Separating the interacting effects of climate, fertilization and crop on N2O emissions: Results from a 4-year multi-site field study of energy crops fertilized with fermentation residues in Germany

English Abstract:

Apart from abiotic (e.g., temperature, moisture) and biotic factors (e.g., microbes), N₂O emissions from agricultural soils largely depend on so-called distal factors like fertilization regime, crop, and management practices. However, the individual effects of these factors on N₂O emissions are difficult to quantify as the high, mainly climate-related spatio-temporal variability of N₂O fluxes and the often non-linear interactions between many factors complicate the quantification of fertilization and crop effects and limit reliable predictions of N₂O emissions from agricultural systems. Moreover, N₂O flux data is particularly rare for energy crops and new NH₄-rich organic fertilizers like organic fermentation residues (OFR).

Multi-year field experiments with staggered replicate crop rotations conducted simultaneously at multiple sites with identical design can be used to generate concise N₂O datasets for energy crops fertilized with OFR and have a large potential for separating fertilization and crop effects from climate-induced variability in N₂O fluxes – particularly in combination with advanced statistics like generalized linear mixed models analysis.

We will present results from a 4-year field study at 5 sites in Germany investigating the interacting effects of i) 3 N-fertilizer treatments (100% OFR, 100% mineral (MIN); 50% OFR + 50% MIN) and ii) 7 energy crops on N₂O emissions. Study sites represent the major precipitation-frost classes relevant for N₂O production in Germany (Jungkunst et al. 2006). Using identical sampling methods at all sites, N₂O was measured periodically from 05/2011–09/2014 at 3 replicate plots per treatment using opaque non-flow-through non-steady-state chambers, 20-min interval sampling and gas chromatography. Measurements were conducted daily for 2–5 days after fertilization, and then bi-weekly. N₂O fluxes were calculated via linear regression using standardized protocols for data processing and interpolation between measurements.