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Genetics contribute to smoking cessation, which is important for cancer prevention. Prior genetic studies, limited by short-term follow-up, have not examined multiple quit attempts and relapse events experienced by most smokers. This research investigated genetic associations with smoking relapse throughout adulthood. Participants were from two, all-female longitudinal cohort studies and included 12,060 European ancestry ever-smokers with existing genotype data who quit smoking at ≥1 timepoint. Median follow-up was 32 years. Associations between selected SNPs and odds of relapse and, conditional on relapse, SNP associations with proportion of follow-up relapsed were modeled using zero-inflated beta regression. Genotype by menopausal status interactions were evaluated. Women with AA genotypes for CHRNA5 SNP rs16969968 G>A or CHRNA3 SNP rs1051730 G>A (P-value = 0.04 for both) had lower odds of relapse. Among women who relapsed, those with CC genotypes of CHRNA5 SNPs rs588765 T>C (P-value = 0.04) and rs680244 T>C (P-value = 0.048) and AA genotype of DRD2 SNP rs6277 G>A (P-value = 0.01) had higher proportion follow-up in relapse. Associations were stronger among postmenopausal women (genotype by menopause interactions: rs588765 P-value = 0.003, rs680244 P-value = 0.001, rs6277 P-value = 0.04). Women with AA or AG genotypes for COMT SNP rs4680 G>A (P-value = 0.03) had lower proportion follow-up relapsed. This study identified SNP associations with likelihood of relapse or proportion of follow-up in relapse. Several associations were stronger among postmenopausal women. The findings demonstrate the importance of long-term follow-up and factors unique to women when characterizing smoking phenotypes. Prevention Relevance: This study is the first to quantify genetic associations with smoking relapse among female smokers throughout adulthood. These findings could inform precision medicine approaches to improve long-term smoking relapse prevention to reduce smoking attributable cancer morbidity and mortality.

Introduction Smoking cessation is more than 50% heritable. Genetic studies of smoking cessation have been limited by short-term follow-up or cross-sectional design. Aims and Methods This study tests single nucleotide polymorphism (SNP) associations with cessation during long-term follow-up throughout adulthood in women. The secondary aim tests whether genetic associations differ by smoking intensity. Associations between 10 SNPs in CHRNA5, CHRNA3, CHRNB2, CHRNB4, DRD2, and COMT and the probability of smoking cessation over time were evaluated in two longitudinal cohort studies of female nurses, the Nurses’ Health Study (NHS) (n = 10 017) and NHS-2 (n = 2793). Participant follow-up ranged from 2 to 38 years with data collected every 2 years. Results Women with the minor allele of either CHRNA5 SNP rs16969968 or CHRNA3 SNP rs1051730 had lower odds of cessation throughout adulthood [OR = 0.93, p-value = .003]. Women had increased odds of cessation if they had the minor allele of CHRNA3 SNP rs578776 [OR = 1.17, p-value = .002]. The minor allele of DRD2 SNP rs1800497 was associated with lower odds of cessation in moderate-to-heavy smokers [OR = 0.92, p-value = .0183] but increased odds in light smokers [OR = 1.24, p-value = .096]. Conclusions Some SNP associations with short-term smoking abstinence observed in prior studies were shown in the present study to persist throughout adulthood over decades of follow-up. Other SNP associations with short-term abstinence did not persist long-term. The secondary aim findings suggest genetic associations may differ by smoking intensity. Implications The results of the present study expand on previous studies of SNP associations in relation to short-term smoking cessation to demonstrate some of these SNPs were associated with smoking cessation throughout decades of follow-up, whereas other SNP associations with short-term abstinence did not persist long-term. The rate of relapse to smoking remains high for several years after quitting smoking, and many smokers experience multiple quit attempts and relapse episodes throughout adulthood. Understanding genetic associations with long-term cessation has potential importance for precision medicine approaches to long-term cessation management.

Nicotine produces its effects by binding to nicotinic acetylcholine receptors (nAChRs). Variants of genes encoding properties of nAChRs are candidates for affecting likelihood of smoking cessation.A systematic review was conducted summarizing evidence of associations between single nucleotide polymorphisms (SNPs) of nAChR genes and smoking cessation. From 24 articles meeting inclusion criteria, summary odds ratios (ORs) for associations between nine SNPs and smoking cessation were calculated from 26 studies (N = 233-29,072) stratified by gene, ancestry, study design, and pharmacotherapy; SNPs in linkage disequilibrium were pooled. Results for a tenth SNP from two GWAS were summarized.People of European ancestry with minor alleles of CHRNA5 rs16969968 and CHRNA3 rs1051730 had longer time to cessation [HR = 0.90, 95 % CI 0.88 - 0.92 (n = 2 studies)] and lower odds of cessation [OR = 0.88, 95 % CI 0.80 - 0.97 (n = 5 cohort studies), OR = 0.64, 95 % CI 0.45 - 0.90 (n = 4 placebo arms)]. Risk of persistent smoking associated with these alleles was attenuated in smokers receiving nicotine replacement therapy (NRT). Recipients of bupropion alone or with NRT with these alleles had higher, though not statistically significant, odds of cessation. Results for CHRNA5 rs588765 and rs680244 were similar to rs16969968/rs1051730 findings. Evidence was limited for other SNPs.Evidence consistently indicates the minor alleles of four SNPs within CHRNA3 or CHRNA5 are risk alleles for cessation failure. Analysis by pharmacotherapy revealed bupropion may be the most efficacious intervention for people with these alleles.

