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

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

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.

Suggested Citation

  • Hunt, Natalie D. & Gower, Stith T. & Nadelhoffer, Knute & Lajtha, Kate & Townsend, Kimberly & Brye, Kristofor R., 2016. "Validation of an agroecosystem process model (AGRO-BGC) on annual and perennial bioenergy feedstocks," Ecological Modelling, Elsevier, vol. 321(C), pages 23-34.
    • Handle: RePEc:eee:ecomod:v:321:y:2016:i:c:p:23-34
    DOI: 10.1016/j.ecolmodel.2015.10.029
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    References listed on IDEAS

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    1. Piñeiro, Gervasio & Perelman, Susana & Guerschman, Juan P. & Paruelo, José M., 2008. "How to evaluate models: Observed vs. predicted or predicted vs. observed?," Ecological Modelling, Elsevier, vol. 216(3), pages 316-322.
    2. Di Vittorio, Alan V. & Anderson, Ryan S. & White, Joseph D. & Miller, Norman L. & Running, Steven W., 2010. "Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses," Ecological Modelling, Elsevier, vol. 221(17), pages 2038-2053.
    3. Yang, J.M. & Yang, J.Y. & Liu, S. & Hoogenboom, G., 2014. "An evaluation of the statistical methods for testing the performance of crop models with observed data," Agricultural Systems, Elsevier, vol. 127(C), pages 81-89.
    4. Powers, S.E. & Ascough, J.C. & Nelson, R.G. & Larocque, G.R., 2011. "Modeling water and soil quality environmental impacts associated with bioenergy crop production and biomass removal in the Midwest USA," Ecological Modelling, Elsevier, vol. 222(14), pages 2430-2447.
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    2. Valentyna Kukharets & Dalia Juočiūnienė & Taras Hutsol & Olena Sukmaniuk & Jonas Čėsna & Savelii Kukharets & Piotr Piersa & Szymon Szufa & Iryna Horetska & Alona Shevtsova, 2023. "An Algorithm for Managerial Actions on the Rational Use of Renewable Sources of Energy: Determination of the Energy Potential of Biomass in Lithuania," Energies, MDPI, vol. 16(1), pages 1-17, January.

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