4.4 Article

A decision support tool for the selection of 15 N analysis methods of ammonium and nitrate

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NUTRIENT CYCLING IN AGROECOSYSTEMS
卷 125, 期 2, 页码 309-343

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SPRINGER
DOI: 10.1007/s10705-022-10227-z

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Decision support tool; (15) N analysis; Ammonium; Nitrate; Liquid samples

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The stable nitrogen isotope (15N) analysis methods for NH4+ and NO3- have advantages and limitations. A decision support tool (DST) was developed to guide environmental researchers in selecting the optimal method. The DST is a decision tree based on key criteria that users need to consider when choosing the sample preparation method.
The stable nitrogen isotope ((15) N) analysis of ammonium (NH4+) and nitrate (NO3-) is widely used in ecological research, providing insights into N cycling and its underlying regulating mechanisms in both aquatic and terrestrial ecosystems. To date, a large number of methods have been developed for the preparation and measurement of (15) N abundance of NH4+ and NO3- in liquid environmental samples at either natural abundance or enriched levels. However, these methods are all subject to certain specific advantages and limitations, and ecologists might be looking for an efficient way to select the most suitable methods in face of shifting sampling and analytical conditions. Based on our extensive review of these (15) N analysis methods we developed a decision support tool (DST) to provide quick and proper guidance for environmental researchers in finding the optimal method for preparing their liquid samples for (15) N analysis in NH4+ or NO3-. The DST is a decision tree based on several key criteria that users need to take into account when choosing the preferred sample preparation method for their samples. The criteria concern: the sample matrix, the (15) N abundance and the concentration of the target N species, the contamination by other N-containing chemicals, the isotopic fractionation, the availability of equipment, concerns about toxicity of reagents, and the preparation time. This work links field-scale experiments and laboratory (15) N analysis. Potential applications of our decision trees include (15) N studies ranging from natural abundance to tracer level in a wide range of terrestrial, freshwater and marine ecosystems.

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