Search

Atmospheric deposition is a major nutrient influx in ecosystems, while high anthropogenic deposition may disrupt ecosystem functioning. Quantification of the deposition flux is required to understand the impact of such anthropogenic pollution. However, current methods to measure nutrient deposition are costly, labor-intensive and potentially inaccurate. Ion exchange resin (IER) appears to be a promising cost- and labor-effective method. The IER method is potentially suited for deposition measurements on coarse timescales and for areas with little rainfall and/or low elemental concentrations. The accuracy of the IER method is, however, hardly classified beyond nitrogen. We tested the IER method for bulk deposition and throughfall measurements of macro- and micro-elements, assessing resin adsorption capacity, recovery efficiency and field behavior. We show that IER is able to adsorb 100 % of Ca, Cu, Fe, K, Mg, Mn, P, S, Zn and NO3- and > 96 % of P and Na. Loading the resin beyond its capacity resulted mainly in losses of Na, P and NH4+, while losses of Ca, Cu, Fe, Mg, Mn and Zn were hardly detected. Heat (40 °C), drought and frost (−15 °C) reduced the adsorption of P by 25 %. Recovery was close to 100 % for NH4+ and NO3- using KCl solution (1 or 2 M), while high (83 %–93 %) recoveries of Ca, Cu, Fe, K, Mg, Mn and S were found using HCl as an extractant (2–4 M). We found good agreement between the conventional method and the IER method for field conditions. Overall, IER is a powerful tool for the measurement of atmospheric deposition of a broad range of elements as the measurements showed high accuracy. The IER method therefore has the potential to expand current monitoring networks and increase the number of sampling sites.

Stellar occultation observations from space can probe the stratosphere and mesosphere at a fine vertical scale around the globe. Unlike other measurement techniques like radiosondes and aircraft, stellar occultation has the potential to observe the atmosphere above 30 km, and unlike radio occultation, stellar occultation probes fine-scale phenomena with potential to observe atmospheric turbulence. We imaged the refractive bending angle of a star centroid for a series of occultations by the atmosphere. Atmospheric refractivity, density, and then temperature are retrieved from the bending observations with the Abel transformation and Edlén's law, the hydrostatic equation, and the ideal gas law. The retrieval technique is applied to data collected by two nanosatellites operated by Terran Orbital. Measurements were primarily taken by the GEOStare SV2 mission, with a dedicated imaging telescope, supplemented with images captured by spacecraft bus sensors, namely the star trackers on other Terran Orbital missions. The bending angle noise floor is 10 and 30 arcsec for the star tracker and GEOStare SV2 data, respectively. The most significant sources of uncertainty are due to centroiding errors due to the fairly low-resolution stellar images and telescope pointing knowledge derived from noisy satellite attitude sensors. The former mainly affects the star tracker data, while the latter limits the GEOStare SV2 accuracy, with both providing low vertical resolution. This translates to a temperature profile retrieval up to roughly 20 km for both star tracker and GEOStare SV2 datasets. In preparation of an upcoming 2023 mission designed to correct these deficiencies, SOHIP, we simulated bending angle measurements with varying magnitudes of error. The expected maximum altitude of retrieved temperature is 41 km on average for these simulated measurements with a noise floor of 0.39 arcsec. Our work highlights the capabilities of stellar occultation observations from nanosatellites for atmospheric sounding. Future work will investigate high-frequency observations of atmospheric gravity waves and turbulence, mitigating the major uncertainties observed in these datasets.

Soil organic amendments can change microbial communities, potentially impacting their resilience to environmental stresses and, consequently, their transformation of soil carbon and nitrogen. While several studies have investigated the impact of a few organic amendments on microbial resilience to stresses in the form of absolute change in environmental conditions, the potential stress effects of different rates of change have received much less attention. The rate of change in environmental properties such as temperature may induce different microbial stress responses, given the reliance of microbial defensive mechanisms on time-dependent signalling and activation processes. In this research, we explored the relevance of the rate of temperature change as a microbial stressor and evaluated the potential use of organic amendments in steering soil ecological response. We monitored the changes in microbial properties and concentrations of different carbon and nitrogen fractions to temperature change treatments of 2.5 and 30 °C/d after the application of three commonly available rural organic amendments to a podzol soil in a laboratory incubation study. Results showed significant effects of the temperature treatments on bacterial and total microbial DNA concentrations, as well as on dissolvable and insoluble carbon and nitrogen ratios regardless of the organic amendment treatment. Temperature impacts on respiration rates, priming rates and the concentration of soil hot water extractable carbon and nitrogen differed depending on the organic amendment treatment. Results demonstrated that compost-amended soils were least sensitive to the temperature treatments, while grasses and fermented grasses treatments were generally more sensitive while showing opposite responses. Our findings indicate that organic amendments might be utilized to manipulate the impact of environmental stresses on soil carbon and nitrogen concentrations, and highlight the need for future research to investigate the relevant ecological properties and mechanisms.

