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6,569 results for “Long-term”
Linked collectors and determiners for: Long-term monitoring of Azorean forest arthropods: the BALA Project (1997-2022).
Natural history specimen data linked to collectors and determiners held within, "Long-term monitoring of Azorean forest arthropods: the BALA Project (1997-2022)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8a4be36d-18cd-484c-b8ce-f67194cf4bac">https://bionomia.net/dataset/8a4be36d-18cd-484c-b8ce-f67194cf4bac</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8a4be36d-18cd-484c-b8ce-f67194cf4bac">https://gbif.org/dataset/8a4be36d-18cd-484c-b8ce-f67194cf4bac</a>. Formatted as a Frictionless Data package.
Long-term biochar and soil organic carbon stability– Evidence from field experiments in Germany-ROW DATA
<p> Row data for researcher paper Long-term biochar and soil organic carbon stability– Evidence from field experiments in Germany</p>
Data products for "3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico"
<p>Data products for '3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico' by A. Perez-Silva, D. Li, A.-A. Gabriel and Y. Kaneko</p>
Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories (dataset and R script)
<p>The present digital archive is the outcome of the paper: <strong>Palmisano, A., Bevan, A., Kabelindde, A., Roberts, N., and Shennan, S., 2021. <a href="https://doi.org/10.1007/s10963-021-09159-3">Long-Term Demographic Trends in Prehistoric Italy: climate impacts and regionalised socio-ecological trajectories</a>. <em>Journal of World Prehistory, 34 (3)</em>, </strong>381-432<strong>.</strong></p> <p>The dataset included here provides a collection of <strong>4,010</strong> radiocarbon dates from <strong>947</strong> archaeological sites for a period spanning between 11,000 and 1500 BP. In addition, the digital archive related to this paper provides reproducible analyses in the form of one script written in R statistical computing language.</p> <p>List of versions:</p> <ul> <li><strong>1.0.</strong> 4 August 2021 - First public release of the dataset on Zenodo. </li> </ul>
The morphometric acclimation to depth explains the long-term resilience of the seagrass Cymodocea nodosa in a shallow tidal lagoon
<p>Original Data set for the article "The morphometric acclimation to depth explains the long-term resilience of the seagrass <em>Cymodocea nodosa</em> in a shallow tidal lagoon" available in the Journal of Environmental Management (JEMA).</p> <p>The sampling site is located in inner water body of Cadiz Bay (SW, Spain) ((36° 23’ - 36° 37’N and 6° 8’ - 6° 15’W).</p>
FIG. 3 in A biotic survey and inventory of the dynastine scarab beetles of Mesoamerica, North America, and the West Indies: review of a long-term, multicountry project
FIG. 3. — Map of the study area showing the phases (I-IV) of the dynastine biotic inventory project.
FIG. 1 in A biotic survey and inventory of the dynastine scarab beetles of Mesoamerica, North America, and the West Indies: review of a long-term, multicountry project
FIG. 1. — Brett Ratcliffe and Renaud Paulian in Bordeaux, France, 13 May 2001. Photo: M. L. Jameson.
