The need for geospatial rice modeling assessments in an uncertain climate – a U.S. perspective

Authors: Fleisher, David; LI, SANAI - Us Forest Service (FS); Barnaby, Jinyoung; McClung, Anna

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/23/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary: The United States is one of the largest rice exporters in the world, with significant production occurring in the Mississippi Delta region. Recent changes from historical climate patterns, including rising temperatures and increased frequency of extreme weather events, are impacting quantity and quality of grain yield. Rice plants will be more likely exposed to heat stress during critical phases of development in response to an increasingly warmer thermal environment. The availability of water resources due to competing demands and changes in rainfall patterns is also of increasing concern. Experimental management trials include assessment of alternate wetting/drying cycles. Breeding work involving the development of high yielding phenotypes that express traits for heat and drought tolerance has also been a major focus. There is thus a need for rigorous crop model-based studies across this five-state region that can help identify and assess potential management and phenotypic adaptation strategies. Because rice production is spread across a relatively large and spatially diverse area in the U.S. (encompassing roughly 18,000 km2), a geospatial approach is required to account for differences in climate, management, and soil conditions. However, comparatively little modeling work for this important crop has been conducted in the U.S. as compared to other major production centers. In this talk we focus on the need for improving geospatial crop-model technologies using an existing rice model and an expansive multi-year, multi-location experimental dataset of rice production from this region.

Technical Abstract: The United States is one of the largest rice exporters in the world, with significant production occurring in the Mississippi Delta region. Recent changes from historical climate patterns, including rising temperatures and increased frequency of extreme weather events, are impacting quantity and quality of grain yield. Rice plants will be more likely exposed to heat stress during critical phases of development in response to an increasingly warmer thermal environment. The availability of water resources due to competing demands and changes in rainfall patterns is also of increasing concern. Experimental management trials include assessment of alternate wetting/drying cycles. Breeding work involving the development of high yielding phenotypes that express traits for heat and drought tolerance has also been a major focus. There is thus a need for rigorous crop model-based studies across this five-state region that can help identify and assess potential management and phenotypic adaptation strategies. Because rice production is spread across a relatively large and spatially diverse area in the U.S. (encompassing roughly 18,000 km2), a geospatial approach is required to account for differences in climate, management, and soil conditions. However, comparatively little modeling work for this important crop has been conducted in the U.S. as compared to other major production centers. In this talk we focus on the need for improving geospatial crop-model technologies using an existing rice model and an expansive multi-year, multi-location experimental dataset of rice production from this region.