CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381]; Chinese Academy of Sciences [KZCX2-YW-432]

Soil organic carbon storage and soil CO2 flux in the alpine meadow ecosystem

High-resolution sampling, measurements of organic carbon contents and C-14 signatures of selected four soil profiles in the Haibei Station situated on the northeast Tibetan Plateau, and application of C-14 tracing technology were conducted in an attempt to investigate the turnover times of soil organic carbon and the soil-CO2 flux in the alpine meadow ecosystem. The results show that the organic carbon stored in the soils varies from 22.12x10(4) kg C hm(-2) to 30.75x10(4) kg C hm(-2) in the alpine meadow ecosystems, with an average of 26.86x10(4) kg C hm(-2). Turnover times of organic carbon pools increase with depth from 45 a to 73 a in the surface soil horizon to hundreds of years or millennia or even longer at the deep soil horizons in the alpine meadow ecosystems. The soil-CO2 flux ranges from 103.24 g C m(-2) a(-1) to 254.93 gC m(-2) a(-1), with an average of 191.23 g C m(-2) a(-1). The CO2 efflux produced from microbial decomposition of organic matter varies from 73.3 g C m(-2) a(-1) to 181 g C m(-2) a(-1). More than 30% of total soil organic carbon resides in the active carbon pool and 72.8%. 81.23% of total CO2 emitted from organic matter decomposition results from the topsoil horizon (from 0 cm to 10 cm) for the Kobresia meadow. Responding to global warming, the storage, volume of flow and fate of the soil organic carbon in the alpine meadow ecosystem of the Tibetan Plateau will be changed, which needs further research.

A stable carbon isotopic approach for understanding the CO2 flux at the Haibei Alpine Meadow Ecosystem - A simple model

Although respiration of organisms and biomass as well as fossil fuel burning industrial production are identified as the major sources, the CO2 flux is still unclear due to the lack of proper measurements. A mass-balance approach that exploits differences in the carbon isotopic signature (delta(13)C) of CO2 Sources and sinks was introduced and may provide a means of reducing uncertainties in the atmospheric budget. delta(13)C measurements of atmospheric CO2 yielded an average of - 10.3 parts per thousand relative to the Peedee Belemnite standard; soil and plants had a narrow range from -25.09 parts per thousand to -26.51 parts per thousand and averaged at -25.80 parts per thousand. Based on the fact of steady fractionation and enrichment during respiration of mitochondria, we obtained the emission Of CO2 of 35.451 mol m(-2) a(-1) and CO2 flux of 0.2149 mu mol m(-2) s(-)1. The positive CO2 flux indicated the Haibei Alpine Meadow Ecosystem a source rather than a sink. The mass-balance model can be applied for other ecosystem even global carbon cycles because it neglects the complicated process of carbon metabolism, however just focuses on stable carbon isotopic compositions in any of compartments of carbon sources and sinks. (C) 2005 Elsevier B.V. All rights reserved.

Strong temperature dependence and no moss photosynthesis in winter CO2 flux for a Kobresia meadow on the Qinghai-Tibetan plateau

We examined the CO2 exchange of a Kobresia meadow ecosystem on the Qinghai-Tibetan plateau using a chamber system. CO2 efflux from the ecosystem was strongly dependence on soil surface temperature. The COZ efflux-temperature relationship was identical under both light and dark conditions, indicating that no photosynthesis could be detected under light conditions during the measurement period. The temperature sensitivity (Q(10)) of the COZ efflux showed a marked transition around -1.0 degrees C; Q(10) was 2.14 at soil surface temperatures above and equal to -1.0 degrees C but was 15.3 at temperatures below -1.0 degrees C. Our findings suggest that soil surface temperature was the major factor controlling winter COZ flux for the alpine meadow ecosystem and that freeze-thaw cycles at the soil surface layer play an important role in the temperature dependence of winter CO2 flux. (c) 2005 Elsevier Ltd. All rights reserved.

Short-term variation of CO2 flux in relation to environmental controls in an alpine meadow on the Qinghai-Tibetan Plateau

