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220 results for “biogeochemical”
MacroSheds: a synthesis of long-term biogeochemical, hydroclimatic, and geospatial data from small watershed ecosystem studies
The MacroSheds dataset is an ongoing synthesis of data records from small-watershed ecosystem studies, including those managed by LTER, CZO/CZNet, NEON, and many other networks. While details of instrumentation and sampling methods vary across these studies, the types of data collected and the questions that motivate their analysis are remarkably similar. Nevertheless, little effort toward the compilation of these datasets has previously been made, and comparative watershed analyses have remained limited in scale. The MacroSheds dataset includes daily time series of streamflow (discharge) and stream chemistry, as well as precipitation and precipitation chemistry where available. Each of the 200+ watersheds included in the MacroSheds dataset is described by a comprehensive collection of watershed attributes, summarized from a diverse set of gridded data products. A subset of these watershed attributes conform as closely as possible to the specifications of the CAMELS dataset (https://ral.ucar.edu/solutions/products/camels), allowing the MacroSheds dataset to function as a small-watershed supplement to that corpus, and a resource for hydrologists as well as biogeochemists and watershed ecosystem scientists. Data paper: https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lol2.10325 Data dashboard for visualization: macrosheds.org R package for data access and analysis: https://github.com/MacroSHEDS/macrosheds R package vignettes: https://macrosheds.org/pages/vignettes Live dataset changelog: https://macrosheds.org/pages/changelog.html Questions: mail@macrosheds.org
Chamber level gas fluxes and soil biogeochemical properties from a tidal salt marsh and an impounded brackish wetland in South Carolina, USA
Archived data from a research project assessing the role of plants in driving methane fluxes from coastal wetland systems. Data collection occurred at the inland edge of a salt marsh and a diked, brackish impounded wetland in Georgetown County, South Carolina during 2022 and 2023. The first archived data table includes soil biogeochemical properties for all soil samples (0-10 cm and 10-50 cm mineral soil depth) collected approximately monthly from our two study sites. Specific biogeochemical properties include copy numbers of the mCRA gene, soil C and N concentrations, soil C:N ratios, soil moisture, pH, conductivity, organic matter content and alive and dead root biomass. The second archived data table includes methane and carbon dioxide fluxes from chambers over plants (whole-plant gas fluxes), adjacent to plants (plant-adjacent chambers) and in non-vegetated areas (non-vegetated fluxes) measured approximately monthly at our two study sites. Metadata associated with flux measurements are also included: leaf area, dead stems, oxidation reduction potential at four depths, atmospheric pressure, incoming solar radiation, relative humidity, chamber temperature, windspeed, water salinity, water temperature and water column depth.
Soil biogeochemical variables collected on the Arctic Long Term Ecological Research (ARC LTER) experimental plots in moist acidic and dry heath tundra, Arctic LTER, Toolik Field Station, Alaska 2017.
**Note: Versions 1 and 2 had the wrong data files.** Soil nutrients (total Carbon and Nitrogen, inorganic nutrients (ammonium ion (NH4), nitrate anion (NO3-), phosphate anion (PO43-)); organic nutrients (extractable organic carbon (EOC), extractable total nitrogen (ETN), extractable organic phosphorus (EOP)), microbial biomass, and extracellular enzyme activity on soils sampled from the Arctic LTER Dry Heath (organic soils only) and Moist Acidic Tundra (organic and mineral soils) herbivore exclosures and control plots at Toolik Lake, AK in July 2017.
Trout Lake USGS Water, Energy, and Biogeochemical Budgets (WEBB) Stream Data 1975-2013
This data was collected by the United States Geological Survey (USGS) for the Water, Energy, and Biogeochemical Budget Project. The data set is primarily composed of water chemistry variables, and was collected from four USGS stream gauge stations in the Northern Highland Lake District of Wisconsin, near Trout Lake. The four USGS stream gauge stations are Allequash Creek at County Highway M (USGS-05357215), Stevenson Creek at County Highway M (USGS-05357225), North Creek at Trout Lake (USGS-05357230), and the Trout River at Trout Lake (USGS-05357245), all near Boulder Junction, Wisconsin. The project has collected stream water chemistry data for a maximum of 36 different chemical parameters,. and three different physical stream parameters: temperature, discharge, and gauge height. All water chemistry samples are collected as grab samples and sent to the USGS National Water Quality Lab in Denver, Colorado. There is historic data for Stevenson Creek from 1975-1977, and then beginning again in 1991. The Trout Lake WEBB project began during the summer of 1991 and sampling of all four sites continues to date.