Ammonia emissions into the atmosphere have increased substantially in Europe since 1960, primarily due to the intensification of agriculture, as illustrated by enhanced livestock and the use of fertilizers. These associated emissions of reactive nitrogen, particulate matter, and acid deposition have contributed to negative societal impacts on human health and terrestrial ecosystems. Due to the limited availability of reliable measurements, emission inventories are used to assess large-scale ammonia emissions from agriculture by creating gridded annual emission maps and emission time profiles globally and regionally. The modeled emissions are subsequently utilized in chemistry transport models to obtain ammonia concentrations and depositions. However, current emission inventories usually have relatively low spatial resolutions and coarse categorizations that do not distinguish between fertilization on various crops, grazing, animal housing, and manure storage in its spatial allocation. Furthermore, in assessing the seasonal variation of ammonia emissions, they do not consider local climatology and agricultural management, which limits the capability to reproduce observed spatial and seasonal variations in the ammonia concentrations. This paper describes a novel ammonia emission model that quantifies agricultural emissions with improved spatial details and temporal dynamics in 2010 in Germany and Benelux. The spatial allocation was achieved by embedding the agricultural emission model Integrated Nitrogen Tool across Europe for Greenhouse gases and Ammonia Targeted to Operational Responses (INTEGRATOR) into the air pollution inventory Monitoring Atmospheric Composition and Climate-III (MACC-III), thus accounting for differentiation in ammonia emissions from manure and fertilizer application, grazing, animal houses and manure storage systems. The more detailed temporal distribution came from the integration of TIMELINES, which provided predictions of the timing of key agricultural operations, including the day of fertilization across Europe. The emission maps and time profiles were imported into LOTOS-EUROS to obtain surface concentrations and total columns for validation. The comparison of surface concentration between modeled output and in situ measurements illustrated that the updated model had been improved significantly with respect to the temporal variation of ammonia emission, and its performance was more stable and robust. The comparison of total columns between remote sensing observations and model simulations showed that some spatial characteristics were smoothened. Also, there was an overestimation in southern Germany and underestimation in northern Germany. The results suggested that updating ammonia emission fractions and accounting for manure transport are the direction for further improvement, and detailed land use is needed to increase the spatial resolution of spatial allocation in ammonia emission modeling.

Reducing soil degradation and improving soil management could make an important contribute to climate change mitigation. Here the authors discuss opportunities and challenges towards implementing a global climate mitigation strategy focused on carbon sequestration in agricultural soils, and propose a framework for guiding region- and soil-specific management options.

The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO3- leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO3- were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep −2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.

The effects of atmospheric nitrogen deposition (Ndep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of Ndep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (Nr) deposition. We propose a methodology for untangling the effects of Ndep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of 22 forest flux towers. Total Nr deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP ∕ dNdep) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP ∕ dNdep value. This model-enhanced analysis of the C and Ndep flux observations at the scale of the European network suggests a mean overall dNEP ∕ dNdep response of forest lifetime C sequestration to Ndep of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus Ndep were non-linear, with no further growth responses at high Ndep levels (Ndep > 2.5–3 g N m−2 yr−1) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high Ndep levels implies that the forecast increased Nr emissions and increased Ndep levels in large areas of Asia may not positively impact the continent's forest CO2 sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC∕dN response.

Acceleration of anthropogenic emissions in China has substantially increased nitrogen (N) deposition during the last 3 decades and may result in an imbalance of atmospheric N and phosphorus (P) inputs in terrestrial ecosystems. However, the status of P deposition in China is poorly understood. This study synthesized data on total P and total N concentrations in bulk precipitation and throughfall from published literature to assess the characteristics of P deposition, N deposition and N : P deposition ratio in China's forests. Our results show relatively high mean rates of bulk P deposition (0.38 kg P ha−1 yr−1) and total P deposition (0.69 kg P ha−1 yr−1), but they were accompanied by even more elevated N inputs via bulk deposition (16.5 kg N ha−1 yr−1) and total deposition (21.6 kg N ha−1 yr−1), resulting in high N : P ratios in bulk deposition (44.4) and total deposition (32.8). Based on the difference between total deposition and bulk deposition, canopy-captured dry P and N deposition was estimated to be 0.31 kg P ha−1 yr−1 and 5.1 kg N ha−1 yr−1, respectively. We found significantly higher P deposition and lower N : P ratios at sites nearby than those far from semiarid regions. The estimated bulk and total deposition of P and N both showed a significant power-law increase with decreasing distance to the nearest large cities either in the areas nearby or far from semiarid regions. Our results suggest an anthropogenic alternation of regional P and N cycling, which may shift large areas of China's forests towards human-induced P limitation especially in southern China.

