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239 results for “field collections”
Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003-2022.
Zooplankton samples were taken on lakes with a 30 cm diameter plankton net with a 256 micron mesh netting from 2018-2022. Prior years used a 156 micron mesh netting. Density was calculated based on the number of each taxa counted in a subsample or whole sample and expanded to the volume sampled to determine the number of each zooplankton taxa per liter. All samples were collected from Toolik Lake and lakes near the University of Alaska Toolik Field Station, Fairbanks, Arctic LTER from 2003-2022.
Bacterial Production Data for lake and stream samples collected in summer 2012 through 2021, Arctic LTER, Toolik Lake Field Station, Alaska
File containing data on bacterial productivity in lakes and streams. Samples were collected at various sites near Toolik Lake Field Station (68 38'N, 149 36'W). Sample site descriptors include an assigned number (sortchem), site, date, time and depth, and bacterial production.
Soil biogeochemical variables collected on the Arctic Long Term Ecological Research (ARC LTER) experimental plots in moist acidic and dry heath tundra, Arctic LTER, Toolik Field Station, Alaska 2017.
**Note: Versions 1 and 2 had the wrong data files.** Soil nutrients (total Carbon and Nitrogen, inorganic nutrients (ammonium ion (NH4), nitrate anion (NO3-), phosphate anion (PO43-)); organic nutrients (extractable organic carbon (EOC), extractable total nitrogen (ETN), extractable organic phosphorus (EOP)), microbial biomass, and extracellular enzyme activity on soils sampled from the Arctic LTER Dry Heath (organic soils only) and Moist Acidic Tundra (organic and mineral soils) herbivore exclosures and control plots at Toolik Lake, AK in July 2017.
Nitrogen mineralization potential in soils collected from the Jornada Basin LTER-I transect and extracted at field collection time, 1989
This data package contains nitrogen mineralization data from soils collected along the Jornada Basin LTER (LTER-I) transects in southern New Mexico, USA. These transects are located in a livestock exclosure established in 1982 in the Chihuahuan Desert Rangeland Research Center (CDRRC) and run from the middle of the College Playa up to the foot of Mt. Summerford (2.7 km in length). Prior to the exclosure, the study site was moderately to heavily grazed for the past 100 years. The Treatment transect was treated annually with ammonium nitrate fertilizer (NH4NO3 at 10g N/m2/yr) until 1987. Along each transect, 91 stations, each with a plant intercept line, are spaced at 30 meter intervals. For this dataset, 60 soil samples (total) were collected along the control and fertilized treatment transects and mixed with potassium chloride solution (KCl) on Nov 27, 1989, then filter extracted the following day. The dataset contains a soil moisture correction factor, sample weights, total inorganic nitrogen (NO3+NO2-N), and nitrogen in ammonium (NH4-N) for Week F (field) of nitrogen mineralization potentials. The soil mineralization data complements the biomass harvest measurements that occurred in September 1989 (dataset knb-lter-jrn.210015001). This study is complete.
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
This dataset contains estimates of gas exchange velocity, gas exchange rate, and hydraulic parameters for streams calculated from tracer-gas experiments and conservative tracer injections collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, the NEON Reaeration field and lab collection data product (DP1.20190.001) was used to calculate these estimates. Gas exchange was estimated in two ways: first, following an unpooled frequentist approach and second, following a partially pooled Bayesian approach. In addition, a salt-correction was applied to gas exchange estimates for sites where it was possible and necessary. All estimates of gas exchange are included in the file gasExchange_ds.csv. A recommended selection of these estimates is included in the dataset (best_k600_mPerDay and best_K600_mPerDay). The stanfit objects used for the partially pooled Bayesian approach are also included as site-specific model objects for gas exchange velocities and rates. In addition, water velocity was calculated from conservative tracer injections, and mean water depth was calculated from these water velocity estimates and measurements of wetted width and water discharge. All hydraulic parameters are included in the file hydraulics_ds.csv. All processing code is available in the reaRates R package. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
Field Evidence of Carbon and Nitrogen Stabilization through Mineral Associated Organic Matter Formation in Coastal Wetland Soils from Apalachicola, Florida, collected in June, 2022.
