35 resultados para soil organic matter
Resumo:
There is much interest in the identification of the main drivers controlling changes in the microbial community that may be related to sustainable land use. We examined the influence of soil properties and land-use intensity (N fertilization, mowing, grazing) on total phospholipid fatty acid (PLFA) biomass, microbial community composition (PLFA profiles) and activities of enzymes involved in the C, N, and P cycle. These relationships were examined in the topsoil of grasslands from three German regions (Schorfheide-Chorin (SCH), Hainich-Dun (HAI), Schwabische Alb (ALB)) with different parent material. Differences in soil properties explained 60% of variation in PLFA data and 81% of variation in enzyme activities across regions and land-use intensities. Degraded peat soils in the lowland areas of the SCH with high organic carbon (OC) concentrations and sand content contained lower PLFA biomass, lower concentrations of bacterial, fungal, and arbuscular mycorrhizal PLFAs, but greater enzyme activities, and specific enzyme activities (per unit microbial biomass) than mineral soils in the upland areas of the HAI and ALB, which are finer textured, drier, and have smaller OC concentrations. After extraction of variation that originated from large-scale differences among regions and differences in land-use intensities between plots, soil properties still explained a significant amount of variation in PLFA data (34%) and enzyme activities (60%). Total PLFA biomass and all enzyme activities were mainly related to OC concentration, while relative abundance of fungi and fungal to bacterial ratio were mainly related to soil moisture. Land-use intensity (LUI) significantly decreased the soil C:N ratio. There was no direct effect of LUI on total PLFA biomass, microbial community composition, N and P cycling enzyme activities independent of study region and soil properties. In contrast, the activities and specific activities of enzymes involved in the C cycle increased significantly with LUI independent of study region and soil properties, which can have impact on soil organic matter decomposition and nutrient cycling. Our findings demonstrate that microbial biomass and community composition as well as enzyme activities are more controlled by soil properties than by grassland management at the regional scale. (C) 2013 Elsevier B.V: All rights reserved.
Resumo:
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.
Resumo:
The decomposition of soil organic matter (SOM) is temperature dependent, but its response to a future warmer climate remains equivocal. Enhanced rates of decomposition of SOM under increased global temperatures might cause higher CO2 emissions to the atmosphere, and could therefore constitute a strong positive feedback. The magnitude of this feedback however remains poorly understood, primarily because of the difficulty in quantifying the temperature sensitivity of stored, recalcitrant carbon that comprises the bulk (>90%) of SOM in most soils. In this study we investigated the effects of climatic conditions on soil carbon dynamics using the attenuation of the 14C ‘bomb’ pulse as recorded in selected modern European speleothems. These new data were combined with published results to further examine soil carbon dynamics, and to explore the sensitivity of labile and recalcitrant organic matter decomposition to different climatic conditions. Temporal changes in 14C activity inferred from each speleothem was modelled using a three pool soil carbon inverse model (applying a Monte Carlo method) to constrain soil carbon turnover rates at each site. Speleothems from sites that are characterised by semi-arid conditions, sparse vegetation, thin soil cover and high mean annual air temperatures (MAATs), exhibit weak attenuation of atmospheric 14C ‘bomb’ peak (a low damping effect, D in the range: 55–77%) and low modelled mean respired carbon ages (MRCA), indicating that decomposition is dominated by young, recently fixed soil carbon. By contrast, humid and high MAAT sites that are characterised by a thick soil cover and dense, well developed vegetation, display the highest damping effect (D = c. 90%), and the highest MRCA values (in the range from 350 ± 126 years to 571 ± 128 years). This suggests that carbon incorporated into these stalagmites originates predominantly from decomposition of old, recalcitrant organic matter. SOM turnover rates cannot be ascribed to a single climate variable, e.g. (MAAT) but instead reflect a complex interplay of climate (e.g. MAAT and moisture budget) and vegetation development.
Resumo:
Excessive runoff and soil erosion in the upper Blue Nile Basin poses a threat that has attracted the attention of the Ethiopian government because of the serious on-site effects in addition to downstream effects, such as the siltation of water harvesting structures and reservoirs. The objective of the study was to evaluate and recommend effective biophysical soil and water conservation measure(s) in the Debre Mewi watershed, about 30 km south of the Lake Tana. Six conservation measures were evaluated for their effects on runoff, soil loss, and forage yield using runoff plots. There was a significant difference between treatments for both runoff and soil loss. The four-year average annual soil loss in the different plots ranged from 26 to 71 t ha−1, and total runoff ranged from 180 to 302 mm, while annual rainfall varied between 854 mm in 2008 and 1247 mm in 2011. Soil bund combined with elephant grass had the lowest runoff and soil loss as compared to the other treatments, whereas the untreated control plot had the highest for both parameters. As an additional benefit, 2.8 and 0.7 t ha−1 year−1 of dried forage was obtained from elephant and local grasses, respectively. Furthermore, it was found that soil bund combined with Tephrosia increased soil organic matter by 13% compared to the control plot. Soil bund efficiency was significantly enhanced by combining them with biological measures and improved farmers’ perception of soil and water conservation measures.
