IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v321y2016icp23-34.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380015005141
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2015.10.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Savelii Kukharets & Algirdas Jasinskas & Gennadii Golub & Olena Sukmaniuk & Taras Hutsol & Krzysztof Mudryk & Jonas Čėsna & Szymon Glowacki & Iryna Horetska, 2023. "The Experimental Study of the Efficiency of the Gasification Process of the Fast-Growing Willow Biomass in a Downdraft Gasifier," Energies, MDPI, vol. 16(2), pages 1-12, January.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Correndo, Adrian A. & Hefley, Trevor J. & Holzworth, Dean P. & Ciampitti, Ignacio A., 2021. "Revisiting linear regression to test agreement in continuous predicted-observed datasets," Agricultural Systems, Elsevier, vol. 192(C).
    2. Booth, Shawn & Walters, William J & Steenbeek, Jeroen & Christensen, Villy & Charmasson, Sabine, 2020. "An Ecopath with Ecosim model for the Pacific coast of eastern Japan: Describing the marine environment and its fisheries prior to the Great East Japan earthquake," Ecological Modelling, Elsevier, vol. 428(C).
    3. Nasca, J.A. & Feldkamp, C.R. & Arroquy, J.I. & Colombatto, D., 2015. "Efficiency and stability in subtropical beef cattle grazing systems in the northwest of Argentina," Agricultural Systems, Elsevier, vol. 133(C), pages 85-96.
    4. Luca Piciullo & Vittoria Capobianco & Håkon Heyerdahl, 2022. "A first step towards a IoT-based local early warning system for an unsaturated slope in Norway," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3377-3407, December.
    5. Amouzou, Kokou Adambounou & Naab, Jesse B. & Lamers, John P.A. & Borgemeister, Christian & Becker, Mathias & Vlek, Paul L.G., 2018. "CROPGRO-Cotton model for determining climate change impacts on yield, water- and N- use efficiencies of cotton in the Dry Savanna of West Africa," Agricultural Systems, Elsevier, vol. 165(C), pages 85-96.
    6. Shi, Xinrui & Batchelor, William D. & Liang, Hao & Li, Sien & Li, Baoguo & Hu, Kelin, 2020. "Determining optimal water and nitrogen management under different initial soil mineral nitrogen levels in northwest China based on a model approach," Agricultural Water Management, Elsevier, vol. 234(C).
    7. Marrou, Hélène & Ghanem, Michel Edmond & Amri, Moez & Maalouf, Fouad & Ben Sadoun, Sarah & Kibbou, Fatimaezzhara & Sinclair, Thomas R., 2021. "Restrictive irrigation improves yield and reduces risk for faba bean across the Middle East and North Africa: A modeling study," Agricultural Systems, Elsevier, vol. 189(C).
    8. Liang, Hao & Lv, Haofeng & Batchelor, William D. & Lian, Xiaojuan & Wang, Zhengxiang & Lin, Shan & Hu, Kelin, 2020. "Simulating nitrate and DON leaching to optimize water and N management practices for greenhouse vegetable production systems," Agricultural Water Management, Elsevier, vol. 241(C).
    9. Kamini Yadav & Hatim M. E. Geli, 2021. "Prediction of Crop Yield for New Mexico Based on Climate and Remote Sensing Data for the 1920–2019 Period," Land, MDPI, vol. 10(12), pages 1-27, December.
    10. Guang Han & Robert A. Martin, 2018. "Teaching and Learning about Biomass Energy: The Significance of Biomass Education in Schools," Sustainability, MDPI, vol. 10(4), pages 1-17, March.
    11. Ma, Shaoxiu & Churkina, Galina & Wieland, Ralf & Gessler, Arthur, 2011. "Optimization and evaluation of the ANTHRO-BGC model for winter crops in Europe," Ecological Modelling, Elsevier, vol. 222(20), pages 3662-3679.
    12. Majid Majzoubi & Eric Yanfei Zhao, 2023. "Going beyond optimal distinctiveness: Strategic positioning for gaining an audience composition premium," Strategic Management Journal, Wiley Blackwell, vol. 44(3), pages 737-777, March.
    13. Shuang Liu & David I Stern, 2008. "A Meta-Analysis of Contingent Valuation Studies in Coastal and Near-Shore Marine Ecosystems," Socio-Economics and the Environment in Discussion (SEED) Working Paper Series 2008-15, CSIRO Sustainable Ecosystems.
    14. Sepaskhah, Ali Reza & Fahandezh-Saadi, Saghar & Zand-Parsa, Shahrokh, 2011. "Logistic model application for prediction of maize yield under water and nitrogen management," Agricultural Water Management, Elsevier, vol. 99(1), pages 51-57.
    15. Michael Gbenga Ogungbuyi & Juan P. Guerschman & Andrew M. Fischer & Richard Azu Crabbe & Caroline Mohammed & Peter Scarth & Phil Tickle & Jason Whitehead & Matthew Tom Harrison, 2023. "Enabling Regenerative Agriculture Using Remote Sensing and Machine Learning," Land, MDPI, vol. 12(6), pages 1-25, May.
    16. Sileshi, Gudeta & Hailu, Girma & Nyadzi, Gerson I., 2009. "Traditional occupancy–abundance models are inadequate for zero-inflated ecological count data," Ecological Modelling, Elsevier, vol. 220(15), pages 1764-1775.
    17. Gergs, André & Ratte, Hans Toni, 2009. "Predicting functional response and size selectivity of juvenile Notonecta maculata foraging on Daphnia magna," Ecological Modelling, Elsevier, vol. 220(23), pages 3331-3341.
    18. Blal, Mohamed & Benatiallah, Ali & NeÇaibia, Ammar & Lachtar, Salah & Sahouane, Nordine & Belasri, Ahmed, 2019. "Contribution and investigation to compare models parameters of (PEMFC), comprehensives review of fuel cell models and their degradation," Energy, Elsevier, vol. 168(C), pages 182-199.
    19. Katzin, David & van Henten, Eldert J. & van Mourik, Simon, 2022. "Process-based greenhouse climate models: Genealogy, current status, and future directions," Agricultural Systems, Elsevier, vol. 198(C).
    20. Yang, Xuan & Zheng, Lina & Yang, Qian & Wang, Zikui & Cui, Song & Shen, Yuying, 2018. "Modelling the effects of conservation tillage on crop water productivity, soil water dynamics and evapotranspiration of a maize-winter wheat-soybean rotation system on the Loess Plateau of China using," Agricultural Systems, Elsevier, vol. 166(C), pages 111-123.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:321:y:2016:i:c:p:23-34. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.