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4,243 results for “seasonality”
Seasonal evolution of basal conditions within Russell sector, West Greenland, inverted from satellite observations of surface flow
<p>An annual set of model-inferred basal and surface properties of ice flow at Russell Gletcher sector in Western Greenland with half-month temporal resolution. Derived using the Elmer/Ice ice-flow model by inversion of satellite-observed ice surface velocity (10.5281/zenodo.5535532). The details on the data creatoin can be found in 10.5194/tc-15-5675-2021 .</p> <p>Dataset contains 24 independent NetCDF files (one per 2-weeks time step) with:<br> * alpha - inverted be model basal friction coefficient in log10 (log10(MPa m-1 a)<br> * base - basal topography altitude (m)<br> * lithk - ice thickness (m)<br> * orog - surface altitude (m)<br> * strbasemag - magnitude of basal friction tb (MPa)<br> * xvelbase, yvelbase, zvelbase - 3D basal velocity (m/yr)<br> * xvelmean, yvelmean - vertically average mean horizontal velocity (m/yr)<br> * xvelsurf, yvelsurf, zvelsurf - 3D surface velocity (m/yr)<br> * n - effective pressure (MPa)</p> <p>The additional WinterMeanState NetCDF file (inversion from the mean velocity of january, Febriary, Mars) contains the same set of variables (except the effective pressure), and in addition contains the <em>As</em> Weertman sliding coeffitient.</p> <p>The results have been interpolated from the native unstructured model grid to the regular grid used for the observed velocity (10.5281/zenodo.5535624).</p>
Surface water and flooding dynamics data set based on seasonally continuous Landsat data (1986-2011) in a dryland river basin
<p>Animations of the data are available here: <a href="https://doi.org/10.5281/zenodo.2438110">https://doi.org/10.5281/zenodo.2438110</a></p> <p>If you are using this data set, please cite the following publication:</p> <p>Tulbure, M.G. and M. Broich (2018). Spatiotemporal patterns and effects of climate and land use on surface water extent dynamics in a dryland region with three decades of Landsat satellite data. Science of the Total Environment. https://www.sciencedirect.com/science/article/pii/S0048969718347466 </p> <p>The data represent statistically validated surface water and flooding extent dynamics derived from seasonally continous Landsat TM/ETM+ data and random forest models, and summarised to the maximum extent of surface water per season between 1986-2011 over Australia's Murray-Darling Basin. The overall accuracy was over 99% and producer's accuracy for water 87% +/- 3%. </p> <p>The method is described in the following publication: <br> Tulbure, M.G., M. Broich, S.V. Stehman, A. Kommareddy. (2016). Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region. Remote Sensing of Environment. 178: 142-157</p> <p>URL: https://www.sciencedirect.com/science/article/pii/S0034425716300621 </p> <p>Data are provided in GeoTIFF format per season per year. File naming convention is as follows:<br> yy_inund_freq_season_SamplingMethod. For example, "99_inund_freq_winter_max" will represent inundation frequency for winter 1999 resampled using a maximum resampling method. </p> <p>Inundation frequency represents the number of times a pixel has been flagged as flooded out of the times that pixel had valid observations * 100. Valid observation exclude no data values and clouds. The valid range of inundation frequency is 0-100 [%], with 255 indicating no data values. Data type is eight bit unsigned integer (uint8). </p> <p>The data were resampled to 120m resolution to reduce file size. The resampling methods used include max (e.g. selects the max value of all non-NODATA contributing 30m pixels) and mean (median and min can be provided upon request). If you are unsure which resampling to use, you may want to start with the mean. </p>
Characterization of photosynthetic epilithic biomass on the river bed of the Upper Clark Fork River (Montana, USA) during the algal growing seasons of 2017 and 2018
These data were collected to support monitoring of the Upper Clark Fork River restoration, and data collection was funded by the US NSF Long Term Research in Environmental Biology (LTREB) program and the US NSF EPSCoR funded Montana Consortium for Research on Environmental Water Systems. The LTREB monitoring project consists of monthly or bi-weekly water quality monitoring across a 200-km restoration gradient contaminated by historic mining practices to monitor inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and heavy metal contamination. The original analytical intent for these data was to assess the response of the river algal community to the floodplain restoration. Data characterize epilithic biomass on the river bed including measurements of benthic standing stocks and abundance of pigments associated with primary producers. Metrics of characterization include areal density of chlorophyll a, areal density of phaeophytin, the ratio of carotenoid to chlorophyll absorbance, percent organic matter, areal density of organic matter, and category of biomass composition (filamentous algae vs. other epilithon). Samples were obtained from collecting and scrubbing five rocks at any given site. Biomass estimates were obtained from area corrected Ash Free Dry Mass. Pigment concentrations were obtained through the use of extraction in acetone followed by spectroscopy. Data are from the 2017 and 2018 algal growing seasons. Data were collected on the Upper Clark Fork River (USGS HUC 17010201) at project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA.
