The largest database of trusted experimental protocols

Carbon Cycle

The carbon cycle is the biogeochemical cycle by which carbon is exchanged among the biosphere, pedosphere, geosphere, hydrosphere, and atmosphere of the Earth.
It is one of the most important cycles on Earth, moving carbon through various reservoirs, such as the atmosphere, oceans, and terrestrial ecosystems.
This cycle plays a crucial role in regulating the Earth's climate and supporting life.
Understaning the carbon cycle is essential for studies related to climate change, ecosystem dynamics, and sustainable resource management.

Most cited protocols related to «Carbon Cycle»

Labeled DMEM medium was prepared from DMEM without glucose or glutamine (Sigma) by addition of 10 mM HEPES and the appropriate forms (labeled or unlabeled) of glucose and glutamine to a final concentration of 4.5 g l−1 glucose and 0.584 g l−1 glutamine (labeled glucose and labeled glutamine from Cambridge Isotope Laboratories), followed by sterile filtration. For kinetic flux profiling experiments, samples were switched to fresh unlabeled medium 1 h before the switch into 13C-labeled medium. This minimized metabolome perturbations at the time of the isotope switch resulting from removal of accumulated metabolic waste products. Metabolome quenching and extraction were conducted as previously described18 (link). Absolute metabolite quantitation involved extended labeling of cellular metabolites with uniformly labeled [13C]glucose and [13C]glutamine and extraction in the presence of known concentrations of unlabeled standards (for details, see refs. 23 (link),27 (link) and Supplementary Methods).
Uptake of glucose and glutamine and excretion of all measured metabolites (excretion of pyruvate, lactate, alanine and glutamate were found to be significant) was determined from medium samples taken over an 8-h time period, centered at 48 h after infection. Glucose was measured by enzyme assay (E00715251, R-Biopharm). The other compounds were measured by LC-MS/MS, with inclusion of isotopic internal standards for glutamine, glutamate, pyruvate, lactate and alanine.
Estimation of the relative carbon flux between glycolysis and the PPP was carried out using [1,2-13C]glucose as described38 (link), with 4 h of incubation in labeled medium and detection of labeled forms of lactate by LC-MS/MS. Estimation of the relative carbon flux between pyruvate dehydrogenase and pyruvate carboxylase was carried out based on the passage of labeled carbon from [3-13C]glucose into malate, aspartate and citrate over 6 h (for details, see Supplementary Methods).
Publication 2008
Alanine Aspartate Carbon Carbon Cycle Cells Citrate Enzyme Assays Filtration Glucose Glutamates Glutamine Glycolysis HEPES Infection Isotopes Kinetics Lactates malate Metabolome Oxidoreductase Pyruvate Pyruvate Carboxylase Sterility, Reproductive Tandem Mass Spectrometry
The changes we made to the sulphur cycle resulted in the need to update other fluxes in the model. In the original GEOCARBSULF, degassing fluxes are contingent on spreading rates at time (t) multiplied by the present day rate, while ancient reservoirs are forced to remain at steady state throughout an entire model run. These formulations introduce a rigidity to the model’s operations, which can be a source of failure, as the model cannot stabilize itself quickly enough following large perturbations. The following changes make the model more dynamic, allowing it to respond faster to fluctuations in the system.
We modified the original equations for the degassing of ancient reservoirs of pyrite, gypsum, organic carbon, and carbonate, so the degassing flux calculated at each time step was dependent on the total amount of material in each reservoir, multiplied by a rate constant and the spreading rate at time (t), with an additional dependence on the relative proportions of carbonates on shallow platforms or the deep ocean for carbonate degassing.
The weathering equations for ancient organic carbon and ancient carbonates were also updated: replacing the terms: F_wg_a0 and F_wc_a0—the modern day weathering fluxes for ancient organic carbon and ancient carbonates respectively—with a rate constant multiplied by the total amount of material in each reservoir at each time step; we also include an oxidative feedback to the weathering equations for young and ancient organic carbon.
Finally, the equations governing the flux of material from young to ancient reservoirs at each iteration were altered, to allow the total amount stored in the ancient reservoirs to vary, instead of remaining constant over geologic time. This young to ancient flux is now dependent on the total amount stored in the respective young reservoir multiplied by a rate constant. The model remains in a steady state, but the total mass apportioned to each reservoir at each time step, by the model, has greater variance.