Cigarette smoking is a major contributor to the cancer burden, so identifying genetic variants associated with smoking cessation is important for cancer prevention. Prior genetic studies of smoking cessation have been limited by short-term follow-up and not accounting for quit attempts and relapse events experienced by most smokers. In this study, candidate SNPs previously found to be associated with smoking cessation were studied in relation to smoking relapse throughout adulthood. Participants were from two, all-female longitudinal cohort studies with repeated smoking behavior measurements collected every 2 years. The study included 12,060 ever-smokers of European ancestry with genotype data who quit smoking at ≥1 timepoint. Median follow-up after first quitting smoking was 32 years. Associations between selected single nucleotide polymorphisms (SNPs) and odds of smoking relapse and, conditional on relapse, SNP associations with the proportion of follow-up in relapse were modeled using zero-inflated beta regression. Genotype by menopausal status interactions were evaluated. Women with AA genotypes for CHRNA5 SNP rs16969968 G>A or CHRNA3 SNP rs1051730 G>A (p-value = 0.04 for both) had lower odds of relapse. Among women who relapsed, those with AA genotypes for CHRNA5 SNPs rs588765 G>A or rs680244 G>A had 2.6% [95% CI 0.1 - 5.0%] and 2.4% [95% CI 0.2 - 4.9%] more follow-up in smoking relapse, respectively, compared to women with AG or GG genotypes. Women with AA or AG genotypes for DRD2 SNP rs6277 G>A had 3.3% [95% CI 0.8 - 5.7%] more follow-up in relapse than women with GG genotypes. In contrast, women with AA genotypes for COMT SNP rs4680 G>A had 2.7% [95% CI 0.2 - 5.2%] lower proportion of follow-up in relapse than women with AG or GG genotypes. These associations with the proportion of follow-up in relapse were stronger among post-menopausal women. The association of SNPs rs588765, rs680244, and rs6277 with a higher proportion of follow-up in relapse was significantly stronger among women who quit smoking post-menopause [rs588765 difference in proportion follow-up in relapse = 9.5% (95% CI 3.8 -15.2%), rs680244 difference in proportion follow-up in relapse = 10.1% (95% CI 4.4% - 15.9%), rs6277 difference in proportion follow-up in relapse = 7.6% (95% CI 1.5 - 13.6%)]. No statistically significant difference in proportion follow-up in relapse by genotype was observed among women who quit smoking prior to menopause. Several SNPs were not associated with odds of smoking relapse but, conditional on relapse, were associated with the proportion of follow-up in relapse. The findings show selected genetic variants contribute to susceptibility to smoking relapse in the long term and that the genetic risk can differ by the stage of smoking cessation. For several SNPs stronger associations were observed among post-menopausal women, indicating the importance of menopausal status. Citation Format: Stephanie K. Jones, Anthony J. Alberg, Kristin Wallace, Brett Froeliger, Matthew J. Carpenter, Bethany J. Wolf. Genetic associations with smoking relapse and proportion of follow-up in relapse throughout adulthood in pre- and post-menopausal women. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4182.

ZC3H14 (Zinc finger CysCysCysHis domain-containing protein 14), an evolutionarily conserved member of a class of tandem zinc finger (CCCH) polyadenosine (polyA) RNA binding proteins, is associated with a form of heritable, nonsyndromic autosomal recessive intellectual disability. Previous studies of a loss of function mouse model, Zc3h14Δex13/Δex13, provide evidence that ZC3H14 is essential for proper brain function, specifically for working memory. To expand on these findings, we analyzed the dendrites and dendritic spines of hippocampal neurons from Zc3h14Δex13/Δex13 mice, both in situ and in vitro. These studies reveal that loss of ZC3H14 is associated with a decrease in total spine density in hippocampal neurons in vitro as well as in the dentate gyrus of 5-month old mice analyzed in situ. This reduction in spine density in vitro results from a decrease in the number of mushroom-shaped spines, which is rescued by exogenous expression of ZC3H14. We next performed biochemical analyses of synaptosomes prepared from whole wild-type and Zc3h14Δex13/Δex13 mouse brains to determine if there are changes in steady state levels of postsynaptic proteins upon loss of ZC3H14. We found that ZC3H14 is present within synaptosomes and that a crucial postsynaptic protein, CaMKIIα, is significantly increased in these synaptosomal fractions upon loss of ZC3H14. Together, these results demonstrate that ZC3H14 is necessary for proper dendritic spine density in cultured hippocampal neurons and in some regions of the mouse brain. These findings provide insight into how a ubiquitously expressed RNA binding protein leads to neuronal-specific defects that result in brain dysfunction.

Managed grasslands are extensive terrestrial ecosystems that provide a range of services. In addition to supporting the world’s various livestock production systems they contain climatically significant amounts of carbon (C). Understanding and quantifying the C dynamics of managed grasslands is complicated yet crucial.This presentation describes a process-model of C dynamics in managed grasslands (DALEC-Grass). DALEC-Grass is a model of intermediate complexity, which calculates primary productivity, dynamicallyallocates C to biomass tissues and describes the impacts of grazing/harvesting activities. The model is integrated into a Bayesian model-data fusion framework (CARDAMOM). CARDAMOM uses observations of ecosystem functioning (e.g. leaf area, biomass, C fluxes) to optimise the model’s parameters while respecting a set of biogeochemical and physiological rules. The model evaluation results presented demonstrate the model’s skill in predicting primary productivity and C allocation patterns in UK grasslands using both ground and satellite based leaf area index (LAI) time series as observational constraints.

