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.
3,139
datasets available to search
ShareScore release 0.9.0
Dataset results
3,139 results for “fitting”
Data from: Interactions between fitness components across the life cycle constrain competitor coexistence
<p><span>Numerous mechanisms can promote competitor coexistence. Yet, these mechanisms are often considered in isolation of one another. Consequently, whether multiple mechanisms shaping coexistence combine to promote or constrain species coexistence remains an open question. </span><span>Here, we aim to understand how multiple mechanisms interact within and between life stages to determine frequency-dependent population growth, which has a key role stabilizing local competitor coexistence. </span><span>We conducted field experiments in three lakes manipulating relative frequencies of two <em>Enallagma</em> damselfly species to evaluate demographic contributions of three mechanisms affecting different fitness components across the life cycle: the effect of resource competition on individual growth rate, predation shaping mortality rates, and mating harassment determining fecundity. We then used a demographic model that incorporates carry-over effects between life stages to decompose the relative effect of each fitness component generating frequency-dependent population growth. </span><span>This decomposition showed that fitness components combined to increase population growth rates for one species when rare, but they combined to decrease population growth rates for the other species when rare, leading to predicted exclusion in most lakes. </span>Because interactions between fitness components within and between life stages vary among populations, these results show that local coexistence is population specific. Moreover, we show that multiple mechanisms do not necessarily increase competitor coexistence, as they can also combine to yield exclusion. Identifying coexistence mechanisms in other systems will require greater focus on determining contributions of different fitness components across the life cycle shaping competitor coexistence in a way that captures the potential for population level variation.</p>
2-point statistics covariance with fewer mocks: covariances from various datasets and results of the fits
<p>A set of covariances from random poissonian samples, LRG and ELG, and lognormal mocks, used for plots in the relevant publication.</p>
mmWave-based Fitness Activity Recognition Dataset
<p><strong>Description:</strong></p><p>This mmWave Datasets are used for fitness activity identification. This dataset (FA Dataset) contains 14 common fitness daily activities. The data are captured by the mmWave radar TI-AWR1642. The dataset can be used by fellow researchers to reproduce the original work or to further explore other machine-learning problems in the domain of mmWave signals.</p><p><strong>Format: </strong>.png format</p><p><strong>Section 1: Device Configuration</strong></p><ul><li>A commodity mmWave radar TI AWR1642, which integrates a 2 × 4 antenna array. The detailed information of it can be found at <a href="https://www.ti.com/product/AWR1642#:~:text=The%20AWR1642%20is%20an%20ideal,of%2076%20to%2081%20GHz">https://www.ti.com/product/AWR1642#:~:text=The%20AWR1642%20is%20an%20ideal,of%2076%20to%2081%20GHz.</a></li><li>A TI DCA1000EVM data capture card is used to collect data from the mmWave device and send data to a laptop. The detailed information can be found at <a href="https://www.ti.com/tool/DCA1000EVM?keyMatch=DCA1000EVM">https://www.ti.com/tool/DCA1000EVM?keyMatch=DCA1000EVM</a>.</li><li>mmWave radar work at the frequency in the range of 77~81GHz. The sampling rate is fixed at 100 frames per second and each frame has 17 chirps.</li></ul><p><strong>Section 2: Data Format</strong></p><p>We provide our mmWave data in heatmaps for this dataset. The data file is in the png format. The details are shown in the following:</p><ul><li>14 activities are included in the FA Dataset.</li><li>2 participants are included in the FA Dataset.</li><li>FA_d_p_i_u_j.png:<ul><li>d represents the date to collect the fitness data.</li><li>p represents the environment to collect the fitness data.</li><li>i represents fitness activity type index</li><li>u represents user id</li><li>j represents sample index</li></ul></li><li>Example:<ul><li>FA_20220101_lab_1_2_3 represents the 3rd data sample of user 2 of activity 1 collected in the lab</li></ul></li></ul><p><strong>Section 3: Experimental Setup</strong></p><ul><li>We place the mmWave device on a table with a height of 60cm.</li><li>The participants are asked to perform fitness activity in front of a mmWave device with a distance of 2m.