778 research outputs found
Advancing national greenhouse gas inventories for agriculture in developing countries : improving activity data, emission factors and software technology
No full textPeer reviewe
Data for: Quantifying effects of soil properties on N2O and CO2 emissions from excreta deposited onto tropical pastures in Kenya
No full text3x Excel files summarizing cumulative N2O/ CO2 emissions, soil and excreta properties6x SIGMA plot graph files with all individual dat
Soil organic carbon changes following degradation and conversion to cypress and tea plantations in a tropical mountain forest in Kenya
No full textAims This study investigates, in a montane forest in Kenya, the changes in amount and stability of soil organic carbon (SOC) as a consequence of: a) forest degradation, by comparing primary and degraded forests; b) the replacement of degraded forests with cypress and tea plantations, by considering sites installed at different time in the past. Methods The SOC concentrations and stocks were determined in different layers to 1 m depth, and the SOC turnover time (TT) derived by measuring the 14C concentration in the layers within the 0–30 cm depth. Results A significant SOC decline was evident in the 0–5 and 5–15 cm layers of degraded forest while, on the long term, both plantations induced a significant SOC increase in the 0–30 cm depth. The longer TT’s and lower SOC concentrations in the upper layers of degraded rather than primary forests imply an impact of forest degradation on the decomposition of the fast cycling SOC. Similarly, the shorter TT with increasing plantations age implies differences in SOC stabilization mechanisms between plantations and forests. Conclusions Cypress and tea plantations established on degraded forests stimulate a long term SOC accrual but at the same time decrease the stability of the SOC pool
Simulating mycorrhiza contribution to forest C- and N cycling-the MYCOFON model
No full textAlthough mycorrhiza has been identified to be of major importance for plant nutrition and ecosystem stability, existing C- and N- simulation models on the ecosystem scale do not explicitly consider the feedbacks between ectomycorrhizal fungi and plants. We present a simple dynamic feedback model which allows estimating the main C- and N- flows between ectomycorrhizal fungi and tree roots in order to test the sensitivity of the system fungus-tree to environmental parameters and to assess the fungal contribution to plant N nutrition. Sensitivity tests carried out showed that the model responses to variations of model parameters, particularly with regard to N availability, are in agreement with published results from field and laboratory studies. However, there are still some processes and parameters which are not well constrained. Fungal N uptake rates and the ratio between mycelium, hartig net, and mantle biomass are parameters which significantly affect model results but for which published data are scarce or missing. Nevertheless, the model is already providing a platform to test our understanding of the importance of mycorrhiza for forest stand nutrition. Future coupling to a mechanistic ecosystem model will allow simulating the importance of mycorrhization for e.g. stand growth and C and N retention
Parameter-induced uncertainty quantification of soil N₂O, NO and CO₂ emission from Höglwald spruce forest (Germany) using the LandscapeDNDC model
No full textAssessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes
Evaluating annual nitrous oxide fluxes at the ecosystem scale
No full textEvaluation of N(2)O flux has been one of the most problematic topics in environmental biogeochemistry over the last 10-15 years. Early ideas that we should be able to use the large body of existing research on terrestrial N cycling to predict patterns of N(2)O flux at the ecosystem scale have been hard to prove due to extreme temporal and spatial variability in flux. The vast majority of the N(2)O flux measurement and modeling activity that has taken place has been process lever and field scale, i.e., measurement, analysis and modeling of hourly and daily fluxes with chambers deployed in field plots. It has been very difficult to establish strong predictive relationships between these hourly and daily fluxes and field-scale parameters such as temperature, soil moisture, and soil inorganic N concentrations. In this study, we addressed the question of whether we can increase our predictive understanding of N(2)O fluxes by examining relationships between flux and environmental parameters at larger spatial and temporal scales, i.e., to explore relationships between annual rather than hourly or daily fluxes and ecosystem-scale variables such as plant community and soil type and annual climate rather than field-scale variables such as soil moisture and temperature. We addressed this question by examining existing data on annual fluxes from temperate forest, cropland, and rangeland ecosystems, analyzing both multiyear data sets from individual sites as well as cross-site comparison of single annual flux values from multiple sites. Results suggest that there are indeed coherent patterns in annual N(2)O flux at the ecosystem scale in forest, cropland, and rangeland ecosystems but that these patterns vary by region and only emerge with continuous (at least daily) flux measurements over multiple years. An ecosystem approach to evaluating N(2)O fluxes will be useful for regional and global modeling and for computation of national N(2)O flux inventories for regulatory purposes but only if measurement programs are comprehensive and continuous
