Open Access

Terrestrial denitrification: challenges and opportunities

Ecological Processes20121:11

DOI: 10.1186/2192-1709-1-11

Received: 21 August 2012

Accepted: 16 October 2012

Published: 8 November 2012

Abstract

Denitrification is a process of great environmental importance but is difficult to study in terrestrial ecosystems. Methods for quantifying the process are problematic, variability in activity is high, and temporal and spatial scaling challenges are extreme. Available methods are problematic for a variety of reasons; they change substrate concentrations, disturb the physical setting of the process, lack sensitivity or are prohibitively costly in time and expense. Most fundamentally, it is very difficult to quantify the dominant end-product (N2) of denitrification given its high background concentration in the atmosphere. Spatial and temporal variation in denitrification is high due to control of the process by multiple factors (oxygen, nitrate, carbon, pH, salinity, temperature etc.) that each vary in time and space. A particular challenge is that small areas (hotspots) and brief periods (hot moments) frequently account for a high percentage of N gas flux activity. These phenomena are challenging to account for in measurement, modeling and scaling efforts. The need for scaling is driven by the fact that there is a need for information on this microscale process at the ecosystem, landscape and regional scales where there are concerns about nitrogen effects on soil fertility, water quality and air quality. In this review, I outline the key challenges involved with denitrification and then describe specific opportunities for making progress on these challenges including advances in measurement methods, new conceptual approaches for addressing hotspot and hot moment dynamics, and new remote sensing and geographic information system–based scaling methods. Analysis of these opportunities suggests that we are poised to make great improvements in our understanding of terrestrial denitrification. These improvements will increase our basic science understanding of a complex biogeochemical process and our ability to manage widespread nitrogen pollution problems.

Introduction

Denitrification refers to the reduction of the nitrogen (N) oxides nitrate (NO3-) and nitrite (NO2-) to the N gases nitric oxide (NO), nitrous oxide (N2O) and dinitrogen (N2). The process is carried out primarily (but not exclusively) by facultatively anaerobic bacteria that normally respire oxygen (O2) but in its absence respire the N oxides. Most denitrifying bacteria are heterotrophs, requiring organic compounds as an energy source. More than 60 genera of denitrifying microorganisms have been identified and denitrifiers represent up to 5% of the total soil microbial community (Philippot et al. 2007; Wallenstein et al. 2006).

At the organismal scale, denitrification is regulated by O2 and levels of available inorganic N and respirable carbon (C) (Table 1). Regulation becomes more complex with increasing scale and requires analysis of relationships between the proximal, process-level factors that control flux (inorganic N levels, O2, available C) and distal factors that control them at the scale of interest (Table 1) (Groffman 1991). For example, if we are studying N gas fluxes at the scale of field plots, we focus on soil moisture as a field-scale controller of the flow of O2 to the organisms that produce N gases. At the landscape scale, we measure soil texture and topography as landscape-scale controllers of soil moisture, landscape water fluxes and groundwater table distance. And at the regional scale, we focus on geology (surface and groundwater), geomorphic features (e.g., glacial till versus outwash) and land use as regional-scale controllers of soil texture and topography. Temporal regulation also varies with scale. While the presence of O2, NO3- and C regulates denitrification activity at the scale of minutes and hours, we need to focus on rainfall events, seasonal weather patterns, management activities, and annual and decadal climate variation as regulators at daily, seasonal, annual and longer time scales.
Table 1

Factors controlling N gas fluxes at different scales of investigation (Groffman 1991 )

Scale of investigation

Controlling factors

Organism……………………….

Oxygen, inorganic N, available C

Field…………………………….

Soil water, inorganic N supply, available C supply, pH, temperature, salinity, etc.

Landscape……………………….

Soil type, plant community type, canopy nutrients, season

Global………………………….

Biome type, climate

The need for information on denitrification at ecosystem (10 m), landscape (1,000 m), regional (>100 km) and global scales is pressing. At the ecosystem scale, N gas fluxes can deplete soil stocks of inorganic N, an essential and frequently limiting nutrient (Vitousek & Howarth 1991). At the landscape scale, denitrification can prevent the movement of excess inorganic N from terrestrial environments into water bodies where it can cause overgrowth of aquatic plants and eutrophication (Seitzinger et al. 2006). There is a great need for information on the yield of N2O during denitrification as it is a “greenhouse” gas that can influence the earth’s radiative budget and plays a role in stratospheric ozone destruction (Prather et al. 1995). Nitric oxide is a highly reactive gas that is a precursor to tropospheric ozone formation and is readily converted to NO2 and deposited back to the earth’s surface in acid precipitation (NRC 1992). Interest in denitrification is particularly high in areas where N use is high, such as North America, Europe and Asia where there is great uncertainty over the fate of anthropogenic N inputs and concern about environmental effects (Davidson et al. 2012; Erisman et al. 2011).

Because the factors that influence N gas production all have complex underlying drivers of their own, N gas fluxes often exhibit extreme variation in time and space (Folorunso & Rolston 1984; Parkin et al. 1987; Robertson et al. 1988). At certain times and places, these factors converge to create high rates of activity resulting in small areas (hotspots) and brief periods (hot moments) that frequently account for a high percentage of N gas flux activity. Moreover, it is difficult to measure fluxes without disturbing the physical soil environment and/or the biological processes that produce the fluxes, leading to frequent concerns that observed results are artifacts of a particular method (Groffman et al. 2006). Methodological problems and high variability are especially a concern when extrapolating point measurements to larger areas and longer time periods. Extrapolating highly variable estimates produced using problematic methods in time and space creates extreme uncertainty and low confidence in these scaled estimates.

In this review, I make the case that several recent developments suggest that our understanding of denitrification is about to markedly improve. At the organismal scale, new molecular methods are transforming our understanding of the organisms and communities that carry out denitrification (note that these methods are not the subject of this review, which focuses on the ecosystem scale and above). Methodological advances have led to improved quantification of the fluxes of all three gaseous products of denitrification. There have also been recent improvements in the development of remote sensing, geographic information system and simulation modeling tools for scaling gas flux measurements to larger areas. Stable isotope mass balance modeling and measurement techniques provide new approaches to constraining estimates of denitrification integrated over several temporal and spatial scales. Most fundamentally, there are new ideas and measurement approaches that can encompass the hotspot and hot moment phenomena that are so important for denitrification. Improved methods, applied in novel experimental designs that incorporate hotspot and hot moment phenomena and coupled with powerful scaling tools, have the potential to reduce the uncertainty in estimates of denitrification. These advances (reviewed below) suggest that we may soon have more definitive assessments of denitrification rates and of the importance of this process in ecosystem, landscape, regional and global N cycles.