</li><li>The data are collected at an lab with a size of (5.0m×3.0m).</li></ul><p><strong>Section 4: Data Description</strong></p><ul><li>We develop a spatial-temporal heatmap to integrates multiple activity features, including the range of movement, velocity, and time duration of each activity repetition.</li></ul><p> </p><ul><li>We first derive the Doppler-range map of the users' activity by calculating Range-FFT and Doppler-FFT. Then, we generate the spatial-temporal heatmap by accumulating the velocity of every distance in every Doppler-range map together. Next, we normalize the derived velocity information and present the velocity-distance relationship in time dimension. In this way, we transfer the original instantaneous velocity-distance relationship to a more comprehensive spatial-temporal heatmap which describes the process of a whole activity.</li></ul><p> </p><ul><li>As shown in Figure attached, in each spatial-temporal heatmap, the horizontal axis represents the time duration of an activity repetition while the vertical axis represents the range of movement. The velocity is represented by color.</li></ul><p> </p><ul><li>We create 14 zip files to store the the dataset. There are 14 zip files starting with "FA", each contains repetitions from the same fitness activity.</li></ul><p>14 common daily activities and their corresponding files </p><p><strong>File Name Activity Type File Name Activity Type</strong></p><p>FA1 Crunches FA8 Squats</p><p>FA2 Elbow plank and reach FA9 Burpees</p><p>FA3 Leg raise FA10 Chest squeezes</p><p>FA4 Lunges FA11 High knees</p><p>FA5 Mountain climber FA12 Side leg raise</p><p>FA6 Punches FA13 Side to side chops</p><p>FA7 Push ups FA14 Turning kicks</p><p> </p><p><strong>Section 5: Raw Data and Data Processing Algorithms</strong></p><ul><li>We also provide the mmWave raw data (.mat format) stored in the same zip file corresponding to the heatmap datasets. Each .mat file can store one set of activity repetitions (e.g., 4 repetations) from a same user.<ul><li>For example: FA_d_p_i_u_j.mat:<ul><li>d represents the data to collect the data.</li><li>p represents the environment to collect the data.</li><li>i represents the activity type index</li><li>u represents the user id</li><li>j represents the set index</li></ul></li></ul></li><li>We plan to provide the data processing algorithms (heatmap_generation.py) to load the mmWave raw data and generate the corresponding heatmap data.</li></ul><p><strong>Section 6: Citations</strong></p><p>If your paper is related to our works, please cite our papers as follows.</p><p><a href="https://ieeexplore.ieee.org/document/9868878/">https://ieeexplore.ieee.org/document/9868878/</a></p><p><i>Xie, Yucheng, Ruizhe Jiang, Xiaonan Guo, Yan Wang, Jerry Cheng, and Yingying Chen. "mmFit: Low-Effort Personalized Fitness Monitoring Using Millimeter Wave." In 2022 International Conference on Computer Communications and Networks (ICCCN), pp. 1-10. IEEE, 2022.</i></p><p>Bibtex:</p><p><i>@inproceedings{xie2022mmfit,</i></p><p><i> title={mmFit: Low-Effort Personalized Fitness Monitoring Using Millimeter Wave},</i></p><p><i> author={Xie, Yucheng and Jiang, Ruizhe and Guo, Xiaonan and Wang, Yan and Cheng, Jerry and Chen, Yingying},</i></p><p><i> booktitle={2022 International Conference on Computer Communications and Networks (ICCCN)},</i></p><p><i> pages={1--10},</i></p><p><i> year={2022},</i></p><p><i> organization={IEEE}</i></p><p><i>}</i></p>
Estimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption: Misfit plots in model parameter space
<p>Supporting documents for the correction of the publication <em>Multi‐Event Explosive Seismic Source for the 2022 Mw 6.3 Hunga Tonga Submarine Volcanic Eruption, </em>published in The Seismic Record (<a href="https://doi.org/10.1785/0320220027">https://doi.org/10.1785/0320220027</a>).</p>
Zenodo Collection: Estimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption
<p>This Zenodo collection contains figures and results from grid searches used to estimate point source parameters (force or moment tensor) for the main seismic subevent of the 2022 Hunga-Tonga submarine volcanic eruption. The collection includes misfit maps and waveform fits for the best-fitting force or moment tensor, as well as MTUQ weight files and a zipped version of the MTUQ code. These results were obtained using various software tools, including MTUQ, Axisem, Instaseis, Syngine, Obspy, GMT, and PyGMT. The collection was prepared for a manuscript in review for Geophysical Journal International.</p>
Database for "Phenotype-fitness relationships and pollen transfer efficiency of five orchid species with different pollination strategies" American Journal of Botany 2023