Full text: Click here
Publication 2018
Carbon Carbonates Carbon Cycle ferrous disulfide Gypsum Muscle Rigidity Sulfur
Thirty two environmental layers were produced for use in the predictive models. These datasets were collated from sources that included ship CTD data, satellites (e.g. MODIS), climatologies such as World Ocean Atlas and modelled data (Table 1). The majority of source data were available as gridded datasets partitioned into bins at standardised depth levels (z-layers), and ranged in depth from 0 to ∼5500 m (z-binned datasets, e.g. temperature), whilst others were available as only a single layer at the surface (e.g. surface primary productivity) (Table 1). For z-binned datasets, it was assumed that the conditions found at a specific gridded depth were representative of conditions at that area of seafloor. This allows for the creation of continuous representations of seafloor conditions by extrapolating each z-bin to the corresponding area of seafloor at that depth using an up-scaling approach. Significant improvements over earlier methods, such as the approach of Davies et al. [4] , have been achieved by integrating the highest resolution global bathymetric dataset available (SRTM30 [18] , a 30-arc second dataset, approximately 1 km2) to allow for the preservation of a higher spatial resolution.
Converting the z-binned datasets into representations of seafloor conditions involved several processes. Firstly, for each variable, all available z-bins were extracted independently and interpolated to a slightly higher spatial resolution (usually 0.1°) using inverse distance weighting. This interpolation procedure was required to minimise gaps that appeared between adjacent z-bins due to non-overlap when extrapolated on to the bathymetry. Secondly, these layers were then resampled to match the extent and cell resolution of the bathymetry with no further interpolation. Thirdly, each resampled z-bin was then draped over the area of seafloor that corresponded to its depth range. Each of these bins did not overlap, and were finally merged to produce a continuous representation of the variable at the seafloor. It was assumed that conditions beyond the maximum depth of the data used in this study (>5500 m) were relatively stable towards the maximum depth of the area. This was unlikely to influence suitability models as framework-forming cold-water corals have not been documented at these depths. This method was used to create annual-mean values for regional current velocity, temperature, salinity, nitrate, phosphate, silicate, dissolved oxygen concentrations and carbonate chemistry parameters (Table 1).
Surface datasets were not up-scaled by the above process as they were only available as a single z-bin. Instead, these variables were initially interpolated to a higher spatial resolution (usually 0.1°) using inverse distance weighting and then resampled to match the extent and cell resolution of the other variables. Surface productivity values were obtained from the Vertically Generalised Productivity Model (VGPM, [27] ) and MODIS chlorophyll a data (years 2002–2007), and particulate organic carbon flux to the seafloor was obtained from Lutz et al. [26] . Terrain variables were calculated using ESRI's ArcGIS 9.3 Spatial Analyst extension or the Benthic Terrain Modeler (BTM) extension [28] using SRTM30 bathymetry. Bathymetric position index and rugosity were calculated using BTM. Slope and aspect were calculated within ArcGIS and converted to continuous radians. Additional slope data were obtained from analyses by Becker & Sandwell [19] for comparison with slope computed in this study. Temporal variability within variables was omitted, as the longevity of many cold-water coral species far exceeds the measuring period of most oceanographic variables. For example, in regions not impacted by recent glacial activity, there is evidence for continuous cold-water coral growth over the last 50,000 years [29] .
The accuracy of the up-scaled environmental variables was tested using quality controlled water bottle data obtained from the Global Ocean Data Analysis Project (GLODAP version 1.1; [30] ). GLODAP data was available for temperature, salinity, nitrate, phosphate and silicate. GLODAP values deeper than 50 m were retained for analysis and validation was conducted by intersecting the location of GLODAP stations with the corresponding 30-arc second environmental layers. Relationships were statistically analysed using Pearson's correlation. To show the spatial distribution of error throughout the world's oceans, the average difference between GLODAP stations and the up-scaled environmental layers were plotted onto a five degree grid (Figure 2).
Full text: Click here
Publication 2011
Biologic Preservation Carbonates Carbon Cycle Cells Chlorophyll A Cold Temperature Coral Nitrates Oxygen Phosphates Salinity Satellite Viruses Silicates
Instead of comparing all computationally (νi) and experimentally identified fluxes (νiexp) in the network, we focused on those that are sufficient to describe the complete systemic degree of freedom because most fluxes are linearly dependent. This minimal subset of fluxes was identified by calculability analysis (Van der Heijden et al, 1994 (link); Klamt et al, 2002 (link)) from the null space of the stoichiometric matrix S and allowed the calculation of all unique reaction rates in the underdetermined network. To reduce the considerable difference in magnitude of different fluxes in the network, their rates were expressed as split ratios R of divergent fluxes (Figure 1 and Table I), hence they are scaled to values between zero and unity. Error propagation was used to take the standard deviation of each of the experimentally determined split ratios into account. A default error of 5% was assumed for inactive flux ratios. Secretion of succinate, pyruvate and formate was not considered for calculability analysis, since the corresponding rates are negligible. Non-carbon fluxes such as respiration were also neglected.