Soil-atmosphere exchange of N 2 O, CH 4 , and CO 2 and controlling environmental factors for tropical rain forest sites in western Kenya
No full text[1] N 2 O, CH 4 and CO 2 soil-atmosphere exchange and controlling environmental factors were studied for a 3-month period (dry-wet season transition) at the Kakamega Rain forest, Kenya, Africa, using an automated measurement system. The mean N 2 O emission was 42.9 ± 0.7 mg N m À2 h À1 (range: 1.1-324.8 mg N m À2 h À1 ). Considering the duration of dry and wet season the annual N 2 O emission was estimated at 2.6 ± 1.2 kg N ha À1 yr À1 . Large pulse emissions of N 2 O were observed after the first rainfall events of the wet season, and the magnitude of N 2 O emissions steadily declined thereafter. A comparable trend in soil CO 2 emissions (mean: 71.8 ± 0.3 mg C m À2 h À1 ) indicates that the rapid mineralization of litter accumulated during the dry period produced the high N 2 O emissions at the start of the wet season. Manual N 2 O emission measurements at four additional rain forest sites were comparable to those measured at the main site, whereas N 2 O emissions measured at a regrowth site were significantly lower. Spatial differences in N 2 O emissions could be explained by differences in soil texture and topsoil C:N-ratio (CO 2 : subsoil C and N concentrations), whereas the temporal variability of N 2 O and CO 2 emissions was primarily driven by soil moisture. Soils predominantly acted as sinks for CH 4 (À56.4 ± 0.8 mg C m À2 h À1 ). For some chamber positions, episodes of net CH 4 release were observed, which could be due to high WFPS and/or termite activity. CH 4 fluxes were weakly correlated with soil moisture levels but showed no relation to temperature, texture, pH, carbon or nitrogen contents. Citation: Werner, C., R. Kiese, and K. Butterbach-Bahl (2007), Soil-atmosphere exchange of N 2 O, CH 4 , and CO 2 and controlling environmental factors for tropical rain forest sites in western Kenya
Spatial variations of nitrogen trace gas emissions from tropical mountain forests in Nyungwe, Rwanda [Discussion paper]
No full textGlobally, tropical forest soils represent the second largest source of N2O and NO. However, there is still considerable uncertainty on the spatial variability and soil properties controlling N trace gas emission. To investigate how soil properties affect N2O and NO emission, we carried out an incubation experiment with soils from 31 locations in the Nyungwe tropical mountain forest in southwestern Rwanda. All soils were incubated at three different moisture levels (50, 70 and 90% water filled pore space (WFPS)) at 17 °C. Nitrous oxide emission varied between 4.5 and 400 μg N m−2 h−1, while NO emission varied from 6.6 to 265 μg N m−2 h−1. Mean N2O emission at different moisture levels was 46.5 ± 11.1 (50% WFPS), 71.7 ± 11.5 (70% WFPS) and 98.8 ± 16.4 (90% WFPS) μg N m−2 h−1, while mean NO emission was 69.3 ± 9.3 (50% WFPS), 47.1 ± 5.8 (70% WFPS) and 36.1 ± 4.2 (90% WFPS) μg N m−2 h−1. The latter suggests that climate (i.e. dry vs. wet season) controls N2O and NO emissions. Positive correlations with soil carbon and nitrogen indicate a biological control over N2O and NO production. But interestingly N2O and NO emissions also showed a negative correlation (only N2O) with soil pH and a positive correlation with free iron. The latter suggest that chemo-denitrification might, at least for N2O, be an important production pathway. In conclusion improved understanding and process based modeling of N trace gas emission from tropical forests will not only benefit from better spatial explicit trace gas emission and basic soil property monitoring, but also by differentiating between biological and chemical pathways for N trace gas formation
Mallit metsämaan hiilivarastojen ennustajina
No full textTutkimusselosteSeloste artikkelista: Peltoniemi, M., Thürig, E., Ogle, S., Palosuo, T., Schrumpf, M., Wutzler, T., Butterbach-Bahl, K., Chertov, O., Komarov, A., Mikhailov, A., Gärdenäs, A., Perry, C., Liski, J., Smith, P. & Mäkipää, R. 2007. Models in country scale carbon accounting of forest soils. Silva Fennica 41(3): 575–602
Association of JAK-STAT pathway related genes with lymphoma risk: results of a European case-control study (EpiLymph)
No full textPrevious studies have suggested an important role for the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signalling pathway in tumour development. Therefore, we explored genetic variants in JAK-STAT pathway associated genes with lymphoma risk. In samples of the EpiLymph case-control study we genotyped 1536 single nucleotide polymorphisms (SNPs) using GoldenGate BeadArrayTM Technology (Illumina, San Diego, CA, USA). Here, we report the associations between selected SNPs and haplotypes of the JAK-STAT pathway and risk of Hodgkin lymphoma (HL), B-cell non-Hodgkin lymphoma (B-NHL) and most frequent B-NHL subtypes. Among 210 relevant JAK-STAT pathway-related SNPs, polymorphisms in nine genes (BMF, IFNG, IL12A, SOCS1, STAT1, STAT3, STAT5A, STAT6, TP63) were significantly associated with lymphoma risk. At a study-wise significance level, we obtained a risk reduction of 28% among carriers of the heterozygous genotype of the STAT3 variant (rs1053023) for B-NHL. For six other variants within the STAT3 gene we observed an inverse association with different lymphoma subtypes. A reduced risk for HL was observed for the heterozygous genotype of the STAT6 SNP (rs324011). This is an explorative investigation to examine associations between JAK-STAT signalling related genes and lymphoma risk. The results implicate a relevant role of certain pathway-related genes in lymphomagenesis, but still need to be approved by independent studies
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