Find research datasets worth reusing

opencc-by-4.0Jun 2022View details →

Cascading effects augment the direct impact of CO2 on phytoplankton growth in a biogeochemical model, links to model results

This dataset provides the output of eight model simulations with the global ocean biogeochemical model FESOM-REcoM necessary to reproduce the findings of Seifert et al. (2022). In addition to information on the mesh, the dataset contains 1) 5-year means of global phytoplankton biomass, chlorophyll, net primary production, growth rates, limitations, calcification, grazing rates, calcite concentrations, zooplankton biomass, export fluxes as well as CO2(aq), HCO3- and nutrient concentrations, and 2) a time series of global and North Atlantic coccolithophore biomass, temperature, and CO2(aq) concentrations from 1958 to 2018. File names refer to the Figures and Tables in the paper where the respective data are used. See “readme” for detailed information on the dataset and separate files.

opencc-by-4.0Sep 2022View details →

Model codes and simulation data for "Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)"

ModelE-BiomeE v1.0 model codes and data This folder contains the simulation data and model codes that were used in the paper ‘Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS’s Earth system model (ModelE-BiomeE v.1.0)’ (https://doi.org/10.5194/gmd-2022-72). We included the data simulated by ModelE-BiomeE v.1.0 with settings of full demography (folder FullDemography) and single cohort (folder SingleCohort), and initial settings of land grids and vegetation data (folder GlobalVegetation). The codes include the full ModelE 2.1, module BiomeE files in ModelE, and the standalone BiomeE. In the folder FullDemography, we have 4 netcdf files for global output and 25 files for single grids output. The files ‘FullDM_2588_JAN.nc’ and ‘FullDM_2588_JUL.nc’ are the original model output of January and July in the year 2588. The file ‘FullDM_2588_Annual.nc’ is the yearly summary of model simulations. The file ‘FullDM_Selected.nc’ is an annual summary of 588 years of model simulation only with selected variables. The csv files are for single grids output at the time steps of daily and yearly. The last digit 1~8 represents the sites of 'BNC','MNT','HF','OKR','KZ','SV','WGK','TPJ', respectively (Table 1). Table 1 Site ID and file number ['BNC',  'MNT',   'HF',  'OKR',  'KZ',   'SV',   'WGK',  'TPJ'] ['8991', '8992', '8993', '8994', '8995', '8996', '8997', '8998'] ['8971', '8972', '8973', '8974', '8975', '8976', '8977', '8978'] ['8961', '8962', '8963', '8974', '8965', '8966', '8977', '8968'] Please refer to Table 2 in the paper for the detail of these 8 sites. ‘DailyLAIGPP.csv’ is a summary of all ‘DailyEcosystem’ files with LAI and GPP data. We included the Python scripts that can be used to generate the figures in out paper (Plotting-BiomeE-MsTMIP.py, Plotting-Scatter-Comparison.py, PlottingBiomeEMaps.py, and PlottingGridOutput.py). For the convenience of readers (in reproducing our figures), we included the summary of reanalysis of the data from observations and MsTMIP in folder ‘Sum-Obs-Simu’. Please refer to the original sources listed in our paper for the detail of these data.

opencc-by-4.0Jul 2024View details →

Data accompanying the manuscript "Biogeochemical cycling of trace elements and nutrients in ferruginous waters – constraints from a deep oligotrophic ancient lake", published in Limnology and Oceanography (doi: 10.1002/lno.12687)

CTD and geochemical data accompanying the publication: Biogeochemical cycling of trace elements and nutrients in ferruginous waters – constraints from a deep oligotrophic ancient lake in Limnology & Oceanography (doi: 10.1002/lno.12687).

opencc-by-4.0Jun 2021View details →

Biogeochemical observations in adjacent mesoscale eddies of opposite polarity

Datasets used for the analyses reported in the manuscript titled "Biogeochemical dynamics in adjacent mesoscale eddies of opposite polarity". For all files, the suffix HL4 indicates the expedition HOE-LEGACY 4, while the suffix MESOSCOPE indicates the MESO-SCOPE expedition. Temperature profiles measured underway across adjacent eddies are saved in files UnderwayTemperature*.csv. Station coordinates are saved in UnderwayCoordinates*.csv Shipboard vertical profiles of dissolved oxygen, chlorophyll fluorescence, and potential density anomaly are   saved in files TransectOxygen*.csv, TransectFluorescence*.csv, and TransectSigma*.csv, respectively. Station coordinates are saved in TransectCoordinates*.csv Inorganic nutrient concentrations measured across adjacent eddies are saved in files EddyNutrients*.csv. Particulate carbon, chlorophyll a, beam attenuation, and chlorophyll fluorescence in the eddy centers are saved in file ParticlePigmentComparison_15m.csv and ParticlePigmentComparison_DCM.csv for the depth of 15 m and the depth of the DCM, respectively. Cell counts from flow cytometry in the eddy centers are saved in files FlowCytometry_cyclone_*.csv and FlowCytometry_anticyclone_*.csv. This files also report the depth of the DCM for each eddy center. Imaging FlowCytobot (IFCb) measurements during MESO-SCOPE are reported in files IFCB_Class_DCM&15m_MESOSCOPE.csv for classes and IFCB_Genera_DCM_MESOSCOPE.xlsx for genera.

