Dr. Zamir Libohova

Research Soil Scientist

United States Department of Agriculture

Agricultural Research Service

Dale Bumpers Small Farms Research Center

6883 South State Highway 23

Booneville AR 72927

(479)675-3834

     Dr. Zamir Libohova received a bachelor’s degree in Agronomy and Doctor of Science in Soil Fertility and Plant Nutrition from the Agriculture University of Tirana, Albania. He worked for 2 years as a research scientist at the National Soil Institute conducting soil fertility trials and leading the North Research Station and the National Soil Laboratory. He received a Fulbright scholarship (named after William J. Fulbright, Senator from Arkansas who started the program) to study soil science at Oregon State University. He joined the World Bank Forestry Project in Albania as the interim director of Project Environmental Management Unit overseeing the implementation of the Environmental impact Assessment program. Zamir graduated with a Master of Science degree from Colorado State University with focus on hydrology and watershed management. While working as a soil scientist with USDA-NRCS in Alabama, he received an advanced certificate on GIS and remote sensing from the University of Alabama in Tuscaloosa. Dr. Libohova graduated with a Doctor of Philosophy (PhD) in soil science from Purdue University and joined the National Soil Survey Center (NSSC) in Lincoln NE as a Research Soil Scientist. At the NSSC he conducted research on soil modelling using digital soil mapping and remote sensing approaches. During this time, he worked for the GlobalSoilMap project, an international initiative funded by Bill & Melinda Gates’ Foundation and supported by the International Union of Soil scientists (IUSS). During his tenure at NSSC, he worked on many projects in different countries like Albania, Brazil, China, El Salvador, Honduras, Nicaragua, Guatemala, Colombia, France, Mexico, Haiti, Kenya, Russia and Switzerland where he continues to collaborate. His research interests are on understanding how technology can be applied to small farm operations to understand animal, plant and soil interactions for optimizing economic gains.

     His research focus on developing models and tools to better manage these systems adding to the technology focus at the Dale Bumpers Small Farms Research Center. Dr. Libohova said “the position at the USDA-ARS Dale Bumpers Small Farms Research Center is a great opportunity and I am very honored and fortunate to join the team of researchers and the center staff to help and contribute to the mission. I look forward to building a research program that supports small farms and contributes to the profitability of rural communities. I am excited to participate in stakeholder meetings and learn more about the challenges of operating small-scale farms.”

• Projects

  Innovations for Small Farms Pasture and Silvopasture In-House Appropriated (D)   Accession Number:444957

  Develop Spatially Explicit Soil Property Maps for Precision Management for Forage Production for Small Farms Non-Assistance Cooperative Agreement (S)   Accession Number:446281

  Development of Spatial Soil Health Recommendations for Small Farms Non-Assistance Cooperative Agreement (S)   Accession Number:446753

  Improving Resilience and Diversification of Small Farms Through Agroforestry and Specialty Crops Non-Assistance Cooperative Agreement (S)   Accession Number:438074

• Publications

  • (Clicking on the reprint icon will take you to the publication reprint.)
  • Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model -(Peer Reviewed Journal)
    Libohova, Z., Mancini, M., Winzeler, H.E., Read, Q.D., Sun, N., Beaudette, D., Williams, C., Blackstock, J.M., Silva, S., Curi, N., Adhikari, K., Ashworth, A.J., Minai, J., Owens, P.R. 2024. Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model. Geoderma Regional. https://doi.org/10.1016/j.geodrs.2024.e00863.
    
  • Vegetation masking of remote sensing data aids machine learning for soil fertility prediction -(Peer Reviewed Journal)
    Winzeler, H.E., Mancini, M., Blackstock, J.M., Libohova, Z., Owens, P.R., Ashworth, A.J., Miller, D., Silva, H.G. 2024. Vegetation masking of remote sensing data aids machine learning for soil fertility prediction. Remote Sensing. https://doi.org/10.3390/rs16173297.
    
  • Mapping topsoil behavior to compation at national scale from an analysis of field observations -(Peer Reviewed Journal)
    Ricjer-De-Forges, A.C., Arrouays, D., Chen, S., Libohova, Z., Beaudette, D.E., Bourennane, H. 2024. Mapping topsoil behavior to compation at national scale from an analysis of field observations. Land. https://doi.org/10.3390/land13071014.
    
  • Revealing topsoil behavior to compaction from mining field observations -(Peer Reviewed Journal)
    Ritcher-De-Fores, A.C., Arrouays, D., Libohova, Z., Chen, S., Beaudette, D.E., Bourennane, H. 2024. Revealing topsoil behavior to compaction from mining field observations. Land. https://doi.org/10.3390/land13070909.
    
