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378 results for “observatory”
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Belowground Carbon Observatory Network (BeCON) at Harvard Forest since 2020
A central goal of the recent Harvard Forest C Synthesis activity was to identify high-priority needs for C-cycle research at the forest. While there were a number of areas needing follow-up research, belowground C pools and fluxes remain the single largest gap in the C budget and therefore our understanding of the C cycle of the forest. To this end, we developed the Belowground Carbon Observatory Network (BeCON) as a part of the LTER-VI grant proposal. The long-term goal of BeCON is to understand temporal and spatial variations in belowground C pools in response to the various environmental changes the forest now faces [e.g., rising CO2, changes in atmospheric N, S and O3 chemistry, invading insects, land-use change, immigrating (large) herbivores]. There are two great challenges in achieving this goal: (1) excessive spatial heterogeneity in belowground C pools; and (2) lack of automated systems for analysis. These characteristics make it very difficult to quantify changes because the work is intrinsically labor intensive with low replication and the noisy data lead to low statistical power. Here, we measured soil carbon content, root biomass and carbon content, and annual root productivity following the protocols for BeCON.
Lake Mendota Microbial Observatory Temperature, Dissolved Oxygen, pH, and conductivity data, 2006-present.
The Lake Mendota Microbial Observatory collects routine water physical and chemical measurements alongside their microbial samples. This dataset includes measurements of water temperature, dissolved oxygen, pH, and conductivity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld probes. Data from 2006-2014 was compiled from multiple sources and includes only water temperature and dissolved oxygen. Data from 2014-2019 is from the same probe, a YSI Pro Plus instrument, and also includes pH and specific conductance. Routine microbial observatory sampling continues into the present.
Lake Mendota Microbial Observatory Secchi Disk Measurements 2012-present
The Lake Mendota Microbial Observatory collects routine water clarity measurements alongside their microbial samples. This dataset includes measurements of water clarity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld Secchi discs. When multiple personnel performed the Secchi disc measurements, the average and standard deviation are reported. To take the Secchi depth, sunglasses are removed and the disc is lowered on the shaded side of the boat. The Secchi depth is the average between where the Secchi disc disappears while lowering it and where it reappears while raising it. Routine microbial observatory sampling continues into the present.
Soil Organic Matter Mechanisms of Stabilization (SOMMOS) - enhanced soil characterization data from 40 National Ecological Observatory Network (NEON) sites
Soil organic matter (SOM) is a critical linkage among many ecosystem services that sustain our society and life on Earth. It is the primary energy source for microbes and the principal storehouse of water necessary for plant growth. SOM also stores nutrients for plants and sorbs pollutants that otherwise could contaminate food and water supplies. Soils also help regulate climate by storing carbon that would otherwise be released to the atmosphere and contribute to climate change. The SOMMOS project investigated processes in the soil that protect SOM from being decomposed by microbes, processes that increase its sensitivity to environmental changes, and how changes in climate and land management influence the amount and stability of SOM. The project, which was a collaboration between scientists from the National Ecological Observatory Network (NEON), University of Colorado, University of Michigan, Oregon State University, Virginia Polytechnic Institute and State University, and the USDA-Forest Service, took advantage of soil samples collected across NEON, a major NSF investment in environmental monitoring that covers the entire United States. This continental-scale soil sample set was analyzed for a wide array of physical and chemical properties, well beyond those typically measured on such a large-scale sample set, including radiocarbon, extractable metals, organic matter chemistry by pyrolysis-GCMS, liquid extract fluorescence spectroscopy, and more. In addition to this dataset, archived samples are available from the project for sharing with interested researchers.
Microbial Observatory at North Temperate Lakes LTER Time series of bacterial community dynamics in Lake Mendota 2000 - 2009
With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.
