Dynamics of soil biogeochemical gas emissions shaped by remolded aggregate sizes and carbon configurations under hydration cycles

Changes in soil hydration status affect microbial community dynamics and shape key biogeochemical processes. Evidence suggests that local anoxic conditions may persist and support anaerobic microbial activity in soil aggregates (or in similar hot spots) long after the bulk soil becomes aerated. To facilitate systematic studies of interactions among environmental factors with biogeochemical emissions of CO₂ , N₂ O and CH₄ from soil aggregates, we remolded silt soil aggregates to different sizes and incorporated carbon at different configurations (core, mixed, no addition). Assemblies of remolded soil aggregates of three sizes (18, 12, and 6 mm) and equal volumetric proportions were embedded in sand columns at four distinct layers. The water table level in each column varied periodically while obtaining measurements of soil GHG emissions for the different aggregate carbon configurations. Experimental results illustrate that methane production required prolonged inundation and highly anoxic conditions for inducing measurable fluxes. The onset of unsaturated conditions (lowering water table) resulted in a decrease in CH₄ emissions while temporarily increasing N₂ O fluxes. Interestingly, N₂ O fluxes were about 80% higher form aggregates with carbon placement in center (anoxic) core compared to mixed carbon within aggregates. The fluxes of CO₂ were comparable for both scenarios of carbon sources. These experimental results highlight the importance of hydration dynamics in activating different GHG production and affecting various transport mechanisms about 80% of total methane emissions during lowering water table level are attributed to physical storage (rather than production), whereas CO₂ emissions (~80%) are attributed to biological activity. A biophysical model for microbial activity within soil aggregates and profiles provides a means for results interpretation and prediction of trends within natural soils under a wide range of conditions.

Simulated Sensitivity of Urban Green Infrastructure Practices to Climate Change

Climate change is likely to alter the quantity and quality of urban stormwater, presenting a risk to water quality and public health. How might stormwater management practices need to change to address future climate? Answering requires understanding how management practices respond to climate forcing. Traditional "gray" stormwater design employs engineered structures, sized based on assumptions about future rainfall, which have limited flexibility once built. Green infrastructure (GI) uses vegetation, soil, and distributed structures to manage rainwater where it falls and may provide greater flexibility for adaptation. There is, however, uncertainty about how a warmer climate may affect performance of different types of GI. This study uses the hydrologic and biogeochemical watershed model, Regional Hydro-Ecologic Simulation System (RHESSys), to investigate sensitivity of different GI practices to climate. Simulations examine 36 urban "archetypes" representing different development patterns (at the city block scale) of typical U.S. cities, eleven regional climatic settings, and a range of mid-21st century scenarios based on downscaled climate model output. Results suggest regionally variable effects of climate change on the performance of GI practices for water quantity, water quality, and carbon sequestration. GI is able to mitigate most projected future increases in surface runoff, while bioretention can mitigate increased nitrogen yield at nine of eleven sites. Simulated changes in carbon balance are small, while local evaporative cooling can be substantial. Given uncertainty in the local expression of future climate, infrastructure design should emphasize flexibility and robustness to a range of future conditions.

Estimation of total CH4 emission from Japanese rice paddies using a new estimation method based on the DNDC-Rice simulation model

Methane (CH₄) is a greenhouse gas, and paddy fields are one of its main anthropogenic sources. In Japan, country-specific emission factors (EFs) have been applied since 2003 to estimate national-scale CH₄ emission from paddy field. However, these EFs did not consider the effects of factors that influence CH₄ emission (e.g., amount of organic C inputs, field drainage rate, climate) and can therefore produce estimates with high uncertainty. To improve the reliability of national-scale estimates, we revised the EFs based on simulations by the DeNitrification-DeComposition-Rice (DNDC-Rice) model in a previous study. Here, we estimated total CH₄ emission from paddy fields in Japan from 1990 to 2010 using these revised EFs and databases on independent variables that influence emission (organic C application rate, paddy area, proportions of paddy area for each drainage rate class and water management regime). CH₄ emission ranged from 323 to 455ktCyr^-1 (1.1 to 2.2 times the range of 206 to 285ktCyr^-1 calculated using previous EFs). Although our method may have overestimated CH₄ emissions, most of the abovementioned differences were presumably caused by underestimation by the previous method due to a lack of emission data from slow-drainage fields, lower organic C inputs than recent levels, neglect of regional climatic differences, and underestimation of the area of continuously flooded paddies. Our estimate (406ktC in 2000) was higher than that by the IPCC Tier 1 method (305ktC in 2000), presumably because regional variations in CH₄ emission rates are not accounted for by the Tier 1 method.