Vegetation indices calculated from reflectance spectra collected at LTER plots at Toolik Lake, Alaska during the 2007-2019 growing seasons.
Vegetation indices calculated from reflectance spectra collected at Arctic LTER experimental plots at Toolik Lake, Alaska during the 2007-2019 growing seasons. Long term experimental plots span several different vegetation types: Heath (HTH89), Moist Acidic Tussock (MAT89 and Low Fert), Moist Non-Acidic Tussock (MNAT), Non-Acidic Non-Tussock (NANT), Shrub (SHB), and Wet Sedge (WSG). Plots are differentiated by their experimental treatment and are located in replicate blocks.Canopy reflectance is measured by hand-held spectrophotometer and several indices of interest (NDVI, EVI, EVI2, PRI, WBI, and Chlorophyll index) are calculated.
Number of bacteria in the water column of lakes sampled near Toolik Lake LTER Alaska, throughout summer season, 1992-2000.
Number of bacteria (using of DAPI for identifying and counting) in Toolik Lake water column and other lakes sample throught the summer from 1992-2000. There is no data for 2006.
Meteorological data collected on Lake E5 during the ice free season since 2000 to present, Arctic LTER, Toolik Research Station, Alaska.
Yearly file describing the metological data on Lake E5 (Lake E5 Climate station) near the Toolik Field Research Station (68 38'N, 149 36'W). Measurements include air temperature, relative humidity, wind direction, and wind speed..
Soil nutrient availability from the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016 growing season
This file contains plant-available nitrate (NO3), ammonium (NH4), and phosphate (PO4) in the upper 5-10 cm of organic matter from a burned and unburned site in the southern section of the 2007 Anaktuvuk River fire in northern Alaska. Soil nutrients were assessed using ion-exchange resin membranes incubated in the soil during the growing season of 2016.
Point-frame measurments from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains point-frame measurements from a nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016 at a severely burned site and an unburned site. Pin-vegetation contact was recorded using a 0.75 m2 frame with 41 evenly spaced pin-drop points. Data was collected once during the height of the growing season in 2016 (when fertilization began) 2017, 2018 and 2019. This data was used to measure the impact of fertilization and fire on community composition.
Soil nutrient availability from the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2019 growing season
This file contains plant-available nitrate (NO3), ammonium (NH4), phosphate (PO4), and total free primary amines (TFPA )in the upper 5-10cm of organic matter from a burned and unburned site in the southern section of the 2007 Anaktuvuk River fire in northern Alaska. Soil nutrients were assessed using buried resin bags which incubated for 1 month during the peak of the growing season in 2019.
Leaf area index (LAI) recorded from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains leaf area index (LAI) measurements from an nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016. LAI was recorded using a handheld plant canopy analyzer (LI-COR 2200C; LI-COR, Lincoln, NE, USA) Data spans 4 years from 2016 (when fertilization began) until 2019. Data was recorded once a year at the peak of each growing season.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Half-hourly growing season, chamber-based, CO2 flux data, 2009-2021
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data contains CO2 fluxes measured using an automated chamber system that measures net ecosystem CO2 exchange (NEE). Measurements are made every ~1.5 hours and modeled half-hourly. Half hour ecosystem respiration is modeled using an exponential Q10 relationship when light conditions are low (PAR<5umol/m2/s) and using a hyperbolic light relationship when PAR>5umol/m2/s. GPP is calculated as the difference between NEE and Reco.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Growing season, chamber-based, CO2 flux data, 2009-2021
This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warming affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieved using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This data set includes measured values of CO2 fluxes during the growing season.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Seasonal water table depth data, 2012-2024
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data includes water table depth measurements collected from winter warming and control treatment plots at CiPEHR for the ice-free period of 2024. Note that the experimental warming portion of this experiment concluded in 2022. These data are a continuation of measurements taken at previously warmed plots but plots were not actively manipulated in 2023 and 2024.