opencc-by-4.0Aug 2021View details →

Prioritizing forestation based on biogeochemical and local biogeophysical impacts - data

Output data produced in "Prioritizing forestation based on biogeochemical and local biogeophysical impacts" Contact: michael.gregory.windisch@alumni.ethz.ch; edouard.davin@wyssacademy.org Content: Global output data of BGC, BGP, and combined effect of forestation and forest conservation in NetCDF4 files of 0.083° resolution Naming Key: {effect}_{LUaction}_{season}_TCR_{TCR}_{stat}.nc Naming List: effect_list = ["dC","dT","full"] # BGC only, BGP only, Combined effect LUaction_list = ["defor", "refor"] # Forest conservation action, Forest establishment action season_list = ["Annual", "JJA", "DJF"] # Yearly values, Boreal summer values (June, July, August), Boreal winter values (December, January, February) TCR_list = ["local", "global"] # Local climate response as translator to CO2 equivalent, Global climate response as translator to CO2 equivalent stat_list = ["median", "STD"] # Median values between all input datasets, Standard deviation values between all input datasets

opencc-by-4.0Aug 2021View details →

Modelled isoscape data for: "Oceanographic and biogeochemical drivers cause divergent trends in the nitrogen isoscape in a changing Arctic Ocean"

The data included in this repository includes the biogeochemical model output of nitrogen isotope fields. These data were generated by simulations with the NEMOv4.0 Ocean General Circulation Model, SI3 sea ice model, and Pelagic Interactions Scheme for Carbon and Ecosystem Studies version 2 (PISCESv2) biogeochemical model. Nitrogen isotopes were integrated within PISCESv2 for the purpoes of this study. All data here are in longitude, latitude and time cordinates. No depth coordinate is provided as all values are averaged over the upper 100 metres of the model.   The file names mean the following:   ETOPO - refers to how the curvilinear, native grid of the model was re-gridded to a regular 360x180 longitude-latitude grid uisng the etopo60 coordinate system. JRA55 - these are the reanalysis-driven simulations, for which we used the Japanese Atmospheric Reanalysis (JRA55do). future - these are the emissions-driven simulations (historical from 1850-2005, then according to Representative Concentration Pathway 8.5 from 2006-2100.) picontrol - these are parallel to the emissions-driven simulations but do not include the increase in emissions. ndep - refers to if the historical increase in anthropogenic nitrogen deposition was included in the simulation d15Nno3 - isotopic composition of nitrate averaged over the upper 100 metres d15Npom - isotopic composition of particulate organic matter averaged over the upper 100 metres predictors - the average values of salinity, N* and particulate organic matter over the upper 100 metres annualave - annual averages, so that the data are inter-annual 1970-1990ave_months - average monthy values over the period 1970-1990.

