DOI: 10.5061/dryad.h18931ztt
title: Statistical identification of nitrous oxide hot moments and their significance across global ecosystems

description: Nitrous oxide (N2O) emissions from agricultural soils contribute 4% of
 total anthropogenic greenhouse gas (GHG) emissions globally. Events known
 as ‘hot moments’ can occur following environmental changes that favor N2O
 production, which contribute disproportionately to annual cumulative
 emissions. Despite their significance, hot moments and their impact have
 not been statistically well defined, particularly on a global scale. We
 collected 13,787 soil N2O flux measurements from 42 publications and
 evaluated 14 methods of statistical anomaly detection for their ability to
 identify hot moments within datasets. Two methods achieved highest overall
 performance by Matthews correlation coefficient (MCC): median absolute
 deviation (MCC: 0.80) and minimum covariance determinant (MCC: 0.80), the
 latter which also performed evenly across highly dissimilar datasets and
 identified more contextually important minor hot moments (39%) that other
 methodologies may misidentify. Interquartile range, which has previously
 been used and recommended, performed poorly when hot moments were either
 very rare or very common within a dataset, and identified few local hot
 moments (14%). Overall, hot moments comprised 19% of measurements while
 contributing 75% of cumulative emissions. The median background N2O
 emission reported in all datasets was 2.2 g N ha -1 day -1, while the
 median hot moment emission was 10-fold higher, ranging from 23 to 25 g N h
 -1 day -1. These findings advance knowledge of how to accurately define
 and identify hot moments globally - a crucial task to investigating and
 mitigating these critical biogeochemical events.
description: # Hot Moment Identification This work uses several methods of statistical
 outlier detection for the detection of hot moments of nitrous oxide
 emissions using a dataset of daily average emissions collected from
 publications across the globe. Three files are included: first is a CSV
 file containing all data collected from publications
 (HotMomentTreatments.csv). Second, “Supplemental_Material.pdf” contains
 further description of statistical concepts and the final optimized model
 parameters used. The third
 file “Hot_Moment_Identification_Code-_Actuals.ipynb” is a Jupyter notebook
 containing all code used to perform data analysis and figures. ##
 Sharing/Access information The source of each data point is cited within
 HotMomentTreatments.csv. ## Code/Software All code for data analysis is
 contained in the file “Hot_Moment_Identification_Code-_Actuals.ipynb”,
 which is a Jupyter notebook file. Analysis was performed using Python 3.8,
 Pyod 1.0.9, Fitter 1.5.2, Pandas 1.4.3, Numpy 1.21.2, Scipy 1.8.1,
 Matplotlib 3.5.2, Plotly 5.13.1, and Scikit-learn 1.1.1. All code was run
 within a Jupyter notebook using Jupyter 1.0.0. ## Description of the data
 and file structure HotMomentTreatments.csv This notebook requires
 HotMomentTreatments.csv to be saved in the same directory as the notebook.
 Running this notebook will generate several additional CSV files which
 serve for data inspection, verification, and as checkpoints so that all
 analysis need not be run at once. These additional CSV files should also
 be maintained in the same directory as the notebook. | **Attribute** |
 **Description** | **Units** | | :---------------- |
 :------------------------------------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------- | | ExperimentID | Identifier for each unique published experiment | NA | | TreatmentID | Identifier for each unique experimental treatment | NA | | RawID | Identifier for each unique experimental measurement | NA | | PubID | Identifier for each unique publication | NA | | HMTruth | Expert classifications of each N2O flux value as either hot moment or background emission, where 1 represents hot moment and 0 represents background emission. | NA | | Date | Date | NA | | DOY | Day of the year | NA | | N2OFlux | Daily average nitrous oxide flux, measured treatment average from multiple replications. | Grams nitrogen per hectare per day | | FluxStandardError | Standard error of treatment average flux value | Grams nitrogen per hectare per day | | NitrogenApplied | Nitrogen fertilizer applied to the field. | Kilograms per hectare | | SandMean | Soil sand content | Percent | | SiltMean | Soil silt content | Percent | | ClayMean | Soil clay content | Percent | | PrimaryCrop | Crop grown within the primary growing season or throughout the majority of the experimental period. | NA | | Latitude | Latitude of the research site. | Decimal degrees | | Longitude | Longitude of the research site. | Decimal degrees | | PubTitle | Title of publication | | | Citation | Citation of the publication from which the data was collected. | NA |