353-8 The Global Yield Gap Atlas: Rationale, Methods, and Applications.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Symposium--the Solar Corridor's Potential to Capture Collaborative Synergy, in the Development of Critical Solutions

Wednesday, November 18, 2015: 11:00 AM
Minneapolis Convention Center, M100 D

Patricio Grassini1, Lenny G.J. van Bussel2, Justin P Van Wart3, Joost Wolf4, Nicolas Guilpart5, Haishun Yang6, Hugo L.E. de Groot2, Hendrik Boogaard2, Martin K. van Ittersum4 and Kenneth G Cassman1, (1)Department of Agronomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE
(2)Wageningen University, Wageningen, Netherlands
(3)Agronomy & Horticulture, University of Nebraska - Lincoln, Lincoln, NE
(4)Plant Production Systems, Wageningen University, Wageningen, Netherlands
(5)University of Nebraska-Lincoln, Lincoln, NE
(6)Agronomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE
Abstract:
Numerous studies have been published during the past two decades that use simulation models to assess crop yield gaps (quantified as the difference between potential and actual farm yields), impact of climate change on future crop yields, and land-use change. However, there is a wide range in quality and spatial and temporal scale and resolution of climate and soil data underpinning these studies, as well as widely differing assumptions about cropping-system context and crop model calibration. Likewise, there is no robust framework to upscale results from locations to larger extrapolations domains. Here we present an explicit rationale and methodology for selecting data sources for simulating crop yields and estimating yield gaps at specific locations, that can be applied across widely different levels of data availability and quality. These guidelines were established based on the lessons learnt from establishing the Global Yield Gap Atlas (www.yieldgap.org). The method consists of a tiered approach that identifies the most scientifically robust requirements for data availability and quality, as well as other, less rigorous options when data are not available or are of poor quality. A limited number of locations is selected for estimating yield potential and yield gaps, based on distribution of crop harvested area, and these estimates are subsequently upscaled to larger spatial domains following a bottom-up approach based on a climate zone scheme. The goal of the proposed methods is to provide transparent, reproducible, and scientifically robust guidelines for estimating and upscaling yield gaps; guidelines that are also relevant for evaluating the impact of climate change and land-use change at local to global spatial scales. Likewise, the improved understanding of data requirements and alternatives for simulating crop yields and estimating yield gaps as described here can help identify the most critical “data gaps” and focus global efforts to fill them.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Symposium--the Solar Corridor's Potential to Capture Collaborative Synergy, in the Development of Critical Solutions