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.
2,586
datasets available to search
ShareScore release 0.9.0
Dataset results
2,586 results for “Gradients”
Data sets, code, figures for Sensing force gradients with cavity optomechanics while evading backaction
<p>The directory contains data sets, code and figures for the published version of the research article Sensing force gradients with cavity optomechanics while evading backaction.</p>
Data from: Monitoring microarthropods assemblages along a pH gradient in a forest soil over a 60 years' time period
<p>The goal of this study was to assess the development, over 60 years, of microarthropod communities over a pH gradient in forest soil.</p> <p>Site Description</p> <p>Hackfort is an oak coppice grove in the East-Southeast of the city of Zutphen in the province of Gelderland, the Netherlands, 52°06′09.7″ N, 6°15′56.0″ E (see Figure 1). The experimental area is about 1.5 ha and is divided in a 10 m × 10 m grid. Vegetation is dominated by common oak (<em>Quercus robur</em>), mixed with birch (<em>Betula pendula</em>), and had in 1959, an understory of wood sage plugs (<em>Teucrium scorodonia</em>), wood anemone (<em>Anemone nemorosa</em>), bracken (<em>Pteridium aquilinum</em>), and wavy-hair grass (<em>Deschampsia flexuosa</em>). In later years, the understory became more dominated by bramble species (<em>Rubus fruticosus </em>and<em> R. idaeus</em>) and common nettles (<em>Urtica dioica</em>) at the edges of the forest, due to increased N deposition from adjacent farmland. The forest is situated at the transition from western riverine deposits and eastern periglacial cover sands. The soil is a riverine deposit with a few elevation differences, making a number of gradients in clay and loam content, which results in many short-distance gradients in soil types, varying from typic haplaquolls with the largest loam contents, via psammaquentic haplorthods to humaqueptic spodic psammaquents, slightly elevated and low in loam contents.</p> <p>Microarthropod Sampling and pH Measurement</p> <p>In 1959, samples were taken at three subsequent dates: 11 September, 9 October, and 30 October. Samples in 1987 were taken on one date, 9 October, just as on 30 October 2019. Samples were taken following a standard procedure, developed at the Institute for Applied Biological Research in Nature, Wageningen, the Netherlands (later merged into the Research Institute for Nature management, Institute for Forestry and Nature Research and Alterra resp., now known as Wageningen Environmental Research); this procedure has been published by Siepel and van de Bund in 1988 (Siepel and van de Bund, 1988). Each mineral soil sample has 100 cc: a volume of 5 cm diameter and 5 cm depth plus litter on top. In 1959, two samples per date were taken on each plot, making a total of 6 samples (only pooled data are available); in 1987 and in 2019, 4 and 5 samples for each plot were taken on, respectively (data per sample available).</p> <p>Soil cores were put on a Tullgren funnel for 1 week, during which temperature was increased from 35 to 45 °C, and then, microarthropods were collected in 70% alcohol and later put into 20% lactic acid for clarification and identification (Siepel, 1990; Siepel and van de Bund, 1988). The Tullgren funnel used for extraction (Siepel, 1990) has been used ever since 1936 and efficiency has not changed as the tool and protocol was the same all over the years.</p> <p>Identification was done to the species level as much as possible using at present the keys for Oribatida(Weigmann and G., 2006), for Gamasina (Lehtinen, 1994), for Uropodina (Karg, 1989), and for Collembola (Hopkin, 2007). Material from the extractions of 1959 and 1987 was re-examined as far as possible to check the correct species identification. In the 1959 and 1987 samples, only oribatid mites were identified to the species level, whereas in 1959, all species of <em>Quadroppiidae, Oppiidae</em>, and <em>Suctobelbidae</em> were pooled. In 2019, all microarthropods were identified to the species level.</p> <p>Sorting and identification of the 1959 microarthropods was carried out by an experienced acarologist (J.G. de Gunst), in 1987, this was done by a student (C. Arnold) and completed and checked by the second author. For the 2019 samples, we decided to demonstrate the potential difference in picking out the microarthropods from the extraction fluid into the slides for identification as part of the experiment: the first author made a first series of slides including all distinguished animals (dataset 2019 a), while the second author made an extra set of slides with the animals missed by the first (dataset 2019 b). The first author did know since the beginning that the second author would check all samples after her sorting session. In this way, we intended to demonstrate the potential difference in this crucial part of the procedure by a starting and an experienced professional. In the analysis, we compare dataset (2019 a) with (2019 a + b), in order to highlight the difference between a starting and an experienced acarologist. Nomenclature adopted was updated according to current standards, following, e.g., the checklists for Oribatida (Siepel et al., 2009), for Astigmatina (Siepel et al., 2016), and for Mesostigmata (Siepel, 2018). Values of pH-KCl were measured in the core material after the extraction of the microarthropods, both in 1959, 1987, and 2019.