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92 results for “nitrogen isotopes”
Carbon and nitrogen content and stable isotope compositions from biota samples from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Stable isotopic composition can be used to differentiate between predominantly marine and terrestrial food sources in nearshore marine food webs. The Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program employs spatial and temporal sampling regimes to track shifts in diet, both seasonally (ice cover, ice break-up, and open water), and spatially among lagoons along the Alaskan Beaufort Sea coast. Ice coring, net tows, ponar grabs, and trawls are employed to collect organisms associated with the sea-ice interface, the water column, and the benthos respectively. Tissues are analyzed for stable isotopic composition as well as organic carbon and nitrogen content.
Carbon and nitrogen content and stable isotope compositions from particulate organic matter samples from lagoon, river, 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 particulate organic carbon (POC) and particulate organic nitrogen (PON) content and stable isotopic composition.
Carbon and nitrogen content and stable isotope composition from sediment organic matter from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple sediment samples from lagoons along the 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. Sediment 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 carbon and nitrogen content and stable isotopic composition.
Primary producer biomarker profiles of bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA) and their fatty acid (FA) collected from the Beaufort Sea coastal lagoons,2021-2024
Within Stefansson Sound in Prudhoe Bay, AK various organic matter sources were collected to determine multiple biomarker baseline profiles (i.e., bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA), fatty acids (FA)). Some organic matter sources were collected from Elson lagoon in Utqiaġvik, AK and Kaktovik and Jago lagoons in Kaktovik, AK to supplement low sample sizes in some organic matter source groups. Kelp, red algae, terrestrial plants, phytoplankton, and ice algae were collected in 2024 with some supplement samples collected in 2021 - 2023. Stable isotope values of δ13C and δ15N are reported as “del_13c” and “del_15n”, respectively. Individual fatty acids are reported as the percent relative to total fatty acids for 23 fatty acids: C11:0, C12:0, C14:0, C15:1, C15:0, C16:0, C16:1n7, C17:0, C17:1, C18:0, C18:1n9 trans, C18:2n6 cis, C18:1n7, C18:3n3, C20:0, C18:3n6, C20:4n6, C21:0, C22:0, C22:1n9, C23:0, C24:0, C22:6n3. Stable isotope values of δ13C are reported in the following essential amino acids: Valine (Val), Leucine (Leu), iLeu (isoleucine), Methionine (Met), Phenylalanine (Phe). Additionally, we used ice algal diatoms collected in the Arctic (landfast ice near Utqiaġvik, Alaska) and cultured in a laboratory setting at the University of Alaska Fairbanks to compare the CSIA-EAA fingerprints of field (composites) ice algal samples and isolate diatoms samples.
Soil and foliar carbon and nitrogen content and stable isotope ratios from rainfall manipulation experiments at the Jornada Basin LTER, 2011-2020
As rainfall extremes are expected to increase in novel magnitude and frequency, especially in dryland regions, we asked how prolonged and directional shifts to water availability may affect ecosystem carbon and nitrogen dynamics. This data set includes foliar and soil carbon and nitrogen stable isotope and concentration data collected from multiple long-term rainfall manipulation experiments at the Jornada Basin LTER. Datasets also include rainfall data adjusted to rainfall manipulation intensities. Collection dates range from 5 to 14 years since the onset of experimental treatments. The primary plant species targeted for this study were the dominant grass, Bouteloua eriopoda, and the dominant shrub, Prosopis glandulosa.
Particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition (delta 13C and delta 15N) sampled during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3. Water samples were collected from the underway seawater supply every 3 hours, filtered onto pre-combusted glass fibre filters, acidified to remove inorganic compounds and analysed for both elements on the same filter using an elemental analyser. These samples provide an estimate of the organic carbon and organic nitrogen concentration and carbon and nitrogen stable isotope composition of living and detrital particles > 0.7 micrometres in size.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metatdata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_poc_pon_blanks_20200512CURRSGCMR.csv, data file, comma-separated values</li> <li>ace_uw_poc_pon_20200512CURRSGCMR.csv, data file, comma-separated values</li> </ul>
Stable carbon and nitrogen isotope data from Arctic coastscapes associated with coastal invertebrate and fish food webs, 1999-2022
Stable carbon and nitrogen isotope data are commonly used to elucidate food web structure and partition food source importance to consumers. Here, stable isotope data were gathered from across the coastal Arctic to assess how differences in coastal type (i.e., coastscape) and longitudinal region differ across the Arctic. Data were collected between 1999-2022.
