|BRADEN, I - Southeast Missouri State University|
|WEST, C - Shenyang Agricultural University|
Submitted to: Agrosystems, Geosciences & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/26/2021
Publication Date: 11/16/2021
Publication URL: https://handle.nal.usda.gov/10113/7709530
Citation: Adhikari, K., Braden, I.S., Owens, P.R., Ashworth, A.J., West, C. 2021. Relating topography and soil phosphorus distribution in litter-amended pastures in Arkansas. Agrosystems, Geosciences & Environment. 4. Article e20207. https://doi.org/10.1002/agg2.20207.
Interpretive Summary: Continuous application of poultry litter in pastures potentially increases soil phosphorus level. Accumulated phosphorus may run-off to nearby surface waters and deteriorate their quality. Among several factors influencing phosphorous distribution in landscapes, topography plays a major role. This study quantified the role of topography on soil phosphorus distribution in litter amended pastures, and generated high-resolution soil phosphorus level, and phosphorus index maps that are helpful in guiding site-specific nutrient management or in best management practice recommendation.
Technical Abstract: Poultry producers in northwest Arkansas fertilize pastures with litter, leading to excessive P buildup on surface soils with risk of contaminating nearby surface waters. Information on the influence of pasture topography on P runoff is limited. Objectives were to assess soil P and P index status in pastures, quantify topographic influence on P distribution, and generate high-resolution P maps for site-specific nutrient management. Soil samples were collected from a commercial farm in a grid design and analyzed for Mehlich-3 P (STP), and dissolved reactive P (DRP). Gburek (GPI) and Sims P indices (SPI) were calculated by considering soil erosion and runoff potentials, STP, and P fertilizer application rate and source. A machine-learning algorithm, based on a random forest model, quantified spatial relationships of STP, DRP, and P indices with topography. The study area was highly variable in topography and soil P levels. High slope areas bordering streams and flat areas with lower elevation had greater GPI and SPI values. Topography explained up to 50% of variation in STP and DRP distribution and >70% variation in GPI and SPI. The key terrain attributes for STP, DRP, GPI, and SPI distribution were elevation, slope position, slope height, valley depth, and valley bottom flatness. Predicted P maps showed that areas along a stream had lower STP and DRP levels, but greater GPI and SPI. This analysis linked topographic relationships with P distribution, as topography controls the flow and distribution of water; therefore, future P management strategies should explicitly incorporate topographic risks.