The evolutionarily conserved RNA exosome is a multisubunit ribonuclease complex that processes and/or degrades numerous RNAs. Recently, mutations in genes encoding both structural and catalytic subunits of the RNA exosome have been linked to human disease. Mutations in the structural exosome gene EXOSC2 cause a distinct syndrome that includes retinitis pigmentosa, hearing loss, and mild intellectual disability. In contrast, mutations in the structural exosome genes EXOSC3 and EXOSC8 cause pontocerebellar hypoplasia type 1b (PCH1b) and type 1c (PCH1c), respectively, which are related autosomal recessive, neurodegenerative diseases. In addition, mutations in the structural exosome gene EXOSC9 cause a PCH-like disease with cerebellar atrophy and spinal motor neuronopathy. Finally, mutations in the catalytic exosome gene DIS3 have been linked to multiple myeloma, a neoplasm of plasma B cells. How mutations in these RNA exosome genes lead to distinct, tissue-specific diseases is not currently well understood. In this chapter, we examine the role of the RNA exosome complex in human disease and discuss the mechanisms by which mutations in different exosome subunit genes could impair RNA exosome function and give rise to diverse diseases.

The evolutionarily conserved RNA exosome is a multisubunit ribonuclease complex that processes and/or degrades numerous RNAs. Recently, mutations in genes encoding both structural and catalytic subunits of the RNA exosome have been linked to human disease. Mutations in the structural exosome gene EXOSC2 cause a distinct syndrome that includes retinitis pigmentosa, hearing loss, and mild intellectual disability. In contrast, mutations in the structural exosome genes EXOSC3 and EXOSC8 cause pontocerebellar hypoplasia type 1b (PCH1b) and type 1c (PCH1c), respectively, which are related autosomal recessive, neurodegenerative diseases. In addition, mutations in the structural exosome gene EXOSC9 cause a PCH-like disease with cerebellar atrophy and spinal motor neuronopathy. Finally, mutations in the catalytic exosome gene DIS3 have been linked to multiple myeloma, a neoplasm of plasma B cells. How mutations in these RNA exosome genes lead to distinct, tissue-specific diseases is not currently well understood. In this chapter, we examine the role of the RNA exosome complex in human disease and discuss the mechanisms by which mutations in different exosome subunit genes could impair RNA exosome function and give rise to diverse diseases.

Grasslands are an important component of the global carbon (C) cycle, with a strong potential for C sequestration. However, an improved capacity to quantify grassland C stocks and monitor their variation in space and time, particularly in response to management, is needed in order to conserve and enhance grassland C reservoirs. To meet this challenge we outline and test here an approach to combine C cycle modelling with observational data. We implemented an intermediate complexity model, DALEC-Grass, within a probabilistic model-data fusion (MDF) framework, CARDAMOM, at two managed grassland sites (Easter Bush and Crichton) in the UK. We used 3 years (Easter Bush, 2002–2004) of management data and observations of leaf area index (LAI) and Net Ecosystem Exchange (NEE) from eddy covariance to calibrate the distributions of model parameters. Using these refined distributions, we then assimilated the remaining 7 years (Easter Bush, 2005–2010 and Crichton, 2015) of LAI observations and evaluated the simulated NEE, above and below-ground biomass and other C fluxes against independent data from the two grasslands. Our results show that fusing model predictions with LAI observations allowed the CARDAMOM MDF system to diagnose the effects of grazing and cutting realistically. The overlap of MDF-predicted and measured NEE (both sites) and ecosystem respiration (Easter Bush) was 92% and 83% respectively while the correlation coefficient (r) was 0.79 for both variables. This study lays the foundation for using MDF with satellite data on LAI to produce the spatially and temporally-resolved estimates of C cycling needed in shaping and monitoring the implementation of relevant policies and farm-management decisions.

The dynamic model Nitrogen Dynamics in Crop rotations in Ecological Agriculture (NDICEA) was used to assess the nitrogen (N), phosphorus (P) and potassium (K) balance of long-term organic cropping trials and typical organic crop rotations on a range of soil types and rainfall zones in the UK. The measurements of soil N taken at each of the organic trial sites were also used to assess the performance of NDICEA. The modeled outputs compared well to recorded soil N levels, with relatively small error margins. NDICEA therefore seems to be a useful tool for UK organic farmers. The modeling of typical organic rotations has shown that positive N balances can be achieved, although negative N balances can occur under high rainfall conditions and on lighter soil types as a result of leaching. The analysis and modeling also showed that some organic cropping systems rely on imported sources of P and K to maintain an adequate balance and large deficits of both nutrients are apparent in stockless systems. Although the K deficits could be addressed through the buffering capacity of minerals, the amount available for crop uptake will depend on the type and amount of minerals present, current cropping and fertilization practices and the climatic environment. A P deficit represents a more fundamental problem for the maintenance of crop yields and the organic sector currently relies on mined sources of P which represents a fundamental conflict with the International Federation of Organic Agriculture Movements organic principles.