Phenological Responses of Equisetum arvense to Early-season Soil and Air Warming in Reseach Plots on the University of Alaska Fairbanks North Campus - May through September 2023
This dataset contains the phenological stages of Equisetum arvense (horsetails) subjected to snow removal in spring (which led to ground warming) and to air warming using open topped chambers in a two by two factorial experiment. The main dataset contains the phenological phases of plants in plots of subjected to the four treatments between 1 May and 29 September 2023, and height data. Supplementary files contain temperature data for dataloggers placed in the soil and in the air and file information.
Seasonal and annual summary statistics of urbanization, vegetation, land surface temperature, and bioclimatic variables derived from remotely-sensed imagery in areas surrounding long-term bird monitoring locations in the greater Phoenix, Arizona, USA metropolitan area (1997-2023)
This data package consists of 26 years (1998-2023) of environmental data and 22 years (2000-2022) years of bioclimatic data associated with CAP-LTER long-term point-count bird censusing sites (https://doi.org/10.6073/pasta/4777d7f0a899f506d6d4f9b5d535ba09), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). The environmental variables include land surface temperature (LST), three spectral indices of vegetation and water – the normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and modified normalized difference water index (MNDWI) – and four spectral indices of impervious surface/urbanization. Impervious surface indices include the normalized difference built-up index (NDBI), the normalized difference impervious surface index (NDISI), the enhanced normalized differences impervious surface index (ENDISI), and the normalized impervious surface index (NISI). LST and all spectral indices were derived from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. The seven bioclimatic variables (e.g., air temperature, precipitation) were sourced from 1-km resolution gridded estimates of daily climatic data from NASA Daymet V4. We created temporally-aggregated Daymet raster images by calculating mean pixel-values for each season and year, as well as seasonally and annually summed precipitation. We summarized the values of each environmental variable by generating variously-sized (100-m, 500-m, 1000-m) buffers around each bird point count location and extracting weighted mean values of each environmental variable, with each pixel's values weighted by the proportion of its area falling within the buffer. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of s
Seasonal and annual vegetation surveys of wetlands along the Salt River in and near the greater metropolitan area of Phoenix, Arizona
The Salt River Biodiversity Project collects vegetation data in several urban wetlands across the Phoenix area (Arizona) along the historic channel of the Salt River. This study, along with bird and reptile monitoring (Bateman and Childers 2022, Bateman and Warren 2022), began in 2012. These biodiversity monitoring initiatives help understand how community composition, biodiversity, and ecosystem structure are changing as a result of pressures such as urbanization, climate change, and land management decisions. This dataset contains vegetation assessments from 2012 as well as a reassessment ten years later (2022 and 2023). Bateman, H. and D. Childers. 2022. Long-term monitoring of herpetofauna along the Salt and Gila Rivers in and near the greater Phoenix metropolitan area, ongoing since 2012 ver 8. Environmental Data Initiative. <https://doi.org/10.6073/pasta/3cc81cce91185cdeeded320c4a3528df> Accessed 2024-09-11. Bateman, H. and P. Warren. 2022. Point-count bird censusing: long-term monitoring of bird abundance and diversity along the Salt River in the greater Phoenix metropolitan area, ongoing since 2013 ver 8. Environmental Data Initiative. <https://doi.org/10.6073/pasta/070c0bec46e1336684c534f9a4034334> Accessed 2024-09-11.