This data set was used to observe the role of Mineral Associated Organic Matter Formation (MAOM) on biogeochemical soil properties in three coastal wetlands in Apalachicola, Florida. One wetland was restored using beneficial dredged sediment, increasing the soil's inorganic matter content. Soil samples were collected in June 2022 from this wetland and two nearby reference wetlands: one with high organic matter and the other with higher inorganic matter content. The samples were analyzed at the University of Central Florida for biogeochemical properties to determine which properties were most related to MAOM pools.
Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003 - 2017 (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-arc/10272/5. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton density,were taken with a 30 cm diameter plankton net with 156 um mesh plankton netting, for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER from 2003 - 2017. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices of species composition will be compiled for each component of the arctic landscape to compare the biogeochemistry and community dynamics of each ecosystem in relation to their responses to climate change and disturbance and to the propagation of those responses across the landscape.
Soil temperature data collected from the Arctic LTER wet sedge experimental site Toolik Field Station North Slope, Alaska from 1994 to 2020
Soil temperature data collected every 4 hours from a wet sedge site at the Arctic Tundra LTER site at Toolik Lake. Temperatures are measured every 3 minutes and averaged every 4 hours in control, nitrogen alone, phosphorus alone, nitrogen and phosphorus, and greenhouse experimental plots soil temperatures.
Presence/absence of new snow-fall scored from time-lapse photography collected near Toolik Field Station, Alaska, summers 2012-2016
This data set describes the presence/absence of new snowfall approximated daily using time -lapse photography images near Toolik Field Station during summers from 2012 to 2016 under National Science Foundation (NSF) Office of Polar Programs ARC 0908444 (to Laura Gough), ARC 0908602 (to Natalie Boelman), and ARC 0909133 (to John Wingfield). Additional cameras funded by other grants were also used for scoring including multiple Toolik EDC timelapse images taken at Toolik, Atigun Ridge, and Imnavait. Additional data were scored from time lapse photography taken by the Deegan and Urban labs (Office of Polar Programs #0902153 and #1417664). All data are associated with publication DOI: 10.1111/jav.01712.
Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions
<p><strong><span>Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions</span></strong></p> <p><span>Mauro A. Di Vito<sup>1</sup>, Ilaria Rucco<sup>2</sup>, Sandro de Vita<sup>1</sup>, Domenico M. Doronzo<sup>1</sup>, Marina Bisson<sup>3</sup>, Elena Zanella<sup>4</sup></span></p> <p><sup><span>1</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Vesuviano, Napoli, Italy</span></p> <p><sup><span>2</span></sup><span> Heriot-Watt University, School of Engineering and Physical Sciences, Edinburgh, United Kingdom</span></p> <p><sup><span>3</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy</span></p> <p><sup><span>4</span></sup><span> Università di Torino, Dipartimento di Scienze della Terra, Torino, Italy</span></p> <p><span> </span></p> <p><span>This dataset is organized in an Excel file, and it includes all the data collected and reviewed during the last 20 years from drill cores, outcrops, archaeological excavations, stratigraphic trenches, and the existing literature. It focuses on the primary (pyroclastic) and secondary (lahar) deposits of the 472 AD (Pollena) and 1631 eruptions from the Somma-Vesuvius volcano. The aim is to collect stratigraphic, stratimetric, sedimentological, lithological and chronological data to generate distribution maps and to validate the numerical simulations and models for the risk assessment. In particular, this dataset is complementary to – and in support of – the full work by Di Vito et al. (2024), in which the distribution of those deposits all around the Somma-Vesuvius complex and further is presented and discussed. Such dataset was used to inform the shallow-water model of lahars by de’ Michieli Vitturi et al. (2024), which in turns was used by Sandri et al. (2024) to elaborate probabilistic maps of lahar invasion in the Somma-Vesuvius and Apennine areas.</span></p> <p><span>All the data are organized in columns: the first four aim to identify the sites, and so there is a numeric identification code (ID), the name of the site (NAME), and the metric coordinates (East-North) in the UTM WGS 84 – Zone 33 reference projection (X, Y). The last two columns are “MUNICIPALITY” and “PROVINCE” and give a spatial location to the points.</span></p> <p><span>For the two eruptions, several columns have been created:</span></p> <p><span><span>·<span> </span></span></span><span>“472_PRIM”, “1631_PRIM” and “472_ASH” and “1631_ASH” indicate, respectively, the fallout primary deposits of the eruptions and the primary ash, particularly the ash related to the last phases of the eruptions (generally phreatomagmatic).