Validation of an agroecosystem process model (AGRO-BGC) on annual and perennial bioenergy feedstocks

Natalie D. Hunt, Stith T. Gower, Knute Nadelhoffer, Kate Lajtha, Kimberly Townsend and Kristofor R. Brye

Ecological Modelling, 2016, vol. 321, issue C, 23-34

Abstract: Corn (Zea mays L.) residues and perennial C4 grasses are two Midwest bioenergy feedstock candidates due to their compatibility with agricultural infrastructure and potential for ecosystem service delivery. We validated the ecosystem process model AGRO-BGC by comparing model estimates with empirical observations from corn and perennial C4 grass systems across Wisconsin and Illinois under no-tillage, nitrogen fertilized, and unfertilized management. Validation parameters included soil organic carbon (SOC), total soil nitrogen (N) to 1.2m, aboveground net primary productivity (ANPP), net ecosystem productivity (NEP), and leaf area index (LAI). We parameterized AGRO-BGC to represent ecophysiological characteristics of corn and perennial prairie grasses, and constructed scenarios to represent corresponding edaphic, climate, and management conditions. Unfertilized annual model estimates had normalized mean average errors relative to field measurements of 0.3, 23, and 4tha−1 for ANPP, SOC, and N, respectively. Fertilized simulations erred from observations by 0.6, 29, 5tha−1 for ANPP, SOC, and N, respectively.

Keywords: Agroecosystem process model; AGRO-BGC; Soil organic carbon; Switchgrass; Corn stover; Bioenergy (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:321:y:2016:i:c:p:23-34

DOI: 10.1016/j.ecolmodel.2015.10.029

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