International audience; Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2O)emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents.Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grass-land growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields(from 36% at stage 1 down to 4% on average) and grassland productivity (from 44%to 27%) and to a lesser and more variable extent for N2O emissions. Yield-scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N

Much of the uncertainty in crop and grassland model predictions of how arable and grassland systems respond to changes in management and environmental drivers can be attributed to differences in the structure of these models. This has created an urgent need for international bench- marking of models, in which uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty in model predictions (Asseng et al. , 2013). Simulations of C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions (Sandor et al. , 2016) and complicated by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C and N Models Inter-comparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide (C-N MIP) and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models that estimate C – N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model- intercomparison-on-agricultural-ghg-emissions). This study presents some preliminary results on the uncertainty of outputs from 12 grassland models, whereas exploring differences in model response when increasing data resources are used for model calibration.

We reviewed specific literature for emissions of ammonia (NH3) and odours from all stages of pig production together with nitrogen (N) leaching from raising pigs outdoors. Emissions of NH3 decrease with decreases in the crude protein (CP) content of pig diets, at all stages of manure management. The CPs of pig diets have been greatly reduced by matching the CP content to the protein required at each stage of the animals' growth and by using synthetic essential amino acids to minimise total CP intake. The CP contents of the dietary ingredients needed to provide energy for the animals impose further limits to reductions in dietary CP. Housing systems have been designed and evaluated which offer potential for reducing NH3 emissions. However such designs may not be applicable at all stages of the pigs' development and the careful management needed to ensure their effective working may be costly and difficult to implement on commercial farms. The factors behind odour emissions are less well characterised. Reducing diet CP to 160 g CP kg− 1 has been shown to reduce odour emissions but further CP reductions may increase them. Some reductions in odour emissions from buildings can be achieved by careful management of the ventilation rate but the most effective measures to reduce emissions of NH3 and odours are to cover slurry stores and to inject slurry into soil. Changes in the feeding and management of outdoor pigs mean that N leaching losses may be up to 50% less than previously reported. No studies have been undertaken that compare the N leached from pigs raised outdoors, versus that arising from the application of pig manure from an equal number of housed pigs. As a precursor to any field study, current models could be used to provide a first estimate of any systematic differences.

Intensively managed grazed grasslands in temperate climates are globally important environments for the exchange of the greenhouse gases (GHGs) carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). We assessed the N and C budget of a mostly grazed, occasionally cut, and fertilized grassland in SE Scotland by measuring or modelling all relevant imports and exports to the field as well as changes in soil C and N pools over time. The N budget was dominated by import from inorganic and organic fertilisers (21.9 g N m2 yr−1) and losses from leaching (5.3 g N m2 yr−1), N2 emissions and NOx and NH3 volatilisation (6.4 g N m2 yr−1). The efficiency of N use by animal products (meat and wool) averaged 11 %. On average over nine years (2002–2010) the balance of N fluxes suggested that 7.2 ± 4.6 g N m−2 y−1 (mean ± confidence interval at p > 0.95) were stored in the soil. The largest component of the C budget was the net ecosystem exchange of CO2 (NEE), at an average uptake rate of 218 ± 155 g C m−2 y−1 over the nine years. This sink strength was offset by carbon export from the field mainly as harvest (48.9 g C m2 yr−1) and leaching (16.4 g C m2 yr−1). The other export terms, CH4 emissions from the soil, manure applications and enteric fermentation were negligible and only contributed to 0.02–4.2 % of the total C losses. Only a small fraction of C was incorporated into the body of the grazing animals. Inclusion of these C losses in the budget resulted in a C sink strength of 163 ± 140 g C m−2 y−1. On the contrary, soil stock measurements taken in May 2004 and May 2011 indicated that the grassland sequestered N in the 0–60 cm soil layer at 4.51 ± 2.64 g N m−2 y−1 and lost C at a rate of 29.08 ± 38.19 g C m−2 y-1, respectively. Potential reasons for the discrepancy between these estimates are probably an underestimation of C and N losses, especially from leaching fluxes as well as from animal respiration. The average greenhouse gas (GHG) balance of the grassland was −366 ± 601 g CO2 eq m−2 y−1 and strongly affected by CH4 and N2O emissions. The GHG sink strength of the NEE was reduced by 54 % by CH4 and N2O emissions. Enteric fermentation from the ruminating sheep proved to be an important CH4 source, exceeding the contribution of N2O to the GHG budget in some years.

Nearly 5000 chamber measurements of CH4 flux were collated from 21 sites across the United Kingdom, covering a range of soil and vegetation types, to derive a parsimonious model that explains as much of the variability as possible, with the least input requirements. Mean fluxes ranged from -0.3 to 27.4 nmol CH4 m-2 s-1, with small emissions or low rates of net uptake in mineral soils (site means of -0.3 to 0.7 nmol m-2 s-1) and much larger emissions from organic soils (site means of -0.3 to 27.4 nmol m-2 s-1). Less than half of the observed variability in instantaneous fluxes could be explained by independent variables measured. The reasons for this include measurement error, stochastic processes and, probably most importantly, poor correspondence between the independent variables measured and the actual variables influencing the processes underlying methane production, transport and oxidation. When temporal variation was accounted for, and the fluxes averaged at larger spatial scales, simple models explained up to ca. 75% of the variance in CH4 fluxes. Soil carbon, peat depth, soil moisture and pH together provided the best sub-set of explanatory variables. However, where plant species composition data were available, this provided the highest explanatory power. Linear and nonlinear models generally fitted the data equally well, with the exception that soil moisture required a power transformation. To estimate the impact of changes in peatland water table on CH4 emissions in the United Kingdom, an emission factor of +0.4 g CH4 m-2 yr-1 per cm increase in water table height was derived from the data.