Resumo:
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.
Resumo:
The role of Soil Organic Carbon (SOC) in mitigating climate change, indicating soil quality and ecosystem function has created research interested to know the nature of SOC at landscape level. The objective of this study was to examine variation and distribution of SOC in a long-term land management at a watershed and plot level. This study was based on meta-analysis of three case studies and 128 surface soil samples from Ethiopia. Three sites (Gununo, Anjeni and Maybar) were compared after considering two Land Management Categories (LMC) and three types of land uses (LUT) in quasi-experimental design. Shapiro-Wilk tests showed non-normal distribution (p = 0.002, a = 0.05) of the data. SOC median value showed the effect of long-term land management with values of 2.29 and 2.38 g kg-1 for less and better-managed watersheds, respectively. SOC values were 1.7, 2.8 and 2.6 g kg-1 for Crop (CLU), Grass (GLU) and Forest Land Use (FLU), respectively. The rank order for SOC variability was FLU>GLU>CLU. Mann-Whitney U and Kruskal-Wallis test showed a significant difference in the medians and distribution of SOC among the LUT, between soil profiles (p<0.05, confidence interval 95%, a = 0.05) while it is not significant (p>0.05) for LMC. The mean and sum rank of Mann Whitney U and Kruskal Wallis test also showed the difference at watershed and plot level. Using SOC as a predictor, cross-validated correct classification with discriminant analysis showed 46 and 49% for LUT and LMC, respectively. The study showed how to categorize landscapes using SOC with respect to land management for decision-makers.
Resumo:
Background and Aims: The response of forest ecosystems to continuous nitrogen (N) deposition is still uncertain. We investigated imports and exports of dissolved N from mull-type organic layers to identify the controls of N leaching in Central European beech forests under continuous N deposition. Methods: Dissolved N fluxes with throughfall and through mull-type organic layers (litter leachate) were measured continuously in 12 beech forests on calcareous soil in two regions in Germany over three consecutive growing seasons. Results Mean growing season net (i.e. litter leachate – throughfall flux) fluxes of total dissolved N (TDN) from the organic layer were low (2.3 ± 5.6 kg ha −1 ) but varied widely from 12.9 kg ha −1 to –8.3 kg ha −1 . The small increase of dissolved N fluxes during the water passage through mull-type organic layers suggested that high turnover rates coincided with high microbial N assimilation and plant N uptake. Stand basal area had a positive feedback on N fluxes by providing litter for soil organic matter forma- tion. Plant diversity, especially herb diversity, reduced dissolved N fluxes. Soil fauna biomass increased NO3−-N fluxes with litter leachate by stimulating mineralization. Microbial biomass measures were not related to dissolved N fluxes. Conclusions Our results show that dissolved N exports from organic layers contain significant amounts of throughfall-derived N (mainly NO3−-N) that flushes through the organic layer but also highlight that N leaching from organic layers is driven by the complex interplay of plants, animals and microbes. Furthermore, diverse understories reduce N leaching from Central European beech forests.
Resumo:
On the orbiter of the Rosetta spacecraft, the Cometary Secondary Ion Mass Analyser (COSIMA) will provide new in situ insights about the chemical composition of cometary grains all along 67P/Churyumov–Gerasimenko (67P/CG) journey until the end of December 2015 nominally. The aim of this paper is to present the pre-calibration which has already been performed as well as the different methods which have been developed in order to facilitate the interpretation of the COSIMA mass spectra and more especially of their organic content. The first step was to establish a mass spectra library in positive and negative ion mode of targeted molecules and to determine the specific features of each compound and chemical family analyzed. As the exact nature of the refractory cometary organic matter is nowadays unknown, this library is obviously not exhaustive. Therefore this library has also been the starting point for the research of indicators, which enable to highlight the presence of compounds containing specific atom or structure. These indicators correspond to the intensity ratio of specific peaks in the mass spectrum. They have allowed us to identify sample containing nitrogen atom, aliphatic chains or those containing polyaromatic hydrocarbons. From these indicators, a preliminary calibration line, from which the N/C ratio could be derived, has also been established. The research of specific mass difference could also be helpful to identify peaks related to quasi-molecular ions in an unknown mass spectrum. The Bayesian Positive Source Separation (BPSS) technique will also be very helpful for data analysis. This work is the starting point for the analysis of the cometary refractory organic matter. Nevertheless, calibration work will continue in order to reach the best possible interpretation of the COSIMA observations.