Microbial Observatory at North Temperate Lakes LTER Spatial and temporal cyanobacterial population dynamics in Lake Mendota 2009 - 2011
Toxic cyanobacterial blooms threaten freshwaters worldwide but have proven difficult to predict because the mechanisms of bloom formation and toxin production are unknown, especially on weekly time scales. Water quality management continues to focus on aggregated metrics, such as chlorophyll and total nutrients, which may not be sufficient to explain complex community changes and functions such as toxin production. For example, nitrogen (N) speciation and cycling play an important role, on daily time scales, in shaping cyanobacterial communities because declining N has been shown to select for N fixers. In addition, subsequent N pulses from N2 fixation may stimulate and sustain toxic cyanobacterial growth. Herein, we describe how rapid early summer declines in N followed by bursts of N fixation have shaped cyanobacterial communities in a eutrophic lake (Lake Mendota, Wisconsin, USA), possibly driving toxic Microcystis blooms throughout the growing season. On weekly time scales in 2010 and *2011, we monitored the cyanobacterial community in a eutrophic lake using the phycocyanin intergenic spacer (PC-IGS) region to determine population dynamics. In parallel, we measured microcystin concentrations, N2 fixation rates, and potential environmental drivers that contribute to structuring the community.
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Lake Mendota Microbial Observatory Nutrient Data 2013-2018
Pelagic water samples were collected from Lake Mendota as part of routine microbial observatory sampling and analyzed for total and dissolved nitrogen and phosphorus, as well as inorganic nitrogen compounds. On a typical sampling trip, a 12m tube approximating the depth of the epilimnion layer was used to collected an integrated epilimnion water sample from the central, deepest location in the lake. Two separate water grabs, which we refer to here as biological replicates, were typically taken from different sides of the small motor boat and processed separately. Water samples were stored frozen at -20 C until nutrient analysis was performed using a segmented flow analyzer. These samples differ in several key ways from the other routine NTL-LTER nutrient measurements, namely in that they reflect a mixed water column sample rather than a discrete depth, that the dissolved fraction is collected using the microbial observatory's 0.22 um filter instead of 0.45 um, and that the nitrate/nitrite speciation is included by repeating the analysis with and without the standard reducing column. This nutrient data is collected from the same water samples used for microbial analysis, and the collection site is also co-located with the Lake Mendota weather buoy.
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) October 2023 - May 2024
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from October 2023 up to May 2024 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: TIME in UTC [yyyy-MM-ddThh:mm:ssZ]; Latitude [deg]; Longitude [deg]; nominal depth [m]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature [°C]; Conductivity [mmS/cm]. Missing data are defined as NaN.</p>
Metabolism dataset: one year of high-frequency temperature, dissolved oxygen, wind, photosynthetically active radiation observations and low-frequency nutrient data for 58 lakes in the Global Lake Ecological Observatory Network
Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We compiled data from 58 diverse and globally distributed and mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP and ER derived from those data. In addition, the data package includes median in-lake and stream concentrations of dissolved organic carbon and total phosphorus for a subset of 18 of those lakes.
AOP01 Correspondence between plant traits and NEON Airborne Observatory Platform (AOP) data at Konza Prairie (2017)
Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, allowing high-resolution trait mapping. However, the reliability of these data depend on establishing rigorous links with in-situ field measurements. We tested the accuracy of NEON’s readily available AOP derived data products – Leaf Area Index, Total biomass, Ecosystem structure (Canopy height model; CHM), and Canopy Nitrogen by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The weakest relationships were between AOP Canopy Nitrogen and ground-based measures of Nitrogen, as well as the CHM and ground-based canopy height measurements. We also examined how well the full reflectance spectra (380-2500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression models. Only one of the eight traits examined, Nitrogen, had an R2 of more than 0.25. For all vegetation traits, R2 ranged from 0.08-0.29 and the root mean square error of prediction ranged from 14-64%. Our results suggest that currently available AOP derived data products are unreliable, at least at this grassland site, and should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although additional assessment of varying spatial scales of field and AOP data, as well as corrections and data pre-processing to improve data quality, are recommended. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area,
Abundance of eukaryote picophytoplankton and Synechococcus from a moored submersible flow cytometer at Martha's Vineyard Coastal Observatory, ongoing since 2003 (NES-LTER since 2017)
This is a decadal-scale time series of the abundance of eukaryote picophytoplankton and Synechococcus at 4 meters depth at the Martha's Vineyard Coastal Observatory, about 3 km south of Katama Beach, Edgartown, Massachusetts, USA. Picophytoplankton were sensed in situ by a submersible flow cytometer (FlowCytobot, or FCB). Sampling frequency was continuous at approximately 20-minute intervals binned to hourly resolution with some exceptions (e.g., winter in some years). This time series is ongoing for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER).