Capture-recapture histories used in our paper "High long-term survival and asymmetric movements in a reintroduced metapopulation of cinereous vultures" published by Ecosphere
<p>These three datasets correspond to the capture-recapture histories used in the E-surge software (in the HEADED format) for both population models (Capture_recapture_histories_ALPS.txt for the Alps and Capture_recapture_histories_CAUSSES.txt for the Causses) and the metapopulation model (Capture_recapture_histories_METAPOPULATION.txt).</p> <p>Columns descriptor:</p> <ul> <li>H:O1 to H:O25 correspond to each occasion (i.e. year)</li> <li>S: correspond to the sample size (i.e. associated number of animals)</li> <li>RC: correspond to the Right Censoring ( -1 if the animal is removed at the last capture or 0 if no right censoring)</li> <li>$COV:Group correspond to the group to which the individual belongs</li> </ul> <p>Individuals were grouped by age (from the 1<sup>st</sup> year until ≥6<sup>th</sup> years), by release status (wild-born / hacking: released juveniles before fledging / aviary: released immatures, sub-adults or adults), by origin (Causses / Alps) and if a missing ring was replaced. All details for the groups are given in the Appendix B for both population models and in the Appendix C for the metapopulation model.</p>
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
<p><strong>1. Summary</strong></p> <p>The Congo basin’s Surface Water Storage (SWS) datasets are generated by Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, Sly Wongchuig in the article entitled "A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015", <strong><em>Earth System Science Data (submitted)</em></strong>.</p> <p>The dataset was generated using two methods, one based on a multi-satellite approach and one on a hypsometric curve approach. The multi-satellite approach consists of the combination of surface water extent (SWE) from the Global Inundation Extent from Multi-satellite (GIEMS-2) and satellite-derived surface water height (SWH) from radar altimetry (long-term series ERS-2_ENV_SRL) on the same period of availability for the two datasets, here 1995-2015. The hypsometric curve approach consists of the combination of SWE from GIEMS-2 dataset and hypsometric curves obtained from various digital elevation models (DEMs) (i.e., ASTER, ALOS, MERIT, and FABDEM). Both methods estimate monthly spatio-temporal variations of SWS changes across the entire Congo River basin.</p> <p><strong>2. Name Description</strong></p> <ul> <li>HYPSO_XX: hypsometric curve providing the surface water extent area-elevation relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>HYPSO_CORR_XX: corrected hypsometric curve providing the surface water extent area-elevation relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>AREA_STOR_XX: hypsometric curve providing the surface water extent area-storage relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>SWS_XX: monthly surface water storage variations from XX (where XX stands for ASTER, ALOS, MERIT, FABDEM DEMs, and Multi-satellite approach).</li> </ul> <p><strong>3. File Description </strong></p> <p>The SWS estimates from the multi-satellite approach (1995-2015), as well as the hypsometric curves providing the surface water extent area-elevation relationship from the four DEMs (before and after the corrections), the surface water extent area-storage relationship, along with the four SWS estimates (1992-2005).</p> <p>The dataset is gridded on equal-area of 0.25° spatial resolution at the equator, each pixel covers almost 773 km². The reference point for calculating the volume variation is the minimum of surface water extent for each pixel.</p> <p>The files are organized in matrix:</p> <ul> <li><strong>First column</strong> represents the latitude in degree.</li> <li><strong>Second column</strong> represents the longitude in degree.</li> <li><strong>From the third column</strong>: data. In case of hypsometric curve, the data represents elevation in meter on 101 columns representing the increment of 1% flooding in each 773 km<sup>2</sup> pixel from GIEMS-2. In case of SWS data (in km³), there are 288 (respectively 252) columns representing each month of the period over 1992-2015 (respectively 1995-2015) from hypsometric curve approach (respectively multi-satellite approach).</li> </ul>
Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning"
<p>Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning".</p>
Data for: Effects of long-term ethanol storage of blood samples on the estimation of telomere length
