Automatic Chamber Research Articles

Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data

Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data

High soil nitrous oxide emissions from a greenhouse vegetable production system in Shouguang, Northern China

In China, the area of greenhouse vegetable production (GVP) has exceeded 4 million ha, accounting for >80% of global GVP systems. Excessive nitrogen (N) fertilization and frequent irrigation have created GVP hotspots of nitrous oxide (N2O) emissions. There are several studies on soil N2O emissions from GVP systems, but all with low-frequency manual sampling, which may have resulted in large uncertainties regarding quantifying N2O emissions. Herein, we utilized an automatic chamber system equipped with 16 channels to measure N2O emissions under common farm practice from a GVP system in Shouguang, Northern China. We measured emissions from both furrows and ridges for 1 year from July 2020 to July 2021. Our continuous monitoring showed that the annual soil N2O emission was 102 kg N ha−1, accounting for 7.6% of the applied N (1338 kg N ha−1). The annual N2O emission from furrows (176 kg N ha−1) was significantly higher than that from ridges (28 kg N ha−1). Large spatial variations in the N2O emissions were observed, ranging from 102 to 273 kg N ha−1 yr−1 for furrows (n = 8) and from 19 to 45 kg N ha−1 yr−1 for ridges (n = 7). In addition, we found that irrigation caused N2O flux pulses from furrows, increasing by 12–396% compared with the level before irrigation. High-frequency measurements using our automatic chamber system provided detailed information on the diurnal and seasonal dynamics of N2O emissions, which could be useful for building more accurate models and developing more effective policies to reduce N2O emissions from global GVP systems.

OpenToolFlux: An Open-Source Software for Estimating Gas Fluxes from Automatic Chamber Data

OpenToolFlux 1.0 is an open-source software designed to estimate soil gas fluxes from gas concentration time-series data generated by automatic chamber systems. This paper describes the physical equipment used as well as the software design and workflow. The software is a command-line application that imports tabular time-series data from the analyzer following the instructions specified in a configuration file by the user, performs configurable data-cleaning operations, and outputs a data file with volumetric flux estimates as well as diagnostic plots. The software can be configured according to the specifics of the physical equipment and experimental setups, and it is, therefore, applicable to a wide range of studies.

Partitioning autotrophic and heterotrophic respiration in an ombrotrophic bog

Northern peatlands are globally significant carbon stores, but the sink strength varies from year to year due to changes in environmental conditions. Ecosystem respiration (ER) is composed of both autotrophic respiration (AR) that consists of respiration by plant parts, and heterotrophic respiration (HR) that consists of respiration by microbial bacteria in the soil, fungi, etc. Manual measurements only crudely partition AR and HR, which may lead to erroneous estimates if a change favours one form of respiration over another and may influence our interpretation in the magnitude of respiration. HR has also been thought to be more linked to vegetation dynamics, particularly in wetter, sedge-dominated ecosystems like fens. It is unknown whether such plant-soil-root interactions influence HR in peatlands dominated by woody shrubs whose water table is located further below the surface. The objectives of this study were to 1) determine the contributions of AR and HR at Mer Bleue, an ombrotrophic bog, 2) explore how environmental conditions influence ER and its components, 3) determine how different methodological approaches (e.g. directly measured respiration using automatic chambers vs. extrapolated calculations) can influence our interpretation in the magnitude of respiration, and 4) compare the respiration dynamics with those found in the literature for other peatland types. Our results revealed differences in AR and HR contributions to ER compared to other peatland types reported in the literature. The AR/HR ratio was 3.0 and AR contributions to ER were ∼75% at our study bog, which is generally higher than AR contributions from fens, but also decreased substantially during extended drier periods. HR contributions increased with rising temperature and water table depth. Directly measured ER was smaller than when ER was estimated using night-time relationships with temperature. The magnitude of ER changed depending on the plant biomass, which we believe to be a result of vegetation dynamics influencing HR. The results of this study improved our understanding of peatland carbon cycling as well as the conceptualization of HR.

