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Background
Cytochrome-P450 (CYP450) epoxygenases metabolise arachidonic acid (AA) into four different biologically active epoxyeicosatrienoic acid (EET) regioisomers. Three of the EETs (i.e., 8,9-, 11,12- and 14,15-EET) are rapidly hydrolysed by the enzyme soluble epoxide hydrolase (sEH). Here, we investigated the role of sEH in nociceptive processing during peripheral inflammation.
Results
In dorsal root ganglia (DRG), we found that sEH is expressed in medium and large diameter neurofilament 200-positive neurons. Isolated DRG-neurons from sEH-/- mice showed higher EET and lower DHET levels. Upon AA stimulation, the largest changes in EET levels occurred in culture media, indicating both that cell associated EET concentrations quickly reach saturation and EET-hydrolyzing activity mostly effects extracellular EET signaling. In vivo, DRGs from sEH-deficient mice exhibited elevated 8,9-, 11,12- and 14,15-EET-levels. Interestingly, EET levels did not increase at the site of zymosan-induced inflammation. Cellular imaging experiments revealed direct calcium flux responses to 8,9-EET in a subpopulation of nociceptors. In addition, 8,9-EET sensitized AITC-induced calcium increases in DRG neurons and AITC-induced calcitonin gene related peptide (CGRP) release from sciatic nerve axons, indicating that 8,9-EET sensitizes TRPA1-expressing neurons, which are known to contribute to mechanical hyperalgesia. Supporting this, sEH-/- mice showed increased nociceptive responses to mechanical stimulation during zymosan-induced inflammation and 8,9-EET injection reduced mechanical thresholds in naive mice.
Conclusion
Our results show that the sEH can regulate mechanical hyperalgesia during inflammation by inactivating 8,9-EET, which sensitizes TRPA1-expressing nociceptors. Therefore we suggest that influencing the CYP450 pathway, which is actually highly considered to treat cardiovascular diseases, may cause pain side effects.
Background Anti-angiogenic treatment is believed to have at least cystostatic effects in highly vascularized tumours like pancreatic cancer. In this study, the treatment effects of the angiogenesis inhibitor Cilengitide and gemcitabine were compared with gemcitabine alone in patients with advanced unresectable pancreatic cancer. Methods A multi-national, open-label, controlled, randomized, parallel-group, phase II pilot study was conducted in 20 centers in 7 countries. Cilengitide was administered at 600 mg/m2 twice weekly for 4 weeks per cycle and gemcitabine at 1000 mg/m2 for 3 weeks followed by a week of rest per cycle. The planned treatment period was 6 four-week cycles. The primary endpoint of the study was overall survival and the secondary endpoints were progression-free survival (PFS), response rate, quality of life (QoL), effects on biological markers of disease (CA 19.9) and angiogenesis (vascular endothelial growth factor and basic fibroblast growth factor), and safety. An ancillary study investigated the pharmacokinetics of both drugs in a subset of patients. Results Eighty-nine patients were randomized. The median overall survival was 6.7 months for Cilengitide and gemcitabine and 7.7 months for gemcitabine alone. The median PFS times were 3.6 months and 3.8 months, respectively. The overall response rates were 17% and 14%, and the tumor growth control rates were 54% and 56%, respectively. Changes in the levels of CA 19.9 went in line with the clinical course of the disease, but no apparent relationships were seen with the biological markers of angiogenesis. QoL and safety evaluations were comparable between treatment groups. Pharmacokinetic studies showed no influence of gemcitabine on the pharmacokinetic parameters of Cilengitide and vice versa. Conclusion There were no clinically important differences observed regarding efficacy, safety and QoL between the groups. The observations lay in the range of other clinical studies in this setting. The combination regimen was well tolerated with no adverse effects on the safety, tolerability and pharmacokinetics of either agent.
