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Objectives: We explore the importance of SARS-CoV-2 sentinel surveillance testing in primary care during a regional COVID-19 outbreak in Austria.
Design: Prospective cohort study.
Setting: A single sentinel practice serving 22 829 people in the ski-resort of Schladming-Dachstein.
Participants: All 73 patients presenting with mild-to-moderate flu-like symptoms between 24 February and 03 April, 2020.
Intervention: Nasopharyngeal sampling to detect SARS-CoV-2 using real-time reverse transcriptase-quantitative PCR (RT-qPCR).
Outcome measures: We compared RT-qPCR at presentation with confirmed antibody status. We split the outbreak in two parts, by halving the period from the first to the last case, to characterise three cohorts of patients with confirmed infection: early acute (RT-qPCR reactive) in the first half; and late acute (reactive) and late convalescent (non-reactive) in the second half. For each cohort, we report the number of cases detected, the accuracy of RT-qPCR, the duration and variety of symptoms, and the number of viral clades present.
Results: Twenty-two patients were diagnosed with COVID-19 (eight early acute, seven late acute and seven late convalescent), 44 patients tested SARS-CoV-2 negative and 7 were excluded. The sensitivity of RT-qPCR was 100% among all acute cases, dropping to 68.1% when including convalescent. Test specificity was 100%. Mean duration of symptoms for each group were 2 days (range 1–4) among early acute, 4.4 days (1–7) among late acute and 8 days (2–12) among late convalescent. Confirmed infection was associated with loss of taste. Acute infection was associated with loss of taste, nausea/vomiting, breathlessness, sore throat and myalgia; but not anosmia, fever or cough. Transmission clusters of three viral clades (G, GR and L) were identified.
Conclusions: RT-qPCR testing in primary care can rapidly and accurately detect SARS-CoV-2 among people with flu-like illness in a heterogeneous viral outbreak. Targeted testing in primary care can support national sentinel surveillance of COVID-19.
Aim: It can be challenging to distinguish COVID-19 in children from other common infections. We set out to determine the rate at which children consulting a primary care paediatrician with an acute infection are infected with SARS-CoV-2 and to compare distinct findings. Method: In seven out-patient clinics, children aged 0–13 years with any new respiratory or gastrointestinal symptoms and presumed infection were invited to be tested for SARS-CoV-2. Factors that were correlated with testing positive were determined. Samples were collected from 25 January 2021 to 01 April 2021. Results: Seven hundred and eighty-three children participated in the study (median age 3 years and 0 months, range 1 month to 12 years and 11 months). Three hundred and fifty-eight were female (45.7%). SARS-CoV-2 RNA was detected in 19 (2.4%). The most common symptoms in children with as well as without detectable SARS-CoV-2 RNA were rhinitis, fever and cough. Known recent exposure to a case of COVID-19 was significantly correlated with testing positive, but symptoms or clinical findings were not. Conclusion: COVID-19 among the children with symptoms of an acute infection was uncommon, and the clinical presentation did not differ significantly between children with and without evidence of an infection with SARS-CoV-2.
We compare multiplicities as well as rapidity and transverse momentum distributions of protons, pions and kaons calculated within presently available transport approaches for heavy ion collisions around 1 AGeV. For this purpose, three reactions have been selected: Au+Au at 1 and 1.48 AGeV and Ni+Ni at 1.93 AGeV.
Aim: It can be challenging to distinguish COVID-19 in children from other common infections. We set out to determine the rate at which children consulting a primary care paediatrician with an acute infection are infected with SARS-CoV-2 and to compare distinct findings. Method: In seven out-patient clinics, children aged 0–13 years with any new respiratory or gastrointestinal symptoms and presumed infection were invited to be tested for SARS-CoV-2. Factors that were correlated with testing positive were determined. Samples were collected from 25 January 2021 to 01 April 2021. Results: Seven hundred and eighty-three children participated in the study (median age 3 years and 0 months, range 1 month to 12 years and 11 months). Three hundred and fifty-eight were female (45.7%). SARS-CoV-2 RNA was detected in 19 (2.4%). The most common symptoms in children with as well as without detectable SARS-CoV-2 RNA were rhinitis, fever and cough. Known recent exposure to a case of COVID-19 was significantly correlated with testing positive, but symptoms or clinical findings were not. Conclusion: COVID-19 among the children with symptoms of an acute infection was uncommon, and the clinical presentation did not differ significantly between children with and without evidence of an infection with SARS-CoV-2.