Day–night discrepancy in soil respiration varies with seasons in a temperate forest

Abstract Soil respiration (Rs) during daytime (Rsday) and nighttime (Rsnight) remains poorly understood owing to the limited availability of high‐resolution temporal measurements of Rs. Using continuous automatic chamber measurements at a half‐hourly interval, we explored Rs and its temperature sensitivity (Q10) during the daytime and nighttime over 10 years and determined the best sampling timeslot in a temperate deciduous broadleaf forest. We demonstrate a higher Rsnight than Rsday in spring and summer, a lower Rsnight than Rsday in autumn, but an insignificant difference between them in winter, contrasting with the consensus of a higher Rsday than Rsnight. Such discrepancy may result from the effect of factors other than temperature (e.g. reallocation of photosynthesis carbon, precipitation and soil moisture). We also reveal significant differences in apparent Q10 between seasons, indicating the highest Q10 in spring and significantly higher Q10 at night than at day in autumn. The Rs measured around midday (9:00–11:00 for autumn and 12:00–15:00 for other seasons) and midnight (20:00–22:00 for autumn and 0:00–2:00 for other seasons) provides the lowest bias to the daily mean Rs, whereas the measurement timeslots around midday are preferred due to practical considerations. Our findings highlight the significant diel variation of Rs and its temperature sensitivity across seasons and the necessity to account for Rsnight for a more accurate estimate of soil carbon budget. Read the free Plain Language Summary for this article on the Journal blog.

What is the pathway that determines the diurnal lag time between soil respiration and soil temperature?

Soil respiration (Rs) is a critical component of the global carbon cycle in terrestrial ecosystems and is considered a function of soil temperature (Ts); however, Rs often shows a hysteresis effect with Ts. The mechanism causing this hysteresis pattern remains controversial, hindering our ability to accurately simulate and predict Rs in response to climate change. Here, a two-year field experiment was conducted to investigate the factors and pathways influencing the diurnal lag time between Rs and Ts (LTTs−Rs); we used an automatic chamber continuous measurement of Rs combined with 3 levels of precipitation manipulation: −30 % (P − 30), +0% (CK), +30 % (P + 30) of ambient precipitation in rain-fed winter wheat (Triticum aestivum L.) and alfalfa (Medicago sativa L.) agroecosystems on the Loess Plateau, China. The results indicated that the monthly average diurnal dynamic peak time of Rs always occurred prior to that of Ts. The LTTs−Rs ranged from 1 h to 8 h in winter wheat under the three precipitation treatments over two years. The range was similar in alfalfa under the CK and P + 30 treatments; however, in alfalfa, the value ranged from 1 h to 10 h under the P − 30 treatment. The LTTs−Rs value is determined by the direct pathway of photosynthetic product transport (the lag time between Rs and photosynthetically active radiation (PAR), LTRs−PAR) and the indirect pathway of heat transfer (the lag time between Ts and PAR, LTTs−PAR); that is, the LTTs−Rs is equal to the sum of the LTRs−PAR and LTTs−PAR. Moreover, the LTTs−PAR is equal to the sum of the lag time between air temperature (Ta) and PAR (LTTa−PAR) and the lag time between Ta and Ts (LTTs−Ta) in both winter wheat and alfalfa under the three precipitation treatments. Soil volume water content (VWC) affects LTTs−Rs by influencing the process (i.e., the transport process of heat and photosynthate) that comprises the LTTs−Rs. This is the first attempt to quantify the pathway processes that determine the LTTs−Rs and clarify the mechanism of the LTTs−Rs response to VWC. The results have important implications for our understanding of the LTTs−Rs production mechanisms and the accurate prediction of soil carbon emissions by future models.

Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N2O

AbstractFluxes of the powerful greenhouse gas nitrous oxide (N2O) are mainly quantified using manually operated or automatic non‐steady‐state chambers. With both systems, fluxes are calculated as the change in N2O concentration over time using linear or non‐linear regression, but the type of regression selected can have a strong influence on the N2O flux magnitude. The HMR package, a regression‐based implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters were recently introduced which allow for pre‐filtering based on sample variance (pfvar and pfalpha), and for constraining the curvilinearity of concentration‐time series(SatPct and SatTimeMin). Currently, there are no guidelines on how to choose the best parameters for specific user conditions. Here we address this knowledge gap using datasets from manual and automatic chambers, and sensitivity analyses. We found that the effect of parameter settings on the cumulative fluxes was greater for manual chamber data compared to the automatic chamber data, with ranges of up to 67.3% and 1.5%, respectively. The parameter pfvar was identified as highly sensitive for both manual and automatic chambers; it is, therefore, critical to select a threshold for when to allow for non‐linear flux calculation that accurately represents the given measurement precision. This can be estimated from the variance of N2O measurements at ambient concentration levels. The parameter SatTimeMin was critical for manual chamber data where the curvature is much less constrained due to the lower number of observations. The parameter pfalpha was the least sensitive and can be set at a p‐value equal to 0.05 following common statistical practice. Parameter values depend on the expected flux characteristics with a given chamber design and are currently best selected based on visual inspection of the data. This study identifies where and how specific care should be taken for the selection of parameters in the HMR package, which may contribute to standardizing the methodologies used worldwide for N2O flux calculations, supporting initiatives in which data from many studies need to be combined.Highlights The HMR package, an implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters in the updated HMR package constrains the use of nonlinear flux calculation and inclusion of outliers. The new parameters affect the cumulative emissions of N2O obtained with manual and automated chambers differently. We found that the choice of parameter values led to differences in cumulative N2O emissions of up to 67.3% This study identifies where and how specific care should be taken for the selection of parameters.