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) cruises to the Martha's Vineyard Coastal Observatory (MVCO) ongoing since 2017
This package provides a table of cruises to the Martha's Vineyard Coastal Observatory for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER). The majority of events are single day cruises, however, samples missing an MVCO Event Number were collected on multi-day NES-LTER transect cruises aboard larger research vessels. The same sampling protocols for CTD and bongo collection are used on both cruise types. Sampling frequency is approximately monthly, with NES-LTER sampling ongoing since 2017. Cruises involve collection of water column bottle samples, surface bucket samples, and zooplankton net tow samples, as well as ship-provided data. NES-LTER transect cruises will have more extensive underway and acoustic data which can be found by searching by cruise at https://www.rvdata.us/data. The event number for each cruise is provided, along with date, vessel name, cruise identifier where applicable, link to data location (for CTD, ADCP, and other underway data), and checklist of six data types.
Na Wind-Temperature Lidar Data at Andes Lidar Observatory on 3/1/2016
<p>Measurement made by the Na Wind-Temperature Lidar at the Andes Lidar Observatory in Cerro Pachón, Chile. It includes Na density, temperature, zonal, meridional, and vertical wind, from 80 to 115 km altitude at 0.5 km interval and from 23.8 UT 2/29/2016 to 8.9 UT 3/1/2016 at 0.1 hour interval. Errors of these values are also included. -999 represents missing value. </p>
Na Wind-Temperature Lidar Data at Andes Lidar Observatory on 10/30/2016
<p>Measurement made by the Na Wind-Temperature Lidar at the Andes Lidar Observatory in Cerro Pachón, Chile. It includes Na density, temperature, zonal, meridional, and vertical wind, from 80 to 115 km altitude at 0.5-km intervals and from 23.7 UT 10/29/2016 to 8.9 UT 10/30/2016 at 0.1-hour intervals. Errors of these values are also included. -999 represents missing values. </p>
Kodaikanal Solar Observatory (KoSO) White-Light Sunspot Regions Masks (1904-2017)
<p>Regular observations at the Kodaikanal Solar Observatory (KoSO) began in 1904 using a white-light telescope with a 10-cm aperture lens and an f/15 light beam. Between 1912 and 1917, the objective lens was changed several times. In 1918, a 15-cm achromatic lens was installed. This new configuration produced a 20.4 cm size image of the Sun in the image plane. Photographic plates were used to capture the image. The same telescope has been used since 1918 up until 2017 to take regular white-light observations of the Sun. This data set provides the sunspot mask in HDF5 format for all the White Light Observations acquired at KoSO. Each HDF5 file contains the sunspot mask for all the observations for that year. The sunspot masks are provided in two different coordinate systems: (i) Full Disk as observed and (ii) Carrington heliographic coordinate, which is transformed from full disk using near point interpolation. Each data set also contains metadata in the form of HDF5 attributes. The Carrington co-ordinate data if full Sun map, hence the near-side of the Sun is the region where values in the mask in non-zero, where as sunspot regions are filled with value 2. </p> <p>A <strong>Python package (KoSOpy), which can be located on <a href="https://github.com/Kodaikanal-Solar-Observatory/kosopy" target="_blank" rel="noopener">GitHub</a>,</strong> is being developed which can be used to navigate through these data sets.</p>
Sampled and simulated benthic invertebrate body-mass data from the Porcupine Abyssal Plain Sustained Observatory (4850 m, 48.83° N 16.50 °W, NE Atlantic)
<p>A dataset of sampled and simulated benthic invertebrate body-mass data from the Porcupine Abyssal Plain Sustained Observatory (4850 m, 48.83° N 16.50 °W, NE Atlantic) has been produced. It includes data on macro- and megabenthos derived from a randomly sampled power law distribution, seabed core samples, large-scale seabed photography, and seabed trawls.</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) January 2014 - December 2014
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from January 2014 to December 2014 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 20 m [°C]; Salinity @ 20 m [psu].</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) March 2015 - December 2015
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from March 2015 to December 2015 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 6 m [°C]; Sea temperature @ 20 m [°C]; Sea temperature @ 36 m [°C]; Salinity @ 6 m [psu]; Salinity @ 20 m [psu], Salinity @ 36 m [psu].</p>
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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)
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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.