Sleep is regulated in a time-of-day dependent manner and profits working memory. However, the impact of the circadian timing system as well as contributions of specific sleep properties to this beneficial effect remains largely unexplored. Moreover, it is unclear to which extent inter-individual differences in sleep-wake regulation depend on circadian phase and modulate the association between sleep and working memory. Here, sleep electroencephalography (EEG) was recorded during a 40-h multiple nap protocol, and working memory performance was assessed by the n-back task 10 times before and after each scheduled nap sleep episode. Twenty-four participants were genotyped regarding a functional polymorphism in adenosine deaminase (rs73598374, 12 G/A-, 12 G/G-allele carriers), previously associated with differences in sleep-wake regulation. Our results indicate that genotype-driven differences in sleep depend on circadian phase: heterozygous participants were awake longer and slept less at the end of the biological day, while they exhibited longer non rapid eye movement (NREM) sleep and slow wave sleep concomitant with reduced power between 8–16 Hz at the end of the biological night. Slow wave sleep and NREM sleep delta EEG activity covaried positively with overall working memory performance, independent of circadian phase and genotype. Moreover, REM sleep duration benefitted working memory particularly when occurring in the early morning hours and specifically in heterozygous individuals. Even though based on a small sample size and thus requiring replication, our results suggest genotype-dependent differences in circadian sleep regulation. They further indicate that REM sleep, being under strong circadian control, boosts working memory performance according to genotype in a time-of-day dependent manner. Finally, our data provide first evidence that slow wave sleep and NREM sleep delta activity, majorly regulated by sleep homeostatic mechanisms, is linked to working memory independent of the timing of the sleep episode within the 24-h cycle.
Background: Identification of families at risk for ovarian cancer offers the opportunity to consider prophylactic surgery thus reducing ovarian cancer mortality. So far, identification of potentially affected families in Germany was solely performed via family history and numbers of affected family members with breast or ovarian cancer. However, neither the prevalence of deleterious variants in BRCA1/2 in ovarian cancer in Germany nor the reliability of family history as trigger for genetic counselling has ever been evaluated.
Methods: Prospective counseling and germline testing of consecutive patients with primary diagnosis or with platinum-sensitive relapse of an invasive epithelial ovarian cancer. Testing included 25 candidate and established risk genes. Among these 25 genes, 16 genes (ATM, BRCA1, BRCA2, CDH1, CHEK2, MLH1, MSH2, MSH6, NBN, PMS2, PTEN, PALB2, RAD51C, RAD51D, STK11, TP53) were defined as established cancer risk genes. A positive family history was defined as at least one relative with breast cancer or ovarian cancer or breast cancer in personal history.
Results: In total, we analyzed 523 patients: 281 patients with primary diagnosis of ovarian cancer and 242 patients with relapsed disease. Median age at primary diagnosis was 58 years (range 16–93) and 406 patients (77.6%) had a high-grade serous ovarian cancer. In total, 27.9% of the patients showed at least one deleterious variant in all 25 investigated genes and 26.4% in the defined 16 risk genes. Deleterious variants were most prevalent in the BRCA1 (15.5%), BRCA2 (5.5%), RAD51C (2.5%) and PALB2 (1.1%) genes. The prevalence of deleterious variants did not differ significantly between patients at primary diagnosis and relapse. The prevalence of deleterious variants in BRCA1/2 (and in all 16 risk genes) in patients <60 years was 30.2% (33.2%) versus 10.6% (18.9%) in patients ≥60 years. Family history was positive in 43% of all patients. Patients with a positive family history had a prevalence of deleterious variants of 31.6% (36.0%) versus 11.4% (17.6%) and histologic subtype of high grade serous ovarian cancer versus other showed a prevalence of deleterious variants of 23.2% (29.1%) and 10.2% (14.8%), respectively. Testing only for BRCA1/2 would miss in our series more than 5% of the patients with a deleterious variant in established risk genes.
Conclusions: 26.4% of all patients harbor at least one deleterious variant in established risk genes. The threshold of 10% mutation rate which is accepted for reimbursement by health care providers in Germany was observed in all subgroups analyzed and neither age at primary diagnosis nor histo-type or family history sufficiently enough could identify a subgroup not eligible for genetic counselling and testing. Genetic testing should therefore be offered to every patient with invasive epithelial ovarian cancer and limiting testing to BRCA1/2 seems to be not sufficient.
