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Klaus Butterbach-Bahl

Publications and source records attributed to Klaus Butterbach-Bahl.

2 recordsLinked to original sources

Methods for measuring denitrification: diverse approaches to a difficult problem.

Denitrification, the reduction of the nitrogen (N) oxides, nitrate (NO3-) and nitrite (NO2-), to the gases nitric oxide (NO), nitrous oxide (N2O), and dinitrogen (N2), is important to primary production, water quality, and the chemistry and physics of the atmosphere at ecosystem, landscape, regional, and global scales. Unfortunately, this process is very difficult to measure, and existing methods are problematic for different reasons in different places at different times. In this paper, we review the major approaches that have been taken to measure denitrification in terrestrial and aquatic environments and discuss the strengths, weaknesses, and future prospects for the different methods. Methodological approaches covered include (1) acetylene-based methods, (2) 15N tracers, (3) direct N2 quantification, (4) N2:Ar ratio quantification, (5) mass balance approaches, (6) stoichiometric approaches, (7) methods based on stable isotopes, (8) in situ gradients with atmospheric environmental tracers, and (9) molecular approaches. Our review makes it clear that the prospects for improved quantification of denitrification vary greatly in different environments and at different scales. While current methodology allows for the production of accurate estimates of denitrification at scales relevant to water and air quality and ecosystem fertility questions in some systems (e.g., aquatic sediments, well-defined aquifers), methodology for other systems, especially upland terrestrial areas, still needs development. Comparison of mass balance and stoichiometric approaches that constrain estimates of denitrification at large scales with point measurements (made using multiple methods), in multiple systems, is likely to propel more improvement in denitrification methods over the next few years.

Acetylene↗

Modeling denitrification in terrestrial and aquatic ecosystems at regional scales.

Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source-transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures.

Agriculture↗