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A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations in the foothills of the Tehachapi mountains at Tejon Ranch, California, 2011-2017
These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies in the foothills of the Tehachapi mountains at Tejon Ranch (Lat 34.983, Long -118.716, elevation 750-930 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges and valleys. To characterize surface temperature variation within a site, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens. An additional 18 sensors were placed along three transects over the landscape running N-S. They were placed strategically to sample topographic inflection points (hill tops and valley bottoms) as well as north and south facing slopes. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor. using HOBO (Onset, www.onsetcomp.com) devices.
A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations in the Tehachapi mountains at Tejon Ranch, California, 2011-2017
These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies in the Tehachapi mountains at Tejon Ranch (Lat 34.967, Long -118.583, elevation 1600-1700 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges and valleys. To characterize surface temperature variation within a site, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens. An additional 18 sensors were placed along three transects over the landscape running N-S. They were placed strategically to sample topographic inflection points (hill tops and valley bottoms) as well as north and south facing slopes. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor. using HOBO (Onset, www.onsetcomp.com) devices.
The Jefferson Project 2021 weather data from ten surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2021, The Jefferson Project had ten weather monitoring stations on and around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, WX_Glenburnie, VP_TeaIsland, VP_AnthonysNose, and VP_HarrisBay. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, and N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which has undergone data correction and downsampling to an hourly frequency.
The Jefferson Project 2022 weather data from nine surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2022, The Jefferson Project had nine weather monitoring stations on and around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, WX_Glenburnie, VP_TeaIsland, and VP_HarrisBay. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, and N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which has undergone data correction and downsampling to an hourly frequency.
Summer high frequency measurements of dissolved O2 and CO2 concentrations and water temperature at the surface of 11 northern lakes
This dataset includes high frequency paired measurements of dissolved O2 and CO2 concentrations at the surface (0.5 to 2 m depth) of 11 lakes in the Northern Hemisphere. Measurements were taken every 2 hours in summer (July and August) of various years depending on lakes (between 2011 and 2014). The dataset is used to test a conceptual framework on the controls of coupling and decoupling of these two gases. In all lakes dissolved CO2 was measured with infrared analyzer coupled with a diffusion membrane and dissolved O2 with optodes. All gas measurements are paired with water temperature provided by one of the gas probe (usually from the O2 probe).
Nyack Floodplain RiverNet surface water and groundwater dissolved oxygen, conductivity, water level, and temperature Northwest Montana, USA, 2012-2020
Water dissolved oxygen, conductivity, temperature, and level from ten locations in the Nyack Floodplain of the Middle Fork of the Flathead River in Northwest Montana, USA. Measurements are made hourly for the period of 2012 to 2020. Six sensor are placed in groundwater wells and four are placed in surface water. Data up to June 26h, 2019 have been cleaned to remove bad data and flag potentially anomalous observations.
LAGOS-US NETWORKS v1.0: Data module of surface water networks characterizing connections among lakes, streams, and rivers in the conterminous U.S
Knowing the degree of surface water connectivity among aquatic ecosystems can help scientists better understand and predict the movement of materials and biota across ecosystems. Methods to quantify surface water networks that include lake and stream connections at broad spatial scales are rare because it is difficult to balance accurate estimates of surface water connectivity and computational challenges. The LAGOS-US NETWORKS (NETS) module contains surface connectivity metrics for lake networks across the conterminous United States. We applied a graph theory approach to identify lake networks (i.e. a set of lakes connected by streams either upstream, downstream, or both) created from the medium resolution NHD lakes, streams, and rivers and subsequently derive surface water connectivity metrics for lakes and networks. Using this approach, we created a total of 898 networks that include 86,511 lakes. The NETS module includes a table with metrics for connections between lakes (both upstream and downstream), dams, network position, and whole networks. NETS also includes a flow table and bidirectional and unidirectional distance tables that provide the distances between every pair of connected lakes.