</p> <p> </p> <p>We have four data files:</p> <p>1959 hackfort microarthropods data.csv</p> <p>1989 hackfort microarthropods data.csv</p> <p>2019 hackfort microarthropods data.csv</p> <p>pH data Hackfort 1959-2019.csv.</p> <p> </p> <p>Explanation of the variables in the datasets:</p> <p>higher taxon: Oribatida, Astigmata, Mesostigmata, Prostigmata, Collembola or Protura</p> <p>Name in De Gunst 1959: taxonomic identification by De Gunst in 1959</p> <p>Valid name: Henk Siepel re-checked these species names in 2019</p> <p>Plot: plot 1, plot 2, plot 3, plot 4, plot 5</p> <p>a: identified by Yuxi Guo</p> <p>b: re-checked by Henk Siepel from remaining soil microarthropods in slide</p> <p>pH(KCL) and pH(H2O): pH values based on indicated methods</p> <p> </p>
Disentangling responses to natural stressor and human impact gradients in river ecosystems across Europe
<p>1. Rivers are dynamic ecosystems in which both human impacts and climate-driven drying events are increasingly common. These anthropogenic and natural stressors interact to influence the biodiversity and functioning of river ecosystems. Disentangling ecological responses to these interacting stressors is necessary to guide management actions that support ecosystems adapting to global change.</p> <p>2. We analysed the independent and interactive effects of human impacts and natural drying on aquatic invertebrate communities—a key biotic group used to assess the health of European freshwaters. We calculated biological response metrics representing communities from 406 rivers in eight European countries: taxonomic richness, functional richness and redundancy, and two biomonitoring indices that indicate ecological status. We analysed metrics based on the whole community and a group of taxa with traits promoting resistance and/or resilience ('high RR') to drying. We also examined how responses vary across Europe in relation to climatic aridity.</p> <p>3. Most community metrics decreased independently in response to impacts and drying. A richness-independent biomonitoring index (the average score per taxon; ASPT) showed particular potential for use in biomonitoring, and should be considered alongside new metrics representing high RR diversity, to promote accurate assessment of ecological status.</p> <p>4. High RR taxonomic richness responded only to impacts, not drying. However, these predictors explained little variance in richness and other high RR metrics, potentially due to low taxonomic richness. Metric responsiveness could thus be enhanced by developing region-specific high RR groups comprising sufficient taxa with sufficiently variable impact sensitivities to indicate ecological status.</p> <p>5. Synthesis and applications. Our results inform recommendations guiding the development of metrics to assess the ecological status of dynamic river ecosystems—including those that sometimes dry—thus identifying priority sites requiring further investigation to identify the stressors responsible for environmental degradation. We recommend concurrent consideration of richness-independent biomonitoring indices (such as an ASPT) and new high RR richness metrics that characterize groups of resistant and resilient taxa for region-specific river types. Interactions observed between aridity, impacts and drying evidence that these new metrics should be adaptable, promoting their ability to inform management actions that protect river ecosystems responding to climate change.</p>
Data from: Environmental variation associated with topography explains butterfly diversity along a tropical elevation gradient
