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6,498 results for “physics”
Soil Physical Data from the Shark River Slough, Everglades National Park (FCE), from November 2000 to January 2007
Soil pH, Eh and temperature readings are taken at SRS1b, SRS1c, SRS1d, SRS2 and SRS3. These measurements are taken only when the marsh is wet. Measurements are taken using an Orion model 250A meter, and the probes attached to the meter are the Orion Thermo pH probe and the Orion Eh probe. All readings are recorded in field notebooks, and then transferred into Microsoft Excel. The Eh reading is taken when the Eh probe is attached to the meter and the word "Ready" appears on the meter screen. The pH and temperature reading are taken when the pH probe is attached to the meter and the word "Ready" appears on the meter screen.
Soil Physical Data from the Taylor Slough, just outside Everglades National Park (FCE), from October 1998 to October 2006
Soil pH, Eh and temperature readings are taken at TS/Ph4 and TS/Ph5. These measurements are taken only when the marsh is wet. Measurements are taken using an Orion model 250A meter, and the probes attached to the meter are the Orion Thermo pH probe and the Orion Eh probe. All readings are recorded in field notebooks, and then transferred into Microsoft Excel. The Eh reading is taken when the Eh probe is attached to the meter and the word "Ready" appears on the meter screen. The pH and temperature reading are taken when the pH probe is attached to the meter and the word "Ready" appears on the meter screen.
Soil Physical Data from the Taylor Slough, within Everglades National Park (FCE), from September 1999 to November 2006
Soil pH, Eh and temperature readings are taken at TS/Ph1b,TS/Ph2,TS/Ph3 and TS/Ph6b. These measurements are taken only when the marsh is wet. Measurements are taken using an Orion model 250A meter, and the probes attached to the meter are the Orion Thermo pH probe and the Orion Eh probe. All readings are recorded in field notebooks, and then transferred into Microsoft Excel. The Eh reading is taken when the Eh probe is attached to the meter and the word "Ready" appears on the meter screen. The pH and temperature reading are taken when the pH probe is attached to the meter and the word "Ready" appears on the meter screen.
Physical soil characteristics, microbial community composition, extracellular enzymatic activity, biologically based phosphorus (BBP) pools, and available phosphorus from two soil depths, four microhabitats, and four landforms at the Jornada Experimental Range, 2021.
This dataset contains physical soil characteristics, PLFA based microbial community composition, extracellular enzymatic activity, nitrate and ammonium activity, and phosphorus availability in various phosphorus pools (Biologically Based Phosphorus, potassium sulfate, Olsen-P). Soils were collected from two depths (0-2cm, 2-30 cm), four microhabitats (grass, shrub, biocrust, interspace), and four landforms (alluvial flat, alluvial fan remnant, erosional scarplet, fan piedmont – see coordinates) within the Jornada Experimental Range in July 2021 to answer questions about how these variables change across these spatial scales in drylands. This project was a collaboration between researchers at New Mexico State University and The University of Texas at El Paso as part of the Drylands Critical Zone Thematic Cluster within the Critical Zone Network. This dataset is complete.
Cascade Project at North Temperate Lakes LTER Core Data Physical and Chemical Limnology 1984 - 2016
Physical and chemical variables are measured at one central station near the deepest point of each lake. In most cases these measurements are made in the morning (0800 to 0900). Vertical profiles are taken at varied depth intervals. Chemical measurements are sometimes made in a pooled mixed layer sample (PML); sometimes in the epilimnion, metalimnion, and hypolimnion; and sometimes in vertical profiles. In the latter case, depths for sampling usually correspond to the surface plus depths of 50percent, 25percent, 10percent, 5percent and 1percent of surface irradiance.