</span></p> <p><span><span>·<span> </span></span></span><span>“472_SYN” and “1631_SYN” indicate the syn-eruptive lahars related to the two eruptions, recognized from the similar composition between the primary deposit and the lahar and from the evidence of a short-term exposure between the two.</span></p> <p><span><span>·<span> </span></span></span><span>“472_POST” AND “1631_POST” indicate the post-eruptive lahars related to the two eruptions. They are considered “post” when in the deposit there are pumices belonging to older eruptions, indicating their involvement in the progressive erosion of the slopes and valleys, and when there is evidence of long periods without deposition, such as the presence of</span><span> </span><span>slightly humified surfaces or traces of human artifacts (excavations, ploughing).</span></p> <p><span><span>·<span> </span></span></span><span>“EROSION_fallout_472” refers to the sites where it was possible to find erosional unconformities between the pyroclastic deposit of the 472 AD eruption and the lahar, as well as between the lower and upper lahar flow units. The erosional features are for example the lack of one or more primary eruptive layers (eroded by the overlying deposit), a change in the granulometry, or lateral discontinuity of the deposit. </span></p> <p><span><span>·<span> </span></span></span><span>“Pdyn (kPa)”, “v (m/s)”, “C (%)” and “T” are all the parameters quantified to validate the numerical models and to assess the hazard from lahars. Pdyn is the flow dynamic pressure, which represents the capability of the flow to entrain a clast, and it depends on the velocity (v) and the flow density, which in turn results from a combination of the density of the particles and the water through the “C (%)”, that is the particle volume concentration. To calculate the flow dynamic pressure and the velocity, the parameters taken into account are the dimensions of the biggest clasts and the nature of the clasts (limestone, ceramic, brick, tephra, lava, sandstone, iron) found in the lahar deposits. The concentration is estimated considering some sites in which the flow expands in correspondence with some obstacles (for example a Roman wall). This can be assumed to be the initial height of the flow before the emplacement. Finally, “T” refers to the estimated deposition temperature of the deposit quantified by the magnetic analysis, in particular in some sites where the lahar interacted with anthropogenic structures.</span></p> <p><span><span>·<span> </span></span></span><span>“DEPOSIT (472)” indicates the type of lahar deposit (syn- or post-eruptive) of the 472 AD eruption in which the fragments were found.</span></p> <p><span><span>·<span> </span></span></span><span>“MULTIPLE LAHAR UNITS” indicates the sites in which multiple flow units are vertically identified in the lahar deposits. They are generally a result of rapid and progressive aggradation of multiple flow pulses, each one resulting from single-pulse “en masse” emplacement</span><span>.</span></p>
Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003 - 2017 (Reformatted to a Darwin Core Archive)
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/262/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-arc/10272/5. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton density,were taken with a 30 cm diameter plankton net with 156 um mesh plankton netting, for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER from 2003 - 2017. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices of species composition will be compiled for each component of the arctic landscape to compare the biogeochemistry and community dynamics of each ecosystem in relation to their responses to climate change and disturbance and to the propagation of those responses ac
Hourly meteorological data gapfilled for sensor downtimes collected near Toolik Field Station, Alaska, summers 2012-2016
This data set includes meteorological parameters collected near Toolik Field Station from 2012 to 2016 under National Science Foundation (NSF) Office of Polar Programs ARC 0908444 (to Laura Gough), ARC 0908602 (to Natalie Boelman), and ARC 0909133 (to John Wingfield). It also includes meteorological data collected by two additional entities that are available on public repositories. Toolik data reflect data collected by the Toolik Envronmental Data Center and Imnavait data reflect data collected by the Arctic Observatory Network (AON). These data have been modified such that that sensor downtimes have been gapfilled by pulling data from the next nearest station. These data are associated with publication DOI: 10.1111/jav.01712
Soil biogeochemical variables collected on the Arctic LTER experimental plots in moist acidic, moist non-acidic, wet shrub and shrub tundra, Arctic LTER Toolik Field Station, Alaska 2015
We investigated the effect of long-term warming on multiple soil and microbial carbon, nitrogen, and phosphorus pools, and microbial extracellular enzyme activities, with a particular focus on phosphorus, in Alaskan tundra plots underlain by permafrost
Chlorophyll and phaeopigments from water column samples, collected at selected depths at Palmer Station Antarctica, during the Palmer LTER field seasons, 1991-2025.