Estimating environmental value losses from earth materials excavation and infilling for large-scale airport construction: a case of Dalian Offshore Airport, Dalian, China

Large-scale airport construction removes large quantities of earth materials, resulting in serious environmental pollution and ecosystem damage. However, studies of environmental concerns caused by the materials used in airport construction are still preliminary, and those case studies on the impacts of large-scale offshore airport development are very limited. China's Dalian Offshore Airport is considered here to study the environmental value loss from 240 million m³ of materials excavations and 21 km² of artificial island infillings. The findings show that the calculated annual environmental value loss for the development of the Dalian Offshore Airport is approximately US$7.75 million, including US$1.81 million and US$1.47 million of direct economic loss of timber resources and marine biology resources, respectively, and US$1.53 million and US$2.79 million value losses of forest and marine ecosystem services damaged caused by materials excavation and infilling, respectively. The conclusions of this study provide an important foundation to quantitatively analyse the environmental impact of the Dalian Offshore Airport's development and can be used as a reference for similar engineering and environment impact assessment programs.

A new theory of plant-microbe nutrient competition resolves inconsistencies between observations and model predictions

Terrestrial plants assimilate anthropogenic CO₂ through photosynthesis and synthesizing new tissues. However, sustaining these processes requires plants to compete with microbes for soil nutrients, which therefore calls for an appropriate understanding and modeling of nutrient competition mechanisms in Earth System Models (ESMs). Here, we survey existing plant-microbe competition theories and their implementations in ESMs. We found no consensus regarding the representation of nutrient competition and that observational and theoretical support for current implementations are weak. To reconcile this situation, we applied the Equilibrium Chemistry Approximation (ECA) theory to plant-microbe nitrogen competition in a detailed grassland ¹⁵ N tracer study and found that competition theories in current ESMs fail to capture observed patterns and the ECA prediction simplifies the complex nature of nutrient competition and quantitatively matches the ¹⁵ N observations. Since plant carbon dynamics are strongly modulated by soil nutrient acquisition, we conclude that (1) predicted nutrient limitation effects on terrestrial carbon accumulation by existing ESMs may be biased and (2) our ECA-based approach may improve predictions by mechanistically representing plant-microbe nutrient competition.

Soil C and N models that integrate microbial diversity

Industrial agriculture is yearly responsible for the loss of 55-100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.

Enhancing Non-symbiotic N2 Fixation in Agriculture

Much of the demand for nitrogen (N) in cereal cropping systems is met by using N fertilisers, but the cost of production is increasing and there are also environmental concerns. This has led to a growing interest in exploring other sources of N such as biological N2fixation. Non-symbiotic N2fixation (by free-living bacteria in soils or associated with the rhizosphere) has the potential to meet some of this need especially in the lower input cropping systems worldwide. There has been considerable research on non-symbiotic N2fixation, but still there is much argument about the amount of N that can potentially be fixed by this process largely due to shortcomings of indirect measurements, however isotope-based direct methods indicate agronomically significant amounts of N2fixation both in annual crop and perennial grass systems. New molecular technologies offer opportunities to increase our understanding of N2-fixing microbial communities (many of them non-culturable) and the molecular mechanisms of non-symbiotic N2fixation. This knowledge should assist the development of new plant-diazotrophic combinations for specific environments and more sustainable exploitation of N2-fixing bacteria as inoculants for agriculture. Whilst the ultimate goal might be to introduce nitrogenase genes into significant non-leguminous crop plants, it may be more realistic in the shorter-term to better synchronise plant-microbe interactions to enhance N2fixation when the N needs of the plant are greatest. The review explores possibilities to maximise potential N inputs from non-symbiotic N2fixation through improved management practices, identification of better performing microbial strains and their successful inoculation in the field, and plant based solutions.