GRiMeDB: a comprehensive global database of methane concentrations and fluxes in fluvial ecosystems with supporting physical and chemical information
The Global River Methane Database (GriMeDB) is a compilation of measurements of CH4 concentrations and fluxes for flowing water environments derived from publications, reports, data repositories, and other outlets between 1973 and 2021. Assembly of GRiMeDB was motivated by the goal of having a centralized, standardized resource to facilitate further studies of CH4 pattern and process in flowing water systems, upscaling efforts, and identification of tendencies in when, where, and how CH4 has been sampled in streams and rivers across the world. Thus, CH4 data are supported by concurrent observations (as available) of aquatic CO2, N2O, temperature, conductivity, pH, dissolved oxygen, nitrogen, phosphorus, organic carbon, and discharge, along with site data (latitude, longitude, elevation, and [as available]: stream order, elevation, channel slope, catchment size, and codes for distinct or disturbed channel types). GRiMeDB includes over 24,000 records of CH4 concentration and greater than 8,000 flux measurements from over 5,000 unique sites, most of which are resolved to the daily time scale.
Damage assessment of a physical beam reinforced with masses - dataset
<p>The dataset beam-signal contains the spectrum vibration signals in the frequency domain measured from a beam reinforced with masses under healthy and faulty conditions. This data is for a commonly used system in various industrial applications. The data can be used for online condition process monitoring to detect and diagnose any anomaly or faulty condition in the system. Hence, the datasets provide the geometric and experimental measurements performed on the beam reinforced with masses for various mass losses considered structural damage. The collected data included the following datasets:</p> <ul> <li>Dataset Mass-position contains 70 sampling positions for the six masses attached to the beam. (<a href="../api/records/8081690/draft/files/Mass%20position.xlsx/content">Mass position</a>)</li> <li>Dataset DI contains 280 damage indexes calculated using the FRAC method. (<a href="../api/records/8081690/draft/files/DI_FRAC_Exp-estimation.xlsx/content">DI_FRAC_Exp-estimation</a>)</li> <li>Dataset beam-signal includes 280 inertances responses magnitudes and respective phases considering 70 samples of healthy and 210 sampled of damaged conditions ( <a href="../api/records/8081690/draft/files/Dataset%20Beam-signal_Healthy.zip/content">Dataset Beam-signal_Healthy, </a><a href="../api/records/8081690/draft/files/Dateset%20Beam-signal_Damaged-2.96.zip/content">Dateset Beam-signal_Damaged-2.96, </a></li> </ul> <p><a href="../api/records/8081690/draft/files/Dataset%20Beam-signal_Damaged-5.92.zip/content"> Dataset Beam-signal_Damaged-5.92, </a><a href="../api/records/8081690/draft/files/Dataset%20Beam-signal_Damaged-8.87.zip/content">Dataset Beam-signal_Damaged-8.87) .</a></p> <p>The dataset beam-signal can be used to develop structural health monitoring techniques for detecting damage and anomalies in the structure. The dataset's Mass-position and DIs can impose parametric uncertainty in the experiment. Stochastic and damage identification metrics can be used for further insights on new monitoring and control techniques. Since the tests include paramedic uncertainty, they can also be employed in uncertainty quantification, stochastic modelling and supervised and unsupervised machine learning techniques. </p> <p>Therefore, the datasets are intended to benefit the scientific community investigating the dynamics of structures and readers interested in experimental practices applied to systems and modelling. These datasets can be used for numerical model validation, identification techniques, uncertainty quantification, machine learning, and structural integrity monitoring algorithms based on experimental measurement samples on the beam reinforced with mass.</p> <p>A detailed description of the experiment can be found in </p> <p>[1] Sousa, A.A.S.R., da Silva Coelho, J., Machado, M.R. et al. Multiclass Supervised Machine Learning Algorithms Applied to Damage and Assessment Using Beam Dynamic Response. J. Vib. Eng. Technol. (2023). https://doi.org/10.1007/s42417-023-01072-7</p> <p>[2] Monitoramento da Integridade Estrutural de Vigas utilizando Técnicas de Aprendizado de Máquina, 2023. Mestrado em Integridade de Materiais da Engenharia - Universidade de Brasília (In Portuguese)</p> <p>[3] Amanda A.S.R. de Sousa, Marcela R. Machado, Experimental vibration dataset collected of a beam reinforced with masses under different health conditions, Data in Brief, 2024, 110043, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2024.110043.</p>
Greenhouse gas partial pressure (CO2, CH4, N2O) and environmental variables (physical, chemical, and biological) measured in urban ponds of Barcelona during summer and winter (2023-2024)
This dataset provides information on the partial pressure of greenhouse gases (CO₂, CH₄, and N₂O) measured in 41 artificial urban ponds—28 naturalized and 13 non-naturalized—using the headspace technique. Additionally, GPS coordinates, as well as physical, chemical, and biological variables for each pond, are included. Data were collected during the summer and winter seasons, during daytime. Furthermore, a subset of 16 ponds (8 naturalized and 8 non-naturalized) was also sampled at night in both seasons. All samples were taken from the water surface.