The challenge of denitrification—where does all the N go?

Researchers and managers have struggled with “the enigma of missing N” for over four decades (Allison 1955; Van Breemen et al. 2002). This enigma arises from the computation of mass balances at multiple scales showing that inputs of N to watersheds from fertilizer, atmospheric deposition and human food/sewage are always much greater than outputs of N in stream flow and/or groundwater (Boyer et al. 2002; Howarth et al. 1996; Söderlund & Svensson 1977). Indeed, global mass balance analyses (Seitzinger et al. 2006) suggest that the biggest global sink for anthropogenic N must be terrestrial denitrification (Figures 1 and 2), or perhaps N2 flux associated with anaerobic oxidation of ammonia (ANAMMOX) (Yang et al. 2012), yet there are few direct measurements to support these results.
Figure 1

Analysis of global anthropogenic nitrogen flows suggests that the vast majority of land-based N inputs disappear in terrestrial ecosystems (soils) and at the interface between terrestrial and aquatic environments (groundwater, lakes and rivers). From Seitzinger et al. (2006).

Figure 2

Denitrification of land-based N sources in terrestrial, freshwater, and marine ecosystems globally shows that terrestrial ecosystems (soils) and the interface between terrestrial and aquatic environments (groundwater, lakes and rivers) dominate global denitrification in terms of mass flux (a) and as a percentage of land-based N sources (b). From Seitzinger et al. (2006).

At very large (regional and global) scales, N imbalances are “explained away” by a mixture of storage in soils and vegetation and/or high rates of denitrification in soils and sediments somewhere within the watershed (David & Gentry 2000; Goodale et al. 2002; Howarth et al. 1996; Van Breemen et al. 2002). But the imbalances are harder to explain in more highly resolved analyses. For example, van Breemen et al. (2002) compiled detailed mass balances for 16 catchments (~500 to 70,000 km2) along a latitudinal profile from Maine to Virginia, USA and made a “best guess” that terrestrial denitrification accounted for 37% of anthropogenic inputs in these watersheds (Figure 3). Yet measured denitrification rates in this region have never been high enough to be consistent with this estimate.
Figure 3

Nitrogen budgets describing “best guesses” of (a) nitrogen sources and (b) nitrogen storages and losses for 16 catchments along a latitudinal profile from Maine to Virginia, USA. Values are the weighted average for the 16 watersheds. From Van Breemen et al. (2002).

Imbalances in detailed studies at smaller scales, where plant and soil processes are carefully accounted for, are more difficult to explain than in large scale balances (Addiscott 1995; Lowrance 1992; Steinheimer et al. 1998). For example, analysis of the fates of fertilizer N added over 22 years in an Iowa watershed with continuous corn show large amounts of “unaccounted for (lost or stored) N” (Figure 4). Given that these agricultural soils are likely not accumulating organic N, the vast majority of the “lost or stored” N was likely denitrified. Yet, measurements suggest that these well drained agricultural soils are not likely to be denitrifying at a high rate (Hofstra & Bouwman 2005). These inconsistencies challenge our fundamental understanding of the N cycle.
Figure 4

Analysis of the fates of fertilizer N added over 22 years in an Iowa watershed with continuous corn show large amounts of “unaccounted for (lost or stored) N.” Given that these agricultural soils are likely not accumulating organic N, the vast majority of the “lost or stored” N was likely denitrified. From Steinheimer et al. (1998).

Addressing the challenge of denitrification requires advances in three main areas: (1) improved methods for quantifying N gas fluxes, (2) experimental designs that incorporate hotspot and hot moment phenomena and (3) approaches for temporal and spatial scaling that account for hotspot and hot moment phenomena at multiple scales. Below, I review the challenges and opportunities in each of these three areas.

It is important to note that this review does not comprehensively address recent advances in molecular and microbial studies of denitrification or other dissimilatory fates of N such as dissimilatory NO3- reduction to ammonia (DNRA) (Burgin & Hamilton 2007) or N2 production associated with ANAMMOX (Yang et al. 2012). These topics, with some key references are mentioned briefly, but the focus here is on the potential for improvements in estimates of terrestrial denitrification relevant to N pollution questions at ecosystem, landscape and regional scales.

Challenges and opportunities in methods for quantifying N gas fluxes

Denitrification has always been a challenging process to measure (Groffman et al. 2006), primarily due to the difficulty of quantifying the flux of N2 from soil against the high natural atmospheric background of this gas (Yang & Silver 2012). Most denitrification methods therefore involve alteration of physical or chemical conditions through the use of inhibitors (e.g., acetylene) or amendments (e.g., 15N) that produce inaccurate or unrealistic estimates of rates. Most methods also involve the use of relatively small samples (e.g., 5 cm diameter soil cores) that exacerbate problems with variability and hotspots. However, there have been recent advances in methods for quantifying N2 flux and in isotope-based methods that provide area and time-integrated estimates of denitrification that are more relevant to ecosystem-scale questions.

Recent efforts to quantify N2 flux have centered on the use of soil core–based gas recirculation systems that allow for replacement of the natural N2/O2 atmosphere with a He/O2 atmosphere, allowing for direct measurement of N2 and N2O production (Butterbach-Bahl et al. 2002; Swerts et al. 1995; Wang et al. 2011a). These systems allow for direct assessment of N2O fluxes and of N2O:N2 yields (Burgin & Groffman 2012) but still involve the use of extracted soil cores, over extended periods, which can create multiple effects on N cycle process rates (Frank & Groffman 2009). The realism of flux estimates from cores can be checked at least partially by comparing estimates of CO2 and N2O fluxes from the cores with estimates from field chambers. Ultimately, it may be possible to directly measure N2 fluxes or N2:Ar ratios from field chambers (Yang & Silver 2012) or to measure fluxes of 15N2 following tracer level additions of 15NO3- to field chambers (Stange et al. 2009). Development of these methods will require improvements in the sensitivity of membrane inlet and/or isotope ratio mass spectrometry. Isotope addition approaches are also essential for separating different dissimilatory fates of inorganic N, i.e., denitrification versus ANAMMOX (Yang et al. 2012) and DNRA (Nicholls & Trimmer 2009).

