Warming can boost denitrification disproportionately due to altered oxygen dynamics

Background

Global warming and the alteration of the global nitrogen cycle are major anthropogenic threats to the environment. Denitrification, the biological conversion of nitrate to gaseous nitrogen, removes a substantial fraction of the nitrogen from aquatic ecosystems, and can therefore help to reduce eutrophication effects. However, potential responses of denitrification to warming are poorly understood. Although several studies have reported increased denitrification rates with rising temperature, the impact of temperature on denitrification seems to vary widely between systems.

Methodology/Principal Findings

We explored the effects of warming on denitrification rates using microcosm experiments, field measurements and a simple model approach. Our results suggest that a three degree temperature rise will double denitrification rates. By performing experiments at fixed oxygen concentrations as well as with oxygen concentrations varying freely with temperature, we demonstrate that this strong temperature dependence of denitrification can be explained by a systematic decrease of oxygen concentrations with rising temperature. Warming decreases oxygen concentrations due to reduced solubility, and more importantly, because respiration rates rise more steeply with temperature than photosynthesis.

Conclusions/Significance

Our results show that denitrification rates in aquatic ecosystems are strongly temperature dependent, and that this is amplified by the temperature dependencies of photosynthesis and respiration. Our results illustrate the broader phenomenon that coupling of temperature dependent reactions may in some situations strongly alter overall effects of temperature on ecological processes.     

Comparison of denitrification characteristics among three habitat types of a large river floodplain: Atchafalaya River Basin,Louisiana

Mobile forms of nitrogen leach from upland environments into aquatic systems, often discharging to coastal zones. Addition of nitrogen to once N-limited systems results in a host of changes ranging from eutrophication to loss of biodiversity. Floodplains can ameliorate these changes by removing and sequestering nitrogen. In many coastal floodplains, sedimentation causes lakes to transition to baldcypress swamps, and ultimately to bottomland hardwood (BLHW) forests. These habitats differ in their contact with floodwater, which directly and indirectly affects their ability to process nutrients, but the effects of habitat change on denitrification at the floodplain scale cannot be predicted because of lack of suitable data. This study compared denitrification characteristics among the aforementioned habitats within the Atchafalaya River Basin (ARB). Microcosms were established in the laboratory, and the acetylene block technique was used to estimate four denitrification characteristics: background denitrification rates, maximum rates, time to reach maximum rates, and the linear response of denitrification to nitrate concentration. There were significant differences in denitrification characteristics among the three habitat types; specifically, all habitats differed in the time required for denitrification to respond to nitrate in the overlying water, and denitrification in lake habitats differed from both BLHWs and baldcypress swamps. Landscape-scale models should account for different linear relationships between denitrification and nitrate concentrations, and different response times to nitrate concentrations for different habitats. Because denitrification characteristics differ across habitats within the ARB, continued habitat change within the floodplain will alter nutrient discharge to coastal waters.     

Tracing sources and pathways of dissolved nitrate in forest and river ecosystems using high-resolution isotopic techniques: a review

Nitrogen inputs into stream and river ecosystems, and the factors influencing those inputs, are important for various ecological and environmental concerns. Reliable information on where and how nitrogen compounds flow into aquatic ecosystems is indispensable to understanding the nutrient status of these ecosystems. Such information should include the biogeochemical mechanisms and hydrological controls of nutrient leaching into rivers from terrestrial systems such as forests, agricultural fields, and urbanized areas. Advancements in stable isotopomer measurements over the past two decades have expanded the variety of target substances and the precision with which they can be investigated. The high-throughput microbial denitrifier method allows for simultaneous measurement of nitrogen and oxygen isotope ratios and can provide high-resolution spatiotemporal information on both nitrate sources and biogeochemical processes. Although advanced techniques of stable isotope analysis have been used extensively to detect sources and estimate the relative contributions of multi-source systems in various rivers, there are still new horizons in investigating nitrogen transformations. For example, stable isotopes of oxygen (¹⁸O and ¹⁷O) occurring in nitrate due to atmospheric deposition can be used as natural tracers for evaluating internal nitrogen cycling; these isotopes are distinct from the oxygen within microbially generated nitrate in soils and water bodies. Another future challenge is improved use of nitrous oxide isotopomers in evaluating the relative contributions of nitrification and denitrification. Such analysis could provide insight into the nitrogen transformation that occurs under redox conditions at the boundary between terrestrial and aquatic systems, where nitrification and denitrification often occur simultaneously in soil and aquatic environments.     

