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ARS Home » Southeast Area » Booneville, Arkansas » Dale Bumpers Small Farms Research Center » Research » Publications at this Location » Publication #352459

Research Project: Sustainable Small Farm and Organic Production Systems for Livestock and Agroforestry

Location: Dale Bumpers Small Farms Research Center

Title: Topographic controls on soil nutrient variations in a Silvopasture system

item ADHIKARI, KABINDRA - University Of Arkansas
item Owens, Phillip
item Ashworth, Amanda
item Sauer, Thomas
item LIBOHOVA, ZAMIR - Natural Resources Conservation Service (NRCS, USDA)
item RICHTER, JENNY - Oak Ridge Institute For Science And Education (ORISE)
item MILLER, DAVID - University Of Arkansas

Submitted to: Agrosystems, Geosciences & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2018
Publication Date: 6/6/2018
Publication URL:
Citation: Adhikari, K., Owens, P.R., Ashworth, A.J., Sauer, T.J., Libohova, Z., Richter, J., Miller, D.M. 2018. Topographic controls on soil nutrient variations in a Silvopasture system. Agrosystems, Geosciences & Environment.

Interpretive Summary: Understanding spatial variation of soil nutrients in a silvopasture system is important for farm management decisions. Distribution of nutrient in a landscape is governed by several factors and topography is among the most important one as it controls water and energy distribution. This study evaluated topographic influence on soil nutrient variations and generated digital soil nutrients maps using measurements and terrain attributes. Based on topographic information, potential management zones were identified among which soil nutrients distribution was different. The maps generated in this study can be used to identify nutrient risk areas that have optimum forage and tree production potentials and can be linked to preferential animal grazing as it relates to hydrology, forage quality, and ultimately soil nutrient variability spatially.

Technical Abstract: Topography plays a crucial role in the spatial distribution of nutrients in soils because of its influence on the flow and (re)distribution of water and energy in a landscape. Information on the spatial pattern of soil nutrient distribution would benefit management decisions to maximize crop yield and minimize environmental impacts; however, such information from a silvopasture system is mostly lacking. This study aims to quantify and model the topographic influence on soil nutrients distribution in a silvopasture system by using state-of-the-art spatial soil mapping techniques. A 4.3 ha silvopasture site in northwest Arkansas was selected for the study and a total of 51 topsoil (0-15 cm) samples were collected and analyzed for primary [Total Nitrogen (TN), Phosphorus (P), and Potassium (K)], secondary [Calcium (Ca), Magnesium (Mg), and Sulphur (S)], and micronutrients [Iron (Fe), Zinc (Zn), Copper (Cu), Manganese (Mn), Boron (B), and Sodium (Na)]. Topographic information was acquired from 12 terrain attributes derived from a 1-m digital elevation model generated through LiDAR and were used as predictors of soil nutrient distribution. The prediction model was based on Random Forest and the model performance was evaluated with R2, RMSE, Lin’s concordance correlation coefficient, and bias in prediction. Results showed that TN, S, and P were best predicted, whereas Cu, Ca, and Mn had the lowest prediction performance. Levels of S, Ca, Zn, Fe, and TN increased with System for Automated Geoscientific Analyses (SAGA) Wetness Index, Valley Depth, Flow Accumulation, and Multi-Resolution Valley Bottom Flatness Index. Normalized Height, and Slope Height were positively related to Na but negatively to Bo and Cu distribution. Aspect had a positive influence in P and Mg concentration. Results showed that most part of the study area had TN, and K levels lower than the corresponding average values of these elements, i.e., 1.6 g kg-1 and 45 mg kg-1, respectively. The eastern half of the study area had more P and Mg than the western half, with management potentially impacting this nutrient distribution. Based on terrain attributes, the study site could be divided into 4 topographic functional units (TFU), namely A, B, C and D. TFU “A” had the greatest nutrients present, whereas TFU “B” had the lowest P, K, Zn, Cu, Fe, and Ca but greatest Na content. Mn, Mg, and B didn’t vary among TFUs. This study affirmed topographic influences on soil nutrient spatial distribution and the resulting continuous soil property maps are useful for fine-tuning production systems through optimum nutrient and pasture management. Keywords: essential plant nutrients, agroforestry, terrain attributes, digital soil mapping, random forest; grazing; spatial variability