opencc-by-4.0Apr 2023View details →

Sea ice core biogeochemical data collected during the 2019 SCALE Winter Cruise

Title: Biogeochemical profiles of sea ice cores sampled during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019.   Authors: Riesna R. Audh, Siobhan Johnson, Mark Hambrock, Hazel Little, Joshua Mirkin, Emmanuel Omatuku, Benjamin Hall, Tokoloho Rampai, Keith MacHutchon, Sebastian Skatulla, Sarah E. Fawcett, Marcello Vichi   Data Description:   Abstract Biogeochemical profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.   A total of four sea ice cores (cores) were sampled during the cruise. Two cores were collected overboard on a consolidated floe that was accessed via a personnel carrier suspended by the ship’s forward crane. Two cores were collected from a pancake that was lifted aboard the ship via a net that was attached to the ship’s aft crane and placed on the helideck for sampling. Profiles were obtained by cutting the cores using a bandsaw in a cold laboratory at -10 °C. The cores were cut into approximately 0.05 m segments, starting from the bottom of the core. These segments were allowed to melt in the dark in an insulated box. The meltwater was filtered for chlorophyll measurements (Welschmeyer, 1994) and the filtrate was analysed for oxygen isotopes (Walker and others, 2015), ammonium (Holmes et al., 1999), phosphate, nitrate, nitrite and silicate (using a SEAL AA500 segmented flow autoanalyser). These values are reported at the depth of the top of the segment in the core in μM. In order to facilitate comparison with the seawater concentrations below the ice, the in-ice nutrients (including NH4+) were salinity normalised using the equation of Fripiat and others (2017):   Cnorm = CSwS   Where C is the measured bulk concentration, Sw is the salinity of the seawater, and S is the corresponding measured bulk salinity of the ice segment.   Although sampling of the core occurred from the bottom of the core to the top of the core, the data are reported as the top of the core (snow/ice interface) being 0 m (depth=0 m).    This research has been funded by the National Research Foundation of South Africa (NRF)   Cruise: VOY-038 (SCALE2019-WINTER) (URL: https://scale.org.za/) Station(s): VOY-038-MIZ3A VOY-038-MIZ1D Position(s): -58.13783 S; 0.00442 W -56.8017 S; 0.30262 E Date/Time: 2019-07-27/10:38:00 2019-07-28/09:15:00 Method(s): Overboard coring Pancake lifting via aft crane, on deck coring Parameters: Station Number (Station) Date/Time of station (Date/Time) Latitude of station (Latitude) Longitude of station (Longitude) Ice type (Ice Type) Core ID(Core), Pancake identifier A/B/C/D Oxygen isotopes (d18O) Chlorophyll (Chl-a) Ammonium (NH4) Nitrate + Nitrite (NO3+NO2) Nitrite (NO2) Phosphate (PO4) Silicate (Si) Nitrate (NO3) Salinity of the ice segment from physical cores (IceSalinity) Standard deviation of the salinity average from physical cores (IceSalinityStdev) Seawater salinity from CTD (SeawaterSalinity) Salinity normalised nitrate+nitrite (N03+N02_Avg_SalinityNormalised) Salinity normalised ammonium (NH4_SalinityNormalised) Salinity normalised nitrite (NO2_SalinityNormalised) Salinity normalised phosphate (PO4_SalinityNormalised) Salinity normalised silicate (Si_SalinityNormalised) Salinity normalised nitrate (NO3_SalinityNormalised)     Keywords: sea ice cores, Antarctica, pancake ice, sea ice, biogeochemistry, winter   References:   Fripiat, F., Meiners, K.M., Vancoppenolle, M., Papadimitriou, S., Thomas, D.N., Ackley, S.F., Arrigo, K.R., Carnat, G., Cozzi, S., Delille, B. and Dieckmann, G.S., 2017. Macro-nutrient concentrations in Antarctic pack ice: Overall patterns and overlooked processes. Elementa: Science of the Anthropocene, 5.     Holmes, R.M., Aminot, A., Kérouel, R., Hooker, B.A. and Peterson, B.J., 1999. A simple and precise method for measuring ammonium in marine and freshwater ecosystems. Canadian Journal of Fisheries and Aquatic Sciences, 56(10), pp.1801-1808.     Walker, S.A., Azetsu‐Scott, K., Normandeau, C., Kelley, D.E., Friedrich, R., Newton, R., Schlosser, P., McKay, J.L., Abdi, W., Kerrigan, E. and Craig, S.E., 2016. Oxygen isotope measurements of seawater (18O/16O): A comparison of cavity ring‐down spectroscopy (CRDS) and isotope ratio mass spectrometry (IRMS). Limnology and Oceanography: Methods, 14(1), pp.31-38.     Welschmeyer, N., 1994. A method for the determination of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnology and Oceanography, 39, pp.1985-1992.

opencc-by-4.0May 2023View details →

Supplemental tables for a study of the seasonal Impacts of the Physical Environment on Biogeochemical Cycles in Arctic Lakes of the Mackenzie River Delta

submitted abstract We conducted two- and six-year-long deployments of continuous water samplers (OsmoSamplers) and sensors (Temperature, pressure, light level, dissolved oxygen (DO) and conductivity) in nine lakes within the mid- to outer-delta region of the Mackenzie River and documented biogeochemical fluctuations (Mn, Fe, sulfate, and DO), defined physical processes that that drive such fluctuations, and constrained the impact of lake solutes on annual riverine fluxes. Five lakes were in the mid-delta region near Inuvik, NT, two lakes were in the outer delta, and two lakes were on the Arctic coastal plain and were not impacted by the Mackenzie River. In general, temperature minima occurred in September/October, indicative of ice formation, and distinct hydrostatic pressure (water level) anomalies occurred in May/June associated with ice breakup, lasting for days to months and impacting lake levels up to 4.2 m higher than “normal”. Such anomalies coincide with a dramatic change in solute concentrations. Systematic changes in solute concentrations indicate redox-driven biogeochemical reactions, salt exclusion during ice formation, and continuous to sporadic exchange of river water. Redox reactions were regulated by DO inputs stemming from atmospheric, photosynthetic, and riverine sources. During ice-covered periods dissolved sulfate may be conservative but was generally removed. Manganese and iron concentrations showed phases of production and removal during ice-covered periods, but both were produced overall. Calculated solute fluxes from lake waters alone to the Arctic Ocean may only impact yearly riverine fluxes for solutes that exceed ten times the river concentration prior to ice breakup (e.g., Mn and Fe).

