This meta-analysis was based on data compiled from 67 peer-reviewed journal articles. The initial database was constructed following the frameworks and datasets reported in two comprehensive reviews:
Wang et al., 2024—Global Change Biology https://doiorg.login.ezproxy.library.ualberta.ca/10.1111/gcb.70007
Wu et al., 2021—Environmental Pollution https://doi.org/10.1016/j.envpol.2020.116365
To be eligible for inclusion, studies were required to contain both a treatment involving the application of nitrification inhibitors (NIs) and a corresponding control treatment without NIs, allowing for direct effect size calculation.
For each study, we extracted bibliographic information and detailed metadata, including geographical coordinates, mean annual temperature, and mean annual precipitation of the study site. Additionally, we collected treatment-specific information such as:
Type of nitrification inhibitor applied
Application rate and timing
Associated crop species
Given that this study focused on the influence of nitrification inhibitors on soil nitrogen dynamics, greenhouse gas emissions, crop productivity, and nitrogen use efficiency (NUE), we extracted the means and standard errors (or deviations) for the following variables from each study:
Soil nitrate (NO₃⁻–N) and ammonium (NH₄⁺–N) concentrations
Nitrous oxide (N₂O) and ammonia (NH₃) emissions
Crop yield
Nitrogen use efficiency (NUE)
Effect sizes were calculated as natural log response ratios (lnRRs) between treatment and control groups. Sampling variances were computed accordingly. All analyses were conducted using the metafor package in R.
We assessed between-study heterogeneity using the I² and τ² statistics. Subgroup analyses were conducted to explore the influence of potential moderators, including nitrification inhibitor type, soil texture, and crop type.