<p>Few studies have evaluated the role of topography on the diversity patterns of biological communities along elevation gradients. We evaluated the influence of microclimate and vegetation structure associated with topographic variation on the richness and composition of species of different families of butterflies on a mountain located in a dry enclave (Chicamocha River Canyon) in the northern Andes, Colombia. We captured butterflies over four months at 18 elevations (300 to 1500 m a.s.l.) in two topographic positions (riverbed and hillslope) using an entomological net and traps baited with fermented fruit. In general, butterfly richness increased with elevation in both topographic positions. However, the richness-elevation relationship changed with butterfly family. The riverbed and hillslope sites host different assemblages of butterflies, and this pattern that was consistent for most families. In the riverbed, two sets of species are recognized along the elevation gradient (one below 700 m a.s.l. and the other above 1000 m a.s.l.), mainly owing to species replacement. On the hillslopes there was no clear pattern of grouping associated with elevation. Microclimate differences between the riverbed and hillslope sites along the elevation gradient were related to the vegetation structure and explained the variation in butterfly species composition. Our results highlight the role of topography not only by explaining the response of species richness and composition to environmental variation determined by elevation, but also as a factor that must be considered in the planning and management of biodiversity conservation in the mountains.</p>
Probabilistic linear inversion of satellite gravity gradient data applied to the northeast Atlantic
<p>% MATLAB scripts to calculate and plot figures as in manuscript by<br> %<br> % Minakov, A., & Gaina, C. (2021).<br> % Probabilistic linear inversion of satellite gravity gradient data applied<br> % to the northeast Atlantic. Journal of Geophysical Research: Solid Earth,<br> % 126, e2021JB021854. https://doi.org/10.1029/2021JB021854<br> % <br> % Last modified by alexamin@uio.no, 26/11/2021<br> %<br> % version v1.1<br> % </p> <p>% Contents of arhcive<br> % /data contains requiried and generated datasets <br> % /fig folder for output figures <br> % /plot scripts to produce figures <br> % /tools additional matlab tools and routines</p> <p>% Dataset in ..data/GOCE_NEATLANTIC is structure containing the full model<br> % <br> % Cm: [6670×6670 double] posterior model covariance matrix<br> % m: [29×23×10 double] mean denstity perturbation model<br> % Cd: [667×667 double] data covariance matrix<br> % d: [29×23 double] data vector (Trr)<br> % r: [1×10 double] distance<br> % lat: [29×1 double] latitute<br> % lon: [23×1 double] longitude<br> %<br> % Run /plot/fig_results.m to produce all figures <br> %<br> % Some scripts require GMT (Wessel et al. 2019) and SHBUNDLE (Sneeuw et al. 2018) software to be installed</p> <p>% and corresponding folders must be added to the matlab search path.</p> <p>% Also ScientificColorMaps7 by F. Crameri (2021) maybe required and have been included in the archive.</p>
Gradient winds and neutral flow dawn-dusk asymmetry in the auroral oval during geomagnetically disturbed conditions (data files)
<p>Data files with wind profiles used to generate figures in the paper entitled "Gradient winds and neutral flow dawn-dusk asymmetry in the auroral oval during geomagnetically disturbed conditions"</p>
Semi‐quantitative metabarcoding reveals how climate shapes arthropod community assembly along elevation gradients on Hawaii Island
<p>Spatial variation in climatic conditions along elevation gradients provides an important backdrop by which communities assemble and diversify. Lowland habitats tend to be connected through time, whereas highlands can be continuously or periodically isolated, conditions that have been hypothesized to promote high levels of species endemism. This tendency is expected to be accentuated among taxa that show niche conservatism within a given climatic envelope. While species distribution modeling approaches have allowed extensive exploration of niche conservatism among target taxa, a broad understanding of the phenomenon requires sampling of entire communities. Species-rich groups such as arthropods are ideal case studies for understanding ecological and biodiversity dynamics along elevational gradients given their important functional role in many ecosystems, but community-level studies have been limited due to their tremendous diversity. Here, we develop a novel semi-quantitative metabarcoding approach that combines specimen counts and size-sorting to characterize arthropod community-level diversity patterns along two elevational gradients across two volcanoes on the island of Hawai`i. We find that arthropod communities between the two transects become increasingly distinct compositionally at higher elevations. Resistance surface approaches suggest that climatic differences between sampling localities are an important driver in shaping beta-diversity patterns, though the relative importance of climate varies across taxonomic groups. Nevertheless, the climatic niche position of OTUs between transects was highly correlated, suggesting that climatic filters shape the colonization between adjacent volcanoes. Taken together, our results highlight climatic niche conservatism as an important factor shaping ecological assembly along elevational gradients and suggest topographic complexity as an important driver of diversification.</p>