Spatial-temporal variations of nitrous oxide emissions in coffee agroforestry systems in Costa Rica

This study investigates spatial-temporal trends in N2O emissions from coffee production systems in Costa Rica with a focus on the effects of nitrogen fertilisation, topography and soil type. This is done by combining (i) multi-year continuous dynamic chamber measurements from sites with different fertilisation levels, (ii) static chamber measurements taken along a typical sloping coffee field and (iii) measurements from a laboratory incubation experiment with nutrient addition to different soil types. In the field and in the laboratory, additions included standard NPK fertiliser, ammonium nitrate (NH4NO3) as well as potassium nitrate (KNO3). Soils in a laboratory experiment were incubated under both drained and flooded conditions. Continuous measurements from automatic chambers show that annual N2O fluxes were dominated by bursts over few weeks following N-fertilisation with peak emissions up to 60 g N-N2O ha−1 day−1. A two-month slope experiment with static chambers after KNO3-fertilisation with 90 kg N ha−1 showed N2O significant differences between the highest daily emission rates from the top and the bottom of the slope (134 ± 20 g N-N2O ha−1 and 336 ± 104 g N-N2O ha−1, respectively) which can be explained by NO3- transport downhill and flooded conditions favouring denitrification at the bottom of the slope. Incubation experiments indicate that denitrification is the main process controlling N2O emissions but also that nitrification can result in low N2O emission rates under drained conditions. It can be concluded that the reported N2O emissions from the coffee agroforestry systems are generally low, but may be underestimated, as both poorly drained depressions functioning as N2O hotspots as well as temporal N2O bursts need to be taken into account.

Effect of nitrification inhibitor (DMPP) on nitrous oxide emissions from agricultural fields: Automated and manual measurements

Nitrogen fertilisation contributes significantly to the atmospheric increase of nitrous oxide (N2O). Application of nitrification inhibitors (NIs) is a promising strategy to mitigate N2O emissions and improve N-use efficiency in agricultural systems. This study investigated the effect of NI, 3,4-dimethylpyrazol phosphate (DMPP) on N2O mitigation from spring barley and spring oilseed rape. Manual and automatic chamber methodologies were used to capture spatial and temporal variability in N2O emissions. In a second experiment, we study the effect of N fertiliser levels without NI (0 %, 50 %, 100 %, 150 % and 200 % of recommended amount of N fertiliser), as well as 100 % of N with NI on N2O emissions in spring barley. The automated chamber measurements showed dynamics of N2O changes throughout the season, including positive and negative peaks that were unobservable with manual chambers due to low temporal resolution. Although not significant, application of NI tended to reduce N2O emissions. The reduction was on average 16 % in spring barley and 58 % in spring oilseed rape in manual chamber measurements. However, N2O reduction was 108 % in continuous automatic chamber measurements in spring barley. The N2O EFs for the growing season were very low (0.025 % to 0.148 %), with a greater reduction in EF in spring oilseed rape (76 %) than in spring barley (32 %) with NI application. A positive correlation (R = 80 %) was observed between N fertiliser levels and N2O emissions. Crop yield and crop N uptake were not significantly affected by the use of NI. This study highlighted that NI can reduce N2O emissions, but the reduction effects are plot, crop and microclimate specific. Long-term experiments with continuous plot-scale measurements are needed to capture and optimise N2O mitigation effect of NIs across wide variability in soils and microclimates in agroecosystems.

