Title: Uncertainties in estimating global potential yields and their impacts for long-term modeling

Abstract

Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potentialmore » yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.« less

Authors:

Ollenburger, Mary ^[1]; Kyle, Page  ^[2];

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Zhang, Xin ^[1]

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1. Univ. of Maryland, Frostburg, MD (United States)
2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Institute

Publication Date:

Sat Mar 26 00:00:00 EDT 2022

Research Org.:

Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:

USDOE Office of Science (SC); National Science Foundation (NSF)

OSTI Identifier:

1899359

Report Number(s):

PNNL-SA-167243
Journal ID: ISSN 1876-4517

Grant/Contract Number:  

AC05-76RL01830

Resource Type:

Accepted Manuscript

Journal Name:

Food Security

Additional Journal Information:

Journal Volume: 14; Journal Issue: 5; Journal ID: ISSN 1876-4517

Publisher:

Springer

Country of Publication:

United States

Language:

English

Subject:

60 APPLIED LIFE SCIENCES; Agricultural intensification; Yield gap; global agricultural models