Physical and chemical data for various lakes near Toolik Research Station, Arctic LTER. Summer 1975 to 1989.
Decadal file describing the physical lake parameters recorded at various lakes near Toolik Research Station during summers from 1975 to 1989. Depth profiles at the sites of physical measures were collected in situ. Values measured included temperature, conductivity, pH, dissolved oxygen, Chlorophyll A, Secchi disk depth and PAR. Note that some sample depths also have additional parameters measured and available in separate files for water chemistry and primary production.
Physical and chemical data for various lakes near Toolik Research Station, Arctic LTER. Summer 2010 to 2021
Decadal file describing the physical/chemical values recorded at various lakes near Toolik Research Station. Sample site descriptors include site, date, time, depth. Depth profiles of physical measures collected in situ with Hydrolab Datasonde in the field include temperature, conductivity, pH, dissolved oxygen in both percent saturation and mg/l, SCUFA chlorophyll-a values in both volts and µg/l, and PAR.
Lake Wingra Exclosure Experiment at North Temperate Lakes LTER: Physical Limnology 2005 - 2008
Starting in late summer 2005, Wisconsin Dept of Natural Resources (WDNR), Dane County, Friends of Lake Wingra (FOLW), and NTL-LTER initiated a 3-year experiment in Lake Wingra to test the response of the native macrophyte community to clearer water produced from a major carp reduction program. This demonstration-scale experiment includes the construction of a 1.0-hectare rectangular carp exclosure with its solid vinyl walls extending from the lake shoreline to a water depth of 2.9 meters. NTL-LTER conducts the routine limnological monitoring of the lake and exclosure and is leading the science evaluation of potential lake restoration activities. The exclosure experiment was terminated in the fall of 2008. The exclosure was removed from Lake Wingra at that time. Sampling is done both within the exclosure and at a control site located nearby in the littoral zone. The sample location within the exclosure is equidistant from the side walls and approximately 75 meters from the shore in a water depth of approximately 2.5 meters. The control site sample location is approximately 75 meters west of the exclosure sample site at the same approximate distance from shore and water depth. Samples are taken at the same time and on the same schedule as the NTL-LTER limnological sampling on Lake Wingra, e.g., biweekly spring through summer, every 4 weeks in the fall, and once during the winter depending on ice conditions. Parameters measured within the exclosure and at the control site include water temperature, dissolved oxygen, secchi depth and chlorophyll-a. Additional parameters measured only within the exclosure include total Kjeldahl nitrogen, nitrate + nitrite nitrogen, ammonia nitrogen, total phosphorus, dissolved reactive phosphorus and dissolved reactive silica. Parameters characterizing the physical limnology are measured within the exclosure and at a nearby control site in the littoral zone at 1-m depth intervals. Measured parameters in the data set include water tempera
Little Rock Lake Experiment at North Temperate Lakes LTER: Physical Limnology 1983 - 2000
