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49 results for “Total nitrogen”
Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) from river, lagoon, and open ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods and analyzed for dissolved organic carbon and total dissolved nitrogen content.
Total dissolved nitrogen (TDN), dissolved organic carbon (DOC), radiocarbon (14C-DOC), and stable carbon (13C-DOC) of surface waters from the Canning River watershed, 2019 and 2021
Sites along the Canning River mainstem and contributing streams near the Kavik River Camp, Alaska, were visited to track changes in stream and river total dissolved nitrogen (TDN) concentration, dissolved organic carbon (DOC) concentration, and the stable carbon (13C) and radiocarbon (14C) isotopic composition of DOC across transitions between the Brooks Range, Brooks foothills, and Arctic Coastal Plain. The dataset also includes water samples collected from lakes, springs, groundwater, and streams and rivers outside the Canning River watershed. Water samples were collected in late April and early August 2019 and in late July and early August 2021. Data include measurements of individual samples for TDN (milligrams nitrogen per liter), DOC (milligrams carbon per liter), carbon-13 of DOC (reported as delta-13C, per mil), carbon-14 of DOC (reported as fraction modern), and analytical error in the fraction modern values. Additional water chemistry data for these samples can be found in Koch et al. (2024). References: Koch, J. C., Connolly, C. T., Repasch, M., Best, H. R., Couvillion, C. S., Hunt, A. (2024). [Dataset] Hydrochemistry and age date tracers from springs, streams, and rivers in the Arctic National Wildlife Refuge, 2019-2022, U.S. Geological Survey data release, https://doi.org/10.5066/P95CXJIT.
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 Nitrogen and Total Carbon 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.
Dissolved Organic Carbon (DOC) and Dissolved Total Nitrogen (DTN) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2022
Dissolved organic carbon and dissolved total nitrogen are measured from discrete bottle samples collected during CTD rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) transect cruises (ongoing since 2022). Sampling frequency is approximately seasonal. Sample collection is paired with particulate organic carbon at surface, subsurface chlorophyll max, and sometimes a third depth. Samples are filtered directly from the CTD rosette and acidified in the field, then analyzed using a Shimadzu TOC-LCPH total organic carbon analyzer coupled to a TNM-L analyzer for total nitrogen. Values are reported in micromoles per liter.
Dissolved oxygen, temperature, chlorophyll-a, total phosphorus, total nitrogen, and dissolved organic carbon at multiple depths in 822 lakes from 1921-2022
Rapid changes in climate and land use are having substantial and interacting impacts on lake water quality around the world. Here, we synthesized time-series data for dissolved oxygen, temperature, chlorophyll-a, total phosphorus, total nitrogen, and dissolved organic carbon at multiple depths in 822 lakes to facilitate analyses of these changes. The dataset extends from 1921–2022, with a median data duration of 29 years (range 5-102) and a median of 5 unique sampling dates per year at each lake. Lakes in the dataset have a median depth of 12.5 m (range 1.5–480 m), median surface area of 85.4 ha (range: 0.5–237000 ha) and median elevation of 264 m (range: -215–2804). The lakes are located in 18 countries across 5 continents, with latitudes ranging from -42.6 to 68.3. To facilitate interoperability with other large-scale datasets, each lake is linked to a unique hydroLAKES lake ID when possible (n = 683).
Modeled dry deposition flux of total nitrogen in central Arizona, USA (1998)
The role of urban vegetation on NOx-derived dry deposition fluxes was investigated for the arid Phoenix (Arizona, USA) metropolitan area using the Community Multiscale Air Quality Model (CMAQ) (9-13 June 1998). A new land cover classification and updated land cover data were introduced in the model to account for spatial extent and heterogeneity of urban land cover. Adjustments were made in the deposition velocity calculations to consider the adaptation of local plants to the environmental conditions of Central Arizona. According to the simulations 25 % of the NOx derived dry deposition fluxes in the urban area were deposited on vegetation. When urban vegetation was excluded from the simulations NO2 deposition was reduced by 57 % because of the significantly lower deposition velocities of impervious compared to vegetated surfaces; nitric acid deposition was relatively unchanged. Using a diagnostic model with input data from urban air quality monitoring sites, hourly NO and NO2 dry N deposition fluxes were simulated for the entire year 1998 to ~6 kg ha-1 yr-1. Dry deposition declined during the summer months, due to lower pollutant concentrations and temperature-induced closure of the plant stomata during afternoon hours.