Fluxes of methane (CH4) and nitrous oxide (N2O) are commonly measured with closed static chambers. Here, we analyse several of the uncertainties inherent in these measurements, including the accuracy of calibration gases, repeatability of the concentration measurements, choice of model used to calculate the flux and lack of fit to the model, as well as inaccuracies in measurements of sampling time, temperature, pressure and chamber volume. In an analysis of almost 1000 flux measurements from six sites in the UK, the choice of model for calculating the flux and model lack-of-fit were the largest sources of uncertainty. The analysis provides confidence intervals based on the measurement errors, which are typically 20%. Our best estimate, using the best-fitting model, but substituting the linear model in the case of concave fits, gave a mean flux that is 25% greater than that calculated with the linear model. The best-fit non-linear model provided a better (convex) fit to the data than linear regression in 36% of the measurements. We demonstrate a method to balance the number of gas samples per chamber (nsamples) and the number of chambers, so as to minimize the total uncertainty in the estimate of the mean flux for a site with a fixed number of gas samples. The standard error generally decreased over the available range in nsamples, suggesting that more samples per chamber (at the expense of proportionally fewer chambers) would improve estimates of the mean flux at these sites.

Managed grasslands are known to be an important source of N2O with estimated global losses of 2.5 Tg N2O-N yr−1. Chambers are to date the most widely used method to measure N2O fluxes, but also micrometeorological methods are successfully applied. In this paper we present a comparison of N2O fluxes measured by non-steady state chambers and eddy covariance (EC) (using an ultra-sonic anemometer coupled with a tunable diode laser) from an intensively grazed and fertilised grassland site in South East Scotland. The measurements were taken after fertilisation events in 2003, 2007 and 2008. In four out of six comparison periods, a short-lived increase of N2O emissions was observed after mineral N application, returning to background level within 2–6 days. Highest fluxes were measured by both methods in July 2007 with maximum values of 1438 ng N2O-N m−2 s−1 (EC) and 651 ng N2O-N m−2 s−1 (chamber method). Negative fluxes above the detection limit were observed in all comparison periods by EC, while with chambers, the recorded negative fluxes were always below detection limit. Median and average fluxes over each period were always positive. Over all 6 comparison periods, 69% of N2O fluxes measured by EC at the time of chamber closure were within the range of the chamber measurements. N2O fluxes measured by EC during the time of chamber closure were not consistently smaller, neither larger, compared to those measured by chambers: this reflects the fact that the different techniques integrate fluxes over different spatial and temporal scales. Large fluxes measured by chambers may be representing local hotspots providing a small contribution to the flux measured by the EC method which integrates over a larger area. The spatial variability from chamber measurements was high, as shown by a coefficient of variation of up to 139%. No diurnal pattern of N2O fluxes was observed, possibly due to the small diurnal variations of soil temperature. The calculation of cumulative fluxes using different integration methods showed EC data provide generally lower estimates of N2O emissions than chambers.

Estimates of carbon leaching losses from different land use systems are few and their contribution to the net ecosystem carbon balance is uncertain. We investigated leaching of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and dissolved methane (CH4), at forests, grasslands, and croplands across Europe. Biogenic contributions to DIC were estimated by means of its δ13C signature. Leaching of biogenic DIC was 8.3±4.9 g m−2 yr−1 for forests, 24.1±7.2 g m−2 yr−1 for grasslands, and 14.6±4.8 g m−2 yr−1 for croplands. DOC leaching equalled 3.5±1.3 g m−2 yr−1 for forests, 5.3±2.0 g m−2 yr−1 for grasslands, and 4.1±1.3 g m−2 yr−1 for croplands. The average flux of total biogenic carbon across land use systems was 19.4±4.0 g C m−2 yr−1. Production of DOC in topsoils was positively related to their C/N ratio and DOC retention in subsoils was inversely related to the ratio of organic carbon to iron plus aluminium (hydr)oxides. Partial pressures of CO2 in soil air and soil pH determined DIC concentrations and fluxes, but soil solutions were often supersaturated with DIC relative to soil air CO2. Leaching losses of biogenic carbon (DOC plus biogenic DIC) from grasslands equalled 5–98% (median: 22%) of net ecosystem exchange (NEE) plus carbon inputs with fertilization minus carbon removal with harvest. Carbon leaching increased the net losses from cropland soils by 24–105% (median: 25%). For the majority of forest sites, leaching hardly affected actual net ecosystem carbon balances because of the small solubility of CO2 in acidic forest soil solutions and large NEE. Leaching of CH4 proved to be insignificant compared with other fluxes of carbon. Overall, our results show that leaching losses are particularly important for the carbon balance of agricultural systems.

