Maize root distributions strongly associated with water tables in Iowa, USA
Root distributions determine crop nutrient access and soil carbon input patterns. To date, root distribution data are rare but needed to improve knowledge and prediction of cropping system sustainability. In this study, we sought to (i) quantify variation in maize (Zea mays) and soybean (Glycine max) roots by depth and environment across Iowa, USA and (ii) identify environmental factors explaining the most variation.
Over three years we collected soil cores from 0 to 210 cm in 16 maize and 12 soybean field experiments at grain filling. Root mass, length, carbon (C) and nitrogen (N) were determined at 30 cm increments, coupled with crop, soil, management, and weather-related measurements.
Percentage of root mass located in the top 30 cm varied from 52 to 94% in maize and 54–84% in soybean. Variation in maize root distributions was strongly associated with depth to water tables, variation in soybean with soil physical attributes. Root C:N ratios were highly variable with no depth-pattern, averaging 20 and 30 for soybean and maize, respectively. In both crops, specific root lengths increased with depth to 60 cm, and thereafter remained constant.
Field studies of roots should consider depth to water tables and soil moisture measurements, as they influence vertical root distributions.
KeywordsRoot mass Root length Root distribution Specific root length Root nitrogen C:N ratio Water table
specific root length
The authors gratefully acknowledge Katherine Goode, Ranae Dietzel, and Rafael Martinez-Feria for statistical advice, and Isaiah Huber for map making. Patrick Edmonds provided invaluable help with the planning and execution of field studies and processing of samples, and all station managers were generous in their time and resources to facilitate data collection from their sites. We also thank numerous undergraduates for assistance in sample collection and processing. We sincerely thank Ranae Dietzel and Max Kuhn for providing support in professional development activities that directly led to this work. This work was funded by the Foundation for Food and Agricultural Research (FFAR; Project title: Improving simulation of soil water dynamics and crop yields in the US Corn Belt), the Iowa Soybean Association, the Plant Sciences Institute of Iowa State University, and USDA-NIFA Hatch project IOW03814.
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