The ability to vary the O2 concentration of the recirculation stream in the new soil core methods provides a basis for temporal extrapolation and for including hot moments of flux driven by decreases in O2 caused by rainfall events. If continuous estimates of soil O2 can be produced either from sensors or from models, denitrification versus O2 relationships established with the recirculation system can be used to produce continuous estimates of flux (Burgin & Groffman 2012; Burgin et al. 2010). These sensors provide a new opportunity to quantify the dominant proximal controller of denitrification at high temporal resolution and can reveal surprising insights on this controller. In a forested riparian zone in New York, USA, we observed marked differences in soil O2 over very short distances and time periods (Figure 5), greatly improving depiction of just where and when denitrification was likely to be occurring at this site.
Figure 5

Continuous soil oxygen, temperature and volumetric moisture content in two wet and two dry areas (a) of a forested riparian zone in New York, USA. Oxygen (b) and moisture (VWC) and temperature (Temp) (c) probes were installed at 10 cm depth. From Burgin and Groffman (2012).

While it has long been known that the lighter isotope of N (14N) is preferentially consumed during denitrification, resulting in enrichment of soils in 15N, recent efforts to constrain biogeochemical models with isotope data have produced improved assessments of denitrification at ecosystem (Amundson et al. 2003; Bai & Houlton 2009; Houlton et al. 2006) and regional/global (Houlton & Bai 2009) scales. These methods need to account for situations (e.g., very wet soils) where denitrification completely consumes NO3-, eliminating any isotopic discrimination. N isotope budgets that account for such local effects can be used to produce independent estimates of denitrification that can be compared with direct measurements and simulation model outputs.

Stable isotopes can provide further information on the role of denitrification through measurements of both δ 15N- and δ 18O- values of residual NO3- in soil (Casciotti et al. 2002; Huygens et al. 2005; Sigman et al. 2001). Denitrification enriches 18O as well as 15N in the residual NO3-, typically in a 1:2 ratio, providing an isotopic signature of NO3- from denitrification different from that in atmospheric deposition or soil nitrification (Kendall 1998; Kendall et al. 2007), although there is recent concern that exchange of O2 between water and NO3- can alter these patterns (Kool et al. 2011; Well & Flessa 2009). This approach does not produce quantitative estimates of denitrification. However it can provide useful confirmation of estimates and patterns produced by other approaches.

Challenges and opportunities in experimental designs that include hotspots and hot moment phenomena

Much of the uncertainty about denitrification arises from the fact that small areas (hotspots) and brief periods (hot moments) frequently account for a high percentage of N gas flux activity. These phenomena are challenging to account for in measurement, modeling and scaling efforts (Groffman et al. 2009). The importance of hotspots and hot moments to denitrification activity became obvious in the 1970s as techniques that allowed for measurement of denitrification in situ, especially in soils, produced observations of extremely high spatial and temporal variability in measured rates (Folorunso & Rolston 1984; Rolston et al. 1979). Early efforts focused on hotspots in the anaerobic centers of soil aggregates (Sexstone et al. 1985; Smith 1980), along growing roots (Haider et al. 1987; Woldendorp 1962), at the aerobic/anaerobic interface of sediments (Reddy & Patrick 1984) and in patches of labile organic matter (Christensen et al. 1990; Parkin 1987). Parkin (1987) dissected an intact soil core and determined that a very high percentage (more than 80%) of the denitrification activity was taking place in and around a decomposing leaf that represented less than 1% of the core volume (Figure 6).
Figure 6

The importance of hotspots in a soil core. After measuring denitrification on the entire core (a), the core was split into three segments (b), which showed that most of the activity was occurring in the top segment. The top segment was then split into five sections (c), which showed that the majority of activity was occurring in the very top segment. This segment was dissected (d), which showed that 85% of the denitrification activity in the 5,190 g soil core was taking place in a 0.08 g piece of plant detritus. From Parkin (1987).

The hotspot concept is also useful at larger scales. For example, particular components of landscapes, e.g., riparian zones or areas of intensive agricultural activity within regions, are potential hotspots of denitrification (Butterbach-Bahl & Dannenmann 2011; Harms & Grimm 2008; McClain et al. 2003; Vidon et al. 2010). Expansion of the hotspot concept to landscape and regional scales was particularly important for producing estimates of denitrification relevant to N-induced water and air quality problems.

The hot moment concept is rooted in the well established idea that bursts of activity following drying-rewetting and freezing-thawing events are important to C and N dynamics in soils (Birch 1958; Edwards & Cresser 1992). Denitrification can be important during these events as the addition of water from rewetting or thawing can restrict O2 diffusion into soil, and bursts of respiration can consume significant amounts of O2 (Goodroad & Keeney 1984; Groffman & Tiedje 1988). Similar to hotspots, hot moments are also useful at larger scales. Particular seasons or seasonal transitions (e.g., snowmelt, early spring) or events (e.g., litterfall, floods) can account for a very high percentage of annual or decadal denitrification activity (McClain et al. 2003).

Recognition of the importance of hotspots and hot moments is a great aid to experimental design for denitrification studies. In any study, at any scale, investigators should design their study to encompass the small areas and brief periods that are likely to account for a significant amount of activity. For example in studies in crop fields, sampling campaigns need to account for low areas in the field that flood for brief periods (Gentry et al. 1998) and for seasonal transitions, e.g., snowmelt or harvest that could create suitable conditions for high rates of denitrification. Landscape-scale studies need to focus on riparian zones and other areas of “hydrologic convergence” that create optimal conditions for denitrification (Harms & Grimm 2008; Tague et al. 2010; Vidon et al. 2010; Walter et al. 2000). In regional-scale studies, we need to focus on areas with high N inputs and/or wet soils. As our ability to conceptualize and then quantitatively map (discussed below) hotspots and hot moments increases, our experimental designs (and results and understanding) are likely to improve.

Recent advances in molecular and microbial approaches are likely to be an important aid to understanding the dynamics of hotspots and hot moments. As our ability to understand the factors regulating denitrifying communities (Bergaust et al. 2011; Kandeler et al. 2006; Philippot et al. 2009; Wallenstein et al. 2006; Wang et al. 2011b) and microbial and molecular dynamics during episodes such as drying/rewetting events and other environmental changes (Attard et al. 2011; Enwall et al. 2010; Evans & Wallenstein 2012) improves, it will become easier to incorporate these phenomena into experimental designs and sampling campaigns.