Long-term composited Modified Normalized Difference Water Index (MNDWI) for the greater Phoenix, Arizona, USA, metropolitan area and the surrounding Sonoran desert derived from annual and seasonal Landsat imagery, 1998 to 2023
Abstract ======== This data package consists of multiple decades of modified normalized difference water index (MNDWI) raster data across the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) study area within metropolitan Phoenix, Arizona (USA), temporally aggregated by year and by four meteorological seasons (Winter, Spring, Summer, Fall). By providing a metric by which to reliably identify bodies of open water, these MNDWI data are intended to facilitate analyses of land-based environmental variables (e.g., urbanization, vegetation, land surface temperature) and can also be used to track long-term and seasonal change in the coarse extent of open water as a land-cover type. MNDWI was derived, following the methods of Xu (2006), from annual and seasonal composites of 30-m resolution Landsat 5-9 Level-2 Surface Reflectance imagery. All imagery retrieval and data processing were completed with Google Earth Engine (Gorelick et al. 2017) and program R. A complete description of data processing methods, including the aggregation of imagery by year and season and the calculation of the spectral index, can be found in the data package metadata (see \'Methods and Protocols\') and accompanying Javascript code. **Citations:** - Gorelick N, Hancher M, Dixon M, et al. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202:18--27. <https://doi.org/10.1016/j.rse.2017.06.031> - Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. *International Journal of Remote Sensing*, *27*(14), 3025--3033. <https://doi.org/10.1080/01431160600589179>
Examination of protein-like fluorophores in chromophoric dissolved organic matter (CDOM) in a wetland and coastal environment for the wet and dry seasons of the years 2002 and 2003 (FCE)
Water samples are collected at the end of the dry and the wet season from all LTER sites and stored on ice until return to the lab. They are pre-filtered through pre-combusted GF/F filters and ultrafiltered and concentrated with a Pellicon 2 Mini tangential flow ultrafiltration system.Concentrated samples were then analyzed using fluorescence and SEC-HPLC. This CDOM optical study revealed the presence of two classes of compounds associated with the protein-like peak (peak T; excitation/emission (Ex/Em) maxima at around 280 nm/325 nm), which have very different chemical structures and ecological roles. In addition to proteins, we propose phenolic compounds as possible origins of peak T in coastal and wetland environments. In this study, natural water samples were obtained from subtropical rivers and estuarine environments within the Florida Coastal Everglades (FCE) ecosystem. The samples were ultra-filtered and excitation-emission fluorescence matrices (EEMs) were obtained. The EEMs showed the presence of four peaks with Ex/Em maxima at around 280 nm/325 nm (T), less than 260 nm/460 nm (A), 300 nm/412nm (M), and 350 nm/470 nm (C). To better understand the nature of peak T, the components originating this peak were separated using size exclusion chromatography (SEC) and detected by fluorescence emission at Ex/Em = 280 nm/325 nm. The elution curves revealed the presence of two elution peaks at a molecular weight of greater than 50K (void volume; T1) and around 7.6K (T2). This result suggested the need of cautious interpretation in the use of peak T as a proxy for the detection of proteinaceous materials in wetland and estuarine environments, since significant amounts of potentially interfering phenolic compounds are leached from senescent biomass in wetland and coastal ecosystems. As such EEM spectra of gallic acid an important component of hydrolysable tannins, and condensed tannins extracted from red mangroves (Rhizophora mangle) showed the presence of a peak maxima
Seasonal Evolution of Terrigenous Dissolved Organic Matter in the South Atlantic Bight off Georgia in 2014
Six surveys of the central South Atlantic Bight (SAB) off of Georgia were conducted in 2014. The primary objective of the research cruises was to characterize estuary-shelf exchange and the dispersal of freshwater into the coastal ocean around Sapelo Island off the Georgia coast. The surveys, in April, May, July, August, September, and November, were intended to sample shelf conditions under different seasons. Most of the sampling stations were located at the mouth of the estu-aries around Sapelo Island and over the inner and mid-shelf (<60 km offshore). Eighty samples from transects extending across the shelf from the mouths of the Altamaha River and of Sapelo Sound were selected for the analyses of molecular composition using ultrahigh resolution mass spectrometry (Fourier transform ion cyclotron reso-nance mass spectrometry [FT-ICR MS]) and stable carbon iso-topic signatures (delta 13C). This data set includes spectral analysis of the DOM, including spectral slope (275-295nm wavelength), terrigenous peaks from mass spectrometry analysis, and a computed terrigenous index indicating fraction of terrigenous DOM in water samples.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Snow and Frost
This dataset contains snow depth and frost depth measurements from the Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest. Samples are collected weekly throughout the winter months. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
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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.