[1] The alpine meadow ecosystem on the Qinghai-Tibetan Plateau may play a significant role in the regional carbon cycle. To assess the CO2 flux and its relationship to environmental controls in the ecosystem, eddy covariance of CO2, H2O, and energy fluxes was measured with an open-path system in an alpine meadow on the plateau at an elevation of 3,250 m. Net ecosystem CO2 influx (Fc) averaged 8.8 g m(-2) day(-1) during the period from August 9 to 31, 2001, with a maximum of 15.9 g m(-2) day(-1) and a minimum of 2.3 g m(-2) day(-1). Daytime Fc averaged 16.7 g m(-2) day(-1) and ranged from 10.4 g m(-2) day(-1) to 21.7 g m(-2) day(-1) during the study period. For the same photosynthetic photon flux density (PPFD), gross CO2 uptake (Gc) was significantly higher on cloudy days than on clear days. However, mean daily Gc was higher on clear days than on cloudy days. With high PPFD, Fc decreased as air temperature increased from 10degreesC to 23degreesC. The greater the difference between daytime and nighttime air temperatures, the more the sink was strengthened. Daytime average water use efficiency of the ecosystem (WUEe) was 8.7 mg (CO2)(g H2O)(-1); WUEe values ranged from 5.8 to 15.3 mg (CO2)(g H2O)(-1). WUEe increased with the decrease in vapor pressure deficit. Daily albedo averaged 0.20, ranging from 0.19 to 0.22 during the study period, and was negatively correlated with daily Fc. Our measurements provided some of the first evidence on CO2 exchange for a temperate alpine meadow ecosystem on the Qinghai-Tibetan Plateau, which is necessary for assessing the carbon budget and carbon cycle processes for temperate grassland ecosystems.

Sensitivity analysis of an ocean carbon cycle model in the North Atlantic: an investigation of parameters affecting the air-sea CO2 flux, primary production and export of detritus

The sensitivity of the biological parameters in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in the calculation of the air-sea CO2 flux, primary production and detrital export is analysed. We explore the effect on these outputs of variation in the values of the twenty parameters that control ocean ecosystem growth in a 1-D formulation of the UK Met Office HadOCC NPZD model used in GCMs. We use and compare the results from one-at-a-time and all-at-a-time perturbations performed at three sites in the EuroSITES European Ocean Observatory Network: the Central Irminger Sea (60° N 40° W), the Porcupine Abyssal Plain (49° N 16° W) and the European Station for Time series in the Ocean Canary Islands (29° N 15° W). Reasonable changes to the values of key parameters are shown to have a large effect on the calculation of the air-sea CO2 flux, primary production, and export of biological detritus to the deep ocean. Changes in the values of key parameters have a greater effect in more productive regions than in less productive areas. The most sensitive parameters are generally found to be those controlling well-established ocean ecosystem parameterisations widely used in many NPZD-type models. The air-sea CO2 flux is most influenced by variation in the parameters that control phytoplankton growth, detrital sinking and carbonate production by phytoplankton (the rain ratio). Primary production is most sensitive to the parameters that define the shape of the photosynthesis-irradiance curve. Export production is most sensitive to the parameters that control the rate of detrital sinking and the remineralisation of detritus.

The impact of diurnal variability in sea surface temperature on the atlantic air-sea CO2 flux

The effect of diurnal variations in sea surface temperature (SST) on the air-sea flux of CO2 over the central Atlantic ocean and Mediterranean Sea (60 S–60 N, 60 W–45 E) is evaluated for 2005–2006. We use high spatial resolution hourly satellite ocean skin temperature data to determine the diurnal warming (ΔSST). The CO2 flux is then computed using three different temperature fields – a foundation temperature (Tf, measured at a depth where there is no diurnal variation), Tf, plus the hourly ΔSST and Tf, plus the monthly average of the ΔSSTs. This is done in conjunction with a physically-based parameterisation for the gas transfer velocity (NOAA-COARE). The differences between the fluxes evaluated for these three different temperature fields quantify the effects of both diurnal warming and diurnal covariations. We find that including diurnal warming increases the CO2 flux out of this region of the Atlantic for 2005–2006 from 9.6 Tg C a−1 to 30.4 Tg C a−1 (hourly ΔSST) and 31.2 Tg C a−1 (monthly average of ΔSST measurements). Diurnal warming in this region, therefore, has a large impact on the annual net CO2 flux but diurnal covariations are negligible. However, in this region of the Atlantic the uptake and outgassing of CO2 is approximately balanced over the annual cycle, so although we find diurnal warming has a very large effect here, the Atlantic as a whole is a very strong carbon sink (e.g. −920 Tg C a−1 Takahashi et al., 2002) making this is a small contribution to the Atlantic carbon budget.

Estimating Annual CO2 Flux for Lutjewad Station Using Three Different Gap-Filling Techniques

Long-term measurements of CO2 flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO2 flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set. The performances of gap-filling techniques were analysed by calculating statistical criteria: coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), maximum absolute error (MaxAE), and mean square bias (MSB). The gap-fill accuracy is seasonally dependent, with better results in cold seasons. The highest accuracy is obtained using ANN technique which is also less sensitive to environmental/seasonal conditions. We argue that filling gaps directly on measured CO2 fluxes is more advantageous than the common method of filling gaps on calculated net ecosystem change, because ANN is an empirical method and smaller scatter is expected when gap filling is applied directly to measurements.