Challenges and opportunities in temporal and spatial scaling

Scaling information from small-scale point measurements to larger areas and time periods is a great challenge in many areas of environmental science but is especially challenging for denitrification due to inherently high variability at the microbial scale of the process. Yet there is a strong need for information on denitrification at relatively large spatial (meters to kilometers and larger) and temporal (years, decades) scales. Recent advances in scaling have come from improvements in the ability to identify and quantify the hotspots and hot moments that dominate denitrification fluxes and in simulation models that can be run over large areas and time periods.

Improvements in remote sensing and geographic information system technology have improved our ability to identify and quantify hotspots of denitrification at ecosystem, landscape and regional scales. For example, in forested ecosystems or landscapes, soil wetness and N availability are the dominant controllers of variation in denitrification (Groffman & Tiedje 1989). New algorithms applied to high resolution digital elevation models can now depict the presence of wet areas in forested landscapes at high resolution (Beven 1997; Tague et al. 2010; Walter et al. 2000). At the same time, remote sensing estimates of foliar N or lignin:N provide a high resolution landscape- and regional-scale index of N cycle hotspots (Martin et al. 2008; Ollinger et al. 2008; Ollinger et al. 2002). Thus we now have landscape- and regional-scale tools capable of identifying and quantifying potential hotspots (Figure 7) of denitrification.
Figure 7

A topographic index of soil wetness (a) and AVIRIS-derived foliar N (~17 m resolution) (b) and for the ~ 3,000 ha Hubbard Brook Experimental Forest, NH, USA. Note “hotspots” of high foliar N (light colors) in the cutover watersheds in the top right corner of the image and dark areas of low foliar N in the conifer-dominated areas at the bottom/center and top left corners of the image. From Kulkarni et al. (2008).

As described above, new soil O2 sensors or models can be used as temporal scaling tools if they can depict hot moments of activity driven by rainfall events or events such as snowmelt or litterfall. These dynamics are likely complex, however, as soil O2 is strongly affected by soil moisture, which inhibits diffusion of O2 into the soil, but also by soil respiration, which consumes O2 (Liptzin et al. 2011; Silver et al. 1999). However, new ecohydrological models have the potential to model the presence of wet areas in the landscape as well as the biogeochemical processes that drive soil respiration (Butterbach-Bahl et al. 2004; Tague 2009).

Indeed there have been many advances in simulation models that facilitate scaling of denitrification estimates to large areas and long time periods. The Denitrification-Decomposition (or DNDC) model is a daily time-step model of C and N biogeochemistry that focuses on simulation of soil O2 levels and denitrification rates (Li et al. 2000). DNDC and other models can be linked to/driven by geographic information to produce landscape- and regional-scale estimates of denitrification (Butterbach-Bahl et al. 20012004). Much of the motivation for model development has come from efforts to provide estimates of N2O flux at large scales for national- and regional-scale greenhouse gas inventories. It is easier to test the ability of a model to depict N2O fluxes, at least at the field chamber scale, than to test the ability of a model to depict total denitrification or N2 fluxes (David et al. 2009). There is a great need to evaluate the ability of these models to simulate N2 fluxes, either through model comparisons or by comparisons of measured fluxes and isotope measurements as discussed above.

The ecohydrological models that are based on spatially explicit depiction of the movement of water across the landscape (Beven & Kirkby 1997) are perhaps the most promising modeling development to increase our ability to estimate denitrification at ecosystem, landscape and regional scales. These models process water and nutrients as they move though different landscape elements and therefore have the potential for depicting both hotspots and hot moments of denitrification activity if they operate at sufficiently high resolution (Band et al. 2001; Haas et al. 2012; Tague 2009; Tague & Band 2004). Testing the denitrification algorithms in these models with field data and independent isotope approaches in multiple sites could yield significant improvements in our understanding and estimates of denitrification at landscape and regional scales.

Conclusions

The need for information on terrestrial denitrification has never been greater. With keen societal interest in reactive N delivery to receiving waters and the atmosphere, there is a great need for information on denitrification rates and controlling factors. Lack of information on denitrification is a fundamental constraint on the ability of society to address N pollution problems in many areas (Davidson et al. 2012; Galloway et al. 2008).

However, new advances in methods, scaling and modeling make it quite likely that we will soon be able to meet societal needs for information on denitrification. Improved methods for measuring flux at the small scale can be combined with new approaches for scaling and/or modeling to produce estimates of denitrification that are increasingly relevant to questions about eutrophication of coastal water bodies and regional and global N2O budgets.

Efforts to improve estimates of terrestrial denitrification need to proceed in several areas. For methods, we need to move beyond extracted soil cores and push for improvements in mass spectrometry that will allow for direct quantification of N2 and/or tracer-level 15N2 in field plots. Ultimately, area-integrated (e.g., from eddy flux towers) measurements need to replace point (core) measurements. While this technology is developing nicely for N2O, it remains very challenging to measure fluxes of N2 from the soil to the atmosphere. Isotope mass balance and modeling methods should continue to improve and should provide an important comparison/validation of direct measurements.

At the same time, we need continued improvements in tools for detecting and quantifying the drivers of hotspot and hot moment phenomena at ecosystem, landscape and regional scales. Improvements in remote sensing of N richness and in geographic depiction of wet areas in the landscape are needed at high spatial and temporal resolution. Technology for continuous, often real-time, data on soil moisture, O2 and NO3- is improving and should be a great aid to depicting hotspot and hot moment dynamics. Finally, there needs to be active interaction between measurement and modeling. Models must be used to evaluate the plausibility of scaled denitrification estimates, and point flux measurements must be used to validate model predictions.

Continued progress in denitrification research will be enhanced if multiple approaches are applied at well-studied research sites (Davidson & Seitzinger 2006). If new flux methods can be compared with stable isotope approaches and if multiple models can be applied at sites with well established mass balances, the chances that definitive estimates of denitrification will be produced are higher. Such a process will allow different methods and models to be compared with each other and against other, more easily quantified aspects of the N cycle. Denitrification will continue to be a challenging process to study for many decades to come. Progress is much more likely if research efforts are coordinated and cooperative.

Declarations

Acknowledgements

This work was partially supported by U.S. National Science Foundation grant NSF DEB – 0919131. The manuscript was greatly improved by the comments of two anonymous reviewers.