Surface and SubSurface Soil Organic Matter Processing following Hurricane Harvey, Texas, USA
Coastal wetland plant identity and cover is changing, as many subtropical salt marshes dominated by low-stature herbaceous species transition to woody mangroves. How changes in dominant plant species affect carbon processing in coastal wetlands during storms is uncertain. We experimentally manipulated patch-scale (3 × 3 m) cover of black mangroves (Avicennia germinans) and saltmarsh plants (e.g., Spartina alterniflora, Batis maritima) in fringe and interior locations of ten plots (24 × 42 m) to create a gradient in mangrove cover in coastal Texas, USA. Hurricane Harvey made direct landfall over our site on 25 August 2017. To test how mangrove cover affected carbon retention after the storm, we measured litter breakdown rates (k) of A. germinans and S. alterniflora in surface soils and fast- and slow-decomposing standard litter substrates (green and red tea, respectively) in subsurface soils (15 cm depth). Soil temperatures were lower in mangrove than marsh patches, and prior microclimate measurements showed non-linear increases in air and soil temperatures with increasing mangrove cover (highest temperatures at intermediate % cover). Litter breakdown rates (k) were 2 higher in surface than in subsurface soils. Avicennia germinans litter k increased linearly in surface soils with plot-level mangrove cover, whereas slow-decomposing red tea had similar k in subsurface soils of all plots. Litter k of S. alterniflora in surface soils and fast-decomposing green tea in subsurface soils increased non-linearly with mangrove cover (highest k at intermediate % cover), explained largely by temperature. Microbial respiration rates (R) were highest in interior marsh patches for S. alterniflora litter and increased with plot-level mangrove cover, whereas R associated with A. germinans litter was similar among fringe and interior patches and highest at higher mangrove cover. Despite widespread declines in soil nutrient concentrations throughout marsh and mangrove patches in all pl
Soil hydraulic and thermal properties determined in surface organic and mineral soils in the region near Toolik Lake on the North Slope of Alaska, 2016-2019
Soil cores of 5 cm diameter down to frozen soil were taken from a subset of sample sites for laboratory analysis. Determinations of hydraulic conductivity, thermal conductivity, porosity, and bulk density were made for each core. For a further subset of sites we developed soil moisture retention curves.
Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest
These data are simultaneous and continuous measurements of carbon, water and energy fluxes of the terrestrial landscape. These fluxes are major regulatory drivers of the boreal climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. At the APEX project site, within Bonanza Creek Experimental Forest, this monitoring is repeated across a chronosequence of permafrost degradation; the Black Spruce site is an area of stable permafrost with intact black spruce forest (APEX gamma site), the Thermokarst site is an active thermokarst zone with considerable tree mortality (APEX betaSW site), the Fen site is within a stable treeless fen with deep active layer depth (APEX apexcon,low, and ele sites). The main variables being monitored are the instananeous fluxes of CO2, water vapor and surface energy (shortwave, longwave and net radiation), secondary variables included photosynthetically active radiation (PAR), air and soil temperatures, rainfall, snow depth, soil moisture content, wind direction and speed, and average atmospheric concentrations of CO2 and H2O through the year.
Numerical summaries of vegetation indices and land surface temperature derived from remotely sensed imagery in Phoenix Area Social Survey (PASS) neighborhoods of central Arizona
This project calculates two vegetation indices: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI), and land surface temperature (LST) from remotely sensed imagery. NDVI and SAVI are calculated from the 2010, 2013, 2015, and 2017 NAIP imagery (1m resolution). LST is calculated from Landsat 5 and 8 imagery (30m resolution) from summer months in 1985, 1990, 1995, 2000, 2005, 2010, and 2015. Summary values are calculated for each of the aforementioned data resources for 2011 and 2017 Phoenix Area Social Survey (PASS) study area boundaries. Tabular summaries of the mean, median, minimum, maximum, and standard deviation of the NDVI, SAVI, and LST values for the 2011 and 2017 Phoenix Area Social Survey boundaries (45 and 12 neighborhoods, respectively) are provided. Javascript code used to process NDVI, SAVI, and LST imagery, and R code used to calculate numerical summaries of NDVI, SAVI, and LST in PASS neighborhoods are included with this dataset. Locations and areas of PASS study neighborhood boundaries and source imagery used to calculate these summaries are available through the Environmental Data Initiative - see resouce listing in the methods of this data set.
