The use of CO2 flux time series for parameter and carbon stock estimation in carbon cycle research

2011 ◽  
Vol 18 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Timothy Charles Hill ◽  
Edmund Ryan ◽  
Mathew Williams
2018 ◽  
Vol 14 (8) ◽  
pp. 1229-1252 ◽  
Author(s):  
Carlye D. Peterson ◽  
Lorraine E. Lisiecki

Abstract. We present a compilation of 127 time series δ13C records from Cibicides wuellerstorfi spanning the last deglaciation (20–6 ka) which is well-suited for reconstructing large-scale carbon cycle changes, especially for comparison with isotope-enabled carbon cycle models. The age models for the δ13C records are derived from regional planktic radiocarbon compilations (Stern and Lisiecki, 2014). The δ13C records were stacked in nine different regions and then combined using volume-weighted averages to create intermediate, deep, and global δ13C stacks. These benthic δ13C stacks are used to reconstruct changes in the size of the terrestrial biosphere and deep ocean carbon storage. The timing of change in global mean δ13C is interpreted to indicate terrestrial biosphere expansion from 19–6 ka. The δ13C gradient between the intermediate and deep ocean, which we interpret as a proxy for deep ocean carbon storage, matches the pattern of atmospheric CO2 change observed in ice core records. The presence of signals associated with the terrestrial biosphere and atmospheric CO2 indicates that the compiled δ13C records have sufficient spatial coverage and time resolution to accurately reconstruct large-scale carbon cycle changes during the glacial termination.


2018 ◽  
Vol 6 (1) ◽  
pp. 66 ◽  
Author(s):  
Cahyaning Windarni ◽  
Agus Setiawan ◽  
Rusita Rusita

Increasing CO2 in the atmosphere and decreasing amount of forest as absorb CO2are factors which was the underlying repercussion of climate change. One of solutions for decreasing CO2 concentration through the forest vegetation’s development and emendation. Mangrove forest estimated that effectively absorb carbon through photosynthesis. The purpose of the studyis to estimate the stand and litter carbon stock of mangrove forest. The research used line transectmethod. The first line and plot determined randomly then the next lineand plots was sistematically. The observation plots had measurement with amount of 20m x 20m with spacing between plot in line 20 m with total 20 plots. Each plot was measured diameter just  ≥ 5 cm. Each plot made observations litter sub plots with amount of 0,5 m x 0,5 m. Carbon estimation of stand biomass using allometric equations B = 0,1848D2.3624 and litter biomass using total dry weight. Carbon concentration of organic material typically contains around 46% thus multiplying the biomass by 46%. The average biomass of mangrove forests amounted to 431,78 tons/ha. Carbon estimated of mangrove stand was 197,36 ton/ha and litter carbon was 1,25 ton/ha, based on the research total of carbon mangrove forest was198,61 ton/ha. Keywords:carbon above ground,line transect, mangrove forest


2018 ◽  
Vol 6 ◽  
pp. 61-67
Author(s):  
Karishma Gubhaju ◽  
Dipesh Raj Pant ◽  
Ramesh Prasad Sapkota

Forests store significant amount of atmospheric carbon in the form of above and below ground biomass and the amount of carbon stored in forests differs along spatial continuum which provides important information regarding forest quality. This study was carried out to estimate the carbon stock of Shree Rabutar Forest of Gaurishankar Conservation Area, Dolakha, Nepal. In total, 20 circular sampling plots with an area 250 m2 were randomly laid in the study area. Ten tree species were observed in the sampling plots laid in the forest. The higher values of density, frequency, abundance and basal area were observed for Rhododendron arboreum, Alnus nepalensis, Pinus roxburghii and Pinus wallichiana. On the basis of Important Value Index, the dominant tree in the forest was Alnus nepalensis followed by Rhododendron arboreum and Pinus roxburghii. Shannon Index of general diversity of trees in the forest was 0.74 with equal value of Evenness Index, whereas the index of dominance was low (0.22) in the forest. Mean biomass of the forest was 464.01±66.71 tonha-1 contributed by above ground tree biomass (384.44 tonha-1), leaf litter, herbs and grasses biomass (2.69±0.196 tonha-1) and below ground tree biomass (76.88±11.13 tonha-1). Mean carbon stock was 262.77±30.79 tonha-1 including soil carbon stock 44.69±2.25 tonha-1. Individuals of trees with 20-30 cm DBH class were observed in maximum number, which shows that the forest has high potential to sequester carbon over time. Carbon stock estimation and forest management can be one of the potential strategies for climate change mitigation especially through carbon dioxide absorption by the forests.


2006 ◽  
Vol 19 (13) ◽  
pp. 3033-3054 ◽  
Author(s):  
Scott C. Doney ◽  
Keith Lindsay ◽  
Inez Fung ◽  
Jasmin John

Abstract A new 3D global coupled carbon–climate model is presented in the framework of the Community Climate System Model (CSM-1.4). The biogeochemical module includes explicit land water–carbon coupling, dynamic carbon allocation to leaf, root, and wood, prognostic leaf phenology, multiple soil and detrital carbon pools, oceanic iron limitation, a full ocean iron cycle, and 3D atmospheric CO2 transport. A sequential spinup strategy is utilized to minimize the coupling shock and drifts in land and ocean carbon inventories. A stable, 1000-yr control simulation [global annual mean surface temperature ±0.10 K and atmospheric CO2 ± 1.2 ppm (1σ)] is presented with no flux adjustment in either physics or biogeochemistry. The control simulation compares reasonably well against observations for key annual mean and seasonal carbon cycle metrics; regional biases in coupled model physics, however, propagate clearly into biogeochemical error patterns. Simulated interannual-to-centennial variability in atmospheric CO2 is dominated by terrestrial carbon flux variability, ±0.69 Pg C yr−1 (1σ global net annual mean), which in turn reflects primarily regional changes in net primary production modulated by moisture stress. Power spectra of global CO2 fluxes are white on time scales beyond a few years, and thus most of the variance is concentrated at high frequencies (time scale <4 yr). Model variability in air–sea CO2 fluxes, ±0.10 Pg C yr−1 (1σ global annual mean), is generated by variability in sea surface temperature, wind speed, export production, and mixing/upwelling. At low frequencies (time scale >20 yr), global net ocean CO2 flux is strongly anticorrelated (0.7–0.95) with the net CO2 flux from land; the ocean tends to damp (20%–25%) slow variations in atmospheric CO2 generated by the terrestrial biosphere. The intrinsic, unforced natural variability in land and ocean carbon storage is the “noise” that complicates the detection and mechanistic attribution of contemporary anthropogenic carbon sinks.


2012 ◽  
Vol 12 (3) ◽  
pp. 7211-7242 ◽  
Author(s):  
T. Kaminski ◽  
P. J. Rayner ◽  
M. Voßbeck ◽  
M. Scholze ◽  
E. Koffi

Abstract. This paper investigates the relationship between the heterogeneity of the terrestrial carbon cycle and the optimal design of observing networks to constrain it. We combine the methods of quantitative network design and carbon-cycle data assimilation to a hierarchy of increasingly heterogeneous descriptions of the European terrestrial biosphere as indicated by increasing diversity of plant functional types. We employ three types of observations, flask measurements of CO2 concentrations, continuous measurements of CO2 and pointwise measurements of CO2 flux. We show that flux measurements are extremely efficient for relatively homogeneous situations but not robust against increasing or unknown complexity. Here a hybrid approach is necessary and we recommend its use in the development of integrated carbon observing systems.


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