  • The Impact of Climate Change on Natural Monuments in Albania-(Abstract Only)
    
    
  • Simulating water dynamics related to pedogenesis across space and time: Implications for four-dimensional digital soil mapping -(Peer Reviewed Journal)
    Owens, P.R., Mancini, M., Winzeler, H.E., Read, Q.D., Sun, N., Blackstock, J.M., Libohova, Z. 2024. Simulating water dynamics related to pedogenesis across space and time: Implications for four-dimensional digital soil mapping. Geoderma. https://doi.org/10.1016/j.geoderma.2024.116911.
    
  • Heavy metals concentration in soils across the conterminous USA: Spatial prediction, model uncertainty, and influencing factors -(Peer Reviewed Journal)
    Adhikari, K., Mancini, M., Libohova, Z., Blackstock, J.M., Winzeler, H.E., Smith, D.R., Owens, P.R., Silva, S.H., Curi, N.C. 2024. Heavy metals concentration in soils across the conterminous USA: Spatial prediction, model uncertainty, and influencing factors. Science of the Total Environment. 919. Article 170972. https://doi.org/10.1016/j.scitotenv.2024.170972.
    
  • Influence of sample size, model selection, and land use on prediction accuracy of soil properties -(Peer Reviewed Journal)
    Safaee, S., Libohova, Z., Kladivko, E., Brown, A., Winzeler, H.E., Read, Q.D., Rahmani, S., Adhikari, K. 2024. Influence of sample size, model selection, and land use on prediction accuracy of soil properties. Geoderma Regional. https://doi.org/10.1016/j.geodrs.2024.e00766.
    
  • Identifying key factors controlling soil respiration in agricultural fields -(Peer Reviewed Journal)
    Adhikari, K., Anderson, K.R., Smith, D.R., Owens, P.R., Moore Jr., P.A., Libohova, Z. 2023. Identifying key factors controlling soil respiration in agricultural fields. Agricultural & Environmental Letters. 8(2). Article e20117. https://doi.org/10.1002/ael2.20117.
    
  • Identification and delineation of broad-base agricultural terraces in flat landscapes in Northeastern Oklahoma, USA -(Peer Reviewed Journal)
    Winzeler, H.E., Owens, P.R., Kharel, T.P., Ashworth, A.J., Libohova, Z. 2023. Identification and delineation of broad-base agricultural terraces in flat landscapes in Northeastern Oklahoma, USA. Land. 12(2):486. https://doi.org/10.3390/land12020486.
    
  • Topographic wetness index as a proxy for soil moisture in a hillslope catena: flow algorithms and map generalization -(Peer Reviewed Journal)
    Winzeler, H.E., Owens, P.R., Read, Q.D., Libohova, Z., Ashworth, A.J., Sauer, T.J. 2022. Topographic wetness index as a proxy for soil moisture in a hillslope catena: flow algorithms and map generalization. Land. 11(11):2018. https://doi.org/10.3390/land11112018.
    
  • Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of particle size distribution. A case study in central France -(Peer Reviewed Journal)
    Richer-De-Forges, A.C., Arrouays, D., Poggio, L., Chen, S., Lacoste, M., Minasny, B., Libohova, Z., Roudier, P., Mulder, V.L., Nedelec, H., Martelet, G., Lemercier, B., Lagacherie, P., Bourennane, H. 2023. Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of particle size distribution. A case study in central France. Pedosphere. 33(5):731-743. https://doi.org/10.1016/j.pedsph.2022.07.009.
    
  • Influence of land use and topographic factors on soil organic carbon stocks and their spatial and vertical distribution -(Peer Reviewed Journal)
    Blackburn, K., Libohova, Z., Adhikari, K., Kome, C., Maness, X., Silman, R.M. 2022. Influence of land use and topographic factors on soil organic carbon stocks and their spatial and vertical distribution. Remote Sensing. https://doi.org/10.3390/rs14122846.
    
  • Assessing wildfire vulnerability of vegetated serpentine soils in the Balkan peninsula -(Peer Reviewed Journal)
    Hysa, A., Teqja, Z., Bani, A., Libohova, Z., Cerda, A. 2022. Assessing wildfire vulnerability of vegetated serpentine soils in the Balkan peninsula. Nature Conservation. https://doi.org/10.1016/j.jnc.2022.126217.
    
  • Characteristics of a benchmark loess-paleosol profile in Northeast China -(Peer Reviewed Journal)
    Sun, Z., Jiang, Y., Wang, Q., Jiang, Z., Libohova, Z., Owens, P.R. 2022. Characteristics of a benchmark loess-paleosol profile in Northeast China. Agronomy Journal. https://doi.org/10.3390/agronomy12061376.
    