Diversity, structure, and size of N(2)O-producing microbial communities in soils--what matters for their functioning?

Nitrous oxide (N(2)O) is mainly generated via nitrification and denitrification processes in soils and subsequently emitted into the atmosphere where it causes well-known radiative effects. How nitrification and denitrification are affected by proximal and distal controls has been studied extensively in the past. The importance of the underlying microbial communities, however, has been acknowledged only recently. Particularly, the application of molecular methods to study nitrifiers and denitrifiers directly in their habitats enabled addressing how environmental factors influence the diversity, community composition, and size of these functional groups in soils and whether this is of relevance for their functioning and N(2)O production. In this review, we summarize the current knowledge on community-function interrelationships. Aerobic nitrification (ammonia oxidation) and anaerobic denitrification are clearly under different controls. While N(2)O is an obligatory intermediate in denitrification, its production during ammonia oxidation depends on whether nitrite, the end product, is further reduced. Moreover, individual strains vary strongly in their responses to environmental cues, and so does N(2)O production. We therefore conclude that size and structure of both functional groups are relevant with regard to production and emission of N(2)O from soils. Diversity affects on function, however, are much more difficult to assess, as it is not resolved as yet how individual nitrification or denitrification genotypes are related to N(2)O production. More research is needed for further insights into the relation of microbial communities to ecosystem functions, for instance, how the actively nitrifying or denitrifying part of the community may be related to N(2)O emission.

Development of a method for estimating total CH4 emission from rice paddies in Japan using the DNDC-Rice model

Methane (CH4) is a greenhouse gas, and paddy fields are one of its main anthropogenic emission sources. To mitigate this emission based on effective management measures, CH4 emission from paddy fields must be quantified at a national scale. In Japan, country-specific emission factors have been applied since 2003 to estimate national CH4 emission from paddy fields. However, this method cannot account for the effects of weather conditions and temporal variability of nitrogen fertilizer and organic matter application rates; thus, the estimated emission is highly uncertain. To improve the accuracy of national-scale estimates, we calculated country-specific emission factors using the DeNitrification-DeComposition-Rice (DNDC-Rice) model. First, we calculated CH4 emission from 1981 to 2010 using 986 datasets that included soil properties, meteorological data, and field management data. Using the simulated site-specific emission, we calculated annual mean emission for each of Japan's seven administrative regions, two water management regimes (continuous flooding and conventional mid-season drainage), and three soil drainage rates (slow, moderate, and fast). The mean emission was positively correlated with organic carbon input to the field, and we developed linear regressions for the relationships among the regions, water management regimes, and drainage rates. The regression results were within the range of published observation values for site-specific relationships between CH4 emission and organic carbon input rates. This suggests that the regressions provide a simplified method for estimating CH4 emission from Japanese paddy fields, though some modifications can further improve the estimation accuracy.

Impacts of management and climate change on nitrate leaching in a forested karst area

Forest management and climate change, directly or indirectly, affect drinking water resources, both in terms of quality and quantity. In this study in the Northern Limestone Alps in Austria we have chosen model calculations (LandscapeDNDC) in order to resolve the complex long-term interactions of management and climate change and their effect on nitrogen dynamics, and the consequences for nitrate leaching from forest soils into the karst groundwater. Our study highlights the dominant role of forest management in controlling nitrate leaching. Both clear-cut and shelterwood-cut disrupt the nitrogen cycle to an extent that causes peak concentrations and high fluxes into the seepage water. While this effect is well known, our modelling approach has revealed additional positive as well as negative impacts of the expected climatic changes on nitrate leaching. First, we show that peak nitrate concentrations during post-cutting periods were elevated under all climate scenarios. The maximal effects of climatic changes on nitrate concentration peaks were 20-24 mg L(-1) in 2090 with shelterwood or clear-cut management. Second, climate change significantly decreased the cumulative nitrate losses over full forest rotation periods (by 10-20%). The stronger the expected temperature increase and precipitation decrease (in summer), the lesser were the observed nitrate losses. However, mean annual seepage water nitrate concentrations and cumulative nitrate leaching were higher under continuous forest cover management than with shelterwood-cut and clear-cut systems. Watershed management can thus be adapted to climate change by either reducing peak concentrations or long-term loads of nitrate in the karst groundwater.

Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region

Fertilized soils have large potential for production of soil nitrogen oxide (NO_x=NO+NO₂), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NO_x contributes to formation of tropospheric ozone (O₃), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NO_x emissions in a high-temperature agricultural region of California. We also investigate whether soil NO_x emissions are capable of influencing regional air quality. We report some of the highest soil NO_x emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NO_x emissions and NO_x at the surface and in the troposphere. Adjusting the model to match NO_x observations leads to elevated tropospheric O₃. Our results suggest management can greatly reduce soil NO_x emissions, thereby improving air quality.

Soil NO_x emissions can significantly impact air quality in agricultural regions, particularly high temperature fertilized systems. Here, the authors investigate NO_x emissions in one such system in California and suggest that the NO_x emissions are the highest ever observed, with implications for air quality.

Simulation of nitrous oxide emissions at field scale using the SPACSYS model

Nitrous oxide emitted to the atmosphere via the soil processes of nitrification and denitrification plays an important role in the greenhouse gas balance of the atmosphere and is involved in the destruction of stratospheric ozone. These processes are controlled by biological, physical and chemical factors such as growth and activity of microbes, nitrogen availability, soil temperature and water availability. A comprehensive understanding of these processes embodied in an appropriate model can help develop agricultural mitigation strategies to reduce greenhouse gas emissions, and help with estimating emissions at landscape and regional scales. A detailed module to describe the denitrification and nitrification processes and nitrogenous gas emissions was incorporated into the SPACSYS model to replace an earlier module that used a simplified first-order equation to estimate denitrification and was unable to distinguish the emissions of individual nitrogenous gases. A dataset derived from a Scottish grassland experiment in silage production was used to validate soil moisture in the top 10 cm soil, cut biomass, nitrogen offtake and N2O emissions. The comparison between the simulated and observed data suggested that the new module can provide a good representation of these processes and improve prediction of N2O emissions. The model provides an opportunity to estimate gaseous N emissions under a wide range of management scenarios in agriculture, and synthesises our understanding of the interaction and regulation of the processes.

Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea

Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents.

Effects of temperature change and tree species composition on N2O and NO emissions in acidic forest soils of subtropical China

Tree species and temperature change arising from seasonal variation or global warming are two important factors influencing N2O and NO emissions from forest soils. However, few studies have examined the effects of temperatures (5-35°C) on the emissions of forest soil N2O and NO in typical subtropical region. A short-term laboratory experiment was carried out to investigate the influence of temperature changes (5-35°C) on soil N2O and NO emissions under aerobic conditions in two contrasting (broad-leaved and coniferous) subtropical acidic forest types in China. The results showed that the temporal pattern of N2O and NO emissions between the three lower temperatures (5°C, 15°C, and 25°C) and 35°C was significantly different for both broad-leaved and coniferous forest soils. The effects of temperature on soil N2O and NO emission rates varied between broad-leaved and coniferous forest soils. Both N2O and NO emissions increased exponentially with an increase in temperature in the broad-leaved forest soil. However, N2O and NO emissions in the coniferous forest soil were not sensitive to temperature change between 5°C and 25°C. N2O and NO emission rates were significantly higher in the broad-leaved forest soil as compared with the coniferous forest soil at all incubation temperatures except 5°C. These results suggest that the broad-leaved forest could contribute more N2O and NO emissions than the coniferous forest for most of the year in the subtropical region of China.