The application of Artificial Neural Network (ANN) model to the simulation of denitrification rates in mesocosm-scale wetlands

Denitrification and its regulating factors are of great importance to aquatic ecosystems, as denitrification is a critical process to nitrogen removal. Additionally, a by-product of denitrification, nitrous oxide, is a much more potent greenhouse gas than carbon dioxide. However, the estimation of denitrification rates is usually clouded with uncertainty, mainly due to high spatial and temporal variations, as well as complex regulating factors within wetlands. This hampers the development of general mechanistic models for denitrification as well, as most previously developed models were empirical or exhibited low predictability with numerous assumptions. In this study, we tested Artificial Neural Network (ANN) as an alternative to classic empirical models for simulating denitrification rates in wetlands. ANN, multiple linear regression (MLR) with two different methods, and simplified mechanistic models were applied to estimate the denitrification rates of 2-year observations in a mesocosm-scale constructed wetland system. MLR and simplified mechanistic models resulted in lower prediction power and higher residuals compared to ANN. Although the stepwise linear regression model estimated similar average values of denitrification rates, it could not capture the fluctuation patterns accurately. In contrast, ANN model achieved a fairly high predictability, with an R² of 0.78 for model validation, 0.93 for model calibration (training), and a low root mean square error (RMSE) together with low bias, indicating a high capacity to simulate the dynamics of denitrification. According to a sensitivity analysis of the ANN, non-linear relationships between input variables and denitrification rates were well explained. In addition, we found that water temperature, denitrifying enzyme activity (DEA), and DO accounted for 70% of denitrification rates. Our results suggest that the ANN developed in this study has a greater performance in simulating variations in denitrification rates than multivariate linear regressions or simplified nonlinear mechanistic model.     

湖泊氮素氧化及脱氮过程研究进展

自然界中氮的生物地球化学循环主要由微生物驱动,由固氮作用、硝化作用、反硝化作用和氨化作用来完成。过去数十年间,随着异养硝化、厌氧氨氧化和古菌氨氧化作用的发现,人们对环境中氮素循环认识逐步深入,提出了多种脱氮途径新假说。对湖泊生态系统中氮素的输入、输出及其在水体、沉积物和水土界面的迁移转化过程进行了概括,对湖泊生态系统中反硝化和厌氧氨氧化脱氮机理及脱氮效率的最新研究进展进行了探讨,并对以后的氮素循环研究进行了展望。     

Challenges to incorporating spatially and temporally explicit phenomena (hotspots and hot moments) in denitrification models

Denitrification, the anaerobic reduction of nitrogen oxides to nitrogenous gases, is an extremely challenging process to measure and model. Much of this challenge arises from the fact that small areas (hotspots) and brief periods (hot moments) frequently account for a high percentage of the denitrification activity that occurs in both terrestrial and aquatic ecosystems. In this paper, we describe the prospects for incorporating hotspot and hot moment phenomena into denitrification models in terrestrial soils, the interface between terrestrial and aquatic ecosystems, and in aquatic ecosystems. Our analysis suggests that while our data needs are strongest for hot moments, the greatest modeling challenges are for hotspots. Given the increasing availability of high temporal frequency climate data, models are promising tools for evaluating the importance of hot moments such as freeze-thaw cycles and drying/rewetting events. Spatial hotspots are less tractable due to our inability to get high resolution spatial approximations of denitrification drivers such as carbon substrate. Investigators need to consider the types of hotspots and hot moments that might be occurring at small, medium, and large spatial scales in the particular ecosystem type they are working in before starting a study or developing a new model. New experimental design and heterogeneity quantification tools can then be applied from the outset and will result in better quantification and more robust and widely applicable denitrification models.     

Nitrogen retention in wetlands,lakes and rivers

As human activities continue to alter the global nitrogen cycle, the ability to predict the impact of increased nitrogen loading to freshwater systems is becoming more and more important. Nitrogen retention is of particular interest because it is through its combined processes (denitrification, nitrogen sedimentation and uptake by aquatic plants) that local and downstream nitrogen concentrations are reduced. Here, we compare the magnitude of nitrogen retention and its components in wetlands, lakes and rivers. We show that wetlands retain the highest proportion of total nitrogen loading, followed by lakes and then rivers. The differences in the proportion of N retained among systems is explained almost entirely by differences in water discharge. Denitrification is the primary mechanism of nitrogen retention, followed by nitrogen sedimentation and uptake by aquatic plants.     

Relations Between Bacterial Biomass and Carbon Cycle in Marine Sediments: An Early Diagenetic Model

A new model for early diagenetic processes has been developed through a new formula explicitly accounting for microbial population dynamics. Following a mechanistic approach based on enzymatic reactions, a new model has been proposed for oxic mineralisation and denitrification. It incorporates the dynamics of bacterial metabolism. We find a general formula for inhibition processes of which some other mathematical expressions are particular cases. Moreover a fast numerical algorithm has been developed. It allows us to perform simulations of different diagenetic models in non-steady states. We use this algorithm to compare our model to a classical one (Soetaert et al., 1996). Dynamical evolutions of a perturbation of particulate organic carbon (POC) input are studied for both models. The results are very similar for stationary cases. But with variable inputs, the bacterial biomass dynamics brings about noticeable differences, and these are discussed.     