Authors’ Affiliations

(1)
Cary Institute of Ecosystem Studies

References

  1. Addiscott TM: Modelling the fate of crop nutrients in the environment: problems of scale and complexity. Eur J Agron 1995, 4: 413–417.View ArticleGoogle Scholar
  2. Allison FE: The enigma of soil nitrogen balance sheets. Adv Agron 1955, 7: 213–250.View ArticleGoogle Scholar
  3. Amundson R, Austin AT, Schuur EAG, Yoo K, Matzek V, Kendall C, Uebersax A, Brenner D, Baisden WT: Global patterns of the isotopic composition of soil and plant nitrogen. Global Biogeochem Cycles 2003, 17: GB001903.View ArticleGoogle Scholar
  4. Attard E, Recous S, Chabbi A, De Berranger C, Guillaumaud N, Labreuche J, Philippot L, Schmid B, Le Roux X: Soil environmental conditions rather than denitrifier abundance and diversity drive potential denitrification after changes in land uses. Glob Chang Biol 2011, 17: 1975–1989. 10.1111/j.1365-2486.2010.02340.xView ArticleGoogle Scholar
  5. Bai E, Houlton BZ: Coupled isotopic and process-based modeling of gaseous nitrogen losses from tropical rain forests. Global Biogeochem Cycles 2009, 23: GB003361.View ArticleGoogle Scholar
  6. Band LE, Tague CL, Groffman P, Belt K: Forest ecosystem processes at the watershed scale: hydrological and ecological controls of nitrogen export. Hydrol Processes 2001, 15: 2013–2028. 10.1002/hyp.253View ArticleGoogle Scholar
  7. Bergaust L, Bakken LR, Frostegard A: Denitrification regulatory phenotype, a new term for the characterization of denitrifying bacteria. Biochem Soc Trans 2011, 39: 207–212. 10.1042/BST0390207View ArticleGoogle Scholar
  8. Beven KJ (Ed): Distributed modelling in hydrology. Applications of TOPMODEL. Wiley, Chichester; 1997.Google Scholar
  9. Beven KJ, Kirkby MJ: A physically-based variable contributing area model of basin hydrology. Hydrol Sci Bull 1997, 24: 4369–4382.Google Scholar
  10. Birch H: The effect of soil drying on humus decomposition and nitrogen availability. Plant Soil 1958, 10: 9–31. 10.1007/BF01343734View ArticleGoogle Scholar
  11. Boyer EW, Goodale CL, Jaworski NA, Howarth RW: Anthropogenic nitrogen sources and relationships to riverine nitrogen export in the northeastern USA. Biogeochemistry 2002, 57: 137–169. 10.1023/A:1015709302073View ArticleGoogle Scholar
  12. Burgin AJ, Groffman PM: Soil O2 controls denitrification rates and N 2 O yield in a riparian wetland. J Geophys Res 2012, 117: G01010.Google Scholar
  13. Burgin AJ, Groffman PM, Lewis DN: Factors regulating denitrification in a riparian wetland. Soil Sci Soc Am J 2010, 74: 1826–1833. 10.2136/sssaj2009.0463View ArticleGoogle Scholar
  14. Burgin AJ, Hamilton SK: Have we overemphasized the role of denitrification in aquatic ecosystems? A review of nitrate removal pathways. Front Ecol Environ 2007, 5: 89–96. 10.1890/1540-9295(2007)5[89:HWOTRO]2.0.CO;2View ArticleGoogle Scholar
  15. Butterbach-Bahl K, Dannenmann M: Denitrification and associated soil N 2 O emissions due to agricultural activities in a changing climate. Curr Opin Environ Sustain 2011, 3: 389–395. 10.1016/j.cosust.2011.08.004View ArticleGoogle Scholar
  16. Butterbach-Bahl K, Stange F, Papen H, Li CS: Regional inventory of nitric oxide and nitrous oxide emissions for forest soils of southeast Germany using the biogeochemical model PnET-N-DNDC. J Geophys Res Atmos 2001, 106: 34155–34166. 10.1029/2000JD000173View ArticleGoogle Scholar
  17. Butterbach-Bahl K, Willibald G, Papen H: Soil core method for direct simultaneous determination of N-2 and N2O emissions from forest soils. Plant Soil 2002, 240: 105–116. 10.1023/A:1015870518723View ArticleGoogle Scholar
  18. Butterbach-Bahl K, Kesik M, Miehle P, Papen H, Li C: Quantifying the regional source strength of N-trace gases across agricultural and forest ecosystems with process based models. Plant Soil 2004, 260: 311–329.View ArticleGoogle Scholar
  19. Casciotti KL, Sigman DM, Hastings MG, Bohlke JK, Hilkert A: Measurement of the oxygen isotopic composition of nitrate in seawater and freshwater using the denitrifier method. Anal Chem 2002, 74: 4905–4912. 10.1021/ac020113wView ArticleGoogle Scholar
  20. Christensen S, Simkins S, Tiedje JM: Spatial variation in denitrification: dependency of activity centers on the soil environment. Soil Sci Soc Am J 1990, 54: 1608–1613. 10.2136/sssaj1990.03615995005400060016xView ArticleGoogle Scholar
  21. David M, Del Grosso S, Hu X, Marshall E, McIsaac G, Parton W, Tonitto C, Youssef M: Modeling denitrification in a tile-drained, corn and soybean agroecosystem of Illinois, USA. Biogeochemistry 2009, 92: 7–30.View ArticleGoogle Scholar
  22. David MB, Gentry LE: Anthropogenic inputs of nitrogen and phosphorus and riverine export for Illinois, USA. J Environ Qual 2000, 29: 494–508.View ArticleGoogle Scholar
  23. Davidson EA, Seitzinger S: The enigma of progress in denitrification research. Ecol Appl 2006, 16: 2057–2063. 10.1890/1051-0761(2006)016[2057:TEOPID]2.0.CO;2View ArticleGoogle Scholar
  24. Davidson EA, David MB, Galloway JN, Goodale CL, Haeuber R, Harrison JA, Howarth RW, Jaynes DB, Lowrance RR, Nolan BT, Peel JL, Pinder RW, Porter E, Snyder CS, Townsend AR, Ward MH: Excess nitrogen in the U.S. environment: trends, risks, and solutions. Issues Ecol 2012, 15: 1–16.Google Scholar
  25. Edwards AC, Cresser MS: Freezing and its effect on chemical and biological properties of soil. Adv Soil Sci 1992, 18: 61–79.Google Scholar