Data from: The extreme rainfall gradient of the Cape Horn Biosphere Reserve and its impact on forest bird richness. Biodiversity and Conservation
<p><strong>Description of dataset</strong></p> <p>This dataset contains information about forest bird species richness and climatic variables in 61 sample sites of the Cape Horn Biosphere Reserve. This dataset was analysed in : Quilodrán CS, Sandvig EM, Aguirre F, Rivero de Aguilar J, Barroso O, Vásquez RA, and R Rozzi. 2022. Effects of the extreme rainfall gradient in the Cape Horn Biosphere Reserve on forest bird richness. <em>Biodiversity and Conservation</em>. </p> <p> </p> <p><strong>Acknowledgments </strong></p> <p>This study was funded by grants for Technological Centers of Excellence with Basal Financing of the National Agency for Research and Development (ANID-Chile), granted to the Cape Horn International Center (CHIC- FB210018) and the Institute of Ecology and Biodiversity (IEB-AFB170008). CSQ acknowledges support from the Swiss National Science Foundation (N°P5R5PB_203169). </p>
dataset for Fig 2 in NatComm "Localised structuring of metal-semiconductor cores in silica clad fibres using laser-driven thermal gradients"
<p>Infrared transmission of silicon core fiber through which gold has been laser-thermally moved to reystallize the material</p>
Dataset for "Searching for a source without gradients: how good is infotaxis and how to beat it"
<p>Dataset containing the results presented in "Searching for a source without gradients: how good is infotaxis and how to beat it".</p>
Data from: Seeing the Forest for the trees: Assessing genetic offset predictions from Gradient Forest
<p><span>Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF predicted environmental association of adapted alleles and a new environment (GF Offset), is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.</span></p>
MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)
<p>The dataset of the abstract "MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)" for ISMRM 2022, London, UK. The data processing code with instructions could be found <a href="https://github.com/BRAIN-TO/girfISMRM2022">here</a>.</p> <p> </p> <p>Meas1.zip and Meas2.zip contain the first and the second measurements of the raw T2* decay signal acquired with the phantom-based method. Note that the coil dimension has been averaged to save data volume for demonstration purposes. This will lead to a lower SNR of the calculated output gradient and GIRF.</p> <p> </p> <p>CalculatedGIRF.zip provides the author's pre-calculated GIRFs using the data without coil averaging. This data is used for all the postprocessing (e.g. SNR and stability analysis, etc.) in the published abstract with the source code provided in the same Github repository.</p> <p> </p>
Data from: Seasonality, body size and maturation time in the neotropical grasshopper Sphenarium histrio across an altitudinal gradient
<p>In insects, male mating success and female fecundity usually increase with body size. However, natural selection favors faster maturation, reducing the risk of pre-reproductive death when the reproductive season is short in habitats located at high altitudes or far from the equator. Also, if males that mature earlier than females under these conditions increase their mating opportunities, protandry may evolve in their populations. Nonetheless, since body size is strongly correlated with maturation time in insects, a faster sexual maturation is reached at the expense of having a small body size. We analyzed the differences in the adult body size of males and females of the grasshopper Sphenarium histrio in three sites across an altitudinal gradient in southern Mexico. We also evaluated the possibility of protandry in these sampling sites using a common garden experiment. Male and female grasshoppers collected from low altitude sites in the field and reared in the laboratory were larger than those from a high altitude, suggesting genetic differentiation. Grasshoppers from a high altitude hatched earlier, had a shorter development time, presented fewer instars, and were smaller than grasshoppers from the other sampling sites. Moreover, development time in the three sampling sites was shorter in males than in females, suggesting protandry. Interestingly, the males from the three sites showed similar growth rates, but the females from low and high altitudes, respectively, had the fastest and slowest growth rates. In general, the adaptive value of the evolution of protandry has been focused on males. However, it may be that the growth rates of females in these sites could modify the degree of protandry as a response to their risk of pre-reproductive death and the potential benefits associated with multiple matings.</p> <p>The xlsx file contains the data for all the statistical analyses.</p>