Greenhouse gas emissions associated to sprinkler-irrigated alfalfa under semi-arid Mediterranean conditions

Aim of the study: Alfalfa is one the most important forage legume crop worldwide but little information is available regarding to greenhouse gas emissions (GHG) under Mediterranean sprinkler-irrigated conditions. Area of study: Middle Ebro valley, Spain Materials and methods: The GHG emissions during two alfalfa growing periods (4th and 5th stands) were evaluated using both the static method chambers and two automatic chambers coupled with a photoacoustic equipment that measured short-term gas emissions. Main results: Year-average CH4 fluxes were -0.71 g C ha-1 day-1, generally no significantly different from zero. Year-average N2O flux was 3.96 g N ha-1 day-1 with higher fluxes associated to some specific large rainfall or irrigation events. Average cumulative emissions of 865 g N ha-1 year-1 were found. We found short-term peaks of N2O (up to 160 g N ha-1 day-1) associated with high values of soil water filled pore space (WFPS) that can go unnoticed using the static chamber procedure. In spite of the higher soil NO3‾ concentration in the alfalfa-precedent field compared to the maize-precedent field, no significant differences in cumulative N2O emissions were observed in the two-month period after alfalfa or maize residues incorporation. Research highlights: Low GHG emissions were found in an irrigated alfalfa crop compared to N-fertilized crops but a deeper knowledge of the limiting factors of denitrification observed during some anoxic events (WFPS>90%) is necessary to properly quantify N2O emissions in irrigated alfalfa.

Seasonal and diurnal variation in ecosystem respiration and environmental controls from an alpine wetland in arid northwest China

AbstractWetlands store large amounts of carbon stocks and are essential in both global carbon cycling and regional ecosystem services. Understanding the dynamics of wetland carbon exchange is crucial for assessing carbon budgets and predicting their future evolution. Although many studies have been conducted on the effects of climate change on the ecosystem carbon cycle, little is known regarding carbon emissions from the alpine wetlands in arid northwest China. In this study, we used an automatic chamber system (LI-8100A) to measure ecosystem respiration (ER) in the Bayinbuluk alpine wetland in northwest China. The ER showed a significant bimodal diurnal variation, with peak values appearing at 16:30 and 23:30 (Beijing time, UTC + 8). A clear seasonal pattern in ER was observed, with the highest value (19.38 µmol m−2 s−1) occurring in August and the lowest value (0.11 µmol m−2 s−1) occurring in late December. The annual ER in 2018 was 678 g C m−2 and respiration during the non-growing season accounted for 13% of the annual sum. Nonlinear regression revealed that soil temperature at 5 cm depth and soil water content (SWC) were the main factors controlling the seasonal variation in ER. The diurnal variation in ER was mainly controlled by air temperature and solar radiation. Higher temperature sensitivity (Q10) occurred under conditions of lower soil temperatures and medium SWC (25% ≤ SWC ≤ 40%). The present study deepens our understanding of CO2 emissions in alpine wetland ecosystems and helps evaluate the carbon budget in alpine wetlands in arid regions.

Comparison of eddy covariance and automatic chamber‐based methods for measuring carbon flux

AbstractAn automatic chamber (AC) is an alternative method to the eddy covariance (EC) technique for estimating of CO2 fluxes. However, few direct comparisons between two techniques have been performed on nature alpine meadows. In order to determine diurnal pattern of net ecosystem exchange (NEE) of CO2 in summer on alpine meadows, and test the NEE measurement performance of AC under site conditions, we conducted simultaneous measurements of NEE using both EC and AC methods. The NEEAC can be estimated with the information from the initial slope of the time series of CO2 mixing ratio. We found that the application of linear regression, when photosynthesis processes were considered, could lead to serious deviations, even if closure times were short. The linear regression, however, was adequate for estimating CO2 fluxes when photosynthesis processes were not involved in, at least for short chamber closing times. Using appropriate fitting method, the fluxes of AC were relatively close to that of EC, but presented a daytime underestimation and nighttime overestimation. With the subsequent friction velocity (u*) filtering (<m s–1), the nighttime overestimation was eliminated, and the fluxes of AC showed a similar diurnal pattern of NEE with that of EC, but an overall underestimation all day long. Here, we may provide a side evidence of the overestimation of chamber fluxes at low atmospheric turbulence. Finally, we assume that the overall underestimation of AC is caused by the absence of detection of effective volume of chamber.