Plattenepithelkarzinome des oberen Aerodigestivtraktes (SCCHN) sind Karzinome, die in den westlichen Industrienationen mit dem sechsten Rang in den Tumorstatistiken recht häufig sind. Ihre Inzidenz ist positiv mit einem erhöhten Tabak- und Alkoholkonsum und dem männlichen Geschlecht korreliert. Die Standardtherapie besteht in der Regel in einer operativen Sanierung und einer adjuvanten Radio- beziehungsweise Radio-Chemotherapie. Eine Induktionschemotherapie verspricht fortgeschrittene Primärtumoren und Tumoren vor einer operativen Intervention zu verkleinern. Jedoch besteht hierbei immer noch das Problem der hohen Rezidivfreundlichkeit dieser Tumoren, die wahrscheinlich mit der hohen Anzahl an G0-Phase-Zellen korreliert ist. Die vorliegende Arbeit hat die Frage untersucht, ob es möglich ist mit einer vorgeschalteten Stimulation durch Wachstumsfaktoren die Anzahl der G0-Phase-Zellen signifikant zu reduzieren und dadurch die gesamte Population der Tumorzellen sensibler für eine chemotherapeutische Intervention zu machen. Hierbei wurden besonders die Wachstumsfaktoren EGF und Serotonin als Stimulus verwendet. Die untersuchten Chemotherapeutika waren Mab425 und ZD1839, die die Signaltransduktion über einen EGFR-vermittelten Weg blockieren, sowie Docetaxel und Cisplatin, die als zytotoxische Substanzen wirksam sind. Die Untersuchungen wurden in vitro an drei Zelllinien durchgeführt. Detroit-562 und A431 bezogen wir von ATCC. Die Zelllinie UMSCC-10B wurde uns freundlicherweise von Thomas Carey von der University of Michigan zur Verfügung gestellt. Im Rahmen von Sondierungsversuchen stimulierten die Zellen mit IL-6, Serotonin, EGF und GCSF und fanden mit Hilfe der FACS-Analyse heraus, dass eine Kombination von EGF und Serotonin zur am stärksten ausgeprägten Stimulation der von uns untersuchten Zellen führte. In einem dreiphasigen Versuchsablauf wurden vier verschiedene Probengruppen untersucht. Zum einen eine Kontrollgruppe, die weder stimuliert noch chemotherapiert wurde. Eine Gruppe, die vor einer chemotherapeutischen Intervention mit Serotonin und EGF stimuliert wurde. Eine weitere Gruppe, die ausschließlich mit Serotonin und EGF stimuliert wurde und eine Gruppe, die nur eine Chemotherapie erhielt. Nach der Kultivierung der entsprechenden Proben, wurden die Zellen geerntet und zur Weiterverarbeitung vorbereitet. Es wurde mit Hilfe der Western-Blot-Analyse die Aktivität der Proteine untersucht, die an der über EGFR vermittelten Signaltransduktion beteiligt sind. Dazu wurden Antikörper gegen Proteine der Signaltransduktion eingesetzt, die dann mit Hilfe von zweiten Antikörpern erkannt wurden. Zum anderen wurden immunhistochemische Zellausstriche angefertigt mit einer Antikörperfärbung gegen das Kernprotein Ki-67, die uns zwischen proliferierenden und nichtproliferierenden Zellen unterscheiden ließ. Es erfolgte eine Auswertung der Gesamtzellanzahl bezogen auf die Reduktion der G0-Phase-Zellen. Die statistische Auswertung erfolgte mittels des Mann-Withney-U-Tests und des Wilcoxon- Tests. Hierbei lag das Signifikanzniveau bei 5%. Als Ergebnis kann man festhalten, dass eine signifikante Reduktion der Anzahl an G0-Phase-Zellen bei einer Vorstimulation und anschließender Chemotherapie durch Docetaxel oder Cisplatin zu beobachten war. Eine chemotherapeutische Intervention durch Mab425 und ZD1839 führte zwar zu einer Reduktion der Zellanzahl, aber nicht zu vergleichbar signifikanten Ergebnissen wie bei einer Intervention mit Docetaxel oder Cisplatin. Hieraus lässt sich der Schluss ableiten, dass eine chemotherapeutische Intervention auf Basis einer Blockade der durch EGFR vermittelten Signaltransduktion nicht ausreichend ist, es also einer zytotoxischen Komponente bedarf, um die Gesamtzellzahl signifikant zu reduzieren. Trotzdem nicht bei allen untersuchten Chemotherapeutika eine signifikante Reduktion der G0-Phase-Zellen beobachtet werden konnte, zeigten unsere Untersuchungen zum ersten Mal, dass durch eine Stimulation mit Wachstumsfaktoren vor einer chemotherapeutischen Intervention, die Sensibilität der Tumorzellen bei SCCHN für eine Chemotherapie durch eine Reduktion der G0-Phase-Zellen erhöht wird.
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
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.