College of Agronomy, Shenyang Agricultural University, Shenyang, 110161, China.
Environ Sci Process Impacts. 2018 Sep 19;20(9):1202-1209. doi: 10.1039/c8em00278a.
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.
为了优化土壤管理实践，以帮助减少陆地碳排放，生物炭已被应用于广泛的土壤环境中，以研究其对土壤温室气体排放的影响。这些研究表明，土壤甲烷（CH4）通量的响应可能有很大差异，导致生物炭添加后 CH4 通量的增加和减少。为了解决这一差异，近年来进行了多项荟萃分析研究，以确定可能控制生物炭处理后 CH4 通量方向的关键因素。然而，即使比较荟萃分析的结论，也存在不一致之处，即哪些因素最终决定了由于生物炭添加而导致的 CH4 通量方向和幅度的变化。此外，在荟萃分析中，由于非独立性，使用单个研究中的多个观测值可能会导致对因素影响的误解。在本研究中，我们使用多元荟萃回归方法，允许因素相互作用，以研究哪些生物炭、土壤和管理实践因素组合或单独最好地解释过去生物炭添加研究中的 CH4 通量响应。我们的结果表明，与仅使用单个因素的所有模型相比，多个土壤因素（即水分饱和度、土壤质地和土壤有机碳含量）的相互作用最好地解释了生物炭添加对土壤 CH4 通量响应（最小偏差信息准则（DIC）值以及最低异质性）。这些发现为优化生物炭添加对 CH4 通量响应以及建立经验模型定量预测土壤 CH4 通量时应同时考虑哪些特定土壤因素提供了深入了解。