Phytoplankton chlorophyll sampling was led by Smith from the 1991-1992 season through the 2001-2002 season, and then by Vernet from the 2002-2003 season through the 2006-2007 season. Schofield is the third, and current lead, beginning in the 2008-2009 season. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Chlorophyll a (Chl a) is the principal photosynthetic pigment of phytoplankton, and is used as a proxy measurement for estimating phytoplankton biomass in water samples. Chl a concentrations reflect the distribution of active phytoplankton spatially and with depth in the water column and their changes over time. Phaeopigments are non-photosynthetic pigments that are degradation products of phytoplankton chlorophylls which form during and after phytoplankton blooms. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Beginning in the 2020-2021 season, Station B is no longer sampled. Chlorophyll and phaeopigment concentrations are determined by filtration, extraction, and fluorometric detection of samples. The primary source of error for phaeopigment measurement is Chlorophyll b. If high amounts of Chlorophyll b are present in the sample, phaeopigments may be overestimated. There was no field season in 2021-2022.
Water column primary production from inorganic carbon uptake for 24h at simulated in situ light levels in deck incubators, collected at Palmer Station Antarctica during Palmer LTER field seasons, 1994-2025.
Primary Production experiments were led by Vernet from the 1994-1995 season through the 2006-2007 season. Schofield is the current lead, beginning in the 2009-2010 season. Methods have been kept consistent as much as possible over the full time series and different Principal Investigators. Primary production is the uptake of inorganic carbon and assimilation of it into organic matter by phytoplankton. Primary production rates, expressed as mgC per m3 per day were measured by the uptake of radioactive (14C) sodium bicarbonate. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Beginning in the 2020-2021 season, Station B is no longer sampled. Water is put into borosilicate bottles, inoculated with 1 uCi of NaH14CO3 per bottle, and incubated in an outdoor deck incubator. The incubator is plumbed to the Palmer Station sea water system to maintain ambient seawater temperature and bottles are screened to in situ light levels. The uptake of 14C-bicarbonate by the phytoplankton was measured in a scintillation counter after a 24-hour incubation period. Primary production experiments were not conducted during the 2020-2021 nor 2023-2024 field seasons. There was no field season in 2021-2022.
Mesozooplankton taxonomic density collected using a 1-m diameter ring net with 200-μm mesh at Palmer Station, Antarctica during Palmer LTER field seasons, 2017-2020
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton in surface waters and thus provide a link between primary producers and higher trophic levels. The numerical density of common mesozooplankton taxa was determined at Palmer LTER Stations B and E. Samples were collected with a 1-m diameter, 200-μm mesh ring net towed obliquely from the surface to a target depth of 50 m and back. Tows were conducted during daytime, and sampling frequency was nominally twice weekly while personnel were at Palmer Station between the months of November and March. The preserved samples were size-fractionated with nested sieves into five size classes (0.2−0.5, 0.5−1, 1−2, 2−5, and >5 mm) prior to microscopic enumeration. Data are provided for the following taxa: copepods Oithona spp., Calanoides acutus (>1 mm only), Calanus propinquus (>1 mm only), Rhincalanus gigas (>1 mm only), and small calanoids (0.2−1 mm), chaetognaths, asteroid larvae, nemertean larvae, and foraminifera (not quantified in all years). Individual size fractions were split and subsampled such that at least 100 individuals of the most abundant taxon were present. Density varies across taxa, seasonally, among years, and between sampling stations. Units of density are individuals per cubic meter.
