photo of Dr. Michael Abraha

Dr. Michael Abraha

Postdoctoral Research Associate, Michigan State University
Landscape Ecology & Ecosystem Science (LEES)

Google Scholar | Research Gate | abraha@msu.edu | 249-290-9766

Michael's research interest lies in measuring and modeling the physical processes involved in the soil-plant-atmosphere continuum, with a special focus on energy and mass exchange measurement between surfaces (bare soil, vegetated, wet-lands and/or water) and the atmosphere using micrometeorological methods. He's interested in investigating energy balance closure using eddy covariance measured fluxes and also the influence of land-use and climate changes on heat, carbon dioxide, water vapor, and other trace gas fluxes.

Education

Postdoctoral Research Associate, Great Lakes Bioenergy Research Center | 2013 — Present
Michigan State University, MI, United States

Postdoctoral Research Associate | 2010 — 2012
University of KwaZulu-Natal, Pietermaritzburg Campus, South Africa

PhD Agrometeorology | 2010
University of KwaZulu-Natal, Pietermaritzburg Campus, South Africa

MS Agriculture | 2002 — 2003
University of Natal, Pietermaritzburg Campus, South Africa

Non-degree Program | 2001
University of Natal, Pietermaritzburg Campus, South Africa

BS Soil and Water Conservation | 1992 — 1997
College of Agricultural and Aquatic Sciences, University of Asmara, Eritrea

Publications

Journal Paper

  1. Shao, C., Chen, J., Li, L., Dong, G., Han, J., Abraha, M., John, R., 2017. Grazing effects on surface energy fluxes in a desert steppe on the Mongolian Plateau. Ecological Applications. DOI:10.1002/eap.1459
  2. Yang, Q., Zhang, X., Abraha, M., Del Grosso, S., Robertson, G.P., Chen, J., 2017. Enhancing the SWAT model for simulating N2O emissions of three agricultural systems. Ecosystem Health and Sustainability. DOI:10.1002/ehs2.1259.
  3. Abraha, M., Gelfand, I., Hamilton, S.K., Shao, C., Su, Y.-J., Robertson, G.P., Chen, J., 2016. Ecosystem water use efficiency of annual corn and perennial grasslands: contributions from land use history and species composition. Ecosystems, DOI: 10.1007/s10021-016-9981-2.
  4. Abraha, M.G., Chen, J., Chu, H., Hamilton, S.K., Zenone, T., Ranjeet, J., Su, Y-J., Robertson, G.P., 2015. Evapotranspiration of annual and perennial biofuel crops in a variable climate. GCB Bioenergy., doi: 0.1111/gcbb.12239.
  5. Savage, M.J., Abraha, M.G., Moyo, N.C., Babikir E.S.N., 2014. Web-based teaching, learning and research using accessible real-time data obtained from field based agrometeorological measurement systems. South African Journal of Plant and Soil., 31: 13-23.
  6. Abraha, M.G., Savage, M.J., 2012. Energy and mass exchange over incomplete vegetation cover. Crit. Rev. Plant Sci., 31:321-341.
  7. Abraha, M.G., Savage, M.J., 2010. A simple three-dimensional solar radiation interception model for tree crops. Ecosyt. Environ., 139:636-652.
  8. Abraha, M.G., Savage, M.J., 2008. Comparison of estimates of daily solar radiation from air temperature range for application in crop simulations, Agric. Forest Meteorol., 148:401-416.
  9. Abraha, M.G., Savage, M.J., 2008. The soil water balance of rainfed and irrigated oats, Italian rye grass and rye using the CropSyst model. Irrig. Sci., 26:203-212.
  10. Abraha, M.G., Savage, M.J., 2006. Potential impacts of climate change on the grain yield of maize for the midlands of KwaZulu-Natal, South Africa. Agric. Ecosyt. Environ., 115:150-160.

 

Book Chapter

  1. Abraha, M.G., Savage, M.J., 2009. Soil water balance and yield of dryland maize using the CropSyst model. In: Danforth, A.T., (Ed.), Corn Crop Production, Growth, Fertilization and Yield. Nova Science Publishers, Inc.

Research

In this project, we use the eddy covariance (EC) method as our primary tool in making intensive, continuous measurements of net ecosystem production (NEP), water loss through evapotranspiration (ET), and energy balance at six "scale-up fields" jointly studied by Kellogg Biological Station and Great Lakes Bioenergy Research Center: switch grass, restored prairie and continuous corn fields (two replicates of each system).

We hypothesize that significant differences exist in ecosystem production, biophysical regulations and below-ground carbon allocation among the three biofuel production systems. These differences are clearly reflected at multiple temporal scales.

Contact

Collaboration makes innovation possible