As soil–atmosphere fluxes of greenhouse gases are characterized by high temporal fluctuations, frequent measurements in the range of hours to days need to be deployed, resulting in high analytical costs. We have therefore developed a new low-cost system that combines high-frequency automated sampling with low-frequency chemical analysis. The System for Inert Gas Monitoring by Accumulation (SIGMA) is suited particularly for stand-alone observations in remote locations. The SIGMA is connected to an automated chamber with headspace sampling several times per day. Air samples are aggregated in sampling bags, which reduces the number of subsequent laboratory analyses and allows calculation of average flux rates over extended sampling periods. The SIGMA was tested under field conditions and compared with a conventional autochamber system, where flux rates were measured several times per day. Sample air fillings of the SIGMA sampling bags varied less than 5% between bags and diverged

We present here a novel instrument for measuring surface–atmosphere exchange fluxes of ammonia. The instrument is the upgraded version of a recently developed near-infrared diode laser based photoacoustic ammonia concentration monitoring instrument, i.e. the original instrument is supplemented with two additional sampling lines, an appropriate gas handling system and an advanced software controlling gradient measurements. As a result of these developments, ammonia concentration can be measured simultaneously at three different heights above the ground and ammonia fluxes can be calculated from these data using the aerodynamic gradient method. The instrument operates fully automatically, requires minimal maintenance and has a temperature controlled, waterproof housing which makes it suitable for measurements even under harsh field conditions. Preliminary tests on stability and accuracy were carried out during two two-week field measurement campaigns, with the three sampling inlets being placed at the same height together with the inlet of a reference instrument. The readings of the three channels agreed well (with correlation coefficients above 0.96). Comparison to reference instruments showed good stability of the photoacoustic instrument, there was no measurable zero-drift or change in sensitivity during the tests. Flux measurements were carried out during a three-week field campaign in southern Scotland over fertilized grassland with reference to a wet-chemical AMANDA instrument in gradient configuration. Ammonia fluxes calculated from the data of the two instruments agreed well. Fluxes up to 2500 ng m −2 s −1 were observed after fertilization. The minimum detectable ammonia flux was calculated on the basis of “virtual ammonia fluxes”, from measurements carried out with all inlets at the same height and was found to be ±60 ng m −2 s −1 which ensures reliable measurements above intensively managed grasslands or agricultural fields.

The Drosophila dNab2 protein is an ortholog of human ZC3H14, a poly(A) RNA binding protein required for intellectual function. dNab2 supports memory and axon projection, but its molecular role in neurons is undefined. Here, we present a network of interactions that links dNab2 to cytoplasmic control of neuronal mRNAs in conjunction with the fragile X protein ortholog dFMRP. dNab2 and dfmr1 interact genetically in control of neurodevelopment and olfactory memory, and their encoded proteins co-localize in puncta within neuronal processes. dNab2 regulates CaMKII, but not futsch, implying a selective role in control of dFMRP-bound transcripts. Reciprocally, dFMRP and vertebrate FMRP restrict mRNA poly(A) tail length, similar to dNab2/ZC3H14. Parallel studies of murine hippocampal neurons indicate that ZC3H14 is also a cytoplasmic regulator of neuronal mRNAs. Altogether, these findings suggest that dNab2 represses expression of a subset of dFMRP-target mRNAs, which could underlie brain-specific defects in patients lacking ZC3H14.

The aim of this study was to quantify N2O release from temperate grassland receiving different forms of N, and to assess the importance of controlling variables in the environment. In 2002 and 2003 three organic manures (sewage sludge pellets, poultry manure and cattle slurry) and two mineral fertilisers (NH4NO3 and urea) were applied to grassland in SE Scotland. All plots except the control received N fertilisers at a rate of 300 kg available N ha−1 a−1 (available N includes NO3−, NH4+ and urea). Fluxes of N2O were measured using static chambers. Losses of N2O from plots receiving mineral fertiliser were short-lived with a peak value of 388 g N2O–N ha−1 day−1 from NH4NO3. Release of N2O from manure treatments however extended over a longer period and was greater in magnitude. Highest emissions were measured from sewage sludge treatments with a peak value of 3488 g N2O–N ha−1 day−1 and 26 times higher cumulative loss compared to the NH4NO3 treatment in 2002. A residual effect on N2O losses was observed from sewage sludge treatments in 2004 when the plots did not receive any fertiliser. There were considerable variations in fluxes between the years, which could be linked to differences in rainfall and temperature. The type of N applied affected the influence of these factors on N2O emissions. The amount of rainfall several days after the N application did not affect N2O fluxes on NH4NO3 treatments. However, in the sewage treated plots increased correlation coefficients were calculated when rainfall amounts over a longer period of time (up to 20 days) were included. A synergistic effect of rainfall and temperature on N2O fluxes could be observed on all treatments. A significant correlation between N2O fluxes and mineral soil N (NO3− and NH4+) was observed when soil water content was not limiting (r2 = 67%, p

Soil management practices that result in increased soil carbon (C) sequestration can make a valuable contribution to reducing the increase in atmospheric CO2 concentrations. We studied the effect of poultry manure, cattle slurry, sewage sludge, NH4NO3 or urea on C cycling and sequestration in silage grass production. Soil respiration, net ecosystem exchange (NEE) and methane (CH4) fluxes were measured with chambers, and soil samples were analysed for total C and dissolved organic C (DOC). Treatments were applied over 2 years and measurements were carried out over 3 years to assess possible residual effects. Organic fertilizer applications increased CO2 loss through soil respiration but also enhanced soil C storage compared with mineral fertilizer. Cumulative soil respiration rates were highest in poultry manure treatments with 13.7 t C ha−1 in 2003, corresponding to 1.6 times the control value, but no residual effect was seen. Soil respiration showed an exponential increase with temperature, and a bimodal relationship with soil moisture. The greatest NEE was observed on urea treatments (with a CO2 uptake of −4.4 g CO2 m−2 h−1). Total C and DOC were significantly greater in manure treatments in the soil surface (0–10 cm). Of the C added in the manures, 27% of that in the sewage pellets, 32% of that in the cattle slurry and 39% of that in the poultry manure remained in the 0–10 cm soil layer at the end of the experiment. Mineral fertilizer treatments had only small C sequestration rates, although uncertainties were high. Expressed as global warming potentials, the benefits of increased C sequestration on poultry manure and sewage pellet treatments were outweighed by the additional losses of N2O, particularly in the wet year 2002. Methane was emitted only for 2–3 days on cattle slurry treatments, but the magnitudes of fluxes were negligible compared with C losses by soil respiration.

