Residue removal and nitrogen cycling in burn and non‐burn Kentucky bluegrass seed production systems

Abstract

Abstract Kentucky bluegrass (Poa pratensis L.) postharvest residue in northern Idaho has historically been burned to maintain stand life and profitability. Alternatives to open field burning are necessary to reduce adverse impacts of burning on air quality and several have been proposed. However, limited information is available on the impact of residue management on residue removal and nitrogen cycling. In this study, the impact of residue management on residue nutrient dynamics and nitrogen availability was evaluated within replicated full load burn (FLB), bale then burn (BB), bale then mow then harrow (BMH), and system (SYST) (BMH year 1, BB year 2, and FLB year 3) plots in Kootenai County, ID from 2002 to 2006. Standing and non‐standing residues were measured immediately following grass seed harvest and periodically thereafter in each plot. Averaged across years, non‐standing residue (thatch) removal ranged from −13% in BMH to 61% in FLB, and removal of standing biomass ranged from 6% in BMH to 92% in FLB. The combined removal of both non‐standing and standing residue was 18% with BMH, 57% with SYST, 69% with BB, and 75% with FLB. Plant N uptake ranged from 53 kg N ha−1 in FLB in 2006 to 131 in SYST (BMH) in 2003 and nitrogen use efficiency, calculated using partial factor productivity formula, ranged from 0.6 to 5.8 kg bluegrass seed per kg N fertilizer. Mean NO3−–N concentrations from lysimeters 10‐cm deep were 14 mg NO3−–N L−1 in FLB, 12 mg NO3−–N L−1 in BB, and 6 mg NO3−–N L−1 in BMH treatments for years 2003–2006. Greater concentrations of NO3−–N in burn treatments were available for plant uptake or leaching compared to the BMH treatment. The data indicate that the efficacy of any residue management system will vary from year to year and impact seed production in the following year. Nitrogen availability varied across residue management systems, suggesting N fertilizer product, rate, and timing to optimize N use efficiency may also need to vary.