Data from: Quantifying soil gaseous nitrogen losses from nitrification and denitrification based on nitrogen isotope model
Data files
Mar 11, 2025 version files 10.63 MB
Mar 13, 2025 version files 10.63 MB
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README.md
6.70 KB
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Yu_et_al._2025_Data_for_Model_validation_at_site_scales.xlsx
32.01 KB
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Yu_et_al._2025_Data_for_Simulation_result.zip
10.48 MB
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Yu_et_al._2025_Data_for_soil_15N_meta.xlsx
110.06 KB
Abstract
Gaseous nitrogen (N) losses from nitrification and denitrification (NO+N2O+N2) pathways contribute a significant fraction of the total N losses from cropland ecosystems. However, a large uncertainty exists in estimating the NO+N2O+N2 losses, hindering effective management of the global N budget. Here we proposed a novel isotope model, which considers N fertilizer, ammonia (NH3) volatilization and crop harvest after testing the steady state assumption of soil δ15N and N pool for croplands, and justified if it could be successfully applied to constrain NO+N2O+N2 losses from cropland ecosystems. We compiled the first bulk-soil δ15N dataset of 0-30cm soils (n=738) from croplands and produced a global map of cropland soil δ15N, which is crucial input data for N isotope model to quantify NO+N2O+N2 losses. The results show that the cropland soil δ15N ranges from 3.5 to 9.0‰, with a mean value of 6.6±0.8‰ (mean ± standard deviation). The estimated NO+N2O+N2 losses accounted for an average of 17±9% of N outputs and were 35.86±24.17 kg N ha-1 yr−1 in China’s rice paddies, with an increasing trend from Central China to South or North China. The estimations were comparable with the results from observation-constrained Denitrification-Decomposition modelling (38.9±4.8 kg N ha−1 yr-1) and in good agreement with experimental observations at site scale (R2=0.58). Our results suggest that soil N isotopes, as a quantitative tracer, provide a valuable alternative approach to constrain the NO+N2O+N2 losses in croplands at large geographic scales.
Authors:
Haoming Yu; Wenxin Ba; Peter Dorsch; Wulahati Adalibieke; Yunting Fang; Longfei Yu; Chao Wang; Yihang Duan; Huayan Zhang; Benjamin Z. Houlton; Yan Bo; Yi Wei Jian; Xiao Qing Cui; Edith Bai; Feng Zhou
Principal Investigator Contact Information
Name: Haoming Yu
Institution: Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, P.R. China
Address: No.100 Zhongguancun North Street, Beijing, 100871, China
Email: haoming.yu@pku.edu.cn
Date of data collection: 2023-2024
Description:
This README file describes the data package accompanying the above publication.
Data and File overview:
1. Yu_et_al._2025_Data_for_soil_15N_meta
Dataset of the results from filtering cropland soil 15N measured research. The columns include:
Sheet1: Data for simulating soil 15N
- Title Title of data reference
- Publication Year Publication year of data reference
- Author Author of data reference
- Latitude () The latitude of the respective site
- Longitude () The longitude of the respective site
- Country The country of study sites for data of this experiment or literature
- Sampling depth (cm) Soil depth for soil collection
- Crop type Crop planting types during soil collection
- Sampling year Year of soil collection
- Observed soilN15 () Soil 15N measured data
- Organic fertilizer type/15N () Organic fertilizer type and its relative abundance of 15N
- Organic fertilizer (kg N ha-1 year-1) The amount of organic fertilizer applied in the sampling year
- Inorganic fertilizer (kg N ha-1 year-1) The amount of inorganic fertilizer applied in the sampling year
- Inorganic fertilizer type/15N () Inorganic fertilizer type and its relative abundance of 15N
The next six columns are Random forest input data:
(a) exp((MAT+273.15)/100) Exponential transformation ofannual average temperature (C).
(b) exp(Silt/100) Exponential transformation ofsoil silt content (%).
(c) ln(BNF) Logarithmic transformation ofbiological nitrogen fixation (kg N ha-1 year-1).
(d) Fer_15N 15N from all types of fertilization (g N ha-1 year-1).
(e) ln(Irrpre) Logarithmic transformation of irrigation and annual precipitation (mm).