Direct sun retrievals of nitrogen dioxide (NO2) total columns from Brewer #067, Rome, Italy (reprocessed with algorithm BNALG2)
<p>Cloud-screened and quality-filtered direct sun retrievals of nitrogen dioxide (NO2) vertical column densities (VCDs) derived from MkIV Brewer #067 measurements in Rome (wavelengths 425.02, 431.40, 437.35, 442.83, 448.08, and 453.20 nm) and processed using the Brewer Nitrogen Dioxide Algoritm BNALG2. Calibration is carried out with Bootstrap Estimation techniques. The values represent averages of 5 samples.</p> <p>In the latest version, days with obviously erroneous data (NO2 VCD > 99.9% percentile) have been removed.</p> <p>A detailed description of the method has been accepted as a research article by the ESSD journal (H. Diémoz et al., Advanced NO2 retrieval technique for the Brewer spectrophotometer applied to the 20-year record in Rome, Italy, Earth Syst. Sci. Data, 2021).</p>
Total organic carbon, total nitrogen, and iron-bound organic carbon in surficial sediment and settling particulate material from Falling Creek and Beaverdam Reservoirs in 2019 and 2021
This dataset includes measurements of sediment properties (total organic carbon, total nitrogen, and iron-bound organic carbon) in surficial sediment and sedimenting material from two reservoirs: Falling Creek and Beaverdam Reservoirs, both located in Vinton, VA, USA. To measure surficial sediment properties, sediment cores were collected at the deepest site in each reservoir using a gravity corer, and the top 1 cm was frozen then lyophilized. Sediment cores were collected approximately once per month in both reservoirs throughout the stratified period (May–November) in 2019 and 2021, though sampling frequency and duration varied by reservoir and year. Sedimenting material was sampled using sediment traps suspended approximately 1 m above the sediment in both reservoirs. Iron-bound organic carbon was measured using the citrate-bicarbonate-dithionite method, and we used a CN analyzer (Elementar VarioMax, Ronkonkoma, NY, USA) to determine the amount of OC per unit mass of sediment.
Total nitrogen and total phosphorus concentrations from surface water samples collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2011-current
Included in this data package are water quality data from the Citizen-Led Environmental Observatory (CLEO), a volunteer water quality monitoring program run by Friends of the Lake (FOTL, friendsofthelake.org) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (data available 2011-current). Trained volunteer monitors collect surface water samples from multiple nearshore sites twice a month from Memorial Day through Labor Day. These samples are analyzed for total nitrogen and total phosphorus concentrations. Water samples are also analyzed for levels of the toxin microcystin. Additionally, CLEO volunteers collect data on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum every 1-3 days during the same period. These additional data are available in EDI packages EDI567 (general water quality) and EDI569 (toxins).
Nitrogen cycling at treeline. III. Total Soil Carbon and Nitrogen Content
We studied spatial and temporal patterns of nitrogen pools and fluxes in soils at treeline and forested sites within three mountain ranges across a 785 km transect in Alaska during 2001- 2002. We measured pools of soil mineral (ammonium and nitrate) and organic (amino acid and microbial biomass) nitrogen, in situ rates of net mineralization, net nitrification, net amino acid production, and decomposition, as well as soil carbon turnover in a laboratory incubation experiment. A complete characterization of the study can be found in Loomis et al. (2006).
Total dissolved organic carbon and nitrogen measurements at selected depths in the water column from CCE LTER process cruises in the California Current System, 2006 - 2021 (ongoing).
Water column bottle samples at multiple depths are taken during CCE Process cruises (since 2006, ongoing) at various CTD stations, and measurements of total organic carbon (TOC) and total nitrogen (TN) are performed onshore in the lab. TOC includes both dissolved and particulate organic carbon (DOC and POC, respectively). TN includes particulate and dissolved organic nitrogen as well as dissolved inorganic nitrogen species. In open ocean waters, POC is subtracted from TOC, and likely provides an accurate estimate of DOC because particles are typically small and homogeneously distributed in the sample. In coastal waters, and at stations where relatively high chlorophyll concentrations are present, the TOC measurement is not easily converted to DOC by subtracting POC values. Experience has shown that particles in these regions are large and inhomogeneously distributed. Therefore, samples collected in the CCE are reported as TOC and TN, expressed as micromoles of carbon (nitrogen) per liter of sea water.