Publication 2007
Carbon Cycle Cell Respiration formate Pyruvate secretion Succinate
We used the FaIR (Finite-Amplitude Impulse Response) v1.3 climate-carbon-cycle model to generate changes in atmospheric concentration, radiative forcing and temperature for a number of methane and/or CO2 emissions scenarios. FaIR captures the relevant dynamics of different climate pollutants, and has been shown to provide good agreement with other, more computationally intensive, climate modelling approaches [20 (link)]. We constrained methane to an average lifespan of 12 years to reflect contemporary conditions, and did not include variations in solar and volcanic forcing to focus on the impacts of our emissions scenarios alone. Radiative forcings are modelled following [21 (link)]. Our scenarios are based on perturbations from the standard RCP4.5 pathway from the year 2000. Default RCP4.5 emissions are generated from [20 (link)] to produce RCP4.5 concentrations [22 (link)] in FaIR. RCP4.5 was used to provide a ‘middle-of-the-road’ scenario, and with relatively stable methane emissions over time (discussed further below). The emissions specified for each scenario were added to these RCP4.5 defaults, and the difference between concentrations, forcings and warming from the modified scenarios and default RCP4.5 show individual contributions of the specified pathways alone.
Individual emission scenarios are described alongside their results below, but were broadly variations on a baseline scenario introducing and then sustaining a methane emission of 4 Mt per year. A default annual emission of 4 Mt methane, close to the average UK methane emissions between 1990 and 2016 [23 ], was selected to represent a significant, policy-relevant methane emission that would not be so large as to greatly perturb the RCP4.5 background conditions. For reference, this is just over 1% of the 353 Mt total anthropogenic methane emissions estimated for 2012 [24 (link)].
‘Equivalent’ CO2 emissions scenarios were derived for GWP100 and GWP* using (1) and (2) respectively, both with a GWP100 conversion factor for methane of 32 from [21 (link)]. A fixed GWP value was used, as though in practice this should be updated as greenhouse gas concentrations and hence the unit forcing per emission change in the future, most current climate policy is also based on fixed, present-date GWP values (see also below and supplementary material section 1, available online at stacks.iop.org/ERL/15/044023/mmedia for further discussion on this topic).
Full text: Click here
Publication 2020
Carbon Cycle Climate Climate Change Environmental Pollutants factor A Greenhouse Gases Methane Radiation

Most recents protocols related to «Carbon Cycle»

In order to independently validate our conventionally-dated ring-width chronology, we utilized high precision 14C bomb pulse dating analysis. From our two best-crossdated samples, we selected five individual rings formed before and after the 14C atmospheric peak. Using this approach, it was possible to assess if the 14C content of the wood material dated by dendrochronological methods matches the 14C curve at both sides of the peak, confirming the number of years that should be between each tree ring measured. This approach allows for the identification of potential dating errors within the period from the onset of the 14C spike to the present. At present the post-AD 1950 atmospheric 14C has been divided into different inter-hemispheric zones: NH1, NH2 and NH3 for the Northern Hemisphere and SH1-2 and SH3 for the Southern hemisphere (Hua et al., 2012 (link); Hua et al., 2013 (link)), based on proxy evidence from around the globe.
We first cut 3mm thick slices of wood longitudinally from the two selected radii. Under a stereomicroscope, we separated each ring using a scalpel and chopped them into small pieces ranging from ∼2.0–3.0 mm long to 0.5–1.0 mm wide (e.g. Rodriguez-Caton et al., 2021 (link), as an example). Extraction of α-cellulose was performed following the protocols developed at LDEO for stable isotope analysis in tree-ring cellulose (Andreu-Hayles et al., 2019 (link)). Any remnants of acetic acid and CO2 were eliminated by performing a final 30-minute bath of 1N HCL at 70°C followed by several ultra-pure (Mili-Q) water rinses (Santos et al., 2020 (link)). Careful ring separation is crucial to obtain precise results on the 14C dating, while fine chopping is essential to facilitate the effectiveness of chemicals during cellulose extraction. Each single cellulose sample was homogenized using a Fisher Scientific FS20 ultrasonic bath, frozen for a minimum of a 24h period and freeze-dried for another 24h. The resulting dried cellulose samples were then stored in an electric desiccator before shipment to the Keck Carbon Cycle Accelerator Mass Spectrometer (KCCAMS) at the University of California where radiocarbon measurements were conducted on graphite targets (Santos and Xu, 2017 (link); Santos et al., 2020 (link)) following established protocols (Reimer et al., 2004 (link)). The 14C results are being reported as F14C (Fraction modern carbon).