<p>Telomeres, DNA structures located at the end of eukaryotic chromosomes, shorten with each cellular cycle. The shortening rate is affected by factors associated with stress, and, thus telomere length has been used as a biomarker of ageing, disease, and different life history trade-offs. Telomere research has received much attention in the last decades; however, there is still a wide variety of factors that may affect telomere measurements and to date no study has thoroughly evaluated the possible long-term effect of a storage medium on telomere measurements. In this study we evaluated the long-term effects of ethanol on relative telomere length (RTL) measured by qPCR, using blood samples of magpies collected over twelve years and stored in absolute ethanol at room temperature. We firstly tested whether storage time had an effect on RTL and secondly we modelled the effect of time of storage (from 1 to 12 years) in differences in RTL from DNA extracted twice in consecutive years from the same blood sample. We also tested whether individual amplification efficiencies were influenced by storage time, and whether this could affect our results. Our study provides evidence of an effect of storage time on telomere length measurements. Importantly, this effect shows a pattern of decreasing loss of telomere sequence with storage time that stops after approximate 4 years of storage, which suggests that telomeres may degrade in blood samples stored in ethanol. Our method to quantify the effect of storage time could be used to evaluate other storage buffers and methods. Our results highlight the need to evaluate the long-term effects of storage on telomere measurements, particularly in long-term studies.</p>
Techno-economic dataset for long-term energy systems modelling in Viet Nam
<p>Techno-economic data and assumptions for long-term energy systems modelling in Viet Nam. This includes data on electricity generation and consumption, electricity imports and exports, fuel prices, emissions, refineries, power transmission and distribution, electricity generation technologies, and renewable energy potential and reserves for the years 2015 to 2050.</p>
Long-term snow chemical composition monitoring - Hansbreen glacier (Hornsund) - raw data
<p>During the accumulation season, snow samples were taken on Hansbreen Glacier. Several times per season. Snow samples were collected in polyethylene sterile bags and transported to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) were analysed in the chemical laboratory of the Polish Polar Station.<br> Snow chemical composition: major ions, HCO3-, pH, conductivity</p> <p>Presented data from 2015 to 2019</p> <p>The data has not been checked, which means that it is raw data.</p> <p>Principal Investigator (PI) Adam Nawrot</p>
Long-term atmospheric precipitation monitoring in Hornsund region (Fuglebekken) - raw data
<p>Since 2004, snow and rain samples have been collected in the Fuglebekken catchment in close vicinity of the Polish Polar Station Hornsund. The rain and snow samples are collected after every event. The pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory. The rain gauge is checked approximately once a day.</p> <p>Presented data from 2016 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p>
Long-term daily hydrometeorological drought indices, soil moisture, and evapotranspiration for ICOS ecosystem sites
<p>Standardized drought indices to support research at ICOS ecosystem sites. Dataset to Nature Scientific Data submission.</p> <p>"The dataset comprises four files for each of the 101 sites: "[site_name]_input" contains the observational data extracted from E-OBS, PET estimates as well as the simulated soil water storage and actual evapotranspiration from mHM; and threemore files for each of the standardized drought indices ("SSMI_[site_name]", "SPI_[site_name]", "SPEI_[site_name]"). Details on the variables, their units and their origin are given in Tab. 1. For the SPI and SPEI, the file of each site contains the estimates for various aggregation times, ranging from 5 to 730 days in steps of 5 days from 5 to 365 and steps of 10 days from 370 to 730. Each data file has a daily temporal resolution and covers the time span from 1950 to 2021."</p>
Dataset for: 'Patterns in the Plankton – Spatial distribution and long-term variability of copepods on the Agulhas Bank'
<p>This dataset contains environmental data (in situ temperature and chlorophyll <em>a</em>) and integrated biomass (mg C m<sup>-2</sup>) data for a number of copepod taxa, as well as total copepod biomass and abundance, on the Agulhas Bank, South Africa, as predicted by a Generalized Additive Model (GAM), during late austral spring (October-December) from 1988 to 2011. Mean environmental and copepod biomass parameters for each area and year are also provided. Relevant information on sampling and statistical analysis of spatial distributions has been extracted from the paper. Please see paper for full details and figures, including supplementary data; <a href="https://doi.org/10.1016/j.dsr2.2023.105265">https://doi.org/10.1016/j.dsr2.2023.105265</a>. Please see the Word document Huggett_et_al_2023_README.docx for a list of the data files and descriptions of the contents.</p>
Data for: Large-scale long-term passive-acoustic monitoring reveals spatiotemporal activity patterns of boreal bats