The Little Rock Acidification Experiment was a joint project involving the USEPA (Duluth Lab), University of Minnesota-Twin Cities, University of Wisconsin-Superior, University of Wisconsin-Madison, and the Wisconsin Department of Natural Resources. Little Rock Lake is a bi-lobed lake in Vilas County, Wisconsin, USA. In 1983 the lake was divided in half by an impermeable curtain and from 1984-1989 the northern basin of the lake was acidified with sulfuric acid in three two-year stages. The target pHs for 1984-5, 1986-7, and 1988-9 were 5.7, 5.2, and 4.7, respectively. Starting in 1990 the lake was allowed to recover naturally with the curtain still in place. Data were collected through 2000. The main objective was to understand the population, community, and ecosystem responses to whole-lake acidification. Funding for this project was provided by the USEPA and NSF. Parameters characterizing the physical limnology of the treatment (north basin, stations 1 and 3) and reference basin (south basin, station 2 and 4) are usually measured at one station in the deepest part of each basin (stations 1 and 2) at 0.5 to 1-m depth intervals depending on the parameter. Parameters measured at depth include water temperature, vertical penetration of photosynthetically active radiation (PAR), dissolved oxygen, chlorophyll and phaeopigments. Additional derived parameters include fraction of surface PAR at each depth and percent oxygen saturation. Auxiliary data include time of day, air temperature, cloud cover, and wind speed and direction and secchi depth. Sampling Frequency: varies - Number of sites: 4
Cascade Project at North Temperate Lakes LTER: Physical and Chemical Limnology 1984 - 2007
Physical and chemical variables are measured at one central station near the deepest point of each lake. In most cases these measurements are made in the morning (0800 to 0900). Vertical profiles are taken at varied depth intervals. Chemical measurements are sometimes made in a pooled mixed layer sample (PML); sometimes in the epilimnion, metalimnion, and hypolimnion; and sometimes in vertical profiles. In the latter case, depths for sampling usually correspond to the surface plus depths of 50percent, 25percent, 10percent, 5percent and 1percent of surface irradiance. The 1991-1995 chemistry data obtained from the Lachat auto-analyzer. Like the process data, there are up to seven samples per sampling date due to Van Dorn collections across a depth interval according to percent irradiance. Voichick and LeBouton (1994) describe the autoanalyzer procedures in detail. Methods for 1984-1990 were described by Carpenter and Kitchell (1993) and methods for 1991-1997 were described by Carpenter et al. (2001). Carpenter, S.R. and J.F. Kitchell (eds.). 1993. The Trophic Cascade in Lakes. Cambridge University Press, Cambridge, England. Carpenter, S.R., J.J. Cole, J.R. Hodgson, J.F. Kitchell, M.L. Pace,D. Bade, K.L. Cottingham, T.E. Essington, J.N. Houser and D.E. Schindler. 2001. Trophic cascades, nutrients and lake productivity: whole-lake experiments. Ecological Monographs 71: 163-186. Number of sites: 8
Vegetation and physical characteristics of Chesapeake Bay retreating Coastal Forests 2022-2024
This data set contains biomass and physical data across an upland forest to marsh transition. These measurements are taken at 5 sites around the Chesapeake and Delaware Bays. Data is collected at up to 5 ectones across the upland to marsh (High Marsh, Transition Zone, Low, Mid and High Forest). These ecotone definitions follow Smith et al. 2019, https://doi.org/10.6073/pasta/4524c22708628eb7f06d174edae89ff2).
Intuitive physics with fMRI
Open the record for dataset details and reuse information.