Full text: Click here
Publication 2023
Acetic Acid Bath Carbon Carbon Cycle Cellulose DDIT3 protein, human Electricity Eye Freezing Graphite Isotopes Radius Trees Ultrasonics
All animal experiments were performed with the approval of Animal Care and Use Ethics Committee of Army Medical Center of PLA. (i) HeLa NC and HeLa shAPE1 cells (ii) HeLa WT cells (5 × 106 in 100 ul medium with Matrigel) were injected subcutaneously in flank of 8 week-old male nude mice. Subcutaneous tumors were allowed to grow for 2 weeks before treatments. When palpable tumors were visible, mice of (i) were divided into four and (ii) were divided into seven groups (n = 7 in each group). Mice were received treatments for 9 days (Ku55933, 10 mg/kg, intraperitonially, daily; E3330, 40 mg/kg intraperitonially, daily; Inhibitor III, 20 mg/kg, intraperitonially, daily; IR, 5 Gy, every 2 days). Specifically, Mice were treated with (i) vehicle, Ku55933, IR, Ku55933 + IR (ii) vehicle, IR, E3330 + IR, Inhibitor III + IR, Ku55933 + IR, E3330 + Ku55933 + IR, and Inhibitor III + Ku55933 + IR. Unblinded tumor measurements were recorded once every 2 days and the volume as calculated by the formula: (width) 2 × length/3. The mice were euthanized in a gas canister with gradual fill carbon dioxide at the end of the treatment cycles and sacrificed. Weighed the tumor with electronic scale.
Full text: Click here
Publication 2023
Animals Carbon Cycle E 3330 Ethics Committees HeLa Cells KU 55933 Males matrigel Mice, Nude Mus Neoplasms
During its 36-month mission, the float visited different oceanic provinces and crossed strong water mass boundaries, such as in September 2016 when the float crossed the Polar Front. Thus, observed changes in biogeochemical properties were not solely due to temporal changes, confounding the study of the seasonality of these properties. We therefore divided the timeseries into three periods in which the contiguous nature of the water masses was verified based on temperature and salinity properties (24-Sep-2016 to 22-May-2017; 10-Oct-217 to 7-Jun-2018; 5-Nov-2018 to 1-May-2019; Fig. S2). The absence of strong water mass contrasts allows us to assume a quasi-Lagrangian framework, where changes in biogeochemical properties can be interpreted as temporal changes. This approach is commonly used in float studies69 (link)–71 (link). For completeness, the Figures show the full float timeseries. However, we focus the Discussion on the three quasi-Lagrangian periods where we can confidently interpret the relationship between phytoplankton phenology in the surface, and the export and fate of POC in the underlying mesopelagic zone. All carbon flux estimates from the different export pathways remain robust for the whole timeseries.
Full text: Click here
Publication 2023
Carbon Cycle Contrast Media Phytoplankton POU3F2 protein, human Salinity
AEs and SEs were first screened using GC fitted with a flame ionization detector (FID) for quantification and general screening of preservation. An Agilent 7890A Series gas chromatograph was fitted with a DB1-high temperature (HT) column (15 m × 0.32 mm × 0.1 µm). One microlitre of the extract was injected via a splitless injector maintained at a temperature of 300°C. The temperature of the column was kept at 100°C for 2 min and then increased by 20°C every minute until a final temperature of 325°C was reached. A temperature of 325°C was then held for 2 min. Helium was used as the carrier gas at constant flow. The detector was kept at 300°C with hydrogen flow of 30 ml min−1. For SEs, the temperature of the column was kept at 50°C for 2 min and then increased by 10°C every minute until a final temperature of 375°C was reached. A temperature of 375°C was then held for 10 min.