opencc-by-4.0Jul 2023View details →

FESOM-REcoM model data: A regime shift on Weddell Sea continental shelves with local and remote physical-biogeochemical implications is avoidable in a 2°C scenario

This data set includes the minimal data necessary to reproduce the findings of Nissen et al. (2023). Output of model simulations with the global ocean biogeochemical model FESOM1.4-REcoM2 is provided. In particular, besides information on the model grid, the data set includes annual mean water mass properties (temperature, salinity, density, oxygen, pH) and freshwater fluxes from sea ice and ice shelves and decadal averages of air-sea CO2 fluxes and deep-ocean carbon accumulation rates. Model results are provided from 1980-2100 for the four emission scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 (sorted from low emission to high emission). Please see README for more information on the individual files.  Data set belongs to:  Nissen, C., R. Timmermann, M. Hoppema, and J. Hauck, 2023: A regime shift on Weddell Sea continental shelves with local and remote physical-biogeochemical implications is avoidable in a 2°C scenario. J. Climate, <a href="https://doi.org/10.1175/JCLI-D-22-0926.1">https://doi.org/10.1175/JCLI-D-22-0926.1</a>, in press.

openCC (other)May 2024View details →

Dataset for: Freshwater biogeochemical hotspots: High primary production and ecosystem respiration in shallow waterbodies

This data accompanies the manuscript: "Freshwater biogeochemical hotspots: High primary production and ecosystem respiration in shallow waterbodies" Ponds, wetlands, and shallow lakes (collectively “shallow waterbodies”) are among the most biogeochemically active freshwater ecosystems. Measurements of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) are rare in shallow waterbodies compared to larger and deeper lakes, which can bias our understanding of lentic ecosystem processes. In this study, we calculated GPP, R, and NEP in 26 small, shallow waterbodies across temperate North America and Europe. We observed high rates of GPP (mean 8.4 g O2 m-3 d-1) and R (mean -9.1 g O2 m-3 d-1), while NEP varied from net heterotrophic to autotrophic. Metabolism rates were affected by depth and aquatic vegetation cover, and the shallowest waterbodies had the highest GPP, R, and the most variable NEP. The shallow waterbodies from this study had considerably higher metabolism rates compared to deeper lakes, stressing the importance of these systems as highly productive biogeochemical hotspots.

openOpenMar 2016View details →

Modeling biogeochemical responses of tundra ecosystems to temporal and spatial variations in climate in the Kuparuk River Basin , Alaska, 1921 to 2100.

Output data set of the MBL-GEM III model run for tussock tundra in the Kuparuk River Basin, Alaska, described in detail in Le DizÃ¨s, S., B. L. Kwiatkowski, E. B. Rastetter, A. Hope, J. E. Hobbie, D. Stow, and S. Daeschner, Modeling biogeochemical responses of tundra ecosystems to temporal and spatial variations in climate in the Kuparuk River Basin (Alaska), J. Geophys. Res., 108(D2), 8165, doi:10.1029/2001JD000960, 2003. We ran the model at a 10 km x 10 km resolution for 123 cells at a yearly time step for 180 years, from 1921 to 2100. Two scenarios enabled the investigation of the effects of two opposing climate change scenarios for the 2001-2100 future period: warmer and wetter ("wet scenario" or Scenario 1) and warmer and drier ("dry scenario" or Scenario 2). These 246 files contain all simulation results for each scenario for individual cells in the Kuparuk River basin.

openCC0Mar 2023View details →

Soil biogeochemical responses to multiple co-occurring forms of human-induced environmental change