Comparison of APSIM and DNDC simulations of nitrogen transformations and N2O emissions

Various models have been developed to better understand nitrogen (N) cycling in soils, which is governed by a complex interaction of physical, chemical and biological factors. Two process-based models, the Agricultural Production Systems sIMulator (APSIM) and DeNitrification DeComposition (DNDC), were used to simulate nitrification, denitrification and nitrous oxide (N2O) emissions from soils following N input from either fertiliser or excreta deposition. The effect of environmental conditions on N transformations as simulated by the two different models was compared. Temperature had a larger effect in APSIM on nitrification, whereas in DNDC, water content produced a larger response. In contrast, simulated denitrification showed a larger response to temperature and also organic carbon content in DNDC. And while denitrification in DNDC is triggered by rainfall ≥5mm/h, in APSIM, the driving factor is soil water content, with a trigger point at water content at field capacity. The two models also showed different responses to N load, with nearly linearly increasing N2O emission rates with N load simulated by DNDC, and a lower rate by APSIM. Increasing rainfall intensity decreased APSIM-simulated N2O emissions but increased those simulated by DNDC.

Simulating the impacts of land use in northwest Europe on Net Ecosystem Exchange (NEE): the role of arable ecosystems, grasslands and forest plantations in climate change mitigation

In this study, we compared measured and simulated Net Ecosystem Exchange (NEE) values from three wide spread ecosystems in the southeast of Ireland (forest, arable and grassland), and investigated the suitability of the DNDC (the DeNitrification-DeComposition) model to estimate present and future NEE. Although, the field-DNDC version overestimated NEE at temperatures >5 °C, forest-DNDC under-estimated NEE at temperatures >5 °C. The results suggest that the field/forest DNDC models can successfully estimate changes in seasonal and annual NEE from these ecosystems. Differences in NEE were found to be primarily land cover specific. The annual NEE was similar for the grassland and arable sites, but due to the contribution of exported carbon, the soil carbon increased at the grassland site and decreased at the arable site. The NEE of the forest site was an order of magnitude larger than that of the grassland or arable ecosystems, with large amounts of carbon stored in woody biomass and the soil. The average annual NEE, GPP and Reco values over the measurement period were -904, 2379 and 1475 g C m(-2) (forest plantations), -189, 906 and 715 g C m(-2) (arable systems) and -212, 1653 and 1444 g C m(-2) (grasslands), respectively. The average RMSE values were 3.8 g C m(-2) (forest plantations), 0.12 g C m(-2) (arable systems) and 0.21 g C m(-2) (grasslands). When these models were run with climate change scenarios to 2060, predictions show that all three ecosystems will continue to operate as carbon sinks. Further, climate change may decrease the carbon sink strength in the forest plantations by up to 50%. This study supports the use of the DNDC model as a valid tool to predict the consequences of climate change on NEE from different ecosystems.

Denitrification and N2O:N2 production in temperate grasslands: processes, measurements, modelling and mitigating negative impacts

In this review we explore the biotic transformations of nitrogenous compounds that occur during denitrification, and the factors that influence denitrifier populations and enzyme activities, and hence, affect the production of nitrous oxide (N2O) and dinitrogen (N2) in soils. Characteristics of the genes related to denitrification are also presented. Denitrification is discussed with particular emphasis on nitrogen (N) inputs and dynamics within grasslands, and their impacts on the key soil variables and processes regulating denitrification and related gaseous N2O and N2 emissions. Factors affecting denitrification include soil N, carbon (C), pH, temperature, oxygen supply and water content. We understand that the N2O:N2 production ratio responds to the changes in these factors. Increased soil N supply, decreased soil pH, C availability and water content generally increase N2O:N2 ratio. The review also covers approaches to identify and quantify denitrification, including acetylene inhibition, (15)N tracer and direct N2 quantification techniques. We also outline the importance of emerging molecular techniques to assess gene diversity and reveal enzymes that consume N2O during denitrification and the factors affecting their activities and consider a process-based approach that can be used to quantify the N2O:N2 product ratio and N2O emissions with known levels of uncertainty in soils. Finally, we explore strategies to reduce the N2O:N2 product ratio during denitrification to mitigate N2O emissions. Future research needs to focus on evaluating the N2O-reducing ability of the denitrifiers to accelerate the conversion of N2O to N2 and the reduction of N2O:N2 ratio during denitrification.