Aim of study: The main aim of the work was to summarize availability, quality and comparability of on-going European Research and Monitoring Networks (ERMN), based on the results of a COST FP0903 Action questionnaire carried out in September 2010 and May 2012.Area of study: The COST Action FP0903 involves 29 European countries and 4 non-COST institutions from USA, Morocco and Tunisia. In this study, the total of 22 replies to the questionnaire from 18 countries were included.Materials and methods: Based on the feedback from the Action FP0903 countries, the most popular European Networks were identified. Thereafter, the access to the network database, available quality assurance/quality control procedures and publication were described. Finally, the so-called “Supersites” concept, defined as a “highly instrumented research infrastructure, for both research and monitoring of soil-plant-atmosphere interactions” was discussed.Main results: The result of the survey indicate that the vast majority of the Action FP0903 countries participate in the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forest (ICP Forest). The multi-disciplinary International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICPIM) is the second most widespread forest programme. Research highlights: To fully understand biochemical cycles in forest ecosystems, long-term monitoring is needed. Hence, a network of “Supersites”, is proposed. The application of the above infrastructure can be an effective way to attain a better integration of research and monitoring networks at forest sites in Europe.Keywords: Supersites; European Research Monitoring Networks; Harmonization; Forest.

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.

Complex dynamic models of carbon and nitrogen are often used to investigate the consequences of climate change on agricultural production and greenhouse gas emissions from agriculture. These models require high temporal resolution input data regarding the timing of field operations. This paper describes the Timelines model, which predicts the timelines of key field operations across Europe. The evaluation of the model suggests that while for some crops a reasonable agreement was obtained in the prediction of the times of field operations, there were some very large differences which need to be corrected. Systematic variations in the date of harvesting and in the timing of the first application of N fertiliser to winter crops need to be corrected and the prediction of soil workability and trafficability might enable the prediction of ploughing and applications of solid manure in preparation for spring crops. The data concerning the thermal time thresholds for sowing and harvesting underlying the model should be updated and extended to a wider range of crops.

To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships and uses detailed GIS-based environmental and farming data in combination with various downscaling methods. This paper analyses the propagation of uncertainties in model inputs and parameters to outputs of INTEGRATOR, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probability distributions, while spatial correlation in these uncertainties was taken into account by assigning correlation coefficients at various spatial scales. The uncertainty propagation was analysed for the emissions of NH3, N2O and NOx, N leaching to groundwater and N runoff to surface water for the entire EU27 and for individual countries. Results show large uncertainties for N leaching and runoff (relative errors of ∼ 19% for Europe as a whole), and smaller uncertainties for emission of N2O, NH3 and NOx (relative errors of ∼ 12%). Uncertainties for Europe as a whole were much smaller compared to uncertainties at country level, because errors partly cancelled out due to spatial aggregation.

A comparison was made between upscaled model results of nitrogen (N) fluxes to air and water from 450 sites within the EU-27 and results derived for the entire EU-27 area using the model INTEGRATOR. The 450 sites were selected using stratified random sampling, dividing the EU-27 into 150 strata and selecting three sites at random within each stratum. The strata were based on important environmental factors influencing N fluxes. Hierarchical divisive cluster analysis was used to reduce the numerous combinations of environmental factors to the required total of 150, such that the heterogeneity of environmental factors within strata was as small as possible. Modelled NH3, N2O and NOx emissions and N leaching/runoff obtained were scaled up from the 450 sites to the entire EU-27 and were within 10% of results obtained by running the model for the whole of the EU-27 using about 36 500 sites. This implies that a reliable estimate of N fluxes for EU-27 can be made by upscaling results of the 450 selected sites suggesting that dramatic reduction in computation time can be achieved without substantial deterioration of results

To evaluate the effects of nitrogen (N) emission policies, reliable information on nitrate concentrations and leaching fluxes from forest ecosystems is necessary. Insight into the regional variability of nitrate concentrations, to support local policy on emission abatement strategies is especially desirable. In this paper, three methods for the calculation of a spatial distribution of soil nitrate concentrations in Dutch forest ecosystems are compared. These are (i) a regression model based on observed nitrate concentrations and additional data on explanatory variables such as soil type, tree species and nitrogen deposition (ii) a semi-empirical dynamic model WANDA, and (iii) a process-oriented dynamic model SMART2. These two dynamic models are frequently used to evaluate the effects of reductions in nitrogen deposition at scales ranging from regional to countrywide. The results of the regression model evaluated the performance of the two dynamic models. Furthermore, the results of the three methods are compared with the steady-state approach currently used for the derivation of nitrogen critical loads. Both dynamic models, in the form of cumulative distribution functions, give similar results on a national scale. Regional variability is predicted differently by both models. Discrepancies are caused mainly by a difference in handling forest filtering and denitrification. All three methods show that, despite the high nitrogen inputs, Dutch forests still accumulate more N than they release. This implies that, in respect of groundwater quality, presently acceptable nitrogen deposition is higher than the (long-term) critical loads. However, in areas with high atmospheric nitrogen input, all three methods indicate that the EU standard for nitrate in groundwater (50 mg NO3 l–1) is exceeded. Steady-state with nitrogen deposition seems to have been reached in about 10% of the forested area, with a nitrate concentration greater than 50 mg NO3–1. Keywords: soil modelling, up-scaling, model validation, critical load

