In an effort to optimize soil management practices that can help mitigate terrestrial carbon emissions, biochar has been applied to a wide range of soil environments to examine its effect on soil greenhouse gas emissions. Such studies have shown that the soil methane (CH4) flux response can vary widely leading to both increase and decrease in CH4 flux upon biochar amendment. To address this discrepancy, multiple meta-analysis studies have been performed in recent years to determine the key factors that may control the direction of CH4 flux upon biochar treatment. However, even comparing across conclusions from meta-analyses reveals disagreement upon which factors ultimately determine the change in direction and magnitude of CH4 flux due to biochar addition. Furthermore, using multiple observations from a single study can lead to misinterpretation of the influence of a factor within a meta-analysis due to non-independence. In this study, we use a multivariate meta-regression approach that allows factor interactions to investigate which biochar, soil, and management practice factors in combination or individually best explain the CH4 flux response in past biochar amendment studies. Our results show that the interaction of multiple soil factors (i.e., water saturation, soil texture, and soil organic carbon content) best explains the soil CH4 flux response to biochar addition (minimum deviance information criterion (DIC) value along with lowest heterogeneity) as compared to all models utilizing individual factors alone. These findings provide insight into the specific soil factors that should be taken into account simultaneously when optimizing the CH4 flux response to biochar amendments and building empirical models to quantitatively predict soil CH4 flux.
Addition of biochar to soils has been shown to increase crop yield and aid in mitigating greenhouse gas emissions by decreasing the extent of soil methane (CH 4 ) flux. Previous studies utilizing meta-analysis to better understand the impact of environmental and management factors on CH 4 flux from biochar treated soil systems have provided contrasting results, ranging from significant increase, decrease, to no change in methane flux 5 after amendment. We hypothesized that these discrepancies could be explained by separating studies into two major land use categories, upland and paddy, prior to analysis so that the overall redox conditions are more comparable across studies upon which statistical comparisons are made. Furthermore, past studies did not consider potentially critical soil properties including soil organic carbon, total nitrogen, C/N, and soil texture; a number of biochar properties including biochar pH and C/N; and five additional management and experimental 10 factors. In this study, Hedge's d metric was calculated and Wilcoxon analyses were used in a meta-analysis to determine the impact of these additional factors on methane flux from biochar-amended upland versus paddy soils. We demonstrate that variations in soil characteristics including SOC, C/N, and pH significantly influences the methane flux from biochar treated soils, while biochar characteristics and management practices have less to no effect as determined by the magnitude of the Hedge's d metric. Soils with low SOC, total nitrogen, C/N, 15 acidic or alkaline pH exhibited lowest CH 4 emission rates/highest CH 4 uptake rates, whereas soils with higher SOC content, C/N, and circumneutral pH exhibited higher CH 4 emission with biochar addition. Several possible mechanisms are suggested to explain the role of these variables in CH 4 cycling. Results from this study will be used to evaluate the input parameters for building a linear additive model to quantitatively predict soil methane flux in response to biochar additions. Ultimately, implementation of the linear additive model can be extremely 20 valuable for advising agricultural practices toward minimize methane emissions or maximizing methane sink Biogeosciences Discuss., https://doi
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