Effects of microarthropod exclusion and water amendments on fluffgrass rhizosphere total soil nitrogen at the Jornada Basin, 1986-1987
This data package contains data on soil nitrogen content in the rhizosphere of fluff grass (Dasyochloa pulchella) plants collected from 1986-1987 at the Jornada Basin LTER site. The purpose of this study was to test how watering, and changing densities of soil microarthropods and nematodes, results in changes in fluff grass rhizosphere total nitrogen. Twenty 6 x 6 m plots were established with a 3 m buffer between plots. Five plots were randomly assigned to one of four treatments: 1) Chlordane to exclude microarthropods, 2) Chlordane and water, 3) Water, and 4) Control. Every three months from June 1986 to January 1987, randomly selected fluff grass plants were harvested from each plot and rhizosphere soil samples were collected for total nitrogen digestion analysis. This data set consists of sampling date, treatment, subsample number, and total nitrogen (mg/kg). This study was completed in January 1987.
Data for: Nitrogen deposition in forests: Statistical modeling of total deposition from throughfall loads
<p><strong>Introduction:</strong> Nitrogen (N) gradient studies in some cases use N deposition in throughfall as measure of N deposition to forests. For evaluating critical loads of N, however, information on total N deposition is required, i.e., the sum of estimates of dry, wet and occult deposition.</p> <p><strong>Methods: </strong>The present paper collects a number of studies in Europe where throughfall and total N deposition were compared in different forest types. From this dataset a function was derived which allows to estimate total N deposition from throughfall N deposition.</p> <p><strong>Results: </strong>At low throughfall N deposition values, the proportion of canopy uptake is high and thus the underestimation of total deposition by throughfall N needs to be corrected. At throughfall N deposition values >20 kg N ha<sup>-1</sup> yr<sup>-1</sup> canopy uptake is getting less important.</p> <p><strong>Conclusions: </strong>This work shows that throughfall clearly underestimates total deposition of nitrogen. With the present data set covering large parts of Europe it is possible to derive a critical load estimate from gradient studies using throughfall data.</p>
Data for: Nitrogen deposition in forests: Statistical modeling of total deposition from throughfall loads
Open the record for dataset details and reuse information.
Surface pelagic total nitrogen concentrations in Lake Sunapee, USA 2009 to 2012
Total nitrogen concentrations were sampled from 2009 to 2012 in Lake Sunapee (Sunapee, NH, USA). The dataset consists of total nitrogen with two to three lab replicates measured at two pelagic sites in Lake Sunapee: 1) Station 210 (S210) of the New Hampshire Department of Environmental Services Volunteer Lake Assessment Program, and 2) the LSPA-GLEON buoy (Buoy) in the main basin of the lake. The samples were collected at the surface, five to six times per year, ranging from June to September each year. The mean total nitrogen concentration with its standard deviation from lab replicates is presented.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest; concentrations of foliar metabolites: polyamines, amino acids, chlorophyll, carotenoids, soluble proteins, soluble elements, sugars, and total nitrogen and carbon in red maple (Acer rubrum) trees.
Foliage was collected in 2015 and 2017 from red maple trees at the Climate Change Across Seasons Experiment (CCASE) as part of the Hubbard Brook Ecosystem Study (HBES). Analyses of foliar metabolites include polyamines, amino acids, chlorophylls, carotenoids, soluble proteins, soluble inorganic elements, sugars, and total nitrogen and carbon. There are six (11 x 14m) plots in total in this study; two control (plots 1 and 2), two warmed 5 degrees (°) Celsius (C) above ambient throughout the growing season (plots 3 and 4), and two warmed 5 °C in the growing season, with snow removal during the winter to induce soil freezing and then warmed with buried heating cables to create a subsequent thaw (plots 5 and 6). Each soil freeze/thaw cycle includes 72 hours of soil freezing followed by 72 hours of thaw. Four kilometers (km) of heating cable are buried in the soil to warm these four plots. Together, these treatments led to warmer growing season soil temperatures and an increased frequency of soil freeze-thaw cycles (FTCs) in winter. Our goal was to determine how these changes in soil temperature affect foliar nitrogen (N) and carbon metabolism of red maple trees. These data were gathered as a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Soil Total Carbon and Total Nitrogen on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2001)
Dataset Abstract Soil carbon and nitrogen are presented as % elemental carbon and nitrogen (g C or N / 100 g soil) for the sampling depth of the specific sampling date unless indicated otherwise. Samples were taken with either a 2.5 cm diameter soil corer (sampling by soil depth) or a 10 cm diameter Giddings probe (sampling by soil profile). See Baseline Soil Sampling protocol for general sampling information. For specific sampling details for a particular date, see Soil Sampling Field Log. Soil samples are sieved to 4mm and composited by plot. Soil % elemental carbon and nitrogen values are determined by sample combustion and subsequent TCD gas chromatography, using a Carlo Erba automated CHN analyzer as described in the sampling protocol. original data source http://lter.kbs.msu.edu/datasets/27
McMurdo Dry Valleys Stream Chemistry - Total Nitrogen
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic aqueous geochemical sampling program has been undertaken. A series of terrestrial water samples have been collected and analyzed for dissolved total nitrogen levels. This dataset shows concentrations of total nitrogen (in filtered samples) found in various streams of the McMurdo Dry Valleys.
