An AgMIP framework for improved agricultural representation in integrated assessment models

Alex C. Ruane, Cynthia Rosenzweig, Senthold Asseng, Kenneth J. Boote, Joshua Elliott, Frank Ewert, James W. Jones, Pierre Martre, Sonali P. McDermid, Christoph Müller, Abigail Snyder, Peter J. Thorburn

    Research output: Contribution to journalArticle

    Abstract

    Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

    Original languageEnglish (US)
    Article number125003
    JournalEnvironmental Research Letters
    Volume12
    Issue number12
    DOIs
    StatePublished - Nov 24 2017

    Keywords

    • AgMIP
    • agricultural impacts
    • climate impacts
    • crop models
    • emulators
    • integrated assessment models
    • model development

    ASJC Scopus subject areas

    • Renewable Energy, Sustainability and the Environment
    • Environmental Science(all)
    • Public Health, Environmental and Occupational Health

    Fingerprint Dive into the research topics of 'An AgMIP framework for improved agricultural representation in integrated assessment models'. Together they form a unique fingerprint.

  • Cite this

    Ruane, A. C., Rosenzweig, C., Asseng, S., Boote, K. J., Elliott, J., Ewert, F., Jones, J. W., Martre, P., McDermid, S. P., Müller, C., Snyder, A., & Thorburn, P. J. (2017). An AgMIP framework for improved agricultural representation in integrated assessment models. Environmental Research Letters, 12(12), [125003]. https://doi.org/10.1088/1748-9326/aa8da6