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Spatio-temporal variations in soil carbon credit by conservation agriculture

Research Scholar

Ekrem Lutfi Aksaka, Soil Science and Plant Nutrients (Turkey)
Kenan Barik
, Soil Science and Plant Nutrients (Turkey)
Khandakar Islam, Faculty Mentor

Biographies

Ekrem Lütfi Aksakal is a postdoctoral scholar whose one-year visit is funded by Turkey's Ministry of Education. In Turkey, he is an assistant professor in the Department of Soil Science at Ataturk University in Erzurum. During his time at The Ohio State University, he can be found at the Ohio State South Centers in the Soil, Water and Bioenergy Resources program, where he focuses on spatial variability and geostatistics, conservation tillage and cover crops, soil quality and carbon sequestration, crop water-use efficiency and techniques of data analysis.

Kenan Barik, assistant professor in the Department of Soil Science at Ataturk University in Erzurum, Turkey, is a scholar visiting The Ohio State University for three months with funding from Turkey's Ministry of Education. He also does research at the Ohio State South Centers in the Soil, Water and Bioenergy Resources program at Piketon, where he works on soil quality and cover crops, tillage management and soil carbon sequestration to complement his professional development.

What is the issue or problem addressed in your research?

Traditional agricultural practices often associated with reduced ecosystem services. Converting from traditional practices to conservation agriculture is one of the sustainable approaches to economize farming costs, reduce greenhouse gas emissions, and sequester soil carbon for enhanced ecosystem services. Spatio-temporal soil properties variability that is associated with carbon credit can be used as tools to help guide sustainability of agricultural management practices to mitigate climate change.

What methodology did you use in your research?

Composite soil samples collected from geo-referenced sites (at different soil depths) of replicated fields under conventional tillage, transition no-till, and long-term no-till with and without cover crops using systematic sampling will be analyzed for carbon and nitrogen pools, bulk density, pH and electrical conductivity, energy content, and soil quality. Automated dry combustion method will be used to measure total soil and particulate organic matter carbon and nitrogen contents. Active carbon as a measure of soil quality will be determined by oxidation and spectrophotometric method. Soil pH and electrical conductivity will be determined by electrode method. Bulk density will be calculated using core method. All the carbon data will be normalized to derive an index of soil carbon credit using the “inductive additive approach” to account for ecosystem services.
Multi-variate statistical analyses using SAS will be performed to determine the significant variations in soil properties including soil carbon credit attributed to the effects of tillage, cover crops, soil depth and their interactions. Geostatistical analyses such as semivariogram and punctual Kriging will be performed to measure and plot the 3-dimentional spatial variability in soil properties within the fields using the GS+ geostatistical software.

What are the purpose/rationale and implications of your research?

The purpose of our study was to use multi-variate and geostatistical techniques as decision making tools to evaluate the impact of conservation management practices (continuous no-till and multi-purpose cover crops) on the distribution of spatio-temporal variability in soil quality properties that are indicators of carbon credit for enhanced agro-ecosystem services.