Bericht der Arbeitsgruppe Technik zur Vorbereitung des Programms "Retrospektive Digitalisierung von Bibliotheksbeständen" im Förderbereich "Verteilte Digitale Forschungsbibliothek" Arbeitssitzungen am 14. Mai 1996 (Frankfurt a. M.), 29.-30. Juli 1996 (München), 12.-13. Dezember 1996 (Göttingen) Mitglieder der Arbeitsgruppe: Prof. Dr. Rudolf Bayer, Technische Universität München, Fakultät für Informatik Dr. Jürgen Bunzel, Deutsche Forschungsgemeinschaft, Bonn Dr. Marianne Dörr, Bayerische Staatsbibliothek München Dr. Reinhard Ecker, Beilstein-Institut bzw. ABC Datenservice GmbH, Frankfurt/Main Dipl.-Math. Heinz-Werner Hoffmann, Hochschulbibliothekszentrum NRW, Köln (als Gast für die AG der Verbundsysteme) Dr. Norbert Lossau, Niedersächsische Staats- und Universitätsbibliothek Göttingen (DFG-Projekt ‘Verteilte Digitale Forschungsbibliothek’) Prof. Dr. Elmar Mittler, Niedersächsische Staats- und Universitätsbibliothek Göttingen Dipl.-Inf. Christian Mönch, FB Informatik der J.W. Goethe-Universität Frankfurt Dr. Wilhelm R. Schmidt, Stadt- und Universitätsbibliothek Frankfurt Dr. Hartmut Weber, Landesarchivdirektion, Stuttgart
The occupation of dental assistants (DAs) involves many health risks of the musculoskeletal system due to static and prolonged work, which can lead to musculoskeletal disorders (MSDs). The aim of the study was to investigate the prevalence of MSDs in DAs in Germany. Methods: For this purpose, an online questionnaire analyzed 406 (401 female participants and 5 male participants, 401w/5m) DAs. It was based on the Nordic Questionnaire (lifetime, 12-month, and seven-day MSDs’ prevalence separated into neck, shoulder, elbow, wrist, upper back, lower back, hip, knee, and ankle), and occupational and sociodemographic questions as well as questions about specific medical conditions. Results: 98.5% of the participants reported complaints of at least one body region in their lives, 97.5% reported at least one complaint in the last 12 months and 86.9% affirmed at least one complaint in the last seven days. For lifetime, 12-month and seven-day prevalence, the neck was the region that was most affected followed by the shoulder, the upper back and the lower back. Conclusion: The prevalence of MSDs among German (female) DAs was very high. The most affected area is the neck, followed by the shoulder, the lower back, and the upper back. It, therefore, seems necessary to devote more attention to ergonomics at the working practice of DAs as well in education and in dental work.
Background: Dentists are at a higher risk of suffering from musculoskeletal disorders (MSD) than the general population. However, the latest study investigating MSD in the dental profession in Germany was published about 20 years ago. Therefore, the aim of this study was to reveal the current prevalence of MSD in dentists and dental students in Germany. Methods: The final study size contained 450 (287 f/163 m) subjects of different areas of specialization. The age of the participants ranged from 23 to 75 years. The questionnaire consisted of a modified version of the Nordic Questionnaire, work-related questions from the latest questionnaire of German dentists, typical medical conditions and self-developed questions. Results: The overall prevalence showed that dentists suffered frequently from MSD (seven days: 65.6%, twelve months: 92%, lifetime: 95.8%). The most affected body regions included the neck (42.7%–70.9%–78.4%), shoulders (29.8%–55.6%–66.2%) and lower back (22.9%–45.8%–58.7%). Overall, female participants stated that they suffered from pain significantly more frequently, especially in the neck, shoulders and upper back. Conclusion: The prevalence of MSD among dentists, especially in the neck, shoulder and back area, was significantly higher than in the general population. In addition, women suffered more frequently from MSD than men in almost all body regions.
