A global dataset of gross nitrogen transformation rates across terrestrial ecosystems

Rates of nitrogen transformations support quantitative descriptions and predictive understanding of the complex nitrogen cycle, but measuring these rates is expensive and not readily available to researchers. Here, we compiled a dataset of gross nitrogen transformation rates (GNTR) of mineralization, nitrification, ammonium immobilization, nitrate immobilization, and dissimilatory nitrate reduction to ammonium in terrestrial ecosystems. Data were extracted from 331 studies published from 1984-2022, covering 581 sites. Globally, 1552 observations were appended with standardized soil, vegetation, and climate data (49 variables in total) potentially contributing to the observed variations of GNTR. We used machine learning-based data imputation to fill in partially missing GNTR, which improved statistical relationships between theoretically correlated processes. The dataset is currently the most comprehensive overview of terrestrial ecosystem GNTR and serves as a global synthesis of the extent and variability of GNTR across a wide range of environmental conditions. Future research can utilize the dataset to identify measurement gaps with respect to climate, soil, and ecosystem types, delineate GNTR for certain ecoregions, and help validate process-based models.

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Publication Details

Journal
Scientific Data
Published
2024-09-19
DOI
https://doi.org/10.1038/s41597-024-03871-3
Citations
10
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
3.34

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article

A global dataset of gross nitrogen transformation rates across terrestrial ecosystems

Wendy H. Yang, Rieko Urakawa, Gerald M. Moser, Pierfrancesco Nardi et al.
10 citations
Scientific Data
Soil Carbon and Nitrogen Dynamics
3.34
article

A global dataset of gross nitrogen transformation rates across terrestrial ecosystems

Wendy H. Yang, Rieko Urakawa, Gerald M. Moser, Pierfrancesco Nardi, Barbara Parisse, Philippe Van Cappellen, Ahmed S. Elrys, Ulderico Neri, Eunji Byun, Anne Jansen‐Willems, Rosario Napoli, José Ignacio Arroyo, Fereidoun Rezanezhad, Jinbo Zhang, Christoph Müller
article en
10 citations

Abstract

Rates of nitrogen transformations support quantitative descriptions and predictive understanding of the complex nitrogen cycle, but measuring these rates is expensive and not readily available to researchers. Here, we compiled a dataset of gross nitrogen transformation rates (GNTR) of mineralization, nitrification, ammonium immobilization, nitrate immobilization, and dissimilatory nitrate reduction to ammonium in terrestrial ecosystems. Data were extracted from 331 studies published from 1984-2022, covering 581 sites. Globally, 1552 observations were appended with standardized soil, vegetation, and climate data (49 variables in total) potentially contributing to the observed variations of GNTR. We used machine learning-based data imputation to fill in partially missing GNTR, which improved statistical relationships between theoretically correlated processes. The dataset is currently the most comprehensive overview of terrestrial ecosystem GNTR and serves as a global synthesis of the extent and variability of GNTR across a wide range of environmental conditions. Future research can utilize the dataset to identify measurement gaps with respect to climate, soil, and ecosystem types, delineate GNTR for certain ecoregions, and help validate process-based models.

Scientific DataVol. 11(1)
University College Dublin (IE), Santa Fe Institute (US), University of Waterloo (CA), Nanjing Normal University (CN), University of Illinois Urbana-Champaign (US), Zagazig University (EG), Justus-Liebig-Universität Gießen (DE), Hainan University (CN), Cereal Research Centre (IT), Asia Center for Air Pollution Research (JP), Yonsei University Health System (KR), University of Chile (CL)
National Science Foundation, Yonsei University, National Research Foundation of Korea
Openalex Percentile: Top 8%
Soil Carbon and Nitrogen Dynamics
3.34
DOIOpen Access PDFOpenAlex
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