Monitoring of greenhouse gas emissions from agricultural and forest soils

Global climate change is becoming a central issue in contemporary science as well as politics. There is a long-lasting debate about the cause of the climate change: anthropogenic activity versus the natural cycle. However, a scientific consensus is coming a conclusion that the contemporary climate change is mainly caused by anthropogenic emissions of the greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). The main objective of the thesis is the monitoring of such GHG emissions from two ecosystem types: a forest and a rice paddy ecosystem. The forest site is a EMEP experimental station, taking part of the activity of GHG-AGOLU of FP7-JRC project, while the agricultural ecosystem was included in the CarboEurope project and represents also a Level 3 site in the frame of NitroEurope project. The gas monitoring was carried out in 2008. The thesis is composed by 4 chapters, corresponding to specific objectives. The first chapter is relative to the study of the spatial variability of the main soil chemical and physical properties on the basis of which the gas monitoring points were selected. The second and the third chapters are relative to a cropland site. In particular, the second chapter includes monitoring data of CH4, N2O and CO2 fluxes from the paddy field, both during the crop growth season and the fallow period, and the validation results of the DeNitrification DeComposition (DNDC) model, a process-oriented biogeochemical model used for simulating soil gas emissions from the paddy field, are reported. The third chapter contains the study of characterization of microbial community composition using phospholipid fatty acid analysis (PLFA), at eight sampling dates representative of different soil conditions and crop stages and consequently characterized by distinct soil greenhouse emission rates. The fourth and last chapter includes the monitoring study of soil respiration in a forest site and its partitioning into autotrophic and heterotrophic components, applying the indirect linear regression method.