Managed grasslands contribute to global warming by the exchange of the greenhouse gases carbon dioxide, nitrous oxide and methane. To reduce uncertainties of the global warming potential of European grasslands and to assess potential mitigation options, an integrated approach quantifying fluxes from all three gases is needed. Greenhouse gas emissions from a grassland site in the SE of Scotland were measured in 2002 and 2003. Closed static chambers were used for N2O and CH4 flux measurements, and samples were analysed by gas chromatography. Closed dynamic chambers were used for soil respiration measurements, using infrared gas analysis. Three organic manures and two inorganic fertilizers were applied at a rate of 300 kg N ha−1 a−1 (available N) and compared with a zero-N control on grassland plots in a replicated experimental design. Soil respiration from plots receiving manure was up to 1.6 times larger than CO2 release from control plots and up to 1.7 times larger compared to inorganic treatments (p

Atmospheric ammonia (NH3) exchange during a single growing season was measured over two grass/clover fields managed by cutting and treated with different rates of mineral nitrogen (N) fertilizer. The aim was to quantify the total NH3 exchange of the two systems in relation to their N budget, the latter was split into N derived from symbiotic fixation, from fertilization, and from the soil. The experimental site was located in an intensively managed agricultural area on the Swiss plateau. Two adjacent fields with mixtures of perennial ryegrass (Lolium perenne L.), cocks foot (Dactylis glomerata L.), white clover (Trifolium repens L.) and red clover (Trifolium pratense L.) were used. These were treated with either 80 or 160 kg N ha−1 applied as NH4NO3 fertilizer in equal portions after each of four cuts. Continuous NH3 flux measurements were carried out by micrometeorological techniques. To determine the contribution of each species to the overall NH3 canopy compensation point, stomatal NH3 compensation points of the individual plant species were determined on the basis of NH4+ + NH3 (NHx) concentrations and pH in the apoplast. Symbiotic N2 fixation was measured by the 15N dilution method.

A new study to address the biosphere-atmosphere exchange of ammonia (NH3) with grasslands is applying a European transect to interpret NH3 fluxes in relation to atmospheric conditions, grassland management and soil chemistry. Micrometeorological measurements using the aerodynamic gradient method (AGM) with continuous NH3 detectors are supported by bioassays of the NH3 `stomatal compensation point' (χs). Relaxed eddy accumulation (REA) is also applied to enable flux measurements at one height; this is relevant to help address flux divergence due to gas-particle inter-conversion or the presence of local sources in a landscape.

Remote sensing and inverse modelling studies indicate that the tropics emit more CH4 and N2O than predicted by bottom-up emissions inventories, suggesting that terrestrial sources are stronger or more numerous than previously thought. Tropical uplands are a potentially large and important source of CH4 and N2O often overlooked by past empirical and modelling studies. To address this knowledge gap, we investigated spatial, temporal and environmental trends in CH4 and N2O fluxes across a~long elevation gradient (600–3700 m a.s.l.) in the Kosñipata Valley, in the southern Peruvian Andes that experiences seasonal fluctuations in rainfall. The aim of this work was to produce preliminary estimates of CH4 and N2O fluxes from representative habitats within this region, and to identify the proximate controls on soil CH4 and N2O dynamics. Ecosystems across this altitudinal gradient were both atmospheric sources and sinks of CH4 on an annual basis. Montane grasslands (or, puna; 3200–3700 m a.s.l.) were strong atmospheric sources, emitting 56.94 ± 7.81kg CH4-C ha−1 yr−1. Upper montane forest (2200–3200 m a.s.l.) and lower montane forest (1200–2200 m a.s.l.) were net atmospheric sinks (−2.99 ± 0.29 kg CH4-C ha−1 yr−1 and −2.34 ± 0.29 kg CH4-C ha−1 yr−1, respectively); while premontane forests (600–1200 m a.s.l.) fluctuated between source or sink depending on the season (wet season: 1.86 ± 1.50 CH4-C ha−1 yr−1; dry season: −1.17 ± 0.40 CH4-C ha−1 yr−1). Analysis of spatial, temporal and environmental trends in CH4 flux across the study site suggest that soil redox was a dominant control on net CH4 flux. CH4 emissions were greatest from elevations, landforms and during times of year when soils were sub-oxic, and CH4 efflux was inversely correlated with soil O2 concentration (r2 = 0.82, F1, 125 = 588.41, P < 0.0001). Ecosystems across the region were net atmospheric N2O sources. N2O fluxes declined with increasing elevation; N2O emissions from premontane forest, lower montane forest, upper montane forest and montane grasslands averaged 2.23 ± 1.31 kg N2O-N ha−1 yr−1, 1.68 ± 0.44 kg N2O-N ha−1 yr−1, 0.44 ± 0.47 kg N2O-N ha−1 yr−1 and 0.15 ± 1.10 kg N2O-N ha−1 yr−1, respectively. N2O fluxes from premontane and lower montane forests exceeded prior model predictions for the region. Comprehensive investigation of field and laboratory data collected in this study suggest that N2O fluxes from this region were primarily driven by denitrification; that nitrate (NO3−) availability was the principal constraint on N2O fluxes; and that soil moisture and water-filled porosity played a secondary role in modulating N2O emissions. Any current and future changes in N management or anthropogenic N deposition may cause shifts in net N2O fluxes from these tropical montane ecosystems, further enhancing this emission source.

