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Land-cover mapping of the central Arizona region based on 2015 National Agriculture Imagery Program (NAIP) imagery
Detailed land-cover mapping is essential for a range of research issues addressed by sustainability science, especially for questions posed of urban areas, such as those of the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) program. This project provides a 1-meter land-cover mapping of the CAP LTER study area (greater Phoenix metropolitan area and surrounding Sonoran desert). The mapping is generated primarily using 2015 National Agriculture Imagery Program (NAIP) four-band data, with auxiliary GIS data used to improve accuracy. Auxiliary data include the 2015 cadastral parcel data, the 2014 USGS LiDAR data (1-meter), the 2014 Microsoft/OpenStreetMap Building Footprint data, the 2015 Street TIGER/Line, and a previous (2010) NAIP-based land-cover map of the study area (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=623). Among auxiliary data, building footprints and LiDAR data significantly improved the boundary detection of above-ground objects. Post-classification, manual editing was applied to minimize classification errors. As a result, the land-cover map achieves an overall accuracy of 94 per cent. The map contains eight land cover classes, including: (1) building, (2) asphalt, (3) bare soil and concrete, (4) tree and shrub, (5) grass, (6) water, (7) active cropland, and (8) fallow. When compared to the aforementioned, previous (2010) NAIP-based land-cover map for the study area, buildings and tree canopies are classified more accurately in this 2015 land-cover map.
Normalized Difference Vegetation Index (NDVI) derived from 2021 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates two vegetation indices —Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI)— from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2021 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, 2017, and 2019 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP LTER study area boundary of central Arizona, USA. The materials presented here include NDVI data with SAVI data presented in a companion dataset that is also available through the EDI.
Soil-Adjusted Vegetation Index (SAVI) derived from 2021 National Agriculture Imagery Program (NAIP) data for the central Arizona region
This project calculates two vegetation indices —Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI)— from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2021 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, 2017, and 2019 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP LTER study area boundary of central Arizona, USA. The materials presented here include SAVI data with NDVI data presented in a companion dataset that is also available through the EDI.
Microbial Sampling from Shark River Slough and Taylor Slough, Everglades National Park, South Florida, USA (FCE LTER), January 2001 - December 2023
We collected monthly observations of water microbial characteristics from each of the FCE LTER sites beginning in February 2001. Bacteria counts using DAPI epifluorescence, heterotrophic bacteria production with tritiated Thymidine uptake, and algal energetics and chl a using the PAM fluorometer were determined from each of the water samples. Bacteria counts in Shark River Slough in the freshwater end of the transect revealed highest bacteria numbers upon marsh rewetting after the dry down. The highest overall count of bacteria was found at the most freshwater point adjacent to the perimeter of the water conservation area but only in March of 2001. Peak numbers of bacteria in the saline end of Shark River transect occurred in December and July. There is some evidence that these higher bacteria numbers in the SR transect are associated with higher salinities. Highest bacteria counts along the Taylor slough transect were observed at the mouth of the Taylor River with peak counts in the wet season in October. Bacteria densities also increased from the eastern to western end of the transect in Florida Bay. Heterotrophic bacterial production did not relate closely bacteria numbers and exhibited highest numbers in the dry season. There was no discernible relationship between salinity and bacteria production as seen in bacteria numbers. Monthly observations using PAM fluorometry revealed that brown algae was the greatest contribution to the algal chal a pool and this relationship was consistent across all FCE LTER sites. Converse to the pattern of bacteria abundance along the Shark River transect, there was evidence that algal biomass decreases from freshwater to estuary. In the Shark River, algal energetics increased from marsh to estuary as well as in the panhandle region of the Taylor River transect. From these observations we conclude the behavior of the microbial loop and interactions generated between functional guilds is highly variable along individual transects an
Large consumer isotope values, Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2005 - ongoing
This dataset provides information on the stable isotope values from multiple tissues from various consumers (especially bull sharks and American alligators) sampled within the Shark River Slough.
Consumer Stocks: Fish, Vegetation, and other Non-physical Data from Everglades National Park (FCE LTER), South Florida, USA from February 2000 to April 2005
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Consumer Stocks: Physical Data from Everglades National Park (FCE), South Florida from February 1996 to April 2008
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the physical data of the sampled plots.