Nitrous oxide emissions from soils: how well do we understand the processes and their controls?

Although it is well established that soils are the dominating source for atmospheric nitrous oxide (N₂O), we are still struggling to fully understand the complexity of the underlying microbial production and consumption processes and the links to biotic (e.g. inter- and intraspecies competition, food webs, plant–microbe interaction) and abiotic (e.g. soil climate, physics and chemistry) factors. Recent work shows that a better understanding of the composition and diversity of the microbial community across a variety of soils in different climates and under different land use, as well as plant–microbe interactions in the rhizosphere, may provide a key to better understand the variability of N₂O fluxes at the soil–atmosphere interface. Moreover, recent insights into the regulation of the reduction of N₂O to dinitrogen (N₂) have increased our understanding of N₂O exchange. This improved process understanding, building on the increased use of isotope tracing techniques and metagenomics, needs to go along with improvements in measurement techniques for N₂O (and N₂) emission in order to obtain robust field and laboratory datasets for different ecosystem types. Advances in both fields are currently used to improve process descriptions in biogeochemical models, which may eventually be used not only to test our current process understanding from the microsite to the field level, but also used as tools for up-scaling emissions to landscapes and regions and to explore feedbacks of soil N₂O emissions to changes in environmental conditions, land management and land use.

Iron: the forgotten driver of nitrous oxide production in agricultural soil

In response to rising interest over the years, many experiments and several models have been devised to understand emission of nitrous oxide (N₂O) from agricultural soils. Notably absent from almost all of this discussion is iron, even though its role in both chemical and biochemical reactions that generate N₂O was recognized well before research on N₂O emission began to accelerate. We revisited iron by exploring its importance alongside other soil properties commonly believed to control N₂O production in agricultural systems. A set of soils from California's main agricultural regions was used to observe N₂O emission under conditions representative of typical field scenarios. Results of multivariate analysis showed that in five of the twelve different conditions studied, iron ranked higher than any other intrinsic soil property in explaining observed emissions across soils. Upcoming studies stand to gain valuable information by considering iron among the drivers of N₂O emission, expanding the current framework to include coupling between biotic and abiotic reactions.

DRAINMOD-FOREST: Integrated Modeling of Hydrology, Soil Carbon and Nitrogen Dynamics, and Plant Growth for Drained Forests

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model, which was adapted mainly from the 3-PG model. The forest growth model estimates net primary production, C allocation, and litterfall using physiology-based methods regulated by air temperature, water deficit, stand age, and soil N conditions. The performance of the newly developed DRAINMOD-FOREST model was evaluated using a long-term (21-yr) data set collected from an artificially drained loblolly pine ( L.) plantation in eastern North Carolina, USA. Results indicated that the DRAINMOD-FOREST accurately predicted annual, monthly, and daily drainage, as indicated by Nash-Sutcliffe coefficients of 0.93, 0.87, and 0.75, respectively. The model also predicted annual net primary productivity and dynamics of leaf area index reasonably well. Predicted temporal changes in the organic matter pool on the forest floor and in forest soil were reasonable compared to published literature. Both predicted annual and monthly nitrate export were in good agreement with field measurements, as indicated by Nash-Sutcliffe coefficients above 0.89 and 0.79 for annual and monthly predictions, respectively. This application of DRAINMOD-FOREST demonstrated its capability for predicting hydrology and C and N dynamics in drained forests under limited silvicultural practices.