Mass per tiller, nitrogen concentration, stable isotope ratios for carbon and nitrogen from the 1980-82 Eriophorum vaginatum reciprocal transplant experiment along a latitudinal gradient in interior Alaska collected in July, 2011
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK in the south to Prudhoe Bay, AK in the north. Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual Eriophorum vaginatum tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. The gardens were harvested in 2011. Important variables are garden name, source population, mass per tiller, nitrogen concentration, and stable isotope ratios for Carbon and Nitrogen.
Carbon and nitrogen isotopes and concentrations in terrestrial plants from a six-year (2006-2012) fertilization experiment at the Arctic LTER, Toolik Field Station, Alaska.
The data set describes stable carbon and nitrogen isotopes and carbon and nitrogen concentrations from an August 2012 pluck of a fertilization experiment begun in 2006. Fertilization was with nitrogen (N) and phosphorus (P). Fertilization levels included control, F2, F5, and F10, with F2 corresponding to yearly additions of 2 g/m2 N and 1 g/m2 P, F5 corresponding to yearly additions of 5 g/m2 N and 2.5 g/m2 P, and F10 corresponding to yearly additions of 10 g/m2 N and 5 g/m2 P. After harvest, plants were separated by species and then by tissue. Tissues were then dried, ground and analyzed for stable isotopes and concentrations at the University of New Hampshire stable isotope laboratory.
SIA-BRA: The carbon and nitrogen stable isotope ratios of animals of Brazilian biomes and coastal marine areas
<p>SIA-BRA is a compilation of C and N stable isotope ratios of terrestrial and aquatic animals sampled in Brazilian biomes and coastal-marine areas.</p> <p>Version 1.0 contains isotopic data of c. 21,804 non-captive wildlife specimens, excluding livestock production or laboratory<br> experiments. They were 13,881 vertebrates and 7,923 invertebrates. There are 11 phyla, with a clear dominance of Chordata (64%) and Arthropoda (29%), 36 classes, 154 orders, 473 families, 894 genera and 1,157 species.</p> <p>They were divided into the following habitats: terrestrial (30% of the total), freshwater (27%), oceanic (40%)<br> and estuarine (4%) (see <a href="https://doi.org/10.1111/geb.13449">https://doi.org/10.1111/geb.13449</a>)</p> <p>Software format: Data are supplied as delimited text files (.csv).</p>
Nitrogen and carbon concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) in European moss samples, 2005-2006
This dataset contains nitrogen (N) and carbon (C) concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) measured in moss samples collected across Europe within the framework of the ICP Vegetation programme (International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops, UNECE LRTAP Convention). Moss surveys are conducted every five years and the data presented here correspond specifically to the first sampling campaign, carried out in 2005/2006. During the 2005/2006 European moss survey, approximately 3,000 moss samples were collected at non-urban and semi-natural sites across 16 European countries following a standardized biomonitoring protocol. The dataset used in this study comprises a subset of 1,022 moss samples (approximately 35 % of the total survey), provided by 12 European countries, which were selected for the determination of nitrogen and carbon concentrations and their corresponding stable isotope signatures (δ¹⁵N and δ¹³C). Moss samples collected by each participating country were sent to the Integrated Environmental Quality Laboratory (LICA), Institute for Biodiversity and Environment (BIOMA - University of Navarra), where all chemical and isotopic analyses were subsequently performed under uniform analytical conditions. In addition, this dataset incorporates moss data from Sweden, Croatia and Macedonia for the same sampling year, which were not included in the official ICP Vegetation 2005/2006 dataset. The European moss biomonitoring network was established to provide a complementary, high spatial resolution and time-integrated measure of atmospheric deposition of nitrogen and other pollutants within terrestrial ecosystems. The approach is based on the ability of ectohydric mosses to accumulate nutrients and trace elements directly from wet and dry atmospheric deposition, enabling dense spatial sampling across large geographical areas. This biomonitoring framework supports the assessment of spatial patterns of atmos
Data from nitrogen isotopic analyses used to calculate biological nitrogen fixation (BNF) rates and field measurements from lichen, bryophyte, litter, and soil samples in MAT2006 plots, Arctic LTER, Toolik Field Station, Alaska, summers 2022-2023.