Warming and Increased Respiration Have Transformed an Alpine Steppe Ecosystem on the Tibetan Plateau From a Carbon Dioxide Sink Into a Source

AbstractCold region ecosystems store vast amounts of soil organic carbon (C), which upon warming and decomposition can affect the C balance and potentially change these ecosystems from C sinks to carbon dioxide (CO2) sources. We quantified the decadal year‐round CO2 flux from an alpine steppe‐ecosystem on the Tibetan Plateau using eddy covariance and automatic chamber approaches during a period of significant warming (0.13°C per 10 years; and 0.18°C in the non‐growing season alone: 1st October to next 30th April). The results showed that ongoing climate change, mainly warming within the topsoil layers, is the main reason for the site’s change from a sink for to a source of CO2 in the atmosphere. Non‐growing‐season ecosystem respiration accounted for 51% of the annual ecosystem respiration and has increased significantly. The growing seasons (1st May to 30th September) were consistent CO2 sink periods without significant changes over the study period. Observations revealed high‐emission events from the end of the non‐growing season to early in the growing season (1st March to fifteenth May), which significantly (p < 0.01) increased at a rate of 22.6 g C m−2 decade−1, ranging from 14.6 ± 10.7 g C m−2 yr−1 in 2012 to 35.3 ± 12.1 g C m−2 yr−1 in 2017. Structural equation modeling suggested that active layer warming was the key factor in explaining changes in ecosystem respiration, leading to significant changes in net ecosystem exchange over the period 2011–2020 and indicated that these changes have already transformed the ecosystem from a CO2 sink into a source. These results can be used to improve our understanding of the sensitivity of ecosystem respiration to increased warming during the non‐growing period.

Low Nitrous Oxide Emissions in a Boreal Spruce Forest Soil, Despite Long-Term Fertilization

Nitrogen (N) fertilization can increase stem wood production by several hundred percent in boreal forests. At the same time, there are concerns about the environmental consequences of N fertilization, especially considering losses of the greenhouse gas nitrous oxide (N2O) to the atmosphere. Soils are a large contributor to N2O emissions on a global scale. The aim of this study was to investigate the consequences of long-term nutrient optimization fertilization on N2O emissions in a boreal forest in Northern Sweden. Field N2O flux measurements were conducted during 2 years with manual and automatic chambers, as well as gas probes in the snow. The N2O emissions were generally low during the whole period of measurements, both from the control and fertilized plots. The emissions were generally highest during the winters, as well as the variability in the observed values. Overall, N2O emissions from fertilized plots were about twice the control, which could be explained by changes in the soil carbon-to-nitrogen ratio.

Emissions of CO2, N2O and CH4 From Cultivated and Set Aside Drained Peatland in Central Sweden

Northern peatlands are important carbon (C) reservoirs, storing about one-third of the global terrestrial soil C pool. Anthropogenic influences, such as drainage for agriculture and forestry, lower the originally high groundwater level, leading to peat aeration and decomposition. This is particularly reflected in significant losses of CO2, while fluxes of N2O and CH4 are generally considered of minor importance for the overall greenhouse gas (GHG) balance of cultivated peatlands in Scandinavia. Setting land aside from agricultural production has been proposed as a strategy to reduce GHG emissions from drained peatland, restore natural habitats, and increase C sequestration. However, the evidence for this is rather scarce unless drainage is terminated. In this study, we measured respiration using dark automatic chambers, and CO2, N2O, and CH4 fluxes using manual static chambers, on: 1) cultivated peatland and 2) adjacent set-aside peatland in Central Sweden. The set-aside site was found to be a greater source of respiration than the cultivated site, while higher N2O fluxes and lower CH4 uptake rates were observed for the cultivated site. However, to compare the full GHG balance and assess the abandonment of drained cultivated peatland, additional measures, such as gross primary production (GPP) but also dissolved organic C losses would have to be taken into account.

Mass spectrometric multiple soil-gas flux measurement system with a portable high-resolution mass spectrometer (MULTUM) coupled to an automatic chamber for continuous field observations

