Modeling N2O Emissions from Agricultural Soils Using a Multi-level Linear Regression
This study consists of a statistical meta-analysis of an agricultural N2O emission database made up of data taken from peer-reviewed literature. A multi-level linear regression is used to investigate the relationship between N fertilizer input and N2O emissions; (1) independent of variation between each study, (2) as a categorical function of crop type and (3) as a categorical function of fertilizer type. An understanding of these relationships could help to establish management strategies to more efficiently use N fertilizers, reducing N2O emissions and lowering expenses for agricultural producers.
The results of the multi-level linear analysis of the dataset indicate that the relationship between N input and N2O emissions is not independent of the conditional variation between studies. The categorical analysis of differences in crop type also did not have a significant influence on N2O emissions. The categorical analysis of N fertilizer forms did show a significant influence on emissions. Differences in the slopes of the fertilizer type models provide relative comparability of expected N2O emissions of different chemical forms of N fertilizer for a given N input. The analysis performed in this study yielded important insight into the factors influencing N2O emissions from agricultural soils. These findings can be used to guide both management strategies and further research dealing with an increasingly important topic.
School Location:USA - North Carolina
Source Type:Master's Thesis
Keywords:nitrous oxide emissions mulit level linear regression
Date of Publication:08/29/2007