(f) NOy N deposition in form of NOy (kg N ha-1 year-1).
The null annotation data in this Excel represents data that is zero in the literature.
Sheet2: Refs_soil15N
- Reference References for Sheet 1
2. Yu_et_al._2025_Data_for_Model_validation_at_site_scales
Dataset of the observed data for testing NO+N2O+N2 N loss and runoff and leaching N loss. The columns include:
Sheet1: Observed NO+N2O+N2 N loss rate
- Title Title of data reference
- Journal Publication Journal of data reference
- Author Author of data reference
- Year Publication year of data reference
- Method Data measurement methods
- Insitu/incubation Is the data measured in situ or lab incubation
- Sample year Year of soil collection
- Latitude () The latitude of the respective site
- Longitude () The longitude of the respective site
- Location The study sites for data of this experiment or literature
- Cropping system Crop planting types during soil collection
- incubation time (day) Incubation time during measurement
- Sampling depth (cm) Soil depth for soil collection
- Annual average temperature (C) Average annual temperature at the sampling site
- Annual precipitation (mm) Annual precipitation at the sampling site
- N application rate (kg N ha-1) Nitrogen application at the sampling site
- Fer_15N 15N from all types of fertilization (g N ha-1 year-1)
- Observed NO+N2O+N2 N loss rate (kg N ha-1 year-1) NO+N2O+N2 N loss rate measured in references
- Simulated NO+N2O+N2 N loss rate (kg N ha-1 year-1) NO+N2O+N2 N loss rate simulated in this study
- pH pH of soil samples
- Silt (%) Silt content of soil samples
The null annotation data in Excel represents data that is not available in the literature.
Sheet2: Refs_Denit_flux
- Reference References for Sheet 1
Sheet3: Observed runoff and leaching N
- Title Title of data reference
- Year Publication year of data reference
- Latitude () The latitude of the respective site
- Longitude () The longitude of the respective site
- Rotation Crop rotation system for study site
- Region Study sites
- Days of growing season Growth season length of study site
- Annual precipitation (mm) Annual precipitation at the respective site
- Annual average temperature (C) Average annual temperature at the respective site
- Observed runoff and leaching N (kg N ha-1) Runoff and leaching N loss rate measured in references
- Simulated runoff and leaching N (kg N ha-1 year-1) Runoff and leaching N loss rate simulated in this study
- N losses via leakage (kg N ha-1 year-1) N losses via leakage measured in references
- N loss via runoff (kg N ha-1) N loss via runoff measured in references
- Fertilized (kg N ha-1) Nitrogen application at the respective site
- Replacement ratio of organic fertilizer % The proportion of organic fertilizer application to total nitrogen application at the respective site
- Fertilized N types Type of fertilizer at the respective site
- Fer_15N 15N from all types of fertilization (g N ha-1 year-1)
- Irrigation (mm) Irrigation amount at the respective site
Sheet4: Refs_runoff and leaching N
- Reference References for Sheet 3
3. Yu_et_al._2025_Data_for_Simulation result.zip
f_gas_China.mat: For the period 2000 to 2020, the fractions of the NO+N2O+N2 losses to total N output in Chinas rice paddies estimated by the nitrogen isotope model.
N_gas_China.mat: For the period 2000 to 2020, the NO+N2O+N2 losses in Chinas rice paddies estimated by the nitrogen isotope model.
soil_15N_rice_China.mat: soil 15N data in Chinas rice paddies estimated by randomForest model.
soil_15N_world.mat: soil 15N data in global cropland estimated by randomForest model.
4. code.mlx
The MATLAB script is the code of the main figures in this study.
Funding
This study was supported by the National Natural Science Foundation of China (42225102, 42361144876), the National Key Research and Development Program of China (2023YFD1500802, 2021YFD700801) and the China Postdoctoral Science Foundation (2024M760082).
Version changes
Mar 12, 2025
In the file Yu_et_al._2025_Data_for_soil_15N_meta.xlsx:
- Change the name of column O from exp(MAT) to exp((MAT + 273.15)/100).
- Change the name of column P from exp(Silt) to exp(Silt/100).