  • Digital mapping of soil organic matter and cation exchange capacity in a low relief lanscape using LiDAR data -(Peer Reviewed Journal)
    Rahmani, S.R., Ackerson, J., Schulze, D., Adhikari, K., Libohova, Z. 2022. Digital mapping of soil organic matter and cation exchange capacity in a low relief lanscape using LiDAR data. Agronomy Journal. https://doi.org/10.3390/agronomy12061338.
    
  • Digital mapping of soil organic matter and cation exchange capacity in a low relief landscape using LiDAR data -(Peer Reviewed Journal)
    Rahmani, S.R., Ackerson, J., Schulze, D., Adhikari, K., Libohova, Z. 2022. Digital mapping of soil organic matter and cation exchange capacity in a low relief landscape using LiDAR data. Agronomy Journal. https://doi.org/10.3390/agronomy12061338.
    
  • Carbon storage in agricultural topsoils and subsoils is promoted by including temporary grasslands into the crop rotation -(Peer Reviewed Journal)
    Guillaume, T., Makowski, D., Libohova, Z., Elfouki, S., Fontana, M., Leifeld, J., Bragazza, L., Sinaj, S. 2022. Carbon storage in agricultural topsoils and subsoils is promoted by including temporary grasslands into the crop rotation. Geoderma. https://doi.org/10.1016/j.geoderma.2022.115937.
    
  • Soil Morphology-(Book / Chapter)
    
    
  • Hand-feel soil texture and particle-size distribution in Central France. Relationships and implications -(Peer Reviewed Journal)
    Richer-De-Forges, A.C., Arrouays, D., Chen, S., Roman Dobarco, M., Libohova, Z., Roudier, P., Minasny, B., Bourennane, H. 2022. Hand-feel soil texture and particle-size distribution in Central France. Relationships and implications. Catena. https://doi.org/10.1016/j.catena.2022.106155.
    
  • Renewal of archival legacy soil data: A case study of the Busia Area, Kenya -(Peer Reviewed Journal)
    Minai, O.J., Schulze, D., Libohova, Z. 2022. Renewal of archival legacy soil data: A case study of the Busia Area, Kenya. Frontiers in Soil Science. https://doi.org/10.3389/fsoil.2021.765248.
    
  • How well does Predictive Soil Mapping represent soil geography? An investigation from the USA Part 2: Case Studies -(Proceedings)
    Rossiter, D.G., Beaudette, D., Libohova, Z., Poggio, L. 2021. How well does Predictive Soil Mapping represent soil geography? An investigation from the USA Part 2: Case Studies. Meeting Abstract. https://doi.org/10.17027/isricwdc-202103.
    
  • Transferability between soil organic matter measurement methods for database harmonization -(Peer Reviewed Journal)
    Shamrikova, E.V., Kondratenok, B.M., Tumanova, E.A., Vanchikova, E.V., Lapteva, E.M., Zonova, T.N., Lu-Lyan-Min, E.I., Davydova, A.P., Libohova, Z., Suvannang, N. 2021. Transferability between soil organic matter measurement methods for database harmonization. Geoderma. https://doi.org/10.1016/j.geoderma.2021.115547.
    
  • Soil organic carbon saturation in cropland-grassland systems: storage potential and soil quality -(Peer Reviewed Journal)
    Guillaume, T., Makowski, D., Libohova, Z., Bragazza, L., Sallaku, F., Sinaj, S. 2021. Soil organic carbon saturation in cropland-grassland systems: storage potential and soil quality. Geoderma. 406. Article 115529. https://doi.org/10.1016/j.geoderma.2021.115529.
    
  • Changes of soil organic carbon after wildfire in a Boreal Forest, Northeast China -(Peer Reviewed Journal)
    Han, C., Sun, Z., Shao, S., Wang, Q., Libohova, Z., Owens, P.R. 2021. Changes of soil organic carbon after wildfire in a Boreal Forest, Northeast China. Agronomy Journal. 11(10):1925. https://doi.org/10.3390/agronomy11101925.
    
  • How well does Predictive Soil Mapping represent soil geography? An investigation from the USA -(Peer Reviewed Journal)
    Rossiter, D.G., Poggio, L., Beaudette, D., Libohova, Z. 2021. How well does Predictive Soil Mapping represent soil geography? An investigation from the USA. Soil. https://doi.org/10.5194/soil-2021-80.
    

• ARS News Articles

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