<p>Public data from the paper: Phenotype-fitness relationships and pollen transfer efficiency of five orchid species with different pollination strategies by M. Capò, J. Borràs, S. Perellò-Suau, J. Rita and J. Cursach, published in American Journal of Botany 2023. <a href="https://doi.org/10.5281/zenodo.7826601">DOI: 10.5281/zenodo.7826601</a></p>
TRACE-Omicron: Epidemiological Counterfactuals; Best Calibration Fit
<p>This repository contains the simulation data corresponding to the Epidemiological Counterfactuals under the Best Calibration Fit baseline scenario in "TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States" published in Advanced Theory and Simulations (doi:10.1002/adts.202300147)</p>
Correlates of early reproduction and apparent fitness consequences in male Soay sheep
<p>Life history trade-offs are ubiquitous across species and place constraints on the timing of life history events, including the optimal age at first reproduction. However, studies on lifetime breeding success of male mammals are rare due to sex-biased dispersal and the requirement for genetic paternity inferences. We studied the correlates and apparent fitness consequences of early-life reproduction among males in a free-living population of Soay sheep (<em>Ovis</em> <em>aries</em>) on St Kilda, Scotland. We investigated the factors associated with early breeding success and the apparent consequences of early success for survival and future reproduction. We used genetic paternity inferences, population data and individual morphology measurements collected over 30 years. We found that individuals born in years with low-density population size had the highest early-life breeding success, and singletons were more likely to be successful than twins. Individuals that bred successfully at seven months were more likely to survive their first winter. For individuals that survived their first winter, early breeding success was not associated with later breeding success. Since individual heterogeneity affects breeding success, we believe that variation in individual quality masks costs of early reproduction in this population. Our findings provide no evidence for selection for delayed age at reproduction in male Soay sheep. </p>
Data for: Plastic maternal effects of social density on reproduction and fitness in the least killifish, Heterandria formosa
<p>Environmental parental effects, also known as transgenerational plasticity, are widespread in plants and animals. Less well known is whether those effects contribute to maternal fitness in the same manner in different populations. We carried out a multi-generational laboratory experiment with females drawn from two populations of the Least Killifish, <em>Heterandria</em> <em>formosa</em>, to assess transgenerational plasticity in reproductive traits in response to differences in social density and its effects on maternal fitness. In the first and second generations, increased density decreased reproductive rate and increased offspring size in females from both populations. There were complicated patterns of transgenerational plasticity on maternal fitness that differed between females from different populations. Females from a population with historically low densities whose mothers experienced lower density had higher fitness than females whose mothers experienced higher density, regardless of their own density. The opposite pattern emerged in females from the population with historically high densities: females whose mothers experienced higher density had higher fitness than females whose mothers experienced lower density. This transgenerational plasticity is not anticipatory but might be considered adaptive in both populations if providing those "silver spoons" enhances offspring fitness in all environments.</p>
Predicting Pulsed-Laser Deposition SrTiO3 Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction - gaussian_fit_parameters - sample untreated_162nm
<p>RHEED raw dataset and Gaussia fitting parameter dataset for sample "untreated_162nm" in work "Predicting Pulsed Laser Deposition SrTiO<sub>3 </sub>Homoepitaxy Growth Dynamics using High-Speed Reflection High-Energy Electron Diffraction."</p>
Social network and fitness data from age-structured populations of forked fungus beetles
<p>We investigated the relationships between age, social behavior, and fitness at three levels of organization: the individual, the local social environment, and the population. Replicate groups of forked fungus beetles (<em>Bolitotherus cornutus</em>) were engineered to have either young- or old- biased age structures, and both social and reproductive behaviors were recorded.</p>