Kinetics of nitrogen removal from sanitary landfill leachate

Leachates from municipal landfill ‘Lublinek‘ in Lodz city (Poland) were treated in two-sludge sequence batch reactor systems (type ND). The external carbon source—sodium acetate was used in denitrification. Two versions were tested—with and without supernatant recirculation from D-SBR to N-SBR. The 99% removal of inorganic nitrogen compounds was achieved in both versions. Due to recirculation, the buffering (by means of sodium bicarbonate) was not necessary. Kinetic models for nitrification and denitrification processes were proposed. Kinetic parameters of the models were estimated by the optimization method. The experimental results of both nitrification steps (oxidation of ammonia to nitrites and nitrites to nitrates) were best fitted with the interactive limitation model of nitrogen compounds and oxygen. The denitrification process was limited only by the concentration of nitrogen compounds.     

Simultaneous estimation of sludge biological activity and influent nitrogen load using ORP and DO dynamics

This paper proposes a new optimization strategy to estimate nitrifiable nitrogen concentration in wastewater, nitrification rate, denitrification rate and/or COD available for denitrification of an activated sludge process submitted to intermittent aeration. The approach uses the oxydo-reduction potential and dissolved oxygen measurements only. The parameter identification is based on a Simplex optimization of a cost function related to the error between an experimental cycle (an aerobic period followed by an anoxic one) and a simulation of a reduced model derived from ASM1. Results show very good prediction of experimental oxygen, ammonium and nitrate profiles. The estimation of nitrifiable nitrogen and removal rates has been validated both on simulated data obtained from COST action 624 benchmark and on experimental data.     

Denitrification in a meromictic lake and its relevance to nitrogen flows within a moderately impacted forested catchment

We analysed the spatial and temporal variability of benthic nitrogen fluxes and denitrification rates in a sub-alpine meromictic lake (Lake Idro, Italy), and compared in-lake nitrogen retention and loss with the net anthropogenic nitrogen inputs to the watershed. We hypothesized a low nitrogen retention and denitrification capacity due to meromixis. This results from nitrate supply from the epilimnion slowing down during stratification and oxygen deficiency inhibiting nitrification and promoting ammonium recycling and its accumulation. We also hypothesized a steep vertical gradient of sedimentary denitrification capacity, decreasing with depth and oxygen deficiency. These are important and understudied issues in inland waters, as climate change and direct anthropic pressures may increase the extent of meromixis. Nearshore sediments had high denitrification rates (87 mg m^?2 day^?1) and efficiency (~ 100%), while in the monimolimnion denitrification was negligible. The littoral zone, covering 10% of the lake surface, contributed ~50% of total denitrification, while the monimolimnion, which covered 70% of the sediment surface, contributed to < 13% of total denitrification. The persistent and expanding meromixis of Lake Idro is expected to further decrease its nitrogen removal capacity (31% of the incoming nitrogen load) compared to what has been measured in other temperate lakes. Values up to 60% are generally reported for other such lakes. Results of this study are relevant as the combination of anthropogenic pressures, climate change and meromixis may threaten the nitrogen processing capacity of lakes.     

Denitrification in coastal ecosystems: methods, environmental controls, and ecosystem level controls, a review

In this review of sediment denitrification in estuaries and coastal ecosystems, we examine current denitrification measurement methodologies and the dominant biogeochemical controls on denitrification rates in coastal sediments. Integrated estimates of denitrification in coastal ecosystems are confounded by methodological difficulties, a lack of systematic understanding of the effects of changing environmental conditions, and inadequate attention to spatial and temporal variability to provide both seasonal and annual rates. Recent improvements in measurement techniques involving ¹⁵ N techniques and direct N₂ concentration changes appear to provide realistic rates of sediment denitrification. Controlling factors in coastal systems include concentrations of water column NO ₃ ^– , overall rates of sediment carbon metabolism, overlying water oxygen concentrations, the depth of oxygen penetration, and the presence/absence of aquatic vegetation and macrofauna. In systems experiencing environmental change, either degradation or improvement, the importance of denitrification can change. With the eutrophication of the Chesapeake Bay, the overall rates of denitrification relative to N loading terms have decreased, with factors such as loss of benthic habitat via anoxia and loss of submerged aquatic vegetation driving such effects.     