This dataset contains nitrogen (N) fixation and isotope data from experimental samples collected at Toolik Lake, Alaska during the 2022 and 2023 growing seasons. Sampling was conducted across multiple block treatments to capture spatial variability and included four substrate types: lichen, moss, litter, and soil. Within each plot, substrates were collected systematically along transects to ensure representative sampling, with lichen samples collected opportunistically due to lower abundance. Samples were incubated in the field under ambient conditions using 15N₂ to measure biological nitrogen fixation (BNF). In 2023, a short-term wetting experiment was conducted to assess the influence of moisture on BNF rates, with subsamples exposed to controlled additions of water. Across both years, data include isotope ratios, incubation conditions, moisture, fresh and dry biomass, and treatment assignments. The dataset provides information on BNF across substrate types, moisture regimes, and fertilization treatments in Arctic tundra. These data support investigation of N cycling processes, the influence of moisture and fertilization on fixation rates, and variability across vegetation types. The dataset is complete for the two field seasons (2022 and 2023) and includes sample- and block-level metadata necessary for reuse in ecological and biogeochemical research.
PIE LTER, stable isotope chemistry (carbon, nitrogen and sulfur) for food web analysis of functional groups in the Plum Island Sound Estuary, Massachusetts.
Stable isotopes of primary producers will be compared to stable isotopes of functional groups of organisms at primarily three sites within the estuary that have different dominant sources of organic matter. The three sites are: Lower (IBYC, SO-3, mouth of Plum Island Sound, 2-3 km upstream of the mouth of the estuary), Middle (OTL, PR-10.1, upper Sound, lower Parker, 8-11 km upstream of the mouth of the estuary) and Upper (P2, PR-21.9, upper Parker, above Middle Rd Bridge (22 km upstream of the mouth of the estuary). The Lower site is dominated by marine phytoplankton, the Middle site is dominated by a mixture of salt marsh and phytoplankton and the Upper site is dominated by oligohaline phytoplankton and fresh marsh. Ten functional groups will be sampled at each site (Surface sediment, benthic diatoms, Nereis, mummichog, ribbed mussels, POM, blue mussels, pelagic copepods (Acartia), silversides and soft shell clams (Mya). Marsh, benthic algae and phytoplankton inputs or benthic vs. pelagic pathways will be evident in the isotopic signals of these functional groups. Samples will be collected between the middle and end of August to reflect a growing season using recently produced OM. Samples of 15 – 20 individuals will be pooled for analysis. Some silverside samplings will have 3 different pooled samples for determination of variance. Often times the same species are not collected at each site due to habitat differences (salinity/discharge) so additional species are collected to try to accomplish task of getting functional groups collected.
Stable isotope content (carbon, nitrogen) for epibenthic suspension feeders and Macrocyctis pyrifera at in the Santa Barbara Channel, 2010-2011
This dataset includes measurments of stable carbon, nitrogen isotopes in tissues of eight epibenthic suspension feeders and Macrocystis pyrifera (giant kelp) at three reefs in the Santa Barbara Channel during 2010 and 2011, as part of a study to (a) determine the contributions of phytoplankton and giant kelp detritus to the pool of suspended reef particulate organic matter (POM), and usage by benthic susupension feeders and (b) whether POM composition varies with distance from kelp forests. Species sampled include Chaceia ovoidea (bivalve), Aglaophenia spp (ostrich plume hydrozoan), Cucumaria piperata (echinoderm), Muricea californica (cnidarian), Phragmatopoma californica (tube worm), Parapholas californica (bivalve), Pachythyone rubra (echinoderm), and Styela montereyensis (tunicate). Samples were collected at three core SBC LTER research reefs: Arroyo Quemado, Arroyo Burro, and Mohawk. Potentially important food sources to benthic suspension-feeders on shallow subtidal reefs include phytoplankton-dominated seston, kelp-derived detritus, and for locations adjacent to sources of freshwater runoff, terrestrially-derived material. Our data will be input to mixing models to estimate the contribution of each source to the reef food web.