Quantification of nitrate leaching from German forest ecosystems by use of a process oriented biogeochemical model

Simulations with the process oriented Forest-DNDC model showed reasonable to good agreement with observations of soil water contents of different soil layers, annual amounts of seepage water and approximated rates of nitrate leaching at 79 sites across Germany. Following site evaluation, Forest-DNDC was coupled to a GIS to assess nitrate leaching from German forest ecosystems for the year 2000. At national scale leaching rates varied in a range of 0->80 kg NO(3)-N ha(-1) yr(-1) (mean 5.5 kg NO(3)-N ha(-1) yr(-1)). A comparison of regional simulations with the results of a nitrate inventory study for Bavaria showed that measured and simulated percentages for different nitrate leaching classes (0-5 kg N ha(-1) yr(-1):66% vs. 74%, 5-15 kg N ha(-1) yr(-1):20% vs. 20%, >15 kg N ha(-1) yr(-1):14% vs. 6%) were in good agreement. Mean nitrate concentrations in seepage water ranged between 0 and 23 mg NO(3)-N l(-1).

Comparison of land nitrogen budgets for European agriculture by various modeling approaches

A comparison of nitrogen (N) budgets for the year 2000 of agro-ecosystems is made for the EU 27 countries by four models with different complexity and data requirements, i.e. INTEGRATOR, IDEAg, MITERRA and IMAGE. The models estimate a comparable total N input in European agriculture, i.e. 23.3-25.7 Mton N yr(-1), but N uptake varies more, i.e. from 11.3 to 15.4 Mton N yr(-1) leading to total N surpluses varying from 10.4 to 13.2 Mton N yr(-1). The estimated overall variation at EU 27 is small for the emissions of ammonia (2.8-3.1 Mton N yr(-1)) and nitrous oxide (0.33-0.43 Mton N yr(-1)), but large for the sum of N leaching and runoff (2.7-6.3 Mton N yr(-1)). Unlike the overall EU estimates, the difference in N output fluxes between models is large at regional scale. This is mainly determined by N inputs, differences being highest in areas with high livestock density.

N2O production pathways in the subtropical acid forest soils in China

To date, N(2)O production pathways are poorly understood in the humid subtropical and tropical forest soils. A (15)N-tracing experiment was carried out under controlled laboratory conditions to investigate the processes responsible for N(2)O production in four subtropical acid forest soils (pH<4.5) in China. The results showed that denitrification was the main source of N(2)O emission in the subtropical acid forest soils, being responsible for 56.1%, 53.5%, 54.4%, and 55.2% of N(2)O production, in the GC, GS, GB, and TC soils, respectively, under aerobic conditions (40%-52%WFPS). The heterotrophic nitrification (recalcitrant organic N oxidation) accounted for 27.3%-41.8% of N(2)O production, while the contribution of autotrophic nitrification was little in the studied subtropical acid forest soils. The ratios of N(2)O-N emission from total nitrification (heterotrophic+autotrophic nitrification) were higher than those in most previous references. The soil with the lowest pH and highest organic-C content (GB) had the highest ratio (1.63%), suggesting that soil pH-organic matter interactions may exist and affect N(2)O product ratios from nitrification. The ratio of N(2)O-N emission from heterotrophic nitrification varied from 0.02% to 25.4% due to soil pH and organic matter. Results are valuable in the accurate modeling of N2O production in the subtropical acid forest soils and global budget.

Nitrogen dynamics of a mountain forest on dolomitic limestone--a scenario-based risk assessment

The dominant nitrogen (N) fluxes were simulated in a mountain forest ecosystem on dolomitic bedrock in the Austrian Alps. Based on an existing small-scale climate model the simulation encompassed the present situation and a 50-yr projection. The investigated scenarios were current climate, current N deposition (SC1) and future climate (+2.5 degrees C and +10% annual precipitation) with three levels of N deposition (SC2, 3, 4). The microbially mediated N transformation, including the emission of nitrogen oxides, was calculated with PnET-N-DNDC. Soil hydrology was calculated with HYDRUS and was used to estimate the leaching of nitrate. The expected change of the forest ecosystem due to changes of the climate and the N availability was simulated with PICUS. The incentive for the project was the fact that forests on dolomitic limestone stock on shallow Rendzic Leptosols that are rich in soil organic matter are considered highly sensitive to the expected environmental changes. The simulation results showed a strong effect due to increased temperatures and to elevated levels of N deposition. The outflux of N, both as nitrate (6-25 kg N ha(-1)yr(-1)) and nitrogen oxides (1-2 kg N ha(-1)yr(-1)), from the forest ecosystem are expected to increase. Temperature exerts a stronger effect on the N(2)O emission than the increased rate of N deposition. The main part of the N emission will occur as N(2) (15 kg N ha(-1)yr(-1)). The total N loss is partially offset by increased rates of N uptake in the biomass due to an increase in forest productivity.