NOAA Daily Surface Meteorologic Data at NCDC Flamingo Ranger Station (ID-083020) (FCE), South Florida, USA, January 1951 - January 2021
The National Climatic Data Center's (NOAA) daily mean, maximum, and minimum air temperatures and daily precipitation collected at Flamingo Station (Coop ID- 083020). This site was terminated in January 2021.
NOAA Daily Surface Meteorologic Data at NCDC Miami International Airport Station (ID-085663), South Florida, USA, January 1948 - ongoing
The National Climatic Data Center's (NOAA) daily mean, maximum, and minimum air temperatures and daily precipitation collected at Miami International Airport Station (Coop ID- 085663).
NOAA Daily Surface Meteorologic Data at NCDC Royal Palm Ranger Station (ID-087760)(FCE LTER), South Florida, USA, May 1949 - ongoing
The National Climatic Data Center's (NOAA) daily mean, maximum, and minimum air temperatures and daily precipitation collected at Royal Palm Ranger Station (Coop ID- 087760).
Abiotic monitoring of physical characteristics in porewaters and surface waters of mangrove forests from the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), South Florida, USA, December 2000 - ongoing
Data on porewater salinity, temperature, conductivity, pH and redox have been collected to help explain patterns found in porewater nutrient concentrations that were sampled in the same plots. See knb-lter-fce.1171 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1171) for related porewater-nutrient-concentration data.
Mangrove soil phosphorus addition experiment from July 2013 to August 2013 at the mangrove peat soil mesocosms (FCE), Key Largo, Florida - Nutrients in Surface Water and Aboveground Biomass
Sea levels in South Florida are conservatively predicted to rise by 0.60 m by 2060. The key mechanisms that maintain coastal peatland elevation against increasing sea level are organic matter accumulation via plant production and mineral sedimentation rates (Smoak et al. 2013). Although coastal mangrove soils are regularly inundated with seawater, little is know about the drivers of carbon sequestration (above or below ground) versus atmospheric efflux under different conditions of salinity and elevated phosphorus (P) associated with sea-level rise and storm surge. A recent study using mangrove peat soils found that seawater inundation reduced soil carbon efflux losses and salinity concentration had little effect on carbon retention or loss pathways. The next logical steps are to understand how plant-soil interactions affect above and below ground carbon processes, as well as how increases in P associated with storm surge from the Gulf of Mexico will influence physical, chemical and biological components of mangrove soils that are associated with above and belowground carbon processes. We will manipulate P in inundated peat soil mesocosms with disturbed and undisturbed red mangrove (Rhizophora mangle) seedlings to identify some of the fundamental mechanisms of soil elevation and carbon cycling given expected increases in seawater-based P availability in South Florida coastal mangroves.
Groundwater and surface water chemistry from the Hole-in-the-Donut and nearby Taylor Slough in Everglades National Park, Florida, USA: 2015-2016
This research investigated the effects of the vegetation and soil removal on the hydrologic conditions of the Hole-in-the-donut (HID) of Everglades National Park. Groundwater and surface water samples were collected from 2 wells within the HID (DO1,DO3) and two wells outside the HID in adjacent Taylor Slough (NP-67, TSB). Surface water was collected at each site if present.
Major Ion Concentrations in Surface Water Collected from Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, December 2003 – December 2015
This package includes data of concentrations of sodium, potassium, magnesium, calcium, chloride, and sulfate in surface water samples collected from Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) Program sites in Taylor Slough. These sites are TS/Ph1a (2003-2013), TS/Ph2 (2003-2012), and TS/Ph3 (2004-2015). Analyzed samples include composite samples, rainfall samples, and grab samples. Composite samples represent water collected over the course of 3 days by autosamplers programmed to draw 250 mL every 18 hours. Rainfall samples represent water collected by the autosamplers when a threshold of = 2.5 cm of rain per hour is passed. A 500 mL sample is collected 30 minutes after meeting the threshold. Composite and rainfall samples are retrieved every 3-4 weeks and returned to the Florida International University (FIU) Modesto A. Maidique campus. A grab sample is collected at each site during these visits. Cation and anion analysis were completed using ion chromatography on a Dionex DX-120. Sample preparation and analysis for major ions were completed in the Hydrogeology laboratory at FIU. This dataset is completed.
December 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in December, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
March 2003 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in March, 2003. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
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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.