Fertilization (NPK) alter dryland biogeochemical processes
Nutrient augmentation is one major global change disturbance that could have cascading effects on local plant and microbial communities thus altering biogeochemical properties (Peñuelas et al. 2012). While many studies have investigated fertilization effects on community change and ecosystem processes, less work has been done in dryland ecosystems (Schimel 2010), where nutrient availability often comes as pulses correlated with rain events (Collins et al. 2008). We leveraged an ongoing fertilization experiment (NutNet) at the Sevilleta to answer the question: How does fertilization alter dryland biogeochemical processes, and how does this effect change seasonally? To explore this topic, we specifically measure three important soil hydrolase enzymes, N-acetyl- glycosaminidase (NAG), phosphatase (AP), and β- glucosidase (BG), microbial biomass, and soil nitrogen levels at 5 points along a seasonal gradient within the NutNet plots.
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>
Data from: Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean
<p><strong>Abstract</strong></p> <p>In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabit- ants. This phenomenon, termed the island mass effect 65 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local bio- geochemical impacts, islands may have even stronger and farther-reaching ecological impacts.</p> <p> </p> <p><strong>Data set and method</strong></p> <p>For each island, an algorithm detected the Island Mass Effect (IME) from climatological satellite chlorophyll maps as a contour enclosing the island and surrounding high-chlorophyll waters, termed IME region. A reference (REF) region of the same size was detected alongside each IME region, enclosing nearby non-IME waters. The IME and REF regions were used to build the IME database described in Messié et al. (2022), that includes variables related to satellite chlorophyll, primary production, and PHYSAT phenoclass diversity metrics in IME and REF regions on a climatological basis.</p> <p>This data set includes 4 files:</p> <ul> <li>island_database.csv: information regarding the 664 islands and shallow reefs where the IME detection was applied</li> <li>IME_masks.nc: monthly climatological masks for the IME and REF regions for all islands,</li> <li>IME_database.nc: IME database as a function of island and climatological month (chlorophyll, primary production, and phenoclass-derived variables calculated within the IME and REF masks).</li> <li>PHYSAT_climatology.nc: climatological maps for each PHYSAT phenoclass, used to calculate phenoclass-derived variables in the IME database.</li> </ul> <p>See details regarding data sources and calculations in <a href="https://rdcu.be/cO4qr">Messié et al. (2022)</a>.</p>
Soil respiration rates, biogeochemical pools, and mineral-associated organic matter from high organic matter and high mineral content coastal wetland soils in Apalachicola, Florida, 2022
This data set was used to observe how the application of dredged sediment would impact soil respirations rates, biogeochemical pools, mineral associated organic matter of coastal wetland soils from Apalachicola, Florida. To achieve this, a combination of intact core and bottle incubations were used, comparing a high organic matter coastal wetland soil to a high mineral content wetland soil which were collected in June, 2022. All laboratory analysis was conducted at the University of Central Florida in Orlando, Florida.
CO₂ and related biogeochemical data from permafrost rivers on the Qinghai-Tibet Plateau (2016–2018, 2023)
This dataset includes four years of direct measurements from 50 permafrost rivers in the Qinghai-Tibet Plateau’s major Asian headwaters (Yellow, Yangtze, Lancang, Nu, Derung, Yarlung Tsangpo, Marja Tsangpo, and Indus Rivers), collected during the ice-free seasons (April–October) of 2016–2018 and 2023. It includes CO₂ partial pressure (pCO₂) and emission rates, concentrations of DOC, DIC, and major dissolved ions, carbon (δ¹³C), sulfur (δ³⁴S), and oxygen (δ¹⁸O) isotopes, alongside site location and other physiochemical data. Given its scarcity and scientific significance, this dataset will greatly support updates to global river CO2 flux estimates.
Soil biogeochemical measurements from the Antarctic Specially Protected Area No. 131 (ASPA 131), McMurdo Dry Valleys Antarctica, December 2022
These data include soil biological properties (16S ASV community sequences, invertebrate community counts, ash-free dry mass, pigment concentrations), physical properties (location, gravimetric soil moisture, pH, electrical conductivity, remote detection of soil moisture change), chemical properties (dissolved inorganic nitrogen, extractable sulfate ions, extractable Cl ions) from soils collected within the Antarctic Specially Protected Area No. 131 (ASPA-131) surrounding Canada Stream in the McMurdo Dry Valleys of Antarctica. Collection sites were associated with a warming event that occurred on March 22, 2022, and include the following remotely-sensed categories: V - validation sites representing arid soils with little soil moisture and minimal detectable change in liquid water, S - significant sites that had a significant increase in liquid water, and N - nonsignificant sites that had detectable moisture but did not experience a significant increase in liquid water. These data aid in our understanding of how landscape heterogeneity and hydroclimate variability influence soil biota communities sensitive to changes in liquid water availability in a polar desert.