Discrete Flow Cytometry of Underway Samples from Gradients 4 (2021) Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the Gradients 2021 (Gradients 4/TN397) oceanographic research cruise in the equatorial Pacific Ocean. The analysis includes cell abundance, forward light scatter, and pigment fluorescence of individual cells, including picoeukaryotes and the cyanobacteria Prochlorococcus and Synechococcus. The analysis also includes estimates of cell size, carbon content, and biomass using forward light scatter values and Mie Theory. Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient
<p>Species interactions underlie most ecosystem functions and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks were constructed from biodiversity monitoring data and known trophic links to assess how ecosystems have changed over time. The Baltic Sea is subject to many anthropogenic pressures, and low species diversity makes it an ideal candidate for determining how pressures change food webs. In this study, we used benthic monitoring data from 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated fundamental food web metrics evaluating network horizontal and vertical diversity, as well as stability that were compared over space and time. Our results show that the west coast of Sweden (Skagerrak) suffered a reduction in benthic invertebrate biodiversity by 32 % between the 1980's and 2010's, and that the number of links, generality of predators, and vulnerability of prey, have been significantly reduced. The other basins (Bothnian Sea, Baltic Proper and Bornholm Basin) do not show any significant changes in species richness or consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.</p>
Trait functional diversity explains mixture effects on litter decomposition at the arid end of a climate gradient
<p><span>Litter decomposition is controlled by climate, litter quality and decomposer communities. Because the decomposition of specific litter types is also influenced by the properties of adjacent types, mixing litter types may result in non-additive effects on overall decomposition rates. The strength of these effects seems to depend on the litter functional diversity. However, it is unclear which functional traits or combination of traits explain litter mixture effects and if these depend on the range of trait values and the ecosystems involved. These uncertainties hamper our ability to predict decomposition in plant communities. </span></p> <p><span>We aimed at understanding whether and how functional diversity (measured as functional dispersion, FDis) influences litter decomposition, and how this influence varies among different climates and across decomposition stages. We calculated FDis based on litter traits related to nutrient concentrations or to litter recalcitrance, and tested whether these diversity measures and climatic parameters (soil moisture and temperature) explained litter mixture effects on decomposition. </span></p> <p><span>Additive mixture effects (i.e. decomposition of mixtures equalling the mean decomposition of the single litter types) were common in most of the evaluated climates. Non-additive, negative effects were mainly restricted to the driest and warmest sites, and decreased with time. Non-additive effects increased in magnitude with the mixtures' FDis, with positive effects being related to FDis in nutrient traits and negative effects being related to FDis in recalcitrance traits. </span></p> <p><span>Synthesis: Litter mixing did not have strong effects on decomposition rates across the studied climatic gradient overall, and the direction and intensity of the mixture effects were context-dependent. The effects were stronger and more negative in the dryer ecosystems. Where effects were found, functional diversity calculated from selected groups of traits (related to nutrients or litter recalcitrance) predicted mixture effects, especially where trait ranges were broad, though much of the variation remains unexplained. We propose that functional diversity metrics based on litter traits that are mechanistically relevant, applied to diverse site-specific litter mixtures in different climates, can help to better understand under which conditions and in which direction litter diversity affects decomposition.</span></p>
Tightly linked zonal and meridional sea surface temperature gradients over the past five million years
