IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v392y2019icp212-225.html
   My bibliography  Save this article

Options to model the effects of tillage on N2O emissions at the global scale

Author

Listed:
  • Lutz, Femke
  • Stoorvogel, Jetse J.
  • Müller, Christoph

Abstract

Strategies on agricultural management can help to reduce global greenhouse gas (GHG) emissions. However, the potential of agricultural management to reduce GHG emissions at the global scale is unclear. Global ecosystem models often lack sufficient detail in their representation of management, such as tillage. This paper explores whether and how tillage can be incorporated in global ecosystem models for the analysis of nitrous oxide (N2O) emissions. We identify the most important nitrogen processes in soils and their response to tillage. We review how these processes and tillage effects are described in field-scale models and evaluate whether they can be incorporated in the global-scale models while considering the data requirements for a global application. The most important processes are described in field-scale models and the basic data requirements can be met at the global scale. We therefore conclude that there is potential to incorporate tillage in global ecosystem models for the analysis of N2O emissions. There are several options for how the relevant processes can be incorporated into global ecosystem models, so that generally there is potential to study the effects of tillage on N2O emissions globally. Given the many interactions with other processes, modelers need to identify the modelling approaches that are consistent with their modelling framework and test these.

Suggested Citation

  • Lutz, Femke & Stoorvogel, Jetse J. & Müller, Christoph, 2019. "Options to model the effects of tillage on N2O emissions at the global scale," Ecological Modelling, Elsevier, vol. 392(C), pages 212-225.
  • Handle: RePEc:eee:ecomod:v:392:y:2019:i:c:p:212-225
    DOI: 10.1016/j.ecolmodel.2018.11.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380018304034
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2018.11.015?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. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike & Wu, Wenbin, 2014. "Generating global crop distribution maps: From census to grid," Agricultural Systems, Elsevier, vol. 127(C), pages 53-60.
    2. Adam, M. & Van Bussel, L.G.J. & Leffelaar, P.A. & Van Keulen, H. & Ewert, F., 2011. "Effects of modelling detail on simulated potential crop yields under a wide range of climatic conditions," Ecological Modelling, Elsevier, vol. 222(1), pages 131-143.
    3. Cameira, M.R. & Fernando, R.M. & Ahuja, L.R. & Ma, L., 2007. "Using RZWQM to simulate the fate of nitrogen in field soil-crop environment in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 90(1-2), pages 121-136, May.
    4. van der Laan, M. & Annandale, J.G. & Bristow, K.L. & Stirzaker, R.J. & Preez, C.C. du & Thorburn, P.J., 2014. "Modelling nitrogen leaching: Are we getting the right answer for the right reason?," Agricultural Water Management, Elsevier, vol. 133(C), pages 74-80.
    5. Hanson, J. D. & Ahuja, L. R. & Shaffer, M. D. & Rojas, K. W. & DeCoursey, D. G. & Farahani, H. & Johnson, K., 1998. "RZWQM: Simulating the effects of management on water quality and crop production," Agricultural Systems, Elsevier, vol. 57(2), pages 161-195, June.
    6. Leslie Lipper & Philip Thornton & Bruce M. Campbell & Tobias Baedeker & Ademola Braimoh & Martin Bwalya & Patrick Caron & Andrea Cattaneo & Dennis Garrity & Kevin Henry & Ryan Hottle & Louise Jackson , 2014. "Climate-smart agriculture for food security," Nature Climate Change, Nature, vol. 4(12), pages 1068-1072, December.
    7. Pannkuk, C. D. & Stockle, C. O. & Papendick, R. I., 1998. "Evaluating CropSyst simulations of wheat management in a wheat-fallow region of the US pacific northwest," Agricultural Systems, Elsevier, vol. 57(2), pages 121-134, June.
    8. S. W. Chung & Philip W. Gassman & L. A. Kramer & Jimmy R. Williams & Roy Gu, 1999. "Validation of EPIC for Two Watersheds in Southwest Iowa," Center for Agricultural and Rural Development (CARD) Publications 99-wp215, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    Full references (including those not matched with items on IDEAS)