Calibration and validation of an activated sludge model for greenhouse gases no. 1 (ASMG1): prediction of temperature-dependent N2O emission dynamics

An activated sludge model for greenhouse gases no. 1 was calibrated with data from a wastewater treatment plant (WWTP) without control systems and validated with data from three similar plants equipped with control systems. Special about the calibration/validation approach adopted in this paper is that the data are obtained from simulations with a mathematical model that is widely accepted to describe effluent quality and operating costs of actual WWTPs, the Benchmark Simulation Model No. 2 (BSM2). The calibration also aimed at fitting the model to typical observed nitrous oxide (N₂O) emission data, i.e., a yearly average of 0.5 % of the influent total nitrogen load emitted as N₂O-N. Model validation was performed by challenging the model in configurations with different control strategies. The kinetic term describing the dissolved oxygen effect on the denitrification by ammonia-oxidizing bacteria (AOB) was modified into a Haldane term. Both original and Haldane-modified models passed calibration and validation. Even though their yearly averaged values were similar, the two models presented different dynamic N₂O emissions under cold temperature conditions and control. Therefore, data collected in such situations can potentially permit model discrimination. Observed seasonal trends in N₂O emissions are simulated well with both original and Haldane-modified models. A mechanistic explanation based on the temperature-dependent interaction between heterotrophic and autotrophic N₂O pathways was provided. Finally, while adding the AOB denitrification pathway to a model with only heterotrophic N₂O production showed little impact on effluent quality and operating cost criteria, it clearly affected N₂O emission productions.     

Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration

Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site‐years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two‐stream albedo submodel provided accurate predictions of boreal needle‐leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two‐stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r²=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r²=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two‐stream albedo model and foliage nitrogen concentration. These nitrogen‐based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.     

Direct and Indirect Effects of Dissolved Organic Matter Source and Concentration on Denitrification in Northern Florida Rivers

Using a natural gradient of dissolved organic carbon (DOC) source and concentration in rivers of northern Florida, we investigated how terrestrially-derived DOC affects denitrification rates in river sediments. Specifically, we examined if the higher concentrations of DOC in blackwater rivers stimulate denitrification, or whether such terrestrially-derived DOC supports lower denitrification rates because (1) it is less labile than DOC from aquatic primary production; whether (2) terrestrial DOC directly inhibits denitrification via biochemical mechanisms; and/or whether (3) terrestrial DOC indirectly inhibits denitrification via reduced light availability to—and thus DOC exudation by—aquatic primary producers. We differentiated among these mechanisms using laboratory denitrification assays that subjected river sediments to factorial amendments of NO₃ ^? and dextrose, humic acid dosing, and cross-incubations of sediments and water from different river sources. DOC from terrestrial sources neither depressed nor stimulated denitrification rates, indicating low lability of this DOC but no direct inhibition; humic acid additions similarly did not affect denitrification rates. However, responses to addition of labile C increased with long-term average DOC concentration, which supports the hypothesis that terrestrial DOC indirectly inhibits denitrification via decreased autochthonous production. Observed and future changes in DOC concentration may therefore reduce the ability of inland waterways to remove reactive nitrogen.     

Anaerobic denitrification in fungi from the coastal marine sediments off Goa, India

Denitrification is a microbial process during which nitrate or nitrite is reduced under anaerobic condition to gaseous nitrogen. The Arabian Sea contains one of the major pelagic denitrification zones and in addition to this, denitrification also takes places along the continental shelf. Prokaryotic microorganisms were considered to be the only players in this process. However recent studies have shown that higher microeukaryotes such as fungi can also adapt to anaerobic mode of respiration and reduce nitrate to harmful green house gases such as NO and N₂O. In this study we examined the distribution and biomass of fungi in the sediments of the seasonal anoxic region off Goa from two stations. The sampling was carried out in five different periods from October 2005, when dissolved oxygen levels were near zero in bottom waters to March 2006. We isolated mycelial fungi, thraustochytrids and yeasts. Species of Aspergillus and thraustochytrids were dominant. Fungi were isolated under aerobic, as well as anaerobic conditions from different seasons. Four isolates were examined for their denitrification activity. Two cultures obtained from the anoxic sediments showed better growth under anaerobic condition than the other two cultures that were isolated from oxic sediments. Our preliminary results suggest that several species of fungi can grow under oxygen deficient conditions and participate in denitrification processes.     

Parameterization of photosystem II photoinactivation and repair

The photoinactivation (also termed photoinhibition or photodamage) of Photosystem II (PSII) and the counteracting repair reactions are fundamental elements of the metabolism and ecophysiology of oxygenic photoautotrophs. Differences in the quantification, parameterization and terminology of Photosystem II photoinactivation and repair can erect barriers to understanding, and particular parameterizations are sometimes incorrectly associated with particular mechanistic models. These issues lead to problems for ecophysiologists seeking robust methods to include photoinhibition in ecological models. We present a comparative analysis of terms and parameterizations applied to photoinactivation and repair of Photosystem II. In particular, we show that the target size and quantum yield approaches are interconvertible generalizations of the rate constant of photoinactivation across a range of incident light levels. Our particular emphasis is on phytoplankton, although we draw upon the literature from vascular plants. This article is part of a Special Issue entitled: Photosystem II.