Abstract. We developed a mass spectrometric soil-gas flux measurement system using a portable high-resolution multi-turn time-of-flight mass spectrometer, called MULTUM, and we combined it with an automated soil-gas flux chamber for the continuous field measurement of multiple gas concentrations with a high temporal resolution. The developed system continuously measures the concentrations of four different atmospheric gases (NO2, CH4, CO2, and field soil–atmosphere flux measurements of greenhouse gases (NO2, O2) ranging over 6 orders of magnitude at one time using a single gas sample. The measurements are performed every 2.5 min with an analytical precision (2 standard deviations) of ±34 ppbv for NO2; ±170 ppbv, CH4; ±16 ppmv, CO2; and ±0.60 vol %, O2 at their atmospheric concentrations. The developed system was used for the continuous field soil–atmosphere flux measurements of greenhouse gases (NO2, CH4, and CO2) and O2 with a 1 h resolution. The minimum quantitative fluxes (2 standard deviations) were estimated via a simulation as 70.2 µgNm-2h-1 for NO2; 139 µgCm-2h-1, CH4; 11.7 mg C m−2 h−1, CO2; and 9.8 g O2 m−2 h−1, O2. The estimated minimum detectable fluxes (2 standard deviations) were 17.2 µgNm-2h-1 for NO2; 35.4 µgCm-2h-1, CH4; 2.6 mg C m−2 h−1, CO2; and 2.9 g O2 m−2 h−1, O2. The developed system was deployed at the university farm of the Ehime University (Matsuyama, Ehime, Japan) for a field observation over 5 d. An abrupt increase in NO2 flux from 70 to 682 µgNm-2h-1 was observed a few hours after the first rainfall, whereas no obvious increase was observed in CO2 flux. No abrupt NO2 flux change was observed in succeeding rainfall events, and the observed temporal responses at the first rainfall were different from those observed in a laboratory experiment. The observed differences in temporal flux variation for each gas component show that gas production processes and their responses for each gas component in the soil are different. The results of this study indicate that continuous multiple gas concentration and flux measurements can be employed as a powerful tool for tracking and understanding underlying biological and physicochemical processes in the soil by measuring more tracer gases such as volatile organic carbon, reactive nitrogen, and noble gases, and by exploiting the broad versatility of mass spectrometry in detecting a broad range of gas species.

A novel robotic chamber system allowing to accurately and precisely determining spatio-temporal CO2 flux dynamics of heterogeneous croplands

The precise and accurate assessment of carbon dioxide (CO2) exchange is crucial to identify terrestrial carbon (C) sources and sinks and for evaluating their role within the global C budget. The substantial uncertainty in disentangling the management and soil impact on measured CO2 fluxes are largely ignored especially in cropland. The reasons for this lies in the limitation of the widely used eddy covariance as well as manual and automatic chamber systems, which either account for short-term temporal variability or small-scale spatial heterogeneity, but barely both. To address this issue, we developed a novel robotic chamber system allowing for dozens of spatial measurement repetitions, thus enabling CO2 exchange measurements in a sufficient temporal and high small-scale spatial resolution. The system was tested from 08th July to 09th September 2019 at a heterogeneous field (100 m × 16 m), located within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The field is foreseen for a longer-term block trial manipulation experiment extending over three erosion induced soil types and was covered with spring barley. Measured fluxes of nighttime ecosystem respiration (Reco) and daytime net ecosystem exchange (NEE) showed distinct temporal patterns influenced by crop phenology, weather conditions and management practices. Similarly, we found clear small-scale spatial differences in cumulated (gap-filled) Reco, gross primary productivity (GPP) and NEE fluxes affected by the three distinct soil types. Additionally, spatial patterns induced by former management practices and characterized by differences in soil pH and nutrition status (P and K) were also revealed between plots within each of the three soil types, which allowed compensating for prior to the foreseen block trial manipulation experiment. The results underline the great potential of the novel robotic chamber system, which not only detects short-term temporal CO2 flux dynamics but also reflects the impact of small-scale spatial heterogeneity.

Long-term diverse rotation alters nitrogen cycling bacterial groups and nitrous oxide emissions after nitrogen fertilization