To identify molecular profiles, all extracts were analysed using GC-MS. For analysis of AEs and ABEs, the GC component was an Agilent 7890A series attached to an MS Agilent 5975 Inert XL mass selective detector with a quadrupole mass analyser (Agilent Technologies, Cheadle, UK). A DB-5MS (5%-phenyl)-methylpolysiloxane column (30 m × 0.250 mm × 0.25 µm; J&W Scientific, Folsom, CA, USA) was used. The GC column was inserted directly into the ion source of the mass spectrometer. One microlitre of sample was injected via a splitless injector maintained at a temperature of 300°C. Helium at constant flow was used as the carrier gas. The ionization energy of the spectrometer was 70 eV and spectra were obtained by scanning between m/z 50 and 800. The temperature of the column was kept at 50°C for 2 min and then increased by 10°C every minute until a final temperature of 325°C was reached. A temperature of 325°C was then held for 15 min. For SEs, a HT column and programme were used to detect the presence of tri-, di and mono-acylglycerols (TAGs, DAGs and MAGs) and wax esters. A DB5-HT column (30 m × 0.25 mm × 0.1 µm) was used, and the temperature of the column was kept at 50°C for 2 min and then increased by 10°C every minute until a final temperature of 375°C was reached. To target ions specific to alkylresorcinols SEs were analysed using the same chromatographic conditions with the mass spectrometer in SIM mode. The ions m/z 73, 268, 464, 492, 520, 548, 576, 604 and 632, corresponding to alkylresorcinols with cyclic carbon chain lengths C17 to C25, were monitored.
AEs were also analysed using an Agilent 7890A series chromatograph attached to an MS Agilent 5975 Inert XL mass selective detector with a quadrupole mass analyser (Agilent Technologies, Cheadle, UK) equipped with a DB-23 (50%-Cyanopropyl)-methylpolysiloxane column (60 m × 0.250 mm × 0.25 µm; J&W Scientific, Folsom, CA, USA). The temperature of the column was kept at 50°C for 2 min and then increased by 10°C every minute until 100°C. The temperature increased then until 140°C by 4°C every minute, then until 160°C by 0.5°C every minute and finally until 250°C by 20°C every minute. A SIM mode was used to target different groups of ions. These groups were: m/z 74, 105, 262, 290, 318 and 346 for the detection of ω-(o-alkyl phenyl)alkanoic acids of carbon lengths C16 to C22 (APAA16–22), m/z 74, 87, 213, 270 for TMTD, m/z 74, 88, 101, 312 for pristanic acid, m/z 74, 101, 171, 326 for phytanic acid and m/z 74, 105, 262, 290, 318, 346 for the detection of ω-(o-alkyl phenyl)alkanoic acids of carbon lengths C16 to C22 (APAA16–22).
Full text: Click here
Publication 2023
ARID1A protein, human Biologic Preservation Carbon Cycle Carbonic Acid Chromatography Diacylglycerol Esters Fever Flame Ionization Gas Chromatography Gas Chromatography-Mass Spectrometry Glycerides Helium Hydrogen Ions MAG protein, human Phytanic Acid pristanic acid Thiram
Eggshell samples for radiocarbon dating (Supplementary Note 3 and Supplementary Data 3) were mechanically cleaned then reduced by 50% with the stoichiometric addition of 2N HCl in vacuo. Cleaned fragments were converted to graphite at the INSTAAR Laboratory for AMS Radiocarbon Preparation and Research (NSRL) before measurement by Accelerator Mass Spectrometry at the Keck Carbon Cycle AMS Laboratory at the UC Irvine (KCCAMS). Conventional radiocarbon ages have been calibrated using CALIB v.7.1 and SHcal1356 (link)–58 . Sample AD1739 was found in an archaeological deposit by KD; eggshell from the same context were radiocarbon dated as above.
The ratio of two enantiomers (A/I), the protein amino acid L-isoleucine and the non-protein diastereomer d-alloisoleucine, was measured in eggshell by ion-exchange high-pressure liquid chromatography (Supplementary Note 4); A/I reflects time and the integrated thermal history experienced by the sample. Quality control is monitored with a laboratory standard, ILC-G59 (link); 383A/I analyses of the ILC-G standard in the lab average 0.457 ± 0.012.
Full text: Click here
Publication 2023
Alloisoleucine Amino Acids Carbon Cycle Egg Shell Graphite High-Performance Liquid Chromatographies Ion Exchange Isoleucine Mass Spectrometry Proteins

Top products related to «Carbon Cycle»

Sourced in United States
The COBRA Toolbox v2.0 is a software package that provides a comprehensive set of tools for the analysis and optimization of metabolic models. The toolbox includes functions for model construction, simulation, and analysis, as well as interfaces to external tools and databases. The core function of the COBRA Toolbox is to enable researchers to perform constraint-based reconstruction and analysis of metabolic networks.