Physical and biogeochemical oceanography data from Conductivity, Temperature, Depth (CTD) rosette deployments during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This data set contains measurements from various sensors mounted on the Conductivity, Temperature, Depth (CTD) rosette that was deployed in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE). 63 CTD casts were carried out during three legs in the period 21st December 2016 to 16th March 2017, including one test cast and one failed cast, for which no data is available. Data include temperature, salinity, pressure, dissolved oxygen, oxygen saturation, chlorophyll-a concentration, backscatter, and photosynthetically active radiation (PAR) and reported are also the computed variables density, depth, and sound velocity. All data has been quality controlled and post-cruise calibrated, except for the oxygen data. Data is provided at 1 dbar pressure intervals for the up- and down-casts separately and as a merged bottle file when Niskin bottles were closed. This circumpolar data set provides insights into the circumpolar hydrography and biogeochemistry of the Southern Ocean during one austral summer season.</p> <p><strong>Dataset contents</strong></p> <p>For transparency, the raw files and files produced at the intermediate stages of data processing have been provided, in addition to the final processed files.</p> <p><em>Raw data files: </em></p> <ul> <li>ace_ctd_raw_files.zip - includes raw files direct from instrument and XMLCON configuration files</li> </ul> <p><em>Intermediate files: </em></p> <ul> <li>files output at each stage of the SeaBird processing</li> </ul> <p><em>Processed data files: </em></p> <ul> <li>ace_ctd_CTD20200406CURRSGCMR - one final set of files for the complete sensor data;</li> <li>ace_ctd_BOTTLE20200406CURRSGCMR_hy1.csv - a merged bottle file extracted from the sensor data is also provided</li> </ul> <p><em>Metadata:</em></p> <ul> <li>range of files describing the CTD deployments, sensors, water sampling; quality-checking and processing of the files.</li> </ul> <p><strong>Dataset license</strong></p> <p>This physical and biogeochemical oceanography dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p> <p><strong>Change log</strong></p> <p><strong>v1.1</strong><br> Quick summary of issues addressed in CTD DOI Update<br> - Resolved discrepancies between upcast and downcast MLD estimates<br> - ‘Bad’ datapoints in file dACE201601_002_ct1.csv which were not flagged with ‘4’ Bad measurement<br> - CTDFLUOR1, CTDFLUOR1Q, CTDFLUOR2, CTDFLUOR2Q ‘dark’ correction was not applied consistently in first processing and should have been applied to all fluorescence variables<br> - CTDFLUOR1Q, CTDFLUOR2Q quenching correction needed to be recalculated and reapplied after update to MLD and dark correction<br> - Limit the number of decimal places for fluorescence, PAR and backscattering variables according to the instrument sensitivity limits (which is 4 decimal places except for backscattering which is 6)<br> - Changed file names described in data_file_header.txt</p> <p>Additional details on ‘Issues’ and resolutions<br> Mixed layer depth estimates<br> - Large discrepancy in MLD estimates from upcast and downcasts at the same station was due to differences in the ‘reference’ depth i.e. depth other than 10 m was used when there were no datapoints at 10 m.<br> - Note: influence of time between casts was also checked and was not the driver of the discrepancies.<br> - Issue was resolved by setting the MLD for any cast where the reference depth was not 10 m to NaN.</p> <p>Bad data flagging<br> - 22 ‘bad’ datapoints for variables salinity, density, temperature and sound at the end of the downcast file dACE201601_002_ct1 were missed during the visual inspection of the first CTD processing and hence were not flagged as bad.<br> - The bad datapoints are now flagged as ‘4’ bad measurement</p> <p>Fluorescence<br> - In the first processing, dark correction was only applied to the files where quenching correction was needed, and only to the quenched corrected fluorescence variable, but should have been applied to all fluorescence variables in all files. This has been corrected<br> - In the first processing, the upcast MLD was used as the MLD estimate in quenching correction for both the upcast and downcast file. This has been changed so that the MLD from the same cast is used i.e. downcast estimate for the downcast file and upcast estimate for the upcasts file, unless the MLD estimate is NaN (because the reference depth was not 10 m), in that case the either the downcast or upcast estimate is used - whichever exists.</p> <p>Decimal places<br> - The number of decimal places for the fluorescence, PAR and backscattering variables far exceeded the sensitivity limits of the respective sensors - for the fluorescence and backscattering variables this was due to the additional calculations and corrections applied. For the PAR variable it was the output from the Seabird processing.</p> <p>Updated files list<br> The following files have been updated:<br> Folder: ace_bottle_BOTTLE20200406CURRSGCMR (all files within)<br> Folder: ace_ctd_CTD20200406CURRSGCMR (all files within)<br> ace_ctd_mld_CURRSSRGCMR20200405.csv<br> ace_ctd_visual_inspection_v2.csv<br> README.txt<br> data_file_header.txt<br> ace_physical_biogeochemical_oceanography_ctd_change_log.txt (new file)</p> <p><strong>v1.0</strong> - Initial release of physical and biogeochemical oceanography data set.</p>
