Boundary-Layer Meteorology

, Volume 170, Issue 1, pp 127–160 | Cite as

Effect of Vegetation on the Energy Balance and Evapotranspiration in Tallgrass Prairie: A Paired Study Using the Eddy-Covariance Method

  • Xiangmin SunEmail author
  • Chris B. Zou
  • Bradford Wilcox
  • Elaine Stebler
Research Article


We carried out a paired study in tallgrass prairie to evaluate the influence of vegetation on the energy exchange and evapotranspiration. Two eddy-covariance systems were installed over two adjoining sites, one of which was denuded of vegetation, with the adjacent, control site kept undisturbed. Our year-long investigation shows that, for quantifying the ground surface heat flux, the soil heat storage above the soil plates is more important than the sub-surface soil heat flux, both temporally and in magnitude. The incorporation of the soil heat storage, therefore, is indispensable for energy balance closure in areas with short vegetation. At our control site, we observed a critical threshold of 0.17 m3 m−3 in the surface (top 0.3 m) soil water content, whereby the energy partitioning is significantly affected by the presence of the photosynthetically active vegetation when the surface soil water content is higher than this critical threshold. The pattern of energy partitioning approaches that of the treated site when the surface soil water content is lower than this threshold (during drought), because of the suppression of plant physiological activities. This threshold also applies to the surface conductance for water vapour at the control site, where yearly evapotranspiration is 728 ± 3 mm (versus 547 ± 2 mm for the treated site). Thus, the soil water content and presence of active vegetation are the key determinants of energy partitioning and evapotranspiration. Any land-cover changes or vegetation-management practices that alter these two factors may change the energy and water budgets in tallgrass prairie.


Eddy covariance Energy balance Evapotranspiration Surface conductance Tallgrass prairie 



We are grateful for the insightful comments from the two anonymous reviewers. This research was funded by the National Science Foundation’s Dynamics of Coupled Natural and Human Systems (CNH) program (DEB-1413900). Xiangmin Sun is a PhD student supported by the Sid Kyle Graduate Merit Assistantships in the Department of Ecosystem Science and Management at Texas A&M University. The authors would like to thank Chris Stansberry and Jay Prater for their excellent management of the research site. We also express our appreciation to Georgios Xenakis for his development of the FREddyPro package and for correspondence with the authors. The authors gratefully acknowledge many useful comments provided by James Heilman. We are deeply appreciative of the technical support provided by James Kathilankal, Jiahong Li, and George G. Burba from LI-COR Biosciences, Inc.; and by Sasha Ivans and Ben Conrad from Campbell Scientific, Inc. Finally, the authors are grateful to the many graduate students who helped with field trips, including Briana Wyatt, Patricia Torquato, Giovanne Serrau, Sumit Sharma, and Cynthia Wright.


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Authors and Affiliations

  1. 1.Department of Ecosystem Science and ManagementTexas A&M UniversityCollege StationUSA
  2. 2.Department of Natural Resource Ecology and ManagementOklahoma State UniversityStillwaterUSA

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