Data used in "BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean"
<div> <p>This repository contains the data used to generate the figures for the submitted manuscript "BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean".</p> </div> <h3>Contents</h3> <div> <ul> <li> <p>Model input:</p> <ul> <li> <p>INPUTS: ocean model input/grid files</p> </li> <li> <p>PISCES_INPUTS: BGC input files</p> </li> <li> <p>OBC: open boundary forcing </p> </li> <li> <p>WEIGHTS: weight files for ERA interim forcing</p> </li> </ul> </li> </ul> </div> <div> <ul> <li> <p>Manuscript files:</p> <ul> <li> <p>data: files used to generate manuscript images</p> </li> <li> <p>config, src, notebooks: Python code and Jupyter notebooks used to generate images</p> </li> <li> <p>figures, supplementary: manuscript figures and supplementary figures</p> </li> </ul> </li> </ul> </div> <div> </div> <div><strong>Abstract: </strong>"We present BIOPERIANT12, a regional model configuration of the Southern Ocean (SO) at a mesoscale-resolving 1/12 degree. This is a stable, ocean–ice–biogeochemical configuration derived from the Nucleus for European Modelling of the Ocean (NEMO) modelling platform. It is specifically designed to investigate questions related to the mean state, seasonal cycle variability and mesoscale processes in the mixed layer and within the upper ocean (<1000 m). In particular, the focus is on understanding processes behind carbon and heat exchange, systematic errors in biogeochemistry and assumptions underlying the parameters chosen to represent these SO processes. The dynamics of the ocean model play a large role in driving ocean biogeochemistry and we show that over the chosen period of analysis 2000–2009 that the simulated dynamics in the upper ocean provide a stable mean state, as compared to observation-based datasets (themselves subject to biases such as sparsity of data, cloud cover, etc.), and through which the characteristics of variability can be described. Using ocean biomes to delineate the major regions of the SO, the model demonstrates a useful representation of ocean biogeochemistry and partial pressure of carbon dioxide (pCO2). In addition to a reasonable model mean state performance, through model–data metrics BIOPERIANT12 highlights several pathways for improving Southern Ocean model simulations such as the representation of temporal variability and the overestimation of biological biomass."</div>
Biogeochemical Argo Adjusted Oxygen Data
<p>This archive contains two netCDF files used in the work reported by Johnson and Bif (2021). These files contain vertical profiles of corrected dissolved oxygen (Argo variable DOXY_ADJ), temperature, salinity, pressure, location, and time data obtained by profiling floats in the Biogeochemical-Argo array. The files were created by downloading all Argo .Sprof files directly from the Argo Global Data Assembly Center (ftp://usgodae.org/pub/outgoing/argo or ftp://ftp.ifremer.fr/ifremer/argo) in December 2020. The corresponding monthly snapshot (December 2020, https://doi.org/10.17882/42182#79118) of the Argo database will contain these .Sprof files, in addition to data for floats that do not have biogeochemical sensors.</p> <p><br> Merged netCDF (.nc) data files were then created by importing all of the .Sprof files into Ocean Data View (ODV, odv.awi.de) using the List File Generator tool in ODV. After eliminating 9 floats with anomalous adjusted oxygen data, which are listed in Johnson and Bif, the vertical profiles for all floats with adjusted oxygen data were exported as two netCDF files using ODV. One file contains data in the northern hemisphere (90N to 10S), which the second contains data from 0N to 90S). The files overlap from 0 to 10S, which enabled all equatorial data (10N to 10S) to be processed with one file.</p> <p><br> The netCDF files contain the adjusted dissolved oxygen concentration in µmol/kg (DOXY_ADJ), oxygen anomaly (oxygen minus oxygen saturation at one atmosphere pressure), temperature, salinity, pressure (dbar), profile position and date, quality flags for each observation, and float WMO number and type.</p> <p><br> Johnson, K. S. &amp; Bif, M. B. (2021) Constraint on net primary productivity of the global ocean by Argo oxygen measurements. Nature Geoscience. In press.</p> <p> </p>
Multiple biogeochemical variables were measured for organic and mineral soils on Arctic LTER experimental plots in moist acidic and non-acidic tundra, Arctic LTER Toolik Field Station, Alaska 2013.