Short-term fitness consequences of parasitism depend on host genotype and within-host parasite community
<p>Multi-parasite communities inhabiting individual hosts are common and often consist of parasites from multiple taxa. The effects of parasite community composition and complexity on host fitness are critical for understanding how host-parasite coevolution is affected by parasite diversity. To test how naturally-occurring parasites affect host fitness of multiple host genotypes, we performed a common-garden experiment where we inoculated four genotypes of host plant <em>Plantago lanceolata</em> with six microbial parasite treatments: three single parasite treatments, a fungal mixture, a viral mixture, and a cross-kingdom treatment. Seed production was affected by both host genotype and parasite treatment, and their interaction jointly determined growth of the hosts. Fungal parasites had more consistent negative effects than viruses in both single mixed parasite treatments. These results demonstrate that parasite communities have the potential to affect the evolution and ecology of host populations through their effects on host growth and reproduction. Moreover, the results highlight the importance of accounting for the diversity of parasites as well as host genotypes when aiming to predict the consequences of parasites for epidemics as the effects of multi-parasitism are not necessarily additive of single parasite effects, nor uniform across all host genotypes.</p>
Fitness and niche differences are both important in explaining responses of plant diversity to nutrient addition
<p><span>Plant species loss due to eutrophication is a common phenomenon in temperate perennial grasslands. It occurs in a non-random fashion and is usually explained by increased competitive size asymmetry between co-occurring winner (tall species with optima in productive habitats) and loser species (small-statured plants typical for unproductive habitats). It remains unclear why nutrient addition decreases diversity in communities consisting of losers only, whereas it has little effect on winner-only communities. Here, I used the framework of modern coexistence theory to explore fertilization-driven changes in fitness and niche differences between different combinations of field-identified winner (W) and loser (L) species. I experimentally estimated competition parameters for plant species pairs constructed from a pool of eight species, including pairs of species from the same (WW, LL) and different species categories (LW) grown for approximately two years in control and fertilized conditions. Concurrently, I also followed plant species diversity in mesocosm communities constructed from the same species pool (four-species communities including winners, losers, or both) exposed to control and nutrient addition. </span><span>I found that nutrient addition can reduce but, unexpectedly, also promote species coexistence depending on the type of species pairs. Whereas nutrient addition eroded coexistence of losers with winners, but also with other losers, treatment had the opposite effect on the persistence of winner species. Fertilization induced large fitness differences between species in loser-winner and loser-loser combinations, but had little effect on the fitness differences of species within the winner-winner combination. In addition, the persistence of winner pairs was promoted by larger niche differences compared to loser species, irrespective of soil nutrients. The differences in how nutrient addition modified coexistence at the pairwise level were reflected by differences in evenness of multispecies communities assembled from the corresponding species categories.</span> <span>These results suggest that the effect of eutrophication on plant species richness cannot simply be explained by an increased competitive asymmetry. To fully understand the effect of fertilization on the diversity of temperate grasslands, interspecific and intraspecific interactions should be explored while considering differences in species' ecological optima.</span></p>
The role of environmental variation in mediating fitness tradeoffs for an amphibian polyphenism
