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Publication Date
26 March 2022

Mind the (Yield) Gap: the Importance of Estimation Methods

Subtitle
How researchers estimate crop yield gaps determines the location of projected future agricultural “breadbasket” regions.
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Science

Presently, average yields of staple agricultural crops vary by a factor of 10 around the world, primarily due to agricultural management practices and agro-climatic conditions. The “yield gap” refers to the potential increase in crop yields in a location from changes in management practices. In a recent study, researchers compared two methods used to estimate yield gaps and found that the methods return dramatically different results for much of the world. In yield gap closure scenarios in an agro-economic model, the Global Change Analysis Model (GCAM), these different methods returned divergent futures for future crop prices and food security, particularly in tropical regions.

Impact

Increasing agricultural yields is a priority for sustainable development. It can improve food security, improve rural economic livelihoods, and reduce future land clearing. Reducing land clearing reduces land use change emissions and mitigates threats to biodiversity and ecosystem function. However, quantifying potential yields for each crop type and region of the world is challenging. Estimates derived in this study show that the uncertainty alone returns divergent pictures for future food security and agricultural land use. The study suggests that understanding the sources of uncertainty is important for agriculture-focused development strategies.

Summary

Estimating realistic potential yields by crop type and region is challenging. Yields depend on both the biophysical characteristics (e.g., soil, climate, etc.) and crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). Researchers first used two different estimation methods to analyze future potential yields of major crop types globally. One method was based on historically observed yields (“Empirical”) and the other was based on biophysical conditions (“Simulated”). The potential yields for major crops and regions were quite different between the two methods. In particular, Simulated potential yields for major crops were typically 200% higher than Empirical potential yields in tropical regions. Applying both potential yields in yield gap closure scenarios in GCAM led to very different outcomes for the global agricultural sector. In the Simulated potential yield closure scenario, Africa, Asia, and South America saw comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, a heavy reliance on production and exports in the temperate regions that currently practice industrial agriculture characterized the Empirical potential yield scenario.

Point of Contact
Marshall Wise
Institution(s)
Pacific Northwest National Laboratory
Funding Program Area(s)
Publication