iSDAsoil: soil total organic Nitrogen for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths
<p>iSDAsoil dataset soil total organic Nitrogen (N) log-transformed predicted at 30 m resolution for 0–20 and 20–50 cm depth intervals. Data has been projected in WGS84 coordinate system and compiled as <a href="https://gdal.org/drivers/raster/cog.html">COG</a>. Predictions have been generated using multi-scale Ensemble Machine Learning with 250 m (MODIS, PROBA-V, climatic variables and similar) and 30 m (DTM derivatives, Landsat, Sentinel-2 and similar) resolution covariates. For model training we use a pan-African compilations of soil samples and profiles (<a href="https://www.isda-africa.com/national-soil-services/">iSDA points</a>, <a href="https://www.isric.org/projects/africa-soil-profiles-database-afsp">AfSPDB</a>, and other national and regional soil datasets). Cite as:</p> <p>Hengl, T., Miller, M.A.E., Križan, J. <em>et al.</em> African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. <em>Sci Rep</em> <strong>11, </strong>6130 (2021). <a href="https://doi.org/10.1038/s41598-021-85639-y">https://doi.org/10.1038/s41598-021-85639-y</a></p> <p>To open the maps in QGIS and/or directly compute with them, please use the <a href="https://gitlab.com/openlandmap/africa-soil-and-agronomy-data-cube"><strong>Cloud-Optimized GeoTIFF version</strong></a>.</p> <p>Layer description:</p> <ul> <li>sol_log.n_tot_mehlich3_m_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil total N mean value,</li> <li>sol_log.n_tot_mehlich3_md_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil total N model (prediction) errors,</li> </ul> <p>Model errors were derived using bootstrapping: md is derived as standard deviation of individual learners from 5-fold cross-validation (using spatial blocking). The model 5-fold cross-validation (<a href="https://mlr.mlr-org.com/reference/makeStackedLearner.html">mlr::makeStackedLearner</a>) for this variable indicates:</p> <pre><code>Variable: log.n_tot_ncs R-square: 0.732 Fitted values sd: 0.326 RMSE: 0.197 Random forest model: Call: stats::lm(formula = f, data = d) Residuals: Min 1Q Median 3Q Max -1.87298 -0.09584 -0.00985 0.07613 3.14728 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.267429 0.493235 0.542 0.588 regr.ranger 1.128208 0.005766 195.669 < 2e-16 *** regr.xgboost -0.048780 0.006108 -7.987 1.4e-15 *** regr.cubist 0.143954 0.004424 32.539 < 2e-16 *** regr.nnet -0.482261 0.797938 -0.604 0.546 regr.cvglmnet -0.170889 0.004955 -34.489 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.1972 on 99249 degrees of freedom Multiple R-squared: 0.7319, Adjusted R-squared: 0.7319 F-statistic: 5.419e+04 on 5 and 99249 DF, p-value: < 2.2e-16</code></pre> <p>To back-transform values (y) to g/kg use the following formula:</p> <pre><code>g/kg = expm1( y / 100 )</code></pre> <p>To submit an issue or request support please visit <a href="https://isda-africa.com/isdasoil"><strong>https://isda-africa.com/isdasoil</strong></a></p>
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