<p class="MsoNormal"><span>Fitness tradeoffs are a foundation of ecological and evolutionary theory because tradeoffs can explain life history variation, phenotypic plasticity, and the existence of polyphenisms. </span></p> <p class="MsoNormal"><span>Using a 32-year mark-recapture dataset on lifetime fitness for 1,093 adult Arizona tiger salamanders (<em>Ambystoma mavortium nebulosum</em>) from a high elevation, polyphenic population, we evaluated the extent to which two life history morphs (aquatic paedomorphs vs terrestrial metamorphs) exhibited fitness tradeoffs in breeding and body condition with respect to environmental variation (e.g., climate) and internal state-based variables (e.g., age). </span></p> <p class="MsoNormal"><span>Both morphs displayed a similar response to higher probabilities of breeding during years of high spring precipitation (i.e., not indicative of a morph-specific fitness tradeoff). There were likely no climate-induced fitness tradeoffs on breeding state for the two life history morphs because precipitation and water availability are vital to amphibian reproduction. </span></p> <p class="MsoNormal"><span>Body condition displayed a contrasting response for the two morphs that was indicative of a climate-induced fitness tradeoff. While metamorphs exhibited a positive relationship with summer snowpack conditions, paedomorphs were unaffected. Fitness tradeoffs from summer snowpack are likely due to extended hydroperiods in temporary ponds, where metamorphs gain a fitness advantage during the summer growing season by exploiting resources that are unavailable to paeodomorphs. However, paedomorphs appear to have the overwintering fitness advantage because they consistently had higher body condition than metamorphs at the start of the summer growing season. </span></p> <p class="MsoNormal"><span>Our results reveal that climate and habitat type (metamorphs as predominately terrestrial, paedomorphs as fully aquatic) interact to confer different advantages for each morph. These results advance our current understanding of fitness tradeoffs in this well-studied polyphenic amphibian by integrating climate-based mechanisms. Our conclusions prompt future studies to explore how climatic variation can maintain polyphenisms and promote life history diversity, as well as the implications of climate change for polyphenisms. </span></p>
Datasets from Growth (2019) by Vaclav Smil with reproducible fits
<p>This repository contains data and code for 80 datasets featured in <a href="https://mitpress.mit.edu/9780262539685/growth/"><em>Growth: from microorganisms to megacities</em></a> (2019) by Vaclav Smil.</p> <p><em>Growth</em> contains a wealth of time-series data collected from diverse sources. Smil fits simple models, most notably the <a href="https://en.wikipedia.org/wiki/Logistic_function">logistic function</a>, to demonstrate how widely applicable they are: from the growth of bacteria to the growth of rail networks.</p> <p>This archive intends to make these datasets available for wider use in statistics teaching. Whatever your interest, there is probably a dataset in here for you!</p> <p>Thanks to Vaclav Smil for sharing these datasets to make this reanalysis possible.</p>
Data from: Humidity stress and its consequences for male pre- and post-copulatory fitness traits in an insect
<p>Global declines in insect abundance are of significant concern. While there is evidence that climate change is contributing to insect declines, we know little of the direct mechanisms responsible for these declines. Male fertility is compromised by increasing temperatures, and the thermal limit to fertility has been implicated as an important factor in the response of insects to climate change. However, climate change is affecting both temperature and hydric conditions, and the effects of water availability on male fertility have rarely been considered. Here we exposed male crickets <em>Teleogryllus</em> <em>oceanicus</em> to either low- or high-humidity environments while holding temperature constant. We measured water loss and the expression of both pre- and post-mating reproductive traits. Males exposed to a low-humidity environment lost more water than males exposed to a high-humidity environment. A male's cuticular hydrocarbon profile (CHC) did not affect the amount of water lost, and males did not adjust the composition of their CHC profiles in response to hydric conditions. Males exposed to a low-humidity environment were less likely to produce courtship song or produced songs of low quality. Their spermatophores failed to evacuate and their ejaculates contained sperm of reduced viability. The detrimental effects of low humidity on male reproductive traits will compromise male fertility and population persistence. We argue that limits to insect fertility based on temperature alone are likely to underestimate the true effects of climate change on insect persistence, and that the explicit incorporation of water regulation into our modelling will yield more accurate predictions of the effects of climate change on insect declines.</p>
