Data for: Biological mitigation of soil nitrous oxide emissions by plant metabolites
Data files
May 03, 2024 version files 60.94 KB
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README.md
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Table_legend_data.xlsx
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Abstract
Plant metabolites significantly affect soil nitrogen (N) cycling, but their influence on nitrous oxide (N2O) emissions has not been quantitatively analyzed on a global scale. We conduct a comprehensive meta-analysis of 173 observations from 42 articles to evaluate global patterns of, and principal factors controlling, N2O emissions in the presence of root exudates and extracts. Overall, plant metabolites promoted soil N2O emissions by about 10%. However, the effects of plant metabolites on N2O emissions from soils varied with experimental conditions and properties of both metabolites and soils. Primary metabolites, such as sugars, amino acids, and organic acids, strongly stimulated soil N2O emissions, by an average of 79%, while secondary metabolites, such as phenolics, terpenoids, and flavonoids, often characterised as both biological nitrification inhibitors (BNIs) and biological denitrification inhibitors (BDIs), reduced soil N2O emissions by an average of 41%. The emission mitigation effects of BNIs/BDIs were closely associated with soil texture and pH, increasing with increasing soil clay content and soil pH on acidic and neutral soils, and with decreasing soil pH on alkaline soils. We furthermore present soil incubation experiments that show that three secondary metabolite types act as BNIs to reduce N2O emissions by 32-45% while three primary metabolite classes possess a stimulatory effect of 56-63%, confirming the results of the meta-analysis. Our results highlight the potential role and application range of specific secondary metabolites in bio-mitigation of global N2O emissions, and provide new biological parameters for N2O emission models that should help improve the accuracy of model predictions.
README: Biological mitigation of soil nitrous oxide emissions by plant metabolites
https://orcid.org/0009-0000-0549-9400
This dataset serves the article "Biological mitigation of soil nitrous oxide emissions by plant metabolites" from the Global Change Biology, containing data of the cumulative N2O emissions under 173 different treatments extracted from 42 studies. The meanings represented by different abbreviations are shown in the “Table legend”. The “Total data” table contains data on plant metabolite properties(metabolite type, metabolite additive amount, and plant type), soil properties(soil pH, texture, and clay content) and experimental background (nitrogen fertilizer type, nitrogen application rate, experiment duration, and experiment type) extracted from 42 studies. “Data sources” table are the 42 studies from which the data is sourced.
Description of the data and file structure
An extensive literature search to identify all relevant studies for our meta-analysis was conducted via the Web of Science, Google Scholar, and the China National Knowledge Infrastructure (CNKI). The keywords “plant metabolite”, “root exudate”, “plant extracts”, “biological nitrification inhibitors (BNIs)”, “biological denitrification inhibitors (BDIs)” AND “nitrous oxide” or “N2O” were used as search terms. Taking into account all relevant articles published before September 2023, a total of 173 observations contained in 42 studies were identified and compiled.
Cumulative nitrous oxide emissions (kg N2O-N ha-1), the number of replicates(Cn) and (Tn), and the average mean of control (Cmean) and Treatment (Tmean)were extracted from the majority of studies and are reported in a tabular format, which all are essential data for calculating the effect value by formula.
The empty cells in the uploaded table is filled with "N/A", representing the value is not available or not applicable. The filling color between the interval rows in the “Total data” table is different, in order to make the data from different studies display clearer. Some words are highlighted in red font.
Access information
Data was derived from the following sources:
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Software
The mean effect sizes and 95% confidence intervals (CIs) were generated using the OpenMEE software (http://www.cebm.brown.edu/openmee. To detect effect size differences among factors of the categorical variables, between-group heterogeneity tests (QB) were performed. A significant QB value (*P *< 0.05) suggests that the weighted effect sizes of a given variable significantly differed between groups by Spass software.