong>: minimum and maximum latitude/longitude, study country, and study location.</li> <li><strong>Added temporal metadata</strong>: earliest and latest reported dates of data collection (YYYY-MM-DD).</li> <li><strong>Refined sampling information</strong>: number of individuals (<code>move_individuals_n</code>) and number of speed measurements (<code>move_measurements_n</code>) are now reported, where available.</li> </ul> </div> </div>
Figures 15-17 from: Kurina O, Õunap E, Põldmaa K (2015) Two new Neuratelia Rondani (Diptera, Mycetophilidae) species from Western Palaearctic: a case of limited congruence between morphology and DNA sequence data. ZooKeys 496: 105-129. https://doi.org/10.3897/zookeys.496.9315
Figures 15-17 - Male terminalia, dorsal view, tergite 9 removed. Neuratelia jabalmoussae sp. n. (15), Neuratelia caucasica Zaitzev, 1994 (16) and Neuratelia minor (Lundström, 1912) (17). Scale bar = 0.1 mm.
Figures 23-26 from: Kurina O, Õunap E, Põldmaa K (2015) Two new Neuratelia Rondani (Diptera, Mycetophilidae) species from Western Palaearctic: a case of limited congruence between morphology and DNA sequence data. ZooKeys 496: 105-129. https://doi.org/10.3897/zookeys.496.9315
Figures 23-26 - Male terminalia of Neuratelia nemoralis (Meigen, 1818) (23, 25) and Neuratelia salmelai sp. n. (24, 26). Lateral view (23, 24) and internal view of the gonostylus (25, 26). Scale bar = 0.1 mm. For abbreviations: see Figs 7–8 and 19–22.
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.