<p>Climatologies for the climate model simulations performed by Fedorov et al., Nature Geoscience, <a href="https://www.nature.com/articles/ngeo2577">https://www.nature.com/articles/ngeo2577</a>. This table shows how the names of the simulation files provided in this dataset relate to the experiment names provided in Table S2 of Fedorov et al., (2015, Nature Geoscience). Note that experiments 1-26 are from Burls and Fedorov (2014) and published in <a href="https://doi.org/10.5281/zenodo.6762450">https://doi.org/10.5281/zenodo.6762450</a></p> <table> <tbody> <tr> <td><strong>Experiment # in Article (Table S2)</strong></td> <td><strong>Name of Files</strong></td> </tr> <tr> <td>27</td> <td> <p>abrupt2xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>28</td> <td> <p>abrupt4xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>29</td> <td> <p>abrupt8xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>30</td> <td> <p>abrupt16xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>Extended Exp 11</td> <td>40p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>Extended Exp 16</td> <td>60p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> </tbody> </table> <p>Article abstract:</p> <p>The climate of the tropics and surrounding regions is defined by pronounced zonal (east–west) and meridional (equator to mid-latitudes) gradients in sea surface temperature. These gradients control zonal and meridional atmospheric circulations, and thus the Earth’s climate. Global cooling over the past five million years, since the early Pliocene epoch, was accompanied by the gradual strengthening of these temperature gradients. Here we use records from the Atlantic and Pacific oceans, including a new alkenone palaeotemperature record from the South Pacific, to reconstruct changes in zonal and meridional sea surface temperature gradients since the Pliocene, and assess their connection using a comprehensive climate model. We find that the reconstructed zonal and meridional temperature gradients vary coherently over this time frame, showing a one-to-one relationship between their changes. In our model simulations, we systematically reduce the meridional sea surface temperature gradient by modifying the latitudinal distribution of cloud albedo or atmospheric CO<sub>2</sub> concentration. The simulated zonal temperature gradient in the equatorial Pacific adjusts proportionally. These experiments and idealized modelling indicate that the meridional temperature gradient controls upper-ocean stratification in the tropics, which in turn controls the zonal gradient along the equator, as well as heat export from the tropical oceans. We conclude that this tight linkage between the two sea surface temperature gradients posits a fundamental constraint on both past and future climates.</p>
High elevation forest age structure across an elevational gradient in the Greater Yellowstone Ecosystem
<p>Dataset for Blomdahl et al. 2022. Drivers of forest change in the Greater Yellowstone Ecosystem. Journal of Vegetation Science. </p> <p>See publication for site description and methods. </p> <p>Descriptions for variables in “trees_seedlings.csv”:</p> <p><strong>Plot_ID: </strong>Plot identifier. Nomeclature follows transect name and plot number. ECO="Ecotone" transect, SBM="South Bird Mountain" transect.</p> <p><strong>Year_Sampled: </strong>Samples collected 2017-2019.</p> <p><strong>Tree_ID: </strong>Identifier for unique trees and seedlings. </p> <p><strong>Core: </strong>Tree core sample identifier. Applies only to trees (cores not taken from seedlings). Generally, 2 cores were taken per Tree >5 cm DCH, though sometimes up to 4 were collected if a sample was rotten.</p> <p><strong>Sample_ID: </strong>Identifier for unique samples, some of which come from the same tree (for unique individuals: "Tree_ID"). Applies to trees and seedlings.</p> <p><strong>Form: </strong>Stems >5 cm diameter at coring height (DCH), coring height=30 cm; Seedlings >30: Stems <5 cm DCH and >30 cm in height (sometimes referred to as "saplings"); Seedlings <30: Stems <30 cm in height</p> <p><strong>Species: </strong>ABLA=<em>Abies</em> <em>lasiocarpa</em>, PIAL=Pinus <em>albicaulis</em>, PICO=<em>Pinus</em> <em>contorta</em>, PIEN=<em>Picea</em> <em>engelmannii</em>, PSME=<em>Pseudotsuga</em> <em>menziesii</em></p> <p><strong>Diam_30_cm: </strong>Diameter (cm) at 30 cm sample height.</p> <p><strong>Diam_0_cm: </strong>Diameter (cm) at 0 cm sample height (i.e., the base). Only seedlings were measured at base, not trees.</p> <p><strong>Seedling_Ht_cm: </strong>Length of seedling stem (cm).</p> <p><strong>Bark_Thick_cm: </strong> Bark thickness (cm). Not recorded in 2018. Bark thickness assumed to be <0.1 cm for seedlings.</p> <p><strong>Live_Dead: </strong>Live/Dead status when sampled. L=Live, D=Dead.