Measures of soil nutrient content (available N and P, Extractable N and P, Total C, N and P), and microbial biomass and activity (exoenzyme activity) were measured for organic and mineral soils on Arctic LTER experimental plots at Toolik field station in moist acidic and non-acidic tundra (organic soils only).
Soil biogeochemical variables collected on the Arctic LTER experimental plots in moist acidic, moist non-acidic, wet shrub and shrub tundra, Arctic LTER Toolik Field Station, Alaska 2015
We investigated the effect of long-term warming on multiple soil and microbial carbon, nitrogen, and phosphorus pools, and microbial extracellular enzyme activities, with a particular focus on phosphorus, in Alaskan tundra plots underlain by permafrost
Soil and plant biogeochemical and soil temperature variables collected at brown lemming (Lemmus trimucronatus) and tundra vole (Microtus oeconomus) structure sties near Nome, Toolik Lake, and Utqaigvik, Alaska, summer 2018-2020
Soil and plant sampling analysis under small mammal-built structures and controls sites from near the Team Vole fences: Nome, Toolik, Utqiagvik, AK 2018-2020.
Biogeochemical data collected from Northeast Shark Slough, Everglades National Park (FCE LTER) from September 2006 to September 2008
Each site's physical characteristics (pH, water depth and temperature) were measured in the field and recorded. Two water samples (filtered and unfiltered) were collected from each throw, along with a floc sample (if present). All samples were taken back to the lab for analysis (e.g. water content, % organic matter, bulk density, and TP/TN/TC).
Biogeochemical data collected from Northeast Shark River Slough, Everglades National Park, Florida, USA, September 2006 - April 2025
This project was established in 2006 to document the pattern of abundance of key ecological indicators (e.g., surface water, soil, floc, periphyton and sawgrass) across the NESRS landscape. A total of 30 sites were established and monitored in 2006, 2007 and 2008. After the completion of 1-mile bridge in 2012, additional 10 new sites were established to observe the ecological impact of 1-mile bridge (known as Bridge & Census sites). In 2015, additional 40 sites were established along eight transects (T1-T8, known as near canal sites) in ENP marshes starting at, and roughly perpendicular to the L-29 canal. The purpose of these sites was to monitor the potential effects of Modified Water Deliveries (MWD) operations on changing nutrient concentrations and ratios in key ecological compartments due to increased downstream discharges from the L-29 canal beneath the 1-mile and 2.6-mile bridges and culverts along Tamiami Trail. Data collection is complete.
Biogeochemical data collected in the eastern marl prairies of the Everglades (Florida, USA) before and after fire, between the years 2018 and 2021
The data included in this database were collected within a project funded by Everglades National Park (ENP). The project was aimed at understanding how fire, characterized by different intensities, differentially affects nutrient cycling in oligotrophic wetlands with distinct levels of phosphorus limitation. The data were collected in the eastern part of the Everglades, close to the boundary of ENP, in South Florida (Homestead). This part of ENP is characterized by marl soils, which are shallow (often less than 10 cm) and C-poor. The data were collected at two sites: one site was more oligotrophic (LP), while the other one had a certain degree of phosphorus enrichment (HP). The database includes date and location (i.e. site and plot) of each sampling event, surface water physio-chemistry, vegetation composition and structure, including dominant macrophyte estimated biomass, litter and root decomposition rates, and carbon, nitrogen, and phosphorus concentrations in the soil, flocculent detrital material, periphyton, sawgrass leaves and roots, and the water column. All these data were collected at different times between September 2018 and March 2021, before and after a prescribed fire that was carried out in February 2020 and which burned all the plots. Each row within the database identifies a unique combination of date and sampling plot.