<p class="MsoNormal"><span>The distribution ranges and spatio-temporal patterns in the occurrence and activity of boreal bats are yet largely unknown due to their cryptic lifestyle and lack of suitable and efficient study methods. We approached the issue by establishing a permanent passive-acoustic sampling setup spanning the area of Finland to gain an understanding on how latitude affects bat species composition and activity patterns in northern Europe. The recorded bat calls were semi-automatically identified for three target taxa; <em>Myotis</em> spp., <em>Eptesicus nilssonii</em> or <em>Pipistrellus nathusii</em> and the seasonal activity patterns were modeled for each taxa across the seven sampling years (2015–2021). We found an increase in activity since 2015 for <em>E. nilssonii</em> and <em>Myotis </em>spp. For <em>E. nilssonii</em> and <em>Myotis</em> spp. we found significant latitude -dependent seasonal activity patterns, where seasonal variation in patterns appeared stronger in the north. Over the years, activity of <em>P. nathusii</em> increased during activity peak in June and late season but decreased in mid season. We found the passive-acoustic monitoring </span><span>network to be an effective and cost-efficient method for gathering b</span><span>at activity data to analyze spatio-temporal patterns. Long-term data on the composition and dynamics of bat communities facilitates better estimates of abundances and population trend directions for conservation purposes and predicting the effects of cli</span><span>mate change.</span></p>
Long-term coastal macrobenthic Community Trajectory Analysis reveals habitat-dependent stability patterns
<p>Long-term monitoring programs are fundamental to detecting changes in ecosystem health and understanding ecological processes. In the current context of increasing anthropogenic threats on marine ecosystems, understanding the dynamics and response of communities becomes essential. We used data collected over 14 years in the REBENT benthic coastal invertebrates monitoring program, at a regional scale in the North-East Atlantic, covering a total of 26 sites and 979 taxa. Four distinct habitats were studied: two biogenic habitats associated with foundation species in the intertidal and subtidal zones and two bare sedimentary habitats in the same respective tidal zones. We used Community Trajectory Analysis, a statistical approach that allows for quantitative measures and comparisons of temporal trajectories of ecosystems. We compared observed community trajectories to trajectories simulated under a non-directional null model in order to better understand the dynamics of the communities, their potential drivers, and the role of the studied habitats in these dynamics. Despite strong differences in the community compositions between sites and habitats, the communities followed non-directional dynamics during the 14 years monitored, which suggested stability at the regional scale. However, the shape, size, and direction of the trajectories of benthic communities were more similar within than among habitats, also suggesting the influence of the nature of the habitat on community dynamics. Results showed a higher variability in community composition in the first years of the monitoring in the intertidal bare habitat and confirmed the role of biogenic habitats in maintaining temporal stability. They also highlighted the need to apprehend the role of transient and rare species and the scale of observation in temporal beta diversity analyses. Finally, our study confirmed the usefulness of Community Trajectory Analysis to link observed trajectory patterns to fundamental ecological processes.</p>
General relativistic precession and the long-term stability of the solar system: SimulationArchive dataset
<p>We share the data for 1280 long-term solar system simulations used in <a href="https://doi.org/10.1093/mnras/stad719">Brown & Rein (2023)</a>. The simulations are zipped together consecutively in groups of 16 and saved in the <code>REBOUND</code> (3.18.1) SimulationArchive format. Please see the companion paper and <a href="https://doi.org/10.5281/zenodo.7753656">code</a> for details.</p> <p><strong>Abstract</strong></p> <p>The long-term evolution of the solar system is chaotic. In some cases, chaotic diffusion caused by an overlap of secular resonances can increase the eccentricity of planets when they enter into a linear secular resonance, driving the system to instability. Previous work has shown that including general relativistic contributions to the planets' precession frequency is crucial when modelling the solar system. It reduces the probability that the solar system destabilizes within 5 Gyr by a factor of 60. We run 1280 additional <em>N</em>-body simulations of the solar system spanning 12.5 Gyr where we allow the general relativistic precession rate to vary with time. We develop a simple, unified, Fokker-Planck advection-diffusion model that can reproduce the instability time of Mercury with, without, and with time-varying general relativistic precession. We show that while ignoring general relativistic precession does move Mercury's precession frequency closer to a resonance with Jupiter, this alone does not explain the increased instability rate. It is necessary that there is also a significant increase in the rate of diffusion. We find that the system responds smoothly to a change in the precession frequency: There is no critical general relativistic precession frequency below which the solar system becomes significantly more unstable. Our results show that the long-term evolution of the solar system is well described with an advection-diffusion model. </p>
A Long-term Experimental Investigation on the Impact of Rainfall on Short 6G D-band Links
<p>Data attached to Radio Science publication "A Long-term Experimental Investigation on the Impact of Rainfall on Short 6G D-band Links"</p>
ScienceDex guides
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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.