</p> <p><strong>Canopy: </strong>Canopy position. D=Dominant, C=Codominant. S=Suppressed. Not recorded in 2017. All seedlings assumed suppressed.</p> <p><strong>Outer_Ring: </strong>Last complete year of growth, generally one year prior to Year_Sampled for live trees. Mortality year for dead trees.</p> <p><strong>Inner_Ring:</strong> Year of innermost ring measured in tree core sample measured at 30 cm sample height. Does not apply to seedlings, which were sampled as cross sections, and therefore the pith was always measureable.</p> <p><strong>Pith_30: </strong>Year of the first ring of the tree or sapling, measured at 30 cm sampling height. </p> <p><strong>Pith_0: </strong>Year of the first ring of the seedling, measuring at 0 cm sampling height (i.e., the base). Applies only to seedlings, which were destructively sampled at the base.</p> <p><strong>Estab_Year: </strong>Estimated year of establishment for trees and saplings, same as Pith_0 for seedlings. See methods of Blomdahl et al., 2022, for how establishment year was estimated.</p> <p><strong>Age:</strong> Estimated age of the tree.</p>
Data from: Bateman gradients reflect variation in sexual selection in a species with dynamic sex roles
<p class="MsoNormal">Bateman gradients, the slope of the regression of reproductive success on mating success, are among the most commonly reported measures of sexual selection. They are particularly insightful in species with reversed sex roles, where females are expected to be under sexual selection. We measured Bateman gradients in replicate experimental populations of the spermatophore gift-giving bushcricket <em>Kawanaphila nartee </em>(Orthoptera: Tettigoniidae). In this species, the operational sex ratio (OSR) and thus the sex competing for mates varies depending on the availability of pollen food resources: under pollen-limited regimens females are more competitive, whereas under pollen-rich regimens males are more competitive. We maintained populations in enclosures with either limited or supplemented pollen, and calculated Bateman gradients for males and females under both conditions. Bateman gradients were significantly positive in males, and the slope was steeper in pollen-supplemented populations where the OSR was more male-biased. Bateman gradients for females were shallow and nonsignificant regardless of pollen availability. Our results show that the strength of sexual selection on males can depend on environmental context. The lack of significant gradients among females may reflect experimental limitations on our ability to estimate Bateman gradients in female <em>K. nartee</em>.</p>
Potential local adaptation in populations of invasive reed canary grass (Phalaris arundinacea) across an urbanization gradient
<p>Urban stressors represent strong selective gradients that can elicit evolutionary change, especially in non-native species that may harbor substantial within-population variability. To test whether urban stressors drive phenotypic differentiation and influence local adaptation, we compared stress responses of populations of a ubiquitous invader, reed canary grass (Phalaris arundinacea). Specifically, we quantified responses to salt, copper, and zinc additions by reed canary grass collected from four populations spanning an urbanization gradient (natural, rural, moderate urban and intense urban). We measured ten phenotypic traits and trait plasticities, because reed canary grass is known to be highly plastic and because plasticity may enhance invasion success. We tested the following hypotheses: 1) source populations vary systematically in their stress response, with the intense urban population least sensitive and the natural population most sensitive, and 2) plastic responses are adaptive under stressful conditions. We found clear trait variation among populations, with the greatest divergence in traits and trait plasticities between the natural and intense urban populations. The intense urban population showed stress tolerator characteristics for resource acquisition traits including leaf dry matter content and specific root length. Trait plasticity varied among populations for over half the traits measured, highlighting that plasticity differences were as common as trait differences. Plasticity in root mass ratio and specific root length were adaptive in some contexts, suggesting that natural selection by anthropogenic stressors may have contributed to root trait differences. Reed canary grass populations in highly urbanized wetlands may therefore be evolving enhanced tolerance to urban stressors, suggesting a mechanism by which invasive species may proliferate across urban wetland systems generally.</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.