This study focuses on spatial variability of throughfall water and chemistry and forest floor water content within a Douglas fir (Pseudotsuga menziesii, Franco L.) forest plot. Spatial patterns of water and chemistry (NH4+, NO3‾, SO42-, Cl‾, Mg2+, Ca2+, Na+ and K+) were compared and tested for stability over time. The spatial coefficient of variation (CV) was between 18 and 26% for amounts of throughfall water and ions, and 17% for forest floor water content. Concentrations and amounts of all ions were correlated significantly. Ion concentrations were negatively correlated with throughfall water amounts, but, except for NH4+, there was no such relation between throughfall water and ion amounts. Spatial patterns of throughfall water fluxes and forest floor water contents were consistent over time; patterns of ion fluxes were somewhat less stable. Because of the spatial variability of forest floor thickness and drainage, it was not possible to relate patterns in throughfall water directly to patterns in water content. The spatial variability of throughfall nitrogen and forest floor water contents can cause significant variability in NO3‾ production within the plot studied. Keywords: nutrient throughfall, forest floor water, spatial variability, time-stability, nitrogen

Dynamics of C and N in forest soils in the Nutrient Cycling and Soil Acidification Model (NUCSAM) are described by the transformation and decomposition of three organic matter compartments, litter, fermented material and humic material. These three compartments are allocated to the morphological distinguishable L, F and H horizons of the organic layer. Changes in the pools of these organic compartments are described with first order equations for decomposition and transformation. Rate constants for decomposition and transformation were derived by calibrating the model to measured organic matter pools in organic layers of a chrono-sequence of five first succession Scots pine stands between 15 and 120 years old. Simulated pools of organic matter in the organic layers were in agreement with measured pools in the five pine stands, except for the first thirty years of the H-horizon. During this period, an increase in organic matter in the H horizon was simulated while no H horizons were observed in the field. The simulated total pool of organic matter in the organic layer agreed well with values from a field inventory in 20 other Scots pine stands, but the simulated distribution over the three horizons differed from the field measurements which varied among sites. For the Scots pine stands the model was able to simulate the organic matter accumulation in the top 40-cm of the mineral soil; derived almost completely from fine root turnover. The accumulated pool of nitrogen in the organic layer was in agreement with measured pools for the oldest Scots pine stand but was too high for the younger stands. Especially, the accumulation of N in the F-horizon was too fast, presumably due to an overestimated retention of nitrogen.

Introduction Attention deficit hyperactivity disorder (ADHD) is the most common childhood behavioural disorder, causing significant impediment to a child’s development. It is a complex disorder with numerous contributing (epi)genetic and environmental factors. Currently, treatment consists of behavioural and pharmacological therapy. However, ADHD medication is associated with several side effects, and concerns about long-term effects and efficacy exist. Therefore, there is considerable interest in the development of alternative treatment options. Double-blind research investigating the effects of a few-foods diet (FFD) has demonstrated a significant decrease in ADHD symptoms following an FFD. However, an FFD requires a considerable effort of both child and parents, limiting its applicability as a general ADHD treatment. To make FFD intervention less challenging or potentially obsolete, we need to understand how, and in which children, an FFD affects ADHD behaviour and, consequently, the child’s well-being. We hypothesise that an FFD affects brain function, and that the nutritional impact on ADHD is effectuated by a complex interplay between the microbiota, gut and brain, that is, the microbiota–gut–brain axis.Methods and analysis The Biomarker Research in ADHD: the Impact of Nutrition (BRAIN) study is an open-label trial with researchers blinded to changes in ADHD symptoms during sample processing and initial data analyses.Ethics and dissemination The Medical Research and Ethics Committee of Wageningen University has approved this study (NL63851.081.17, application 17/24). Results will be disseminated through peer-reviewed journal publications, conference presentations, (social) media and the BRAIN study website. A summary of the findings will be provided to the participants.Trial registration number NCT03440346.Study dates Collection of primary outcome data started in March 2018 and will be ongoing until 100 children have participated in the study. Sample data analysis will start after all samples have been collected.