Sourced in United States
The LI-8100 is a portable soil respiration system designed for measuring soil CO2 flux. It features an infrared gas analyzer for accurate measurement of CO2 concentrations and an automated chamber system for efficient data collection. The device is intended for use in field research and environmental monitoring applications.
Sourced in United States, United Kingdom, Germany, Canada, Japan, Sweden, Austria, Morocco, Switzerland, Australia, Belgium, Italy, Netherlands, China, France, Denmark, Norway, Hungary, Malaysia, Israel, Finland, Spain
MATLAB is a high-performance programming language and numerical computing environment used for scientific and engineering calculations, data analysis, and visualization. It provides a comprehensive set of tools for solving complex mathematical and computational problems.
Sourced in United States
The LI-7500 is an open-path CO2/H2O gas analyzer. It uses a non-dispersive infrared (NDIR) sensor to measure the concentrations of carbon dioxide and water vapor in the atmosphere.
Sourced in United States
The CSAT3 is a three-dimensional sonic anemometer that measures wind speed and wind direction. It is designed to provide accurate measurements of turbulence and momentum flux. The CSAT3 utilizes ultrasonic transducers to measure the time of flight of sound pulses between pairs of transducers, which allows for the calculation of wind speed and direction.
Sourced in United States
The LI-7500 is a closed-path infrared gas analyzer that measures carbon dioxide and water vapor concentrations in the air. It is designed for continuous, in-situ monitoring of these gases in environmental research applications.
Sourced in United States
The LI-6400 is a portable photosynthesis system designed for measuring gas exchange in plants. It is capable of measuring net carbon dioxide and water vapor exchange, as well as environmental conditions such as temperature, humidity, and light levels.
Sourced in United States, Germany
The Exactive mass spectrometer is a high-resolution, accurate-mass (HRAM) instrument designed for applications that require sensitive and selective analysis. It utilizes Orbitrap technology to achieve accurate mass measurements, providing reliable qualitative and quantitative data.
Sourced in United States, Germany, France, Canada, Italy, United Kingdom, Slovenia
Xcalibur is a powerful data acquisition and analysis software for Thermo Fisher Scientific mass spectrometry systems. It enables users to control instrument operation, acquire data, and perform data analysis.
Sourced in United States, Germany, China
Amino acid standards are reference materials used to identify and quantify amino acids in various samples. They provide a known concentration of individual amino acids for calibration and validation purposes in analytical methods such as chromatography and electrophoresis.

More about "Carbon Cycle"

The carbon cycle is a fundamental biogeochemical process that governs the movement and exchange of carbon among the Earth's major reservoirs: the biosphere, pedosphere, geosphere, hydrosphere, and atmosphere.
This cyclic process is essential for regulating the planet's climate and supporting life.
Understanding the intricate dynamics of the carbon cycle is crucial for studies related to climate change, ecosystem dynamics, and sustainable resource management.
The carbon cycle involves the uptake, storage, and release of carbon through various pathways, including photosynthesis, respiration, decomposition, and combustion.
Carbon can be stored in different forms, such as atmospheric carbon dioxide (CO2), organic carbon in soil and vegetation, and dissolved carbon in the oceans.
Key subtopics within the carbon cycle research include: - Terrestrial carbon sinks and sources: The role of forests, grasslands, and other terrestrial ecosystems in sequestering and releasing carbon. - Oceanic carbon sinks and sources: The absorption and release of CO2 by the world's oceans, influenced by factors like ocean circulation and marine life. - Anthropogenic carbon emissions: The impact of human activities, such as fossil fuel combustion and land-use changes, on the carbon cycle and climate. - Carbon cycle modeling and simulation: The use of tools like the COBRA Toolbox v2.0, MATLAB, and models like CSAT3 and LI-7500 to study and predict carbon fluxes and dynamics. - Carbon cycle measurement and analysis: Techniques like the use of the LI-8100, LI-6400, and Exactive mass spectrometer with Xcalibur software, as well as the analysis of amino acid standards, to quantify and characterize carbon cycling processes.
By incorporating these key concepts and related tools, researchers can gain a deeper understanding of the carbon cycle and its pivotal role in shaping the Earth's climate and ecosystems.
This knowledge is essential for developing effective strategies to mitigate the impacts of climate change and promote sustainable resource management.