A major international experiment on ammonia (NH3) biosphere-atmosphere exchange was conducted over intensively managed grassland at Braunschweig, Germany. The experimental strategy was developed to allow an integrated analysis of different features of NH3 exchange including: a) quantification of nearby emissions and advection effects, b) estimation of net NH3 fluxes with the canopy by a range of micrometeorological measurements, c) analysis of the sources and sinks of NH3 within the plant canopy, including soils and bioassay measurements, d) comparison of the effects of grassland management options on NH3 fluxes and e) assessment of the interactions of NH3 fluxes with aerosol exchange processes. Additional technical objectives included the inter-comparison of different estimates of sensible and latent heat fluxes, as well as continuous-gradient and Relaxed Eddy Accumulation (REA) systems for NH3 fluxes. The prior analysis established the spatial and temporal design of the experiment, allowing significant synergy between these objectives. The measurements were made at 7 measurement locations, thereby quantifying horizontal and vertical profiles, and covered three phases: a) tall grass canopy prior to cutting (7 days), b) short grass after cutting (7 days) and c) re-growing sward following fertilization with ammonium nitrate (10 days). The sequential management treatments allowed comparison of sources-sinks, advection and aerosol interactions under a wide range of NH3 fluxes. This paper describes the experimental strategy and reports the grassland management history, soils, environmental conditions and air chemistry during the experiment, finally summarizing how the results are coordinated in the accompanying series of papers.

Species diversity in grasslands usually declines with increasing input of nitrogen from fertilizers or atmospheric deposition. Conversely, species diversity may also impact the build-up of soil and plant nitrogen pools. One important pool is NH3/NH4+ which also can be exchanged between plant leaves and the atmosphere. Limited information is available on how plant-atmosphere ammonia exchange is related to species diversity in grasslands. We have here investigated grass species abundance and different foliar nitrogen pools in 4-year-old intensively managed grassland. Apoplastic pH and NH4+ concentrations of the 8 most abundant species (Lolium perenne, Phleum pratense, Festuca pratensis, Lolium multiflorum, Poa pratensis, Dactylis glomerata, Holcus lanatus, Bromus mollis) were used to calculate stomatal NH3 compensation points. Apoplastic NH4+ concentrations differed considerably among the species, ranging from 13 to 117 μM, with highest values in Festuca pratensis. Also apoplastic pH values varied, from pH 6.0 in Phleum pratense to 6.9 in Dactylis glomerata. The observed differences in apoplastic NH4+ and pH resulted in a large span of predicted values for the stomatal NH3 compensation point which ranged between 0.20 and 6.57 nmol mol−1. Three species (Lolium perenne, Festuca pratensis and Dactylis glomerata) had sufficiently high NH3 compensation point and abundance to contribute to the bi-directional NH3 fluxes recorded over the whole field. The other 5 grass species had NH3 compensation points considerably below the atmospheric NH3 concentration and were thus not likely to contribute to NH3 emission but only to NH3 uptake from the atmosphere. Evaluated across species, leaf bulk-tissue NH4+ concentrations correlated well (r2=0.902) with stomatal NH3 compensation points calculated on the basis of the apoplastic bioassay. This suggests that leaf tissue NH4+ concentrations combined with data for the frequency distribution of the corresponding species can be used for predicting the NH3 exchange potential of a mixed grass sward.

Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N2 fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N2O, NO and bi-directional NH3 exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols., JRC.H.2-Climate change

Eleven instruments for the measurement of ambient concentrations of atmospheric ammonia gas (NH3), based on eight different measurement methods were inter-compared above an intensively managed agricultural field in late summer 2008 in Southern Scotland. To test the instruments over a wide range of concentrations, the field was fertilised with urea midway through the experiment, leading to an increase in the average concentration from 10 to 100 ppbv. The instruments deployed included three wet-chemistry systems, one with offline analysis (annular rotating batch denuder, RBD) and two with online-analysis (Annular Denuder sampling with online Analysis, AMANDA; AiRRmonia), two Quantum Cascade Laser Absorption Spectrometers (a large-cell dual system; DUAL-QCLAS, and a compact system; c-QCLAS), two photo-acoustic spectrometers (WaSul-Flux; Nitrolux-100), a Cavity Ring Down Spectrosmeter (CRDS), a Chemical Ionisation Mass Spectrometer (CIMS), an ion mobility spectrometer (IMS) and an Open-Path Fourier Transform Infra-Red (OP-FTIR) Spectrometer. The instruments were compared with each other and with the average concentration of all instruments. An overall good agreement of hourly average concentrations between the instruments (R2>0.84), was observed for NH3 concentrations at the field of up to 120 ppbv with the slopes against the average ranging from 0.67 (DUAL-QCLAS) to 1.13 (AiRRmonia) with intercepts of −0.74 ppbv (RBD) to +2.69 ppbv (CIMS). More variability was found for performance for lower concentrations (