  26. Enwall K, Throback IN, Stenberg M, Soderstrom M, Hallin S: Soil resources influence spatial patterns of denitrifying communities at scales compatible with land management. Appl Environ Microbiol 2010, 76: 2243–2250. 10.1128/AEM.02197-09View ArticleGoogle Scholar
  27. Erisman JW, Galloway J, Seitzinger S, Bleeker A, Butterbach-Bahl K: Reactive nitrogen in the environment and its effect on climate change. Curr Opin Environ Sustain 2011, 3: 281–290. 10.1016/j.cosust.2011.08.012View ArticleGoogle Scholar
  28. Evans S, Wallenstein M: Soil microbial community response to drying and rewetting stress: does historical precipitation regime matter? Biogeochemistry 2012, 109: 101–116. 10.1007/s10533-011-9638-3View ArticleGoogle Scholar
  29. Folorunso OA, Rolston DE: Spatial variability of field measured denitrification gas fluxes. Soil Sci Soc Am J 1984, 48: 1214–1219. 10.2136/sssaj1984.03615995004800060002xView ArticleGoogle Scholar
  30. Frank DA, Groffman PM: Plant rhizospheric N processes: what we don't know and why we should care. Ecology 2009, 90: 1512–1519. 10.1890/08-0789.1View ArticleGoogle Scholar
  31. Galloway JN, Townsend AR, Erisman JW, Bekunda M, Cai ZC, Freney JR, Martinelli LA, Seitzinger SP, Sutton MA: Transformation of the nitrogen cycle: recent trends, questions, and potential solutions. Science 2008, 320: 889–892. 10.1126/science.1136674View ArticleGoogle Scholar
  32. Gentry LE, David MB, Smith KM, Kovacic DA: Nitrogen cycling and tile drainage nitrate loss in a corn/soybean watershed. Agric Ecosyst Environ 1998, 68: 85–97. 10.1016/S0167-8809(97)00139-4View ArticleGoogle Scholar
  33. Goodale CL, Lajtha K, Nadelhoffer KJ, Boyer EW, Jaworski NA: Forest nitrogen sinks in large eastern US watersheds: estimates from forest inventory and an ecosystem model. Biogeochemistry 2002, 57: 239–266. 10.1023/A:1015796616532View ArticleGoogle Scholar
  34. Goodroad LL, Keeney DR: Nitrous oxide emissions from soils during thawing. Can J Soil Sci 1984, 64: 187–194. 10.4141/cjss84-020View ArticleGoogle Scholar
  35. Groffman P, Butterbach-Bahl K, Fulweiler R, Gold A, Morse J, Stander E, Tague C, Tonitto C, Vidon P: Challenges to incorporating spatially and temporally explicit phenomena (hotspots and hot moments) in denitrification models. Biogeochemistry 2009, 92: 49–77.View ArticleGoogle Scholar
  36. Groffman PM: Ecology of nitrification and denitrification in soil evaluated at scales relevant to atmospheric chemistry. In Microbial production and consumption of greenhouse gases: methane. Edited by: Whitman WB, Rogers J. Nitrogen Oxides and Halomethanes American Society of Microbiology, Washington DC; 1991:201–217.Google Scholar
  37. Groffman PM, Tiedje JM: Denitrification hysteresis during wetting and drying cycles in soil. Soil Sci Soc Am J 1988, 52: 1626–1629. 10.2136/sssaj1988.03615995005200060022xView ArticleGoogle Scholar
  38. Groffman PM, Tiedje JM: Denitrification in north temperate forest soils—spatial and temporal patterns at the landscape and seasonal scales. Soil Biol Biochem 1989, 21: 613–620. 10.1016/0038-0717(89)90053-9View ArticleGoogle Scholar
  39. Groffman PM, Altabet MA, Bohlke JK, Butterbach-Bahl K, David MB, Firestone MK, Giblin AE, Kana TM, Nielsen LP, Voytek MA: Methods for measuring denitrification: diverse approaches to a difficult problem. Ecol Appl 2006, 16: 2091–2122. 10.1890/1051-0761(2006)016[2091:MFMDDA]2.0.CO;2View ArticleGoogle Scholar
  40. Haas E, Klatt S, Fröhlich A, Kraft P, Werner C, Kiese R, Grote R, Breuer L, Butterbach-Bahl K: LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale. Landsc Ecol 2012., 27: in press in pressGoogle Scholar
  41. Haider K, Mosier A, Heinemeyer O: The effect of growing plants on denitrification at high soil nitrate concentrations. Soil Sci Soc Am J 1987, 51: 97–102. 10.2136/sssaj1987.03615995005100010021xView ArticleGoogle Scholar
  42. Harms TK, Grimm NB: Hot spots and hot moments of carbon and nitrogen dynamics in a semiarid riparian zone. J Geophys Res-Biogeo 2008, 113: G101020.View ArticleGoogle Scholar
  43. Hofstra N, Bouwman A: Denitrification in agricultural soils: summarizing published data and estimating global annual rates. Nutr Cycl Agroecosyst 2005, 72: 267–278. 10.1007/s10705-005-3109-yView ArticleGoogle Scholar
  44. Houlton BZ, Bai E: Imprint of denitrifying bacteria on the global terrestrial biosphere. Proc Natl Acad Sci U S A 2009, 106: 21713–21716. 10.1073/pnas.0912111106View ArticleGoogle Scholar
  45. Houlton BZ, Sigman DM, Hedin LO: Isotopic evidence for large gaseous nitrogen losses from tropical rainforests. Proc Natl Acad Sci U S A 2006, 103: 8745–8750. 10.1073/pnas.0510185103View ArticleGoogle Scholar
  46. Howarth RW, Billen G, Swaney D, Townsend A, Jaworski N, Lajtha K, Downing JA, Elmgren R, Caraco N, Jordan T, Berendse F, Freney J, Kudeyarov V, Murdoch P, Zhu ZL: Regional nitrogen budgets and riverine N&P fluxes for the drainages to the North Atlantic Ocean: natural and human influences. Biogeochemistry 1996, 35: 75–139. 10.1007/BF02179825View ArticleGoogle Scholar
  47. Huygens D, Boeckx P, Vermeulen J, De Paepe X, Park A, Barker S, Pullan C, Van Cleemput O: Advances in coupling a commercial total organic carbon analyser with an isotope ratio mass spectrometer to determine the isotopic signal of the total dissolved nitrogen pool. Rapid Commun Mass Spectrom 2005, 19: 3232–3238. 10.1002/rcm.2178View ArticleGoogle Scholar