Multiple forms of human-induced environmental change are impacting arid ecosystems. Climate change is increasing temperatures and altering precipitation patterns, and many rapidly-growing urban centers are in arid locations. Nitrogen deposition from air pollution accompanies urban activities in many of these locations. These forms of environmental stressors will certainly impact soil communities and the biogeochemical processes for which they are responsible. However, most studies investigate these multiple environmental change factors independently or sometimes in pairs, but rarely all together as co-occurring forms of change. We examined how the simultaneous manipulation of increasing temperatures, altered precipitation patterns (both pulse size and frequency), nitrogen deposition, and urbanization influenced soil respiration and mineral N pools in the Sonoran Desert. In a laboratory microcosm, we incubated soils collected from an urban vs. exurban site, from plots receiving ~20 yrs of experimental N fertilization vs. control plots. The microcosm soils were incubated at ambient vs. +2 degree C temperatures under a factorial precipitation treatment of decreased frequency and increased pulse size. We measured the response of soil respiration rates and inorganic N pools to these co-occurring forms of environmental change.

openCC (other)Jan 2020View details →

Biogeochemical rate data and sediment properties of samples used for a controlled flow through experiment testing the effect of nitrate on organic matter decomposition, PIE LTER, Plum Island Sound estuary, Massachusetts.

In this dataset, we used a controlled flow-through reactor (FTR) experiment to test the role of nitrate as an electron acceptor, and its effect on organic matter decomposition and the associated microbial community in salt marsh sediments. Organic matter decomposition significantly increased in response to nitrate, even at sediment depths typically considered resistant to decomposition. The use of isotope tracers suggests this pattern was largely driven by stimulated denitrification. Nitrate addition also significantly altered the microbial community and decreased alpha diversity, selecting for taxa belonging to groups known to reduce nitrate and oxidize more complex forms of organic matter. Fourier Transform-Infrared Spectroscopy further supported these results, suggesting that nitrate facilitated decomposition of complex organic matter compounds into more bioavailable forms. Taken together, these results suggest the existence of organic matter pools that only become accessible with nitrate and would otherwise remain stabilized in the sediment. The existence of such pools could have important implications for carbon storage, since greater decomposition rates as N loading increases may result in less overall burial of organic-rich sediment. Given the extent of nitrogen loading along our coastlines, it is imperative that we better understand the resilience of salt marsh systems to nutrient enrichment, especially if we hope to rely on salt marshes, and other blue carbon systems, for long-term carbon storage.

opencc-by-4.0Aug 2020View details →

Code and data for "Contrasting upper and deep ocean oxygen response to protracted global warming," by Frölicher et al., Global Biogeochemical Cycles, 34, e2020GB006601: https://doi.org/10.1029/2020GB006601

This file contains the data and python/NCL scripts that have been used for the analysis in this paper.

opencc-by-4.0Dec 2020View details →

Data, Sensitivity of 21st-century projected ocean new production changes to idealized biogeochemical model structure

Data for reproducing figures in journal article submitted to Biogeosciences in December 2020. Data generated from global 1-degree simulations of the CESM in an ocean-ice configuration. NP model by Brett. See 10.5281/zenodo.4361705 for code for NP model and to use this dataset to recreate paper figures.

opencc-by-4.0Jun 2024View details →

In situ dataset for initialization and validation of the Copernicus Med-MFC biogeochemical model system (MedBGCins)

The biogeochemical model system in use by the Mediterranean Monitoring Forecasting Centre (Med-MFC) of the EU Copernicus Marine Service requires several observational datasets for data assimilation and model initialization and validation (Coppini et al., 2023; Cossarini et al., 2021; Salon et al., 2019). The present MedBGCins dataset consists of the in situ measurements, coming from selected platforms, on which the initialization and validation of the biogeochemical model system are built. The MedBGCins dataset collects in situ measurements along the Mediterranean Sea water column and during the 1995-2023 time period for nutrients (i.e., nitrate, nitrite, phosphate, silicate, ammonium), dissolved oxygen, dissolved inorganic carbon, total alkalinity, total scale pH at 25°C. The dataset also provides pCO2 and total scale pH at in situ conditions, reconstructed by using the PyCO2SYS Python toolbox (Humpreys et al., 2024). The complete list of variables is indicated in Table 1. The largest subset of the original data are from EMODnet Chemistry Mediterranean Sea - Eutrophication and Acidity aggregated datasets 1911/2022 v2023 (reference in Table 2), including both profiles and time series, plus other documented cruises (same table). Additional information and references are included in the UserGuide file.

opencc-by-4.0Dec 2022View details →

Insight into the impact of viruses on biogeochemical processes in agricultural soils

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2022View details →

Insight into the impact of viruses on biogeochemical processes in agricultural soils

Open the record for dataset details and reuse information.

opencc-by-4.0Mar 2024View details →

Impact of viruses on microbial communities and biogeochemical processes in agricultural soils

The source data of microcosm experiment.