Background: Dentists (Ds) and dental assistants (DAs) have a high lifetime prevalence of musculoskeletal disorders (MSDs). In this context, it is assumed that they have an increased intake of substances such as pain medication. Currently, there exist no data on the use of medication among Ds and DAs with MSDs in Germany. Methods: The online questionnaire (i.e., the Nordic Questionnaire) analysed the medical therapies used by 389 Ds (240 f/149 m) and 406 DAs (401 f/5 m) to treat their MSDs. Results: Ds (28.3–11.5%) and DAs (29.4–10.3%) with MSDs took medication depending on the affected body region. A trend between the Ds and DAs in the intake of drug therapy and the frequency was found for the neck region (Ds: 21.1%, DAs: 28.7%). A single medication was taken most frequently (Ds: 60.0–33.3%, DAs: 71.4–27.3%). The frequency of use varied greatly for both occupational groups depending on the region affected. Conclusion: Ds and DAs perceived the need for medical therapies because of their MSDs. Painkillers such as ibuprofen and systemic diclofenac were the medications most frequently taken by both occupational groups. The intake of pain killers, most notably for the neck, should prevent sick leave.
Background: dental professionals suffer frequently from musculoskeletal disorders (MSD). Dentists and dental assistants work closely with each other in a mutually dependent relationship. To date, MSD in dental assistants have only been marginally investigated and compared to their occurrence in dentists. Therefore, the aim of this study was to compare the prevalence of MSD between dentists and dental assistants by considering occupational factors, physical activity and gender. Methods: This was a cross-sectional observational study. A Germany-wide survey, using a modified version of the Nordic Questionnaire and work-related questions, was applied. In total, 2548 participants took part, of which 389 dentists (240 females and 149 males) and 322 dental assistants (320 females and 2 males) were included in the analysis. Data were collected between May 2018 and May 2019. Differences between the dentists and dental assistants were determined by using the Chi2 test for nominal and the Wilcoxon–Mann–Whitney U test for both ordinal and non-normally distributed metric data. Results: A greater number of dental assistants reported complaints than dentists in all queried body regions. Significant differences in the most affected body regions (neck, shoulders, wrist/hands, upper back, lower back and feet/ankles) were found for the lifetime prevalence, annual prevalence and weekly prevalence. Data from the occupational factors, physical activity and gender analyses revealed significant differences between dentists and dental assistants. Conclusions: Dental assistants appear to be particularly affected by MSD when compared to dentists. This circumstance can be explained only to a limited extent by differences in gender distribution and occupational habits between the occupations.
Environmental change impacts on the C- and N-cycle of European forests: a model comparison study
(2013)
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m−2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m−2 y−1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.
Strong seasonal variability of hygric and thermal soil conditions are a defining environmental feature in northern Australia. However, how such changes affect the soil–atmosphere exchange of nitrous oxide (N2O), nitric oxide (NO) and dinitrogen (N2) is still not well explored. By incubating intact soil cores from four sites (three savanna, one pasture) under controlled soil temperatures (ST) and soil moisture (SM) we investigated the release of the trace gas fluxes of N2O, NO and carbon dioxide (CO2). Furthermore, the release of N2 due to denitrification was measured using the helium gas flow soil core technique. Under dry pre-incubation conditions NO and N2O emissions were very low (<7.0 ± 5.0 μg NO-N m−2 h−1; <0.0 ± 1.4 μg N2O-N m−2 h−1) or in the case of N2O, even a net soil uptake was observed. Substantial NO (max: 306.5 μg N m−2 h−1) and relatively small N2O pulse emissions (max: 5.8 ± 5.0 μg N m−2 h−1) were recorded following soil wetting, but these pulses were short lived, lasting only up to 3 days. The total atmospheric loss of nitrogen was generally dominated by N2 emissions (82.4–99.3% of total N lost), although NO emissions contributed almost 43.2% to the total atmospheric nitrogen loss at 50% SM and 30 °C ST incubation settings (the contribution of N2 at these soil conditions was only 53.2%). N2O emissions were systematically higher for 3 of 12 sample locations, which indicates substantial spatial variability at site level, but on average soils acted as weak N2O sources or even sinks. By using a conservative upscale approach we estimate total annual emissions from savanna soils to average 0.12 kg N ha−1 yr−1 (N2O), 0.68 kg N ha−1 yr−1 (NO) and 6.65 kg N ha−1 yr−1 (N2). The analysis of long-term SM and ST records makes it clear that extreme soil saturation that can lead to high N2O and N2 emissions only occurs a few days per year and thus has little impact on the annual total. The potential contribution of nitrogen released due to pulse events compared to the total annual emissions was found to be of importance for NO emissions (contribution to total: 5–22%), but not for N2O emissions. Our results indicate that the total gaseous release of nitrogen from these soils is low and clearly dominated by loss in the form of inert nitrogen. Effects of seasonally varying soil temperature and moisture were detected, but were found to be low due to the small amounts of available nitrogen in the soils (total nitrogen <0.1%).