    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. Ojeda, Jonathan J. & Volenec, Jeffrey J. & Brouder, Sylvie M. & Caviglia, Octavio P. & Agnusdei, Mónica G., 2018. "Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM," Agricultural Water Management, Elsevier, vol. 195(C), pages 154-171.
    2. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    3. Movedi, Ermes & Valiante, Daniele & Colosio, Alessandro & Corengia, Luca & Cossa, Stefano & Confalonieri, Roberto, 2022. "A new approach for modeling crop-weed interaction targeting management support in operational contexts: A case study on the rice weeds barnyardgrass and red rice," Ecological Modelling, Elsevier, vol. 463(C).
    4. Jeetendra Prakash Aryal & Cathy R. Farnworth & Ritika Khurana & Srabashi Ray & Tek B. Sapkota & Dil Bahadur Rahut, 2020. "Does women’s participation in agricultural technology adoption decisions affect the adoption of climate‐smart agriculture? Insights from Indo‐Gangetic Plains of India," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 973-990, August.
    5. Islam, Zeenatul & Sabiha, Noor E & Salim, Ruhul, 2022. "Integrated environment-smart agricultural practices: A strategy towards climate-resilient agriculture," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 59-72.
    6. Nelson Mango & Clifton Makate & Lulseged Tamene & Powell Mponela & Gift Ndengu, 2018. "Adoption of Small-Scale Irrigation Farming as a Climate-Smart Agriculture Practice and Its Influence on Household Income in the Chinyanja Triangle, Southern Africa," Land, MDPI, vol. 7(2), pages 1-19, April.
    7. Kibria, Abu SMG & Costanza, Robert & Soto, José R, 2022. "Modeling the complex associations of human wellbeing dimensions in a coupled human-natural system: In contexts of marginalized communities," Ecological Modelling, Elsevier, vol. 466(C).
    8. Maren Radeny & Elizaphan J. O. Rao & Maurice Juma Ogada & John W. Recha & Dawit Solomon, 2022. "Impacts of climate-smart crop varieties and livestock breeds on the food security of smallholder farmers in Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(6), pages 1511-1535, December.
    9. Ignaciuk, Ada & Malevolti, Giulia & Scognamillo, Antonio & Sitko, Nicholas J., 2022. "Can food aid relax farmers’ constraints to adopting climate-adaptive agricultural practices? Evidence from Ethiopia, Malawi and the United Republic of Tanzania," ESA Working Papers 324073, Food and Agriculture Organization of the United Nations, Agricultural Development Economics Division (ESA).
    10. Xavier, Antonio & Martins, Maria de Belem Costa Freitas & Fragoso, Rui Manuel de Sousa, 2011. "Recovery of Incomplete Data of Statistical Livestock Number Applying an Entropy Approach," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115790, European Association of Agricultural Economists.
    11. Channing Arndt & William Farmer & Kenneth Strzepek & James Thurlow, 2012. "Climate Change, Agriculture and Food Security in Tanzania," Review of Development Economics, Wiley Blackwell, vol. 16(3), pages 378-393, August.
    12. Shahadha, Saadi Sattar & Wendroth, Ole & Zhu, Junfeng & Walton, Jason, 2019. "Can measured soil hydraulic properties simulate field water dynamics and crop production?," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    13. António Xavier & Rui Fragoso & Maria Belém Costa Freitas & Maria Socorro Rosário, 2019. "An Approach Using Entropy and Supervised Classifications to Disaggregate Agricultural Data at a Local Level," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 763-779, December.
    14. Iban, Muzaffer Can & Aksu, Oktay, 2020. "A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach," Land Use Policy, Elsevier, vol. 91(C).
    15. Cameira, M.R. & Rolim, João & Valente, Fernanda & Faro, Afonso & Dragosits, Ulrike & Cordovil, Cláudia M.d.S., 2019. "Spatial distribution and uncertainties of nitrogen budgets for agriculture in the Tagus river basin in Portugal – Implications for effectiveness of mitigation measures," Land Use Policy, Elsevier, vol. 84(C), pages 278-293.
    16. Scognamillo, Antonio & Sitko, Nicholas J., 2021. "Leveraging social protection to advance climate-smart agriculture: An empirical analysis of the impacts of Malawi’s Social Action Fund (MASAF) on farmers’ adoption decisions and welfare outcomes," World Development, Elsevier, vol. 146(C).
    17. Dongrui Han & Hongyan Cai & Xiaohuan Yang & Xinliang Xu, 2020. "Multi-Source Data Modeling of the Spatial Distribution of Winter Wheat Yield in China from 2000 to 2015," Sustainability, MDPI, vol. 12(13), pages 1-16, July.
    18. Helena Shilomboleni, 2020. "Political economy challenges for climate smart agriculture in Africa," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 37(4), pages 1195-1206, December.
    19. Chauhdary, Junaid Nawaz & Bakhsh, Allah & Engel, Bernard A. & Ragab, Ragab, 2019. "Improving corn production by adopting efficient fertigation practices: Experimental and modeling approach," Agricultural Water Management, Elsevier, vol. 221(C), pages 449-461.
    20. Graham von Maltitz & Marna van der Merwe, 2017. "Land and agronomic potential for biofuel production in Southern Africa," WIDER Working Paper Series 085, World Institute for Development Economic Research (UNU-WIDER).

    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:392:y:2019:i:c:p:212-225. 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.