Consumer Stocks: Fish Biomass from Everglades National Park (FCE), South Florida from February 2000 to April 2005
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Consumer Stocks: Fish Biomass from Everglades National Park (FCE), South Florida from February 1996 to March 2000
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Consumer Stocks: Wet weights from Everglades National Park (FCE), South Florida from March 2003 to April 2008
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Water Quality Data (Porewater) from the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, January 2001 - ongoing
Porewater samples are collected at Florida Coastal Everglades Long Term Ecological Research (FCE LTER) Program Shark River Slough sites SRS1b (not active), SRS1c (not active), SRS1d, SRS2, and SRS3 within the 1 m^2 aboveground sawgrass nondestructive biomass plots. Airstones connected to Tygon tubing are inserted 10-15 cm below the soil surface. Biannually during the wet season, Monoject 140cc syringes are used to collect at least 80 mL of porewater sample and after collection they are immediately placed in an ice filled cooler. The lab processing of these samples include salinity measurements using a YSI, and filtering the sample through a filter (Whatman GF/F from 2000 to 2017 and Whatman polydisc GW from 2017 to present) . Samples are analyzed for inorganic nutrients such as NO2-,NO3-,NH4+,SRP, and DOC. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques and DOC is quantified on a Shimadzu TOC Analyzer.
Sawgrass Above and Below Ground Total Nitrogen and Total Carbon from the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, September 2002 - ongoing
Once a year during the dry season (Dec-May) three live sawgrass plants are collected from each site. These plants are divided into their live above and live below ground parts. Then both the above and below ground parts are analyzed for total nitrogen (TN), total carbon (TC), and total phosphorus (TP). The TN and TC data are included in this data package. For Shark River Slough sawgrass TP data, please see package knb-lter-fce.1071 in the FCE LTER website's data catalog or in the EDI repository.
Sawgrass Above and Below Ground Total Phosphorus from the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, September 2002 - ongoing
Once a year during the dry season (Dec-May) three live sawgrass plants are collected from each site. These plants are divided into their live above and live below ground parts. Then both the above and below ground parts are analyzed for total nitrogen (TN), total carbon (TC), and total phosphorus (TP). The TP data are included in this data package. For Shark River Slough sawgrass TN and TC data, please see package knb-lter-fce.1070 in the FCE LTER website's data catalog or in the EDI repository.
Water Quality Data (Extensive) from the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, October 2000 - ongoing
Water quality samples are being collected using ISCO autosamplers at all Florida Coastal Everglades Long Term Ecological Research Program (FCE LTER) wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a filter (Whatman GF/F from 2000 to 2017 and Whatman polydisc GW from 2017 to ongoing) immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP and TN. We use these monthly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter or refractometer. In January 2007 a 6 days interval began for SRS1d, SRS2 & SRS3; the ISCOs did not change their sampling scheduled, they kept collecting water sample every 18 hours and switching bottles every three days; once in the lab, the 3 days was turned into 6 days by combining two bottles into 2 liters container. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain e
Water Quality Data (Grab Samples) from the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2001 - ongoing
Water quality samples are being collected using ISCO autosamplers at all Florida Coastal Everglades Long Term Ecological Research (FCE LTER) Program wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a filter (Whatman GF/F from 2000 to 2017 and Whatman polydisc GW from 2017 to ongoing) immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP and TN. We use these monthly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an ANTEK 9000N analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter or refractometer. In January 2007 a 6 days interval began for SRS1d, SRS2 & SRS3; the ISCOs did not change their sampling scheduled, they kept collecting water sample every 18 hours and switching bottles every three days; once in the lab, the 3 days was turned into 6 days by combining two bottles into 2 liters container. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rai
Water Quality Data (Extensive) from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, April 1996 - ongoing
Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these monthly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with an YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 500mL sample 30 minutes after the threshold has been reached. Rain event samples are collected, treated, and analyzed as all other water quality samples.
Water Quality Data (Grab Samples) from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, May 2001 - ongoing
Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these montly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 500mL sample 30 minutes after the threshold has been reached. Rain event samples are collected, treated, and analyzed as all other water quality samples.
Water Quality Data (Extensive) from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, July 1999 - ongoing
Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these monthly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with an YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 500mL sample 30 minutes after the threshold has been reached. Rain event samples are collected, treated, and analyzed as all other water quality samples.
Water Quality Data (Grab Samples) from the Taylor Slough, Everglades National Park (FCE), Florida, USA, September 1999 - ongoing
Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these montly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 500mL sample 30 minutes after the threshold has been reached. Rain event samples are collected, treated, and analyzed as all other water quality samples.
Sawgrass Above and Below Ground Total Phosphorus from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, March 2002 - ongoing
Once a year during the dry season (Dec-May) three live sawgrass plants are collected from each site. These plants are divided into their live above and live below ground parts. Then both the above and below ground parts are analyzed for TN, TC, and TP.
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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.