Modeling effects of temperature and precipitation on carbon characteristics and GHGs emissions in Abies fabric forest of subalpine

Abies fabric forest in the eastern slope of Gongga mountain is one type of subalpine dark coniferous forests of southwestern China. It is located on the southeastern edge of the Qinghai-Tibet plateau and is sensitive to climatic changes. A process-oriented biogeochemical model, Forest-DNDC, was applied to simulate the effects of climatic factors, temperature and precipitation changes on carbon characteristics, and greenhouse gases (GHGs) emissions in A. fabric forest. Validation indicated that the Forest-DNDC could be used to predict carbon characteristics and GHGs emissions with reasonable accuracy. The model simulated carbon fluxes, soil carbon dynamics, soil CO2, N2O, and NO emissions with the changes of temperature and precipitation conditions. The results showed that with variation in the baseline temperature from -2 degrees C to +2 degrees C, the gross primary production (GPP) and soil organic carbon (SOC) increased, and the net primary production (NPP) and net ecosystem production (NEP) decreased because of higher respiration rate. With increasing baseline precipitation the GPP and NPP increased slightly, and the NEP and SOC showed decreasing trend. Soil CO2 emissions increased with the increase of temperature, and CO2 emissions changed little with increased baseline precipitation. With increased temperature and decreased baseline temperature, the total annual soil N2O emissions increased. With the variation of baseline temperature from -2 degrees C to +2 degrees C, the total annual soil NO emissions increased. The total annual N2O and NO emissions showed increasing trends with the increase of precipitation. The biogeochemical simulation of the typical forest indicated that temperature changes strongly affected carbon fluxes, soil carbon dynamics, and soil GHGs emissions. The precipitation was not a principal factor affecting carbon fluxes, soil carbon dynamics, and soil CO2 emissions, but changes in precipitation could exert strong effect on soil N2O and NO emissions.

Effect of pH, temperature and substrate on N2O, NO and CO2 production by Alcaligenes faecalis p

AIMS

To study the effect of pH, temperature and substrate on the magnitude of N(2)O and NO production by heterotrophic nitrifiers.

METHODS AND RESULTS

The change in N(2)O and NO production by the heterotrophic nitrifiers Alcaligenes faecalis subsp. parafaecalis and Paracoccus pantotrophus because of variations in pH, temperature and substrate was studied in chemostat cultures under steady-state conditions. N(2)O, NO and CO(2) production increased with temperature between 4 and 32 degrees C. For N(2)O an optimum temperature of 28 degrees C was observed. No optimum temperature was found for NO. Highest N(2)O and CO(2) productions were observed at a pH of 7.0. However, besides having an optimum at pH 7.0, especially NO production but also N(2)O production increased significantly at pH <or= 4.0. This increase in NO production under acidic conditions was partly because of chemo-denitrification, which contributed up to 62% of total NO production at pH 3.0 (0.8% for N(2)O). Furthermore, we could demonstrate that substrate quality significantly affects N(2)O, NO and CO(2) production. N(2)O and especially NO production by A. faecalis p. was significantly lower on an ammonium citrate medium when compared with rates obtained for a peptone-meat extract medium.

CONCLUSIONS

The results indicate that heterotrophic nitrifiers are suitable model organisms to study the influence of environmental factors on microbial N trace gas production. SIGNIFICANCE IMPACT OF THE STUDY: The results allow an improved description, e.g. of the pH dependency of N trace gas production by microbes and/or chemo-denitrification in process-oriented models describing the exchange of N trace gases between soils and the atmosphere.