Global Carbon Budget 2024, surface ocean fugacity of CO2 (fCO2) and air-sea CO2 flux of individual global ocean biogeochemical models and surface ocean fCO2-based data-products
<p><strong>v2 update: </strong></p> <ul> <li>update to data in UoEX-UEPFFNU fCO2-product</li> <li>fix of lat-lon issue in Jena-MLS fCO2-product</li> <li>minor fixes to metadata in fCO2-products</li> </ul> <p><br>The v2 data is used for the final published version of the Global Carbon Budget 2024.</p> <p>-----------------</p> <p><strong>Surface ocean fugacity of CO2 (fCO2) and air-sea CO2 flux data from individual Global Ocean Biogeochemistry Models (GOBMs) and surface ocean fCO2-based data-products (fCO2-products).</strong><br>There are three types of files: (1) one file per fCO2-product with gridded fields and regionally-integrated CO2 flux time-series, (2) one file per GOBM with gridded fields, and (3) one file with the regionally-integrated time-series for the GOBMs. </p> <p><strong>Note: </strong>These provided gridded outputs from fCO2-based data-products and GOBMs are regridded datasets, without adjustments. <strong>The best estimates of the annual global ocean carbon sink, based on the native grids of fCO2-products and GOBMs and with the adjustments described in the Global Carbon Budget 2024 (https://essd.copernicus.org/preprints/essd-2024-519), are available in the Global Carbon Budget 2024 spreadsheet.</strong></p> <p>The regionally-integrated time-series are as provided by the contributing groups, i.e. integrated from their native grids. In order to reproduce Figure 14 of the Global Carbon Budget 2024 paper (https://essd.copernicus.org/preprints/essd-2024-519), the river flux adjustment needs to be added to the CO2 flux estimated from the fCO2-products (North: 0.14 GtC yr-1, Tropics: 0.42 GtC yr-1, South: 0.09 GtC yr-1, see GCB 2024 paper). The sum of the regional fluxes may differ from the global estimates as reported in the GCB spreadsheet, because some adjustments were applied only for global fluxes.</p> <p><strong>What is in the files?</strong></p> <p>(1) The files for the fCO2-based data-products contain the following variables (temporal resolution: monthly):<br><br>fgco2_reg: Regionally integrated air-sea CO2 flux (positive downward), monthly, for regions: global, north, tropics, south<br>fgco2: Flux density of the total air-sea CO2 flux (positive downward), dimensions: time, latitude, longitude<br>sfco2: Surface ocean fCO2, dimensions: time, latitude, longitude<br>area: Area per pixel, dimensions: latitude, longitude<br>area_reg: Total surface ocean area covered by native grid, for global, north, tropics, south</p> <p>(2) The files for the GOBMs contain the following fields, for simulation A ('contemporary simulation', including effects of rising CO2, climate change and variability) and simulation B ('control simulation', constant CO2, no climate change and variability). Temporal resolution: monthly</p> <p>fgco2: Flux density of the total air-sea CO2 flux (positive downward), dimensions: time, latitude, longitude<br>sfco2: Surface ocean fCO2, dimensions: time, latitude, longitude<br>area: Area per pixel, dimensions: latitude, longitude</p> <p>(3) One file 'GCB-2024_OceanModel_RegionalBreakdown_1959-2023.nc' with the regionally-integrated CO2 flux time-series for all individual GOBMs, and for simulations A and B. Regions: North, tropics, south. Temporal resolution: annual.</p> <p><strong>Fair data use statement:</strong><br>The data and model output provided on this site are freely available and were furnished by individual scientists who encourage their use.<br><strong>Citation:</strong> Please cite the Global Carbon Budget 2024 (Friedlingstein et al., 2024, ESSD, https://essd.copernicus.org/preprints/essd-2024-519) for all data. In addition, please also cite the corresponding original reference for each dataset that has been used - see Table 4 in Global Carbon Budget 2024 for references of all the individual Global Ocean Biogeochemical Models and fCO2-based data-products. Further, for an overview of the Global Ocean Biogeochemical Model output, you may find it useful to cite Hauck et al. (2020, Frontiers, doi:10.3389/fmars.2020.571720).</p> <p><strong>Acknowledgement:</strong> Please add the following text in the acknowledgement of your paper: "We acknowledge the Global Carbon Project, which is responsible for the Global Carbon Budget and we thank the ocean modeling and fCO2-mapping groups for producing and making available their model and fCO2-product output."<br><strong>Co-authorship: </strong>An invitation of co-authorship to the contributing groups is encouraged if these data are the central data set of the publication.</p> <p>Besides the surface fCO2 and air-sea CO2 flux data that is made available open access, we make<strong> additional 3D output</strong> from the Global Ocean Biogeochemical models (GCB-ocean) available upon request and with its own data policy. Please refer to the Global Carbon Budget website for these additional data: https://globalcarbonbudgetdata.org/closed-access-requests.html</p>
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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.