/AnMtgsAbsts2009.55889 Nutrient Mass Balances and Agroecosystem Management in New York State.

Wednesday, November 4, 2009
Convention Center, Exhibit Hall BC, Second Floor

Meagan Schipanski1, Laurie Drinkwater1, Steven Vanek2 and Stacey W. Waterman3, (1)Department of Horticulture, Cornell Univ., Ithaca, NY
(2)Department of Crop and Soil Sciences, Cornell Univ., Ithaca, NY
(3)Department of Plant and Soil Science, University of Vermont, Burlington, VT
Abstract:
Nutrient mass balances are a useful tool for understanding how agroecosystem management strategies influence biogeochemical processes. Multi-year nutrient mass balances are a particularly useful for diversified, legume-based systems because legume nitrogen (N) inputs cycle through soil organic matter pools and become available over several years. We developed 5-year N, phosphorus (P) and potassium (K) mass balances for more than 30 fields across 15 grain farms representing a range of management strategies in central New York State. Published values and data from several years of field-based legume N fixation estimates and compost, manure, cover crop, and grain sample analysis were combined with farmer records of field inputs and exports to estimate mass balances for each field. Nitrogen balances decreased with increasing reliance on legume N fixation inputs. Potassium balances were negative across almost all farm types, indicating the potential for soil K depletion over time. We conducted a sensitivity analysis for legume N fixation inputs and N concentration of corn exports. The use of field-based estimates of the proportion of legume N from fixation compared with the use of one average value across all sites changed average N balances by less than 25%. The use of high or low values for corn grain N content (1.07 % to 1.62% N) changed annual average N balances by up to 324%. Corn grain N concentrations decreased, yield increased, and net N removal increased between 2002 and 2008 across a subset of organic farms. The high sensitivity of balances to shifts in grain N concentrations, suggests the importance of adapting nutrient models to reflect shifts in grain varieties and breeding priorities over time and across farms.