An analysis of the effects of prior drying and vertebrate colonization on ecological functioning and vertebrate fitness
<p>We investigated the legacy effects of drying and refilling of wetlands via mesocosms on growth and survival of recolonizing aquatic vertebrates and their subsequent effects on ecological function. Specifically, we tested the effects of prior drying on anuran and fish growth and survival (using Gompertz growth curves), and joint effects of vertebrates and drying on periphyton biomass, and whole-system gross primary productivity. Using 64 1,000-L hard plastic cattle tanks to create replicate aquatic mesocosms, four trophic treatments (no vertebrate control, larval anurans, fish, larval anurans and fish) were crossed with two drying treatments (undried and dried-refilled) to simulate different outcomes of colonization by two common vertebrate guilds and drying/refilling cycles. Mesocosms with anuran treatments received 50 <em>Lithobates</em> <em>blairi</em> tadpoles (1,600 total) and mesocosms with fish treatments received one <em>Lepomis</em> <em>cyanellus</em> juvenile (32 total). We recorded anuran growth rates, survival, and time/size at metamorphosis, fish growth, gross primary productivity, and periphyton biomass over 12 weeks from 9 May 2021 to 1 August 2021.</p> <p>This dataset contains 4 R script files (one for each of the 4 components of this study: Amphibians, fish, gross primary productivity, and periphyton) along with their corresponding Excel files. Survival for each tank was calculated as the total number of emerged frogs from weeks 1–12 divided by 50 (initial number of larvae per tank). Size at metamorphosis was determined by dry mass (g) measured after 72 hours in a drying oven at 60° C. Metamorph dry mass and wet mass were strongly correlated (grams dry mass = 0.1957*grams wet mass – 0.0398; R<sup>2</sup> = 0.9733) and we chose dry mass for size at metamorphosis to reduce variability caused by water weight. We measured the dry mass of metamorphosed frogs to the nearest 0.01g. Time to metamorphosis was measured as the days past the first day of the experiment (9 May 2021) to the day the frog reached Gosner stage 46 (Gosner, 1960). We calculated relative fish growth as the change in standard length (SL) over the duration of the experiment divided by the initial SL for each fish. Individual fish growth calculations used each of the single fish per tank as independent replicates. Relative fish growth measurements for fish within the same treatments (n = 8) were combined and analyzed together. Gross primary productivity values were collected by measuring dissolved oxygen (DO) values after sunset for maximum DO and before sunrise for minimum DO. DO measurements were collected using a YSI meter (ProQuatro XA00088 – 02; YSI Inc., Yellow Springs, OH, USA) as a percentage out of 500. </p> <p>Gompertz growth curves provided estimates of asymptotic larval body mass (W<sub>max</sub>), maximum growth rate (K), and the time at which growth rates reach K (xm). However, only W<sub>max</sub> and K were included in statistical analyses as they were the primary parameters of interest for our study. All statistical analyses were performed in RStudio version 4.1.1 (R Core Team, 2021). We constructed generalized linear models (GLMs; 'stats' package in R; R Core Team, 2021) for each of Wmax, K, number of emerged frogs (survival), size at metamorphosis, time to metamorphosis, range of metamorph sizes, and range of metamorphosis days as response variables with drying treatment as the predictor variable. We also constructed GLMs with fish growth as the response variable and a combination of drying treatment and anuran presence as predictor variables with interaction terms. We then used type II ANOVAs for models without significant interaction terms and type III ANOVAs for models with interaction terms via the 'car' package in R (Fox & Weisberg, 2019) to determine the treatment effects on above response variables. GLM model fit and assumptions were checked by a visual assessment of the plotted residuals of each GLM model.