Macrozooplankton taxonomic density collected using a 1 x 1 m square net with 700-μm mesh at Palmer Station, Antarctica during Palmer LTER field seasons, 2017-2020
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton in surface waters and thus provide a link between primary producers and higher trophic levels. The numerical density of common macrozooplankton taxa was determined at Palmer LTER Stations B and E. Samples were collected with a 1 x 1 m square, 700-μm mesh Metro net towed obliquely from the surface to a target depth of 50 m and back. Duplicate tows typically were conducted at each sampling site. Tows were conducted during daytime, and sampling frequency was nominally twice weekly while personnel were at Palmer Station between the months of November and March. The catch was sorted and counted live. Data are provided for the following taxa, which dominated biomass: the euphausiids Euphausia superba and Thysanoessa macrura, the thecosome pteropod Limacina rangii, gymnosome pteropods, the salp Salpa thompsoni, amphipods, and larval fishes. Density varies across taxa, seasonally, among years, and between sampling stations. Units of density are individuals per cubic meter.
Size-fractionated zooplankton dry weight collected using a 1-m diameter ring net with 200-μm mesh at Palmer Station, Antarctica during Palmer LTER field seasons, 2017-2020
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton in surface waters and thus provide a link between primary producers and higher trophic levels. The density of zooplankton dry weight for five size fractions was determined at Palmer LTER Stations B and E. Samples were collected with a 1-m diameter, 200-μm mesh ring net towed obliquely from the surface to a target depth of 50 m and back. Tows were conducted during daytime, and sampling frequency was nominally twice weekly while personnel were at Palmer Station between the months of November and March. One-half of the catch was size-fractionated with nested sieves into the following five size classes for biomass analysis: 0.2−0.5, 0.5−1, 1−2, 2−5, and >5 mm. Individual size fractions were concentrated on preweighed 200 μm mesh filters and frozen at −20°C until analysis. Samples were thawed, weighed to determine wet biomass, dried at 60°C for at least 24 h, and weighed again to determine dry biomass. Zooplankton density varies across size groups, seasonally, among years, and between sampling stations. Units of biomass density are milligrams dry weight per cubic meter.
Field-Collected Spectral Reflectance of Dominant Vegetation at the Sevilleta National Wildlife Refuge
This dataset includes field-collected spectral reflectance of dominant vegetation species in grassland and shrubland at the Sevilleta National Wildlife Refuge collected monthly May – September 2019. A spectroradiometer was used to collect the percent spectral reflectance of electromagnetic radiation (range 400-2500nm) of a sample of dominant vegetation species ("spectra"), yielding a spectral curve for each species. At least ten individuals per species were sampled. These data form a spectral library which was used to calibrate a multiple-endmember spectral mixture analysis (MESMA) of satellite imagery of the Sevilleta NWR, as part of an ongoing collaboration between the LTER and the Center for the Advancement of Spatial Informatics Research and Education (ASPIRE). Ultimately, we aim to produce fractional images of green vegetation, non-photosynthetic vegetation, bare soil, and shade to form a synoptic thirty-year record of vegetation dynamics at the Refuge. The spectral library can be referenced by future researchers using remote sensing methods to examine vegetation dynamics at the Sevilleta NWR.
Size-resolved cloud condensation nuclei data collected during the CalWater 2015 field campaign
<p>This repository contains raw and processed data for the size-resolved cloud condensation nuclei instrument deployed during the Calwater-2015 field campaign. It also contains the averaged cluster data presented in the paper "Classification of aerosol population type and cloud condensation nuclei properties in a coastal California littoral environment using an unsupervised cluster model" by Atwood et al. (2019). Details about the datafiles are provided in README.md file in markdown format.</p>
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