  48. Kandeler E, Deiglmayr K, Tscherko D, Bru D, Philippot L: Abundance of narG, nirS, nirK, and nosZ genes of denitrifying bacteria during primary successions of a glacier foreland. Appl Environ Microbiol 2006, 72: 5957–5962. 10.1128/AEM.00439-06View ArticleGoogle Scholar
  49. Kendall C: Tracing nitrogen sources and cycling. In Isotope tracers in catchment hydrology. Edited by: Kendall C, McDonnell JJ. Elsevier Scientific, New York; 1998:519–576.View ArticleGoogle Scholar
  50. Kendall C, Elliott EM, Wankel SD: Tracing anthropogenic inputs of nitrogen to ecosystems. In Stable isotopes in ecology and environmental science. 2nd edition. Edited by: Michener RM, Lajtha K. Blackwell Scientific, London; 2007:375–449.View ArticleGoogle Scholar
  51. Kool DM, Wrage N, Oenema O, Van Kessel C, Van Groenigen JW: Oxygen exchange with water alters the oxygen isotopic signature of nitrate in soil ecosystems. Soil Biol Biochem 2011, 43: 1180–1185. 10.1016/j.soilbio.2011.02.006View ArticleGoogle Scholar
  52. Kulkarni MV, Groffman PM, Yavitt JB: Solving the global nitrogen problem: it's a gas! Front Ecol Environ 2008, 6: 199–206. 10.1890/060163View ArticleGoogle Scholar
  53. Li CS, Aber J, Stange F, Butterbach-Bahl K, Papen H: A process-oriented model of N 2 O and NO emissions from forest soils: 1. Model development. J Geophys Res-Atmos 2000, 105: 4369–4384. 10.1029/1999JD900949View ArticleGoogle Scholar
  54. Liptzin D, Silver W, Detto M: Temporal dynamics in soil oxygen and greenhouse gases in two humid tropical forests. Ecosystems 2011, 14: 171–182. 10.1007/s10021-010-9402-xView ArticleGoogle Scholar
  55. Lowrance R: Nitrogen outputs from a field size agricultural watershed. J Environ Qual 1992, 21: 602–607.View ArticleGoogle Scholar
  56. Martin ME, Plourde LC, Ollinge SV, Smith ML, McNeil BE: A generalizable method for remote sensing of canopy nitrogen across a wide range of forest ecosystems. Remote Sens Environ 2008, 112: 3511–3519. 10.1016/j.rse.2008.04.008View ArticleGoogle Scholar
  57. McClain ME, Boyer EW, Dent CL, Gergel SE, Grimm NB, Groffman PM, Hart SC, Harvey JW, Johnston CA, Mayorga E, McDowell WH, Pinay G: Biogeochemical hot spots and hot moments at the interface of terrestrial and aquatic ecosystems. Ecosystems 2003, 6: 301–312. 10.1007/s10021-003-0161-9View ArticleGoogle Scholar
  58. Nicholls JC, Trimmer M: Widespread occurrence of the anammox reaction in estuarine sediments. Aquat Microb Ecol 2009, 55: 105–113.View ArticleGoogle Scholar
  59. NRC: Rethinking the ozone problem in urban and regional Air pollution. National Academy Press, Washington DC; 1992.Google Scholar
  60. Ollinger SV, Richardson AD, Martin ME, Hollinger DY, Frolking SE, Reich PB, Plourde LC, Katuld GG, Mungere JW, Orend R, Smith M-L, Paw UKT, Bolstad PV, Cook BD, Daya MC, Martin TA, Monson RK, Schmid HP: Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: functional relations and potential climate feedbacks. Proc Natl Acad Sci U S A 2008, 105: 19336–19341. 10.1073/pnas.0810021105View ArticleGoogle Scholar
  61. Ollinger SV, Smith ML, Martin ME, Hallett RA, Goodale CL, Aber JD: Regional variation in foliar chemistry and N cycling among forests of diverse history and composition. Ecology 2002, 83: 339–355.Google Scholar
  62. Parkin TB: Soil microsites as a source of denitrification variability. Soil Sci Soc Am J 1987, 51: 1194–1199. 10.2136/sssaj1987.03615995005100050019xView ArticleGoogle Scholar
  63. Parkin TB, Starr JL, Meisinger JJ: Influence of sample size on measurement of soil denitrification. Soil Sci Soc Am J 1987, 51: 1492–1501. 10.2136/sssaj1987.03615995005100060017xView ArticleGoogle Scholar
  64. Philippot L, Hallin S, Schloter M: Ecology of denitrifying prokaryotes in agricultural soil. Adv Agron 2007, 96: 249–305.View ArticleGoogle Scholar
  65. Philippot L, Čuhel J, Saby NPA, Chèneby D, Chroňáková A, Bru D, Arrouays D, Martin-Laurent F, Šimek M: Mapping field-scale spatial patterns of size and activity of the denitrifier community. Environ Microbiol 2009, 11: 1518–1526. 10.1111/j.1462-2920.2009.01879.xView ArticleGoogle Scholar
  66. Prather M, Derwent R, Ehhalt D, Fraser PJ, Sanhueza E, Zhou X: Other trace gases and atmospheric chemistry. In Climate change 1994. Radiative forcing of climate change and an evaluation of the IPCC IS92 Emission Scenarios. Edited by: Houghton JT, Meiro Filho LG, Callander BA, Harris N, Kattenburg A, Maskell K. Cambridge University Press, New York; 1995:73–126.Google Scholar
  67. Reddy KR, Patrick WH: Nitrogen transformations and loss in flooded soils and sediments. CRC Crit Rev Environ Control 1984, 13: 273–309.View ArticleGoogle Scholar
  68. Robertson GP, Huston MA, Evans FC, Tiedje JM: Spatial variability in a successional plant community: patterns of nitrogen availability. Ecology 1988, 69: 1517–1524. 10.2307/1941649View ArticleGoogle Scholar
  69. Rolston DE, Broadbent FE, Goldhamer DA: Field measurement of denitrification: II. Mass balance and sampling uncertainty. Soil Sci Soc Am J 1979, 43: 703–708. 10.2136/sssaj1979.03615995004300040015xView ArticleGoogle Scholar