</p> <p>Since GPP varied nonlinearly over the duration of the experiment (Fig. 4), we investigated the effects of drying and refilling and trophic treatment on GPP using generalized additive mixed models (GAMMs) with the 'gam' function ('mgcv' package; Wood, 2015). The GAMM model included trophic treatment and drying treatment as parametric effects, trophic treatment over time, drying treatment over time, and time as cubic regression smoother terms, and individual mesocosm and individual mesocosm over time as random effects. The number of knots was set to -1 to utilize the generalized cross-validation method to automatically choose the number of knots for the model. GAMMs allow us to test hypotheses related to main effects (e.g., trophic treatment, drying treatment) within non-linear time series while accounting for random effects related to individual mesocosms and changes over time due to seasonality. We then used a subsequent ANOVA via the 'anova.gam' function within the 'gam' package to determine treatments effects. </p> <p>We investigated the effects of drying and refilling and trophic treatment on periphyton biomass using GAMMs constructed and analyzed identically to GPP except that they are only for experimental days 19–80. This is because periphyton sampling techniques were not standardized until after the second week of data collection. Because data for periphyton biomass was right-skewed and included some 0's that were not true zeros (periphyton was present but below measurement limits), we added 0.5 to each measurement (untransformed mean was 1.838 g) and then log-transformed them. Models run with the transformed data met the assumptions of GAMMs and subsequent ANOVAs.</p>
Novel environments induce variability in fitness-related traits
<p class="MsoNormal">Environmental change from anthropogenic activities threatens individual organisms, the persistence of populations, and entire species. Rapid environmental change puts organisms in a double bind, they are forced to contend with novel environmental conditions but with little time to respond. Phenotypic plasticity can act quickly to promote establishment and persistence of individuals and populations in novel or altered environments. In typical environmental conditions, fitness-related traits can be buffered, reducing phenotypic variation in expression of traits, and allowing underlying genetic variation to accumulate without selection. In stressful conditions, buffering mechanisms can break down, exposing underlying phenotypic variation and permitting the expression of phenotypes that may allow populations to persist in the face of altered or otherwise novel environments. Using reciprocal transplant experiments of freshwater snails, we demonstrate that novel conditions induce higher variability in growth rates and, to a lesser degree, morphology (area of the shell opening) relative to natal conditions. Our findings suggest a potentially important role of phenotypic plasticity in population persistence as organisms face a rapidly changing, human-altered world.</p>
[Dataset] Difference spectrum fitting of the ion-neutral collision frequency from dual-frequency EISCAT measurements
<p>Dataset used for "Difference spectrum fitting of the ion-neutral collision frequency from dual-frequency EISCAT measurements"</p>
Data from: The quest for good genes: epigamic traits, fitness, MHC and multilocus heterozygosity in the guppy
<p><span>The "good genes" hypothesis for the evolution of male secondary sexual traits poses that female preferences for such traits are driven by indirect genetic benefits. However, support for the hypothesis remains ambiguous, and, in particular, the genetic basis for the benefits has rarely been investigated. Here, we use semi-natural populations of Trinidadian guppies to investigate whether sexually selected traits (orange, black and iridescent colouration, gonopodium length and body size) predict fitness measured as the number of grandoffspring, a metric that integrates across fitness components and sexes. Furthermore, we tested whether two potential sources of genetic benefits – major histocompatibility complex (MHC) genotypes and multilocus heterozygosity (MLH) – are significant predictors of fitness and of the size of sexually selected traits. We found a significant, non-linear effect of the area of black pigmentation and male body size on the number of grandoffspring, suggesting stabilising selection on black area, and non-linear selection favouring small body size. MLH was heritable (h<sup>2</sup> = 0.14) and significantly predicted the number of grandoffspring, indicating the potential for genetic benefits based on heterozygosity. We also found support for local heterozygosity effects, which may reflect a non-even distribution of genetic load across the genome. MHC genotype was not significantly associated with any tested fitness component, or with the load of <em>Gyrodactylus</em> parasites. Neither MHC nor MLH was a significant predictor of sexually selected traits. Overall, our results highlight the role of heterozygosity in determining fitness but do not provide support for male sexually selected traits being indicators of genetic quality. </span></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.