Physical and biogeochemical oceanography data from underway measurements with an AquaLine Ferrybox during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This data set contains measurements from various sensors installed on the Aqualine Ferrybox system that was connected to the underway seawater supply in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE). Data was collected continuously except for periods when the pump of the underway system was switched off or the system was turned off. Data collection covers all three cruise legs in the period 24th December 2016 to 18th March 2017. Data collected with the CTG MiniPack CTD-F are temperature, salinity, pressure, and turbidity. Data collected by the Aanderaa oxygen optode include dissolved oxygen and oxygen saturation. An SBE 18 sensor measured pH. The CTG UniLux fluorometer measured chlorophyll-a concentration. All data has been quality controlled and post-cruise calibrated. Data is provided at 1-minute intervals along the cruise track. In addition, we provide satellite data (sea-surface temperature, sea-surface height, geostrophic velocity, sea-ice concentration) that was interpolated to the cruise-track and an estimate of frontal positions to supplement this underway data set where data was missing or for additional information. This circumpolar data set provides insights into the circumpolar surface ocean conditions and biogeochemistry of the Southern Ocean during one austral summer season.</p> <p>Note on version 1.0: The first version of this data set only contains temperature, salinity, pressure, and potential density in the post-processed file, since post-processing and quality control for turbidity, chlorophyll-a, dissolved oxygen, oxygen saturation, and pH have not been finalized. These variables will be added to the post-processed data file in a future release.</p> <p><strong>Dataset license</strong></p> <p>This dataset of physical and biogeochemical oceanography underway measurements from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Luke) and Geological Survey of Finland (GTK)
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland </strong></p><p><strong>Creators: </strong>Larmola T, Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M </p><p>The dataset consists of peat properties in a subset of 16 undrained peatland sites (32 peat samples) in Geological Survey of Finland (GTK) national peatland inventory. These sites were sampled between 2002 and 2017 and the subset selected from GTK peat sample archives. These 16 sites represented two pine-<i>Sphagnum-</i> dominated site types (IR, KR) and two treeless sedge fen types (VSN, RhSN) all in 4 replicates and sampled in 2 depths 20-40, 40-60cm). </p><p><strong>Peat analyses</strong> The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S).</p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola T, Anttila J, Alm J Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description </strong></p><p>ID - Site identifier</p><p>site - undrained peatland (UDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 20: 0-20 cm, 40: 20-40cm, 60: 40-60cm.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin - UDP site type. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p><strong>References</strong></p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p>
Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland, Natural Resources Institute Finland
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</strong></p><p><strong>Creators: Larmola T, Anttila J, Alm J </strong></p><p>The dataset consists of peat properties in a subsample of 30 drained peatland forests in Finland selected from the permanent sample plots of the 8th National Forest Inventory (systematic sample of plots on drained peatland forests, e.g., Hotanen et al. 2006). The subsample included equally different site types of forestry-drained peatlands of those parts of Finland where drainage for forestry is economically viable (Latitude 60-66 ºN, annual temperature sum > 750 dd). </p><p><strong>The site selection criteria</strong> were average peat layer thickness of over 20 cm, no clear-cut areas, site drained before 1995 and ditching had detectably altered hydrology or vegetation. <strong>Peat analyses</strong> Finnish Forest Research Institute (now Natural Resources Institute Finland) sampled peat cores with a box corer in 2002, samples were analysed for bulk density, archived and remaining samples at depths 20-30, 30-40 cm (total of 58) were analysed in 2021. The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. </p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola, T. Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Version 1) [Dataset]. Zenodo. doi.org/<strong>10.5281/zenodo.10068486</strong></p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description</strong></p><p>ID - Site identifier</p><p>site - Forestry-drained peatland (FDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 30: 20-30 cm, 40: 30-40cm, avg: average of both depths.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin – Origin of the FDP site type at undrained state. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p>n - Number of samples. 2 for averages from both depths, 1 for all other rows.</p><p> </p><p><strong>References</strong></p><p>Hotanen JP, Maltamo M, Reinikainen A (2006) Canopy stratification in peatland forests in Finland. Silva Fennica 40:53–82.</p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p><p> </p>
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>
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