  70. Seitzinger S, Harrison JA, Bohlke JK, Bouwman AF, Lowrance R, Peterson B, Tobias C, Van Drecht G: Denitrification across landscapes and waterscapes: a synthesis. Ecol Appl 2006, 16: 2064–2090. 10.1890/1051-0761(2006)016[2064:DALAWA]2.0.CO;2View ArticleGoogle Scholar
  71. Sexstone AJ, Revsbech NP, Parkin TB, Tiedje JM: Direct measurement of oxygen profiles and denitrification rates in soil aggregates. Soil Sci Soc Am J 1985, 49: 645–651. 10.2136/sssaj1985.03615995004900030024xView ArticleGoogle Scholar
  72. Sigman DM, Casciotti KL, Andreani M, Barford C, Galanter M, Bohlke JK: A bacterial method for the nitrogen isotopic analysis of nitrate in seawater and freshwater. Anal Chem 2001, 73: 4145–4153. 10.1021/ac010088eView ArticleGoogle Scholar
  73. Silver WL, Lugo AE, Keller M: Soil oxygen availability and biogeochemistry along rainfall and topographic gradients in upland wet tropical forest soils. Biogeochemistry 1999, 44: 301–328.Google Scholar
  74. Smith KA: A model of the extent of anaerobic zones in aggregated soils, and its potential application to estimates of denitrification. J Soil Sci 1980, 31: 263–277. 10.1111/j.1365-2389.1980.tb02080.xView ArticleGoogle Scholar
  75. Söderlund R, Svensson BH: The global nitrogen cycle. In Nitrogen, phosphorus and sulfur—global cycles. SCOPE report 7. Edited by: Svensson BH, Söderlund R. Ecological Bulletins, Stockholm; 1977:23–73.Google Scholar
  76. Stange CF, Spott O, Müller C: An inverse abundance approach to separate soil nitrogen pools and gaseous nitrogen fluxes into fractions related to ammonium, nitrate and soil organic nitrogen. Eur J Soil Sci 2009, 60: 907–915. 10.1111/j.1365-2389.2009.01188.xView ArticleGoogle Scholar
  77. Steinheimer TR, Scoggin KD, Kramer LA: Agricultural chemical movement through a field-size watershed in Iowa: subsurface hydrology and distribution of nitrate in groundwater. Environ Sci Technol 1998, 32: 1039–1047. 10.1021/es970598jView ArticleGoogle Scholar
  78. Swerts M, Uytterhoeven G, Merckx R, Vlassak K: Semicontinuous measurement of soil atmosphere gases with gas-flow soil core method. Soil Sci Soc Am J 1995, 59: 1336–1342. 10.2136/sssaj1995.03615995005900050020xView ArticleGoogle Scholar
  79. Tague C: Modeling hydrologic controls on denitrification: sensitivity to parameter uncertainty and landscape representation. Biogeochemistry 2009, 92: 79–90.View ArticleGoogle Scholar
  80. Tague CL, Band LE: RHESSys: regional hydro-ecologic simulation system—an object oriented approach to spatially distributed modeling of carbon, water and nutrient cycling. Earth Interact 8 2004. Paper 19 Paper 19Google Scholar
  81. Tague C, Band L, Kenworthy S, Tenebaum D: Plot- and watershed-scale soil moisture variability in a humid Piedmont watershed. Water Resour Res 2010, 46: W12541.View ArticleGoogle Scholar
  82. Van Breemen N, Boyer EW, Goodale CL, Jaworski NA, Paustian K, Seitzinger SP, Lajtha K, Mayer B, Van Dam D, Howarth RW, Nadelhoffer KJ, Eve M, Billen G: Where did all the nitrogen go? Fate of nitrogen inputs to large watersheds in the northeastern USA. Biogeochemistry 2002, 57: 267–293. 10.1023/A:1015775225913View ArticleGoogle Scholar
  83. Vidon P, Allan C, Burns D, Duval TP, Gurwick N, Inamdar S, Lowrance R, Okay J, Scott D, Sebestyen S: Hot spots and hot moments in riparian zones: potential for improved water quality management. JAWRA J Am Water Resour As 2010, 46: 278–298. 10.1111/j.1752-1688.2010.00420.xView ArticleGoogle Scholar
  84. Vitousek PM, Howarth RW: Nitrogen limitation on land and in the sea—how can it occur? Biogeochemistry 1991, 13: 87–115.View ArticleGoogle Scholar
  85. Wallenstein MD, Myrold DD, Firestone M, Voytek M: Environmental controls on denitrifying communities and denitrification rates: insights from molecular methods. Ecol Appl 2006, 16: 2143–2152. 10.1890/1051-0761(2006)016[2143:ECODCA]2.0.CO;2View ArticleGoogle Scholar
  86. Walter MT, Walter MF, Brooks ES, Steenhuis TS, Boll J, Weiler K: Hydrologically sensitive areas: variable source area hydrology implications for water quality risk assessment. J Soil Water Conserv 2000, 55: 277–284.Google Scholar
  87. Wang R, Willibald G, Feng Q, Zheng X, Liao T, Br̈ggemann N, Butterbach-Bahl K: Measurement of N 2 , N 2 O, NO, and CO 2 emissions from soil with the gas-flow-soil-core technique. Environ Sci Technol 2011a, 45: 6066–6072. 10.1021/es1036578View ArticleGoogle Scholar
  88. Wang S-Y, Sudduth EB, Wallenstein MD, Wright JP, Bernhardt ES: Watershed urbanization alters the composition and function of stream bacterial communities. PLoS One 2011, 6: e22972. 10.1371/journal.pone.0022972View ArticleGoogle Scholar
  89. Well R, Flessa H: Isotopologue signatures of N 2 O produced by denitrification in soils. J Geophys Res-Biogeo 2009, 114: G02020.View ArticleGoogle Scholar
  90. Woldendorp JW: The quantitative influence of the rhizosphere on denitrification. Plant Soil 1962, 17: 267–270. 10.1007/BF01376229View ArticleGoogle Scholar
  91. Yang WH, Silver WL: Application of the N2/Ar technique to measuring soil-atmosphere N2 fluxes. Rapid Commun Mass Spectrom 2012, 26: 449–459. 10.1002/rcm.6124View ArticleGoogle Scholar
  92. Yang WH, Weber KA, Silver WL: Nitrogen loss from soil through anaerobic ammonium oxidation coupled to iron reduction. Nature Geosci 2012, 5: 538–541. 10.1038/ngeo1530View ArticleGoogle Scholar

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