935 resultados para Soil carbon change


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Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

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Our understanding of Earth's carbon climate system depends critically upon interactions between rising atmospheric CO2, changing land use, and nitrogen limitation on vegetation growth. Using a global land model, we show how these factors interact locally to generate the global land carbon sink over the past 200 years. Nitrogen constraints were alleviated by N2 fixation in the tropics and by atmospheric nitrogen deposition in extratropical regions. Nonlinear interactions between land use change and land carbon and nitrogen cycling originated from three major mechanisms: (i) a sink foregone that would have occurred without land use conversion; (ii) an accelerated response of secondary vegetation to CO2 and nitrogen, and (iii) a compounded clearance loss from deforestation. Over time, these nonlinear effects have become increasingly important and reduce the present-day net carbon sink by ~40% or 0.4 PgC yr−1.

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A recent study relying purely on statistical analysis of relatively short time series suggested substantial re-thinking of the traditional view about causality explaining the detected rising trend of atmospheric CO2 (atmCO2) concentrations. If these results are well-justified then they should surely compel a fundamental scientific shift in paradigms regarding both atmospheric greenhouse warming mechanism and global carbon cycle. However, the presented work suffers from serious logical deficiencies such as, 1) what could be the sink for fossil fuel CO2 emissions, if neither the atmosphere nor the ocean – as suggested by the authors – plays a role? 2) What is the alternative explanation for ocean acidification if the ocean is a net source of CO2 to the atmosphere? Probably the most provocative point of the commented study is that anthropogenic emissions have little influence on atmCO2 concentrations. The authors have obviously ignored the reconstructed and directly measured carbon isotopic trends of atmCO2 (both δ13C, and radiocarbon dilution) and the declining O2/N2 ratio, although these parameters provide solid evidence that fossil fuel combustion is the major source of atmCO2 increase throughout the Industrial Era.

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Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.

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Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs.

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Activated carbon has become a widely used tool to investigate root-mediated allelopathy of plants, especially in plant invasion biology, because it adsorbs and thereby neutralizes root exudates. Allelopathy has been a controversially debated phenomenon for years, which revived in plant invasion biology as one possible reason for the success of invasive plants. Noxious plant exudates may harm other plants and provide an advantage to the allelopathic plant. However, root exudates are not always toxic, but may stimulate the microbial community and change nutrient availability in the rhizosphere. In a greenhouse experiment, we investigated the interacting effects of activated carbon, arbuscular mycorrhiza and plant competition between the invasive Senecio inaequidens and the native Artemisia vulgaris. Furthermore, we tested whether activated carbon showed any undesired effects by directly affecting mycorrhiza or soil chemistry. Contrary to the expectation, S. inaequidens was a weak competitor and we could not support the idea that allelopathy was involved in the competition. Activated carbon led to a considerable increase in the aboveground biomass production and reduced the infection with arbuscular mycorrhiza of both plant species. We expected that arbuscular mycorrhiza promotes plant growth by increasing nutrient availability, but we found the contrary when activated carbon was added. Chemical analyses of the substrate showed, that adding activated carbon resulted in a strong increase in plant available phosphate and in a decrease of the C(organic)/N(total) ration both of which suggest stimulated microbial activity. Thus, activated carbon not only reduced potential allelopathic effects, but substantially changed the chemistry of the substrate. These results show that activated carbon should be handled with great care in ecological experiments on allelopathy because of possible confounding effects on the soil community.

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In a first step to obtain a proxy record of past climatic events (including the El Ni (n) over tildeo-Southern Oscillation) in the normally aseasonal tropical environment of Sabah, a radial segment from a recently fallen dipterocarp (Shorea Superba) was radiocarbon dated and subjected to carbon isotope analysis. The high-precision radiocarbon results fell into the ambiguous modern plateau where several calibrated dates can exist for each sample. Dating was achieved by wiggle matching using a Bayesian approach to calibration. Using the defined growth characteristics of Shorea superba, probability density distributions were calculated and improbable dates rejected. It was found that the tree most likely started growing around AD 1660-1685. A total of 173 apparent growth increments were measured and, therefore, it could be determined that the tree formed one ring approximately every two years. Stable carbon isotope values were obtained from resin-extracted wholewood from each ring. Carbon cycling is evident in the `juvenile effect', resulting from the assimilation of respired carbon dioxide and lower light levels below the canopy, and in the `anthropogenic effect' caused by increased industrial activity in the late-nineteenth and twentieth centuries. This study demonstrates that palaeoenvironmental information can be obtained from trees growing in aseasonal environments, where climatic conditions prevent the formation of well-defined annual rings.

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In this study, we assess the climate mitigation potential from afforestation in a mountainous snow-rich region (Switzerland) with strongly varying environmental conditions. Using radiative forcing calculations, we quantify both the carbon sequestration potential and the effect of albedo change at high resolution. We calculate the albedo radiative forcing based on remotely sensed data sets of albedo, global radiation and snow cover. Carbon sequestration is estimated from changes in carbon stocks based on national inventories. We first estimate the spatial pattern of radiative forcing (RF) across Switzerland assuming homogeneous transitions from open land to forest. This highlights where forest expansion still exhibits climatic benefits when including the radiative forcing of albedo change. Second, given that forest expansion is currently the dominant land-use change process in the Swiss Alps, we calculate the radiative forcing that occurred between 1985 and 1997. Our results show that the net RF of forest expansion ranges from −24 W m−2 at low elevations of the northern Prealps to 2 W m−2 at high elevations of the Central Alps. The albedo RF increases with increasing altitude, which offsets the CO2 RF at high elevations with long snow-covered periods, high global radiation and low carbon sequestration. Albedo RF is particularly relevant during transitions from open land to open forest but not in later stages of forest development. Between 1985 and 1997, when overall forest expansion in Switzerland was approximately 4%, the albedo RF offset the CO2 RF by an average of 40%. We conclude that the albedo RF should be considered at an appropriately high resolution when estimating the climatic effect of forestation in temperate mountainous regions.

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Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

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The Tibetan Plateau has a significant role with regard to atmospheric circulation and the monsoon in particular. Changes between a closed plant cover and open bare soil are one of the striking effects of land use degradation observed with unsustainable range management or climate change, but experiments investigating changes of surface properties and processes together with atmospheric feedbacks are rare and have not been undertaken in the world's two largest alpine ecosystems, the alpine steppe and the Kobresia pygmaea pastures of the Tibetan Plateau. We connected measurements of micro-lysimeter, chamber, 13C labelling, and eddy covariance and combined the observations with land surface and atmospheric models, adapted to the highland conditions. This allowed us to analyse how three degradation stages affect the water and carbon cycle of pastures on the landscape scale within the core region of the Kobresia pygmaea ecosystem. The study revealed that increasing degradation of the Kobresia turf affects carbon allocation and strongly reduces the carbon uptake, compromising the function of Kobresia pastures as a carbon sink. Pasture degradation leads to a shift from transpiration to evaporation while a change in the sum of evapotranspiration over a longer period cannot be confirmed. The results show an earlier onset of convection and cloud generation, likely triggered by a shift in evapotranspiration timing when dominated by evaporation. Consequently, precipitation starts earlier and clouds decrease the incoming solar radiation. In summary, the changes in surface properties by pasture degradation found on the highland have a significant influence on larger scales.