Agriculture accounts for a majority of global soil nitrous oxide (N2O) emissions. Increased crop diversity can change soil nitrogen (N), physicochemical properties and alter belowground microbial communities, leading to changes in potential N2O emissions when inorganic N fertilizer is applied. Nitrification and denitrification are two main N cycling pathways under investigation due to their contribution to soil N cycling and production of N2O. The goal of this study was to understand the impacts of 35 years of crop diversification in shaping diversity and the community size and activity of nitrifier and denitrifier bacteria and N2O emissions after N fertilization in corn. In 2017, after fertilizer addition, N2O emissions were continuously measured using automatic chambers from a long-term experiment of simple (corn-corn-soybean-soybean) and diverse (corn-corn-soybean-wheat underseeded with red clover cover crop) four year rotations under second year corn. Soil was collected during peak N2O emissions using high frequency temporal sampling to capture shifts in 16S rRNA, amoA, nirS, nirK, nosZ1 and nosZ2 genes and gene transcripts in soil where urea-ammonium-nitrate (UAN) was applied. An N2O emission event occurred in both rotations following UAN application but was higher in the diverse rotation, which also had persistent higher total and denitrifying (nirK and nosZ2) bacterial abundance. Bacterial amoA significantly increased in both rotations shortly after UAN addition, but gene detection decreased significantly in the simple rotation and remained elevated in the diverse. Transcripts for atypical nosZ2 were consistently detected but higher after UAN addition. Total bacterial diversity did not differ between simple and diverse rotations, however, abundance of microbial pathways leading to soil N2O emissions, ammonia oxidizers and denitrifiers, were elevated in soil with a more diverse cropping history. Best management practices (BMPs) that include crop diversification need to consider microbial communities and greenhouse gas (GHG) production, in order to fully quantify the soil ecosystem services.

Soil CO<sub>2</sub> efflux errors are lognormally distributed – implications and guidance

Abstract. Soil CO2 efflux is the second-largest carbon flux in terrestrial ecosystems. Its feedback to climate determines model predictions of the land carbon sink, which is crucial to understanding the future of the earth system. For understanding and quantification, however, observations by the most widely applied chamber measurement method need to be aggregated to larger temporal and spatial scales. The aggregation is hampered by random error that is characterized by occasionally large fluxes and variance heterogeneity that is not properly accounted for under the typical assumption of normally distributed fluxes. Therefore, we explored the effect of different distributional assumptions on the aggregated fluxes. We tested the alternative assumption of lognormally distributed random error in observed fluxes by aggregating 1 year of data of four neighboring automatic chambers at a Mediterranean savanna-type site. With the lognormal assumption, problems with error structure diminished, and more reasonable prediction intervals were obtained. While the differences between distributional assumptions diminished when aggregating data of single chambers to an annual value, differences were important on short timescales and were especially pronounced when aggregating across chambers to plot level. Hence we recommend as a good practice that researchers report plot-level fluxes with uncertainties based on the lognormal assumption. Model data integration studies should compare predictions and observations of soil CO2 efflux on a log scale. This study provides methodology and guidance that will improve the analysis of soil CO2 efflux observations and hence improve understanding of soil carbon cycling and climate feedbacks.

Combining no-till with rye (Secale cereale L.) cover crop mitigates nitrous oxide emissions without decreasing yield

No-till (NT) often increases soil carbon (C) sequestration compared with conventional tillage (CT), yet its net effect on N2O emissions is controversial. Cover crops (CCs) adoption is promoted in NT systems because CCs growth curbs nitrate losses via leaching. However, incorporating CC residues into the soil may have positive or negative effects on N2O emissions depending on CC species and agro-ecosystem management. A better understanding of how tillage practices and CC species affect N2O emissions is therefore needed for the development of productive agroecosystems that contribute to climate change mitigation. The objectives of this three-year (2015–2017) field experiment on a Udertic Haplustalf soil in the Po Valley were to compare N2O emissions and crop yield of soybean under NT and CT, and to examine how contrasting residues from two CCs (rye, Secale cereale L. vs hairy vetch, Vicia villosa Roth) affect N2O emissions in NT soybean and maize. We hypothesized that N2O emissions would be lower with NT than with CT and with rye residues than with vetch ones. Nitrous oxide was continuously sampled using automatic chambers during three periods (emergence, N-fixation and maturity) over the soybean-cropping season in 2015 and during the entire cropping maize season in 2017. The DNDC model was calibrated (2015 data) and validated (2017 data), and then used to estimate the annual cumulative N2O emissions in different treatments. Overall, N2O emissions in NT were 40–55% lower than in CT, for both in situ measurements (Period I) and modelled estimations. These differences could be ascribed to the higher water-filled pore space (WFPS) and soil nitrate availability in CT than in NT. No-till also increased SOC content (28%; 0–5 cm) and earthworm abundance (5 times) compared with CT. Within NT systems, N2O emissions were 20–36% lower with rye CC than with vetch CC (P < 0.05), which was a consequence of the lower availability of soil mineral N under rye than under vetch due to the high C/N ratio of rye residues. Yield of soybean and maize under NT was higher with rye CC than with vetch CC. The combination of NT and rye CC that led to the lowest N2O emissions and highest yields should be recommended in the Po Valley region.