Isotopes and content of carbon, nitrogen, and sulfur of eelgrass (Zostera marina) from West Falmouth Harbor from 2005 through 2019
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000’s. As part of a long-term study into the effects of this nitrogen enrichment, we have been assessing changes in the extent and health of the eelgrass (Zostera marina) community within the harbor. Eelgrass shoots were collected during the summer and run for carbon (C), nitrogen (N), and sulfur (S) content and isotopic composition. Samples were analyzed from 7 stations in the more well-flushed outer harbor (OH), 4 stations in the middle of the harbor (MH), and 6 stations in the inner portion of the harbor in close proximity to a high groundwater nitrate source (Snug Harbor, SH). Carbon data is available from 2011 through 2018, nitrogen data from 2006 through 2018, and sulfur data from 2005 through 2019 with a few samples from 2021. Sulfur results have been published in Haviland et al. 2022 (doi: 10.1002/lno.12025).
Stable isotope (carbon, nitrogen and sulfur) data for primary producers and consumer organisms in the Plum Island Sound Estuary.
Flora and fauna stable isotope study to help characterize organic matter/primary production sources important to the food web of the Plum Island Sound estuary. Sampling occured during 1993 and 1994.
Model output for "Impact of intensifying nitrogen limitation of ocean net primary production is fingerprinted by nitrogen isotopes"
<p><strong>Description.</strong></p> <p>The data included in this repository is output of simulations performed with the NEMO-PISCESv2 global ocean-biogeochemical model. Simulations involved forcing the NEMO-PISCESv2 with global warming associated with historical and future emissions, as well as the historical and future trends in atmospheric nitrogen deposition. Future climate change was according to the Representative Concentration Pathway 8.5 scenario (Dufresne et al., 2013; Riahi et al., 2011), which sees rapid warming during the 21<sup>st</sup> century. Historical and future atmospheric nitrogen deposition fields were created via linear interpolation of fields produced by Hauglustaine et al. (2014) at years 1850, 2000, 2030, 2050 and 2100. To represent the amplification of deposition since 1950 (Galloway 2014), 60 % of the increase between 1850 and 2000 occurred from 1950 onwards.</p> <p>In this study, we quantified the effect anthropogenic climate change and anthropogenic increases in atmospheric nitrogen deposition on the marine nitrogen cycle. The response of the marine nitrogen cycle to these combined stressors is highly uncertain, and we therefore employed this complex model with a strong representation of nitrogen cycling in an attempt to constrain the global behaviour of this important cycle. In addition, through the addition of nitrogen isotopes to the ocean-biogeochemical model, we also explored and described how the isotopes responded to these anthropogenic forcings, and if the isotopes uniquely fingerprinted the response for potential monitoring/detection purposes.</p> <p>Our abstract reads:</p> <p>“The open ocean nitrogen cycle is being altered by increases in anthropogenic atmospheric nitrogen deposition and climate change. How the nitrogen cycle responds will determine long-term trends in net primary production (NPP) in the nitrogen-limited low latitude ocean, but is poorly constrained by uncertainty in how the source-sink balance will evolve. Here we show that intensifying nitrogen limitation of phytoplankton, associated with near-term reductions in NPP, causes detectable declines in nitrogen isotopes (δ<sup>15</sup>N) and constitutes the primary perturbation of the 21<sup>st</sup> century nitrogen cycle. Model experiments show that ~75% of the low latitude twilight zone develops anomalously low δ<sup>15</sup>N by 2060, predominantly due to the effects of climate change that alter ocean circulation, with implications for the nitrogen sources-sink balance. Our results highlight that δ<sup>15</sup>N changes in the low latitude twilight zone may provide a useful constraint on emerging changes to nitrogen limitation and NPP over the 21<sup>st</sup> century.”