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon source was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Strong seasonal variability of hygric and thermal soil conditions are a defining environmental feature in Northern Australia. However, how such changes affect the soil–atmosphere exchange of nitrous oxide (N2O), nitric oxide (NO) and dinitrogen (N2) is still 5 not well explored. By incubating intact soil cores from four sites (3 savanna, 1 pasture) under controlled soil temperatures (ST) and soil moisture (SM) we investigated the release of the trace gas fluxes of N2O, NO and carbon dioxide (CO2). Furthermore, the release of N2 due to denitrification was measured using the helium gas flow soil core technique. Under dry pre-incubation conditions NO and N2O emission were very low (< 7.0± 5.0 μgNO-Nm−2 h−1; < 0.0± 1.4 μgN2O-Nm−2 h−1) or in case of N2O, even a net soil uptake was observed. Substantial NO (max: 306.5 μgNm−2 h−1) and relatively small N2O pulse emissions (max: 5.8±5.0 μgNm−2 h−1) were recorded following soil wetting, but these pulses were short-lived, lasting only up to 3 days. The total atmospheric loss of nitrogen was dominated by N2 emissions (82.4–99.3% of total N lost), although NO emissions contributed almost 43.2% at 50% SM and 30 °C ST. N2O emissions were systematically higher for 3 of 12 sample locations, which indicates substantial spatial variability at site level, but on average soils acted as weak N2O sources or even sinks. Emissions were controlled by SM and ST for N2O and CO2, ST and pH for NO, and SM and pH for N2.
Assessing 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.
Assessing the uncertainties of simulation results of ecological models is becoming of increasing importance, specifically if these models are used to estimate greenhouse gas emissions at 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 showed that by means of the joined 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 the 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 (Residual mean squared error (RMSE) NO: 2.5 to 21.3 g N ha−1 d−1, N2O: 0.2 to 21.4 g N ha−1 d−1, CO2: 5.8 to 12.6 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes limited to accurately predict observed seasonal variations in fluxes.
Tropical forest soils are a significant source for the greenhouse gas N2O as well as for NO, a precursor of tropospheric ozone. However, current estimates are uncertain due to the limited number of field measurements. Furthermore, there is considerable spatial and temporal variability of N2O and NO emissions due to the variation of environmental conditions such as soil properties, vegetation characteristics and meteorology. In this study we used a process-based model (ForestDNDC-tropica) to estimate N2O and NO emissions from tropical highland forest (Nyungwe) soils in southwestern Rwanda. To extend the model inputs to regional scale, ForestDNDC-tropica was linked to an exceptionally large legacy soil dataset. There was agreement between N2O and NO measurements and the model predictions though the ForestDNDC-tropica resulted in considerable lower emissions for few sites. Low similarity was specifically found for acidic soil with high clay content and reduced metals, indicating that chemo-denitrification processes on acidic soils might be under-represented in the current ForestDNDC-tropica model. The results showed that soil bulk density and pH are the most influential factors driving spatial variations in soil N2O and NO emissions for tropical forest soils. The area investigated (1113 km2) was estimated to emit ca. 439 ± 50 t N2O-N yr−1 (2.8–5.5 kg N2O-N ha−1 yr−1) and 244 ± 16 t NO-N yr−1 (0.8–5.1 kg N ha−1 yr−1). Consistent with less detailed studies, we confirm that tropical highland rainforest soils are a major source of atmospheric N2O and NO.
Spatial variations of nitrogen trace gas emissions from tropical mountain forests in Nyungwe, Rwanda
(2012)
Globally, 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. Therefore, 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 positive correlation with free iron and a negative correlation with soil pH (only N2O). 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 benefit from spatially explicit trace gas emission estimates linked to basic soil property data and differentiating between biological and chemical pathways for N trace gas formation.
Globally, 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.