</p> <p> </p> <p><strong>Coordinates</strong></p> <p>Spatial resolution is global (90°S-90°N, 180°W-180°E, surface ocean to 5000 metres depth) and temporal resolution runs from years 1801 to 2100.</p> <p> </p> <p><strong>Citation.</strong></p> <p>Buchanan PJ, Aumont O, Bopp L, Mahaffey C, and Tagliabue A (2021): An isotopic fingerprint of increasingly nitrogen-limited phytoplankton in a changing oceanic nitrogen cycle. Nature Communications.</p> <p> </p> <p><strong>Files provided.</strong></p> <p>The data files provided are those that are required to create the figures for this study and/or perform key analyses (i.e. the time of emergence calculations). In the following, each figure or analysis has an associated python script and we list the data files needed to run that script.</p> <p>Python scripts can be found the lead authors GitHub at <a href="https://github.com/pearseb/PISCESiso_Ncycle_analysis">https://github.com/pearseb/PISCESiso_Ncycle_analysis</a>. </p> <p> </p> <p>Put δ<sup>15</sup>N<sub>NO3</sub> observations on model grid (<em>process-d15Nno3_observations_on_model_grid.py</em>):</p> <ul> <li>“RafterTuerena_watercolumn_d15N_no3.txt”</li> </ul> <p>Model assessment (<em>process-model_assessment.py</em>):</p> <ul> <li>“ETOPO_spinup_d15Nno3.nc”</li> <li>“ETOPO_ORCA2.0_Basins_float.nc”</li> <li>“ETOPO_ORCA2.0.full_grid.nc”</li> <li>“RafterTuerena_watercolumn_d15N_no3_gridded.npz”</li> </ul> <p>Time of emergence calculations (<em>process-compute_toe.py</em>):</p> <ul> <li>“ETOPO_picontrol_1y_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_1y_nst_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_1y_d15n_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_1y_d15n_pom_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_ndep_1y_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_ndep_1y_nst_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_ndep_1y_d15n_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_ndep_1y_d15n_pom_ez_utz_ltz.nc”</li> <li>“ETOPO_future_1y_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_future_1y_nst_ez_utz_ltz.nc”</li> <li>“ETOPO_future_1y_d15n_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_future_1y_d15n_pom_ez_utz_ltz.nc”</li> <li>“ETOPO_future_ndep_1y_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_future_ndep_1y_nst_ez_utz_ltz.nc”</li> <li>“ETOPO_future_ndep_1y_d15n_no3_ez_utz_ltz.nc”</li> <li>“ETOPO_future_ndep_1y_d15n_pom_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_1y_temp_ez_utz_ltz.nc”</li> <li>“ETOPO_future_1y_temp_ez_utz_ltz.nc”</li> <li>“ETOPO_picontrol_1y_npp.nc”</li> <li>“ETOPO_picontrol_ndep_1y_npp.nc”</li> <li>“ETOPO_future_1y_npp.nc”</li> <li>“ETOPO_future_ndep_1y_npp.nc”</li> <li>“ETOPO_picontrol_1y_nfix.nc”</li> <li>“ETOPO_picontrol_ndep_1y_nfix.nc”</li> <li>“ETOPO_future_1y_nfix.nc”</li> <li>“ETOPO_future_ndep_1y_nfix.nc”</li> </ul> <p>Figure 1 (<em>fig-main1.py</em>):</p> <ul> <li>“ncycle_changes.nc”</li> <li>“sources_and_sinks.nc”</li> </ul> <p>Figure 2 (<em>fig-main2.py</em>):</p> <ul> <li>“figure2D_ndep_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_ndep_d15npom_signal_usingPAR.nc”</li> <li>“figure2D_cc_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_cc_d15npom_signal_usingPAR.nc”</li> <li>“figure2D_picdep_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_picdep_d15npom_signal_usingPAR.nc”</li> <li>“ETOPO_ToE_futndep_depthzones.nc”</li> <li>“ETOPO_ToE_fut_depthzones.nc”</li> <li>“ETOPO_ToE_picndep_depthzones.nc”</li> <li>“ToE_futndep_curves.txt”</li> <li>“ToE_fut_curves.txt”</li> <li>“ToE_picndep_curves.txt”</li> </ul> <p>Figure 3 (<em>fig-main3.py</em>):</p> <ul> <li>“figure2D_cc_d15npom_signal_usingPAR.nc”</li> <li>“ETOPO_fluxanalysis_results.nc”</li> <li>“figure2D_cc_din_e15n.nc”</li> </ul> <p>Figure 4 (<em>fig-main4.py</em>):</p> <ul> <li>“ETOPO_direct_indirect_effects.nc”</li> </ul> <p>Supp Figure 1 (<em>fig-supp1.py</em>):</p> <ul> <li>“figure_d15Nmaps.nc”</li> </ul> <p>Supp Figure 2 (<em>process-model_assessment.py</em>):</p> <ul> <li>Produced by <em>process-model_assessment.py </em>(see data above)</li> </ul> <p>Supp Figure 3 (<em>fig-supp3.py</em>):</p> <ul> <li>“d15nstats.txt”</li> </ul> <p>Supp Figure 4 (<em>fig-supp4.py</em>):</p> <ul> <li>“ndep_Tg_yr.nc”</li> </ul> <p>Supp Figure 5 (<em>fig-supp5.py</em>):y</p> <ul> <li>“ncycle_changes_climatechangeonly.nc”</li> </ul> <p>Supp Figure 6 (<em>fig-supp6.py</em>):</p> <ul> <li>“ncycle_changes_ndeponly.nc”</li> </ul> <p>Supp Figure 7 (<em>fig-supp7.py</em>):</p> <ul> <li>“figure_depthzones.nc”</li> </ul> <p>Supp Figure 8 (<em>fig-supp8.py</em>):</p> <ul> <li>“figure2D_ndep_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_ndep_d15npom_signal_usingPAR.nc”</li> <li>“figure2D_cc_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_cc_d15npom_signal_usingPAR.nc”</li> <li>“figure2D_picdep_d15nno3_signal_usingPAR.nc”</li> <li>“figure2D_picdep_d15npom_signal_usingPAR.nc”</li> <li>“BGCP_ETOPO_merged_alt.nc”</li> <li>“ETOPO_ToE_futndep_depthzones.nc”</li> <li>“ETOPO_ToE_fut_depthzones.nc”</li> <li>“ETOPO_ToE_picndep_depthzones.nc”</li> <li>“BGCP_ETOPO_merged_alt.nc”</li> <li>“ToE_fut_curves.txt”</li> <li>“ToE_futndep_curves.txt”</li> <li>“ToE_picndep_curves.txt”</li> </ul> <p>Supp Figure 9 (<em>fig-supp9.py</em>):</p> <ul> <li>“figure2D_ndep_no3_utz.nc”</li> </ul> <p>Supp Figures 10 and 11 (<em>process-0D_model_phyto_frac.py</em>):</p> <ul> <li>Produced by <em>process-0D_model_phyto_frac.py</em> and no data required.</li> </ul> <p>Supp Figure 12 (<em>process-compute_toe.py</em>):</p> <ul> <li>Produced by <em>process-compute_toe.py </em>(see data above)</li> </ul> <p> </p> <p><strong>References.</strong></p> <p>Dufresne, J. L., Foujols, M. A., Denvil, S., Caubel, A., Marti, O., Aumont, O., et al. (2013). <em>Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5</em>. <em>Climate Dynamics</em> (Vol. 40). https://doi.org/10.1007/s00382-012-1636-1</p> <p>Galloway, J. N. (2014). The Global Nitrogen Cycle. In <em>Treatise on Geochemistry</em> (2nd ed., Vol. 10, pp. 475–498). Elsevier. https://doi.org/10.1016/B978-0-08-095975-7.00812-3</p> <p>Hauglustaine, D. A., Balkanski, Y., & Schulz, M. (2014). A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate. <em>Atmospheric Chemistry and Physics</em>, <em>14</em>(20), 11031–11063. https://doi.org/10.5194/acp-14-11031-2014</p> <p>Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., et al. (2011). RCP 8.5—A scenario of comparatively high greenhouse gas emissions. <em>Climatic Change</em>, <em>109</em>(1–2), 33–57. https://doi.org/10.1007/s10584-011-0149-y</p>
Isotopic nitrogen fractionation and fermentation products from invitro culture experiments using rumen bacteria
<p>Dataset used in the paper titled : The extent of nitrogen isotopic fractionation in rumen bacteria is associated with changes in rumen nitrogen metabolism (DOI: 10.21203/rs.3.rs-2350552/v1). It contains individual data for isotopic nitrogen fractionation and fermentation products from invitro culture experiments using rumen bacteria</p>
Carbon and nitrogen stable isotope values for lake trout from 6 different Arctic lakes near Toolik, Arctic LTER 1987 to 1988.
Lake trout were analysed for carbon and nitrogen stable isotope values in 6 Arctic lakes near Toolik Lake at the Arctic LTER in 1987 and 1988. The fish were also analysed for age using otoliths.
Concentration of dissolved inorganic carbon (DIC), carbon and nitrogen concentrations, C:N ratios and del 13C isotope value for lakes and rivers on North Slope from Brooks Range to Prudhoe Bay, Arctic LTER 1988 to 2005
Composite file describing plant, animal, water, and sediment samples collected at various sites near Toolik Research Station (68 38'N, 149 36'W). Sample site descriptors include an assigned number specific to the file, a number that relates the samples to other samples collected on the same date and time (sortchem), site, date, time, and depth. Samples are identified by type, category, and a short description. Data include isotope values, carbon and nitrogen concentrations, and C:N ratios of samples.
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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.