Forbes Walker

Comparing phosphorus indices from twelve southern U.S. states against monitored phosphorus loads from six prior southern studies.

Forty-eight states in the United States use phosphorus (P) indices to meet the requirements of their Natural Resources Conservation Service (NRCS) Code 590 Standard, which provides national guidance for nutrient management of agricultural lands. The majority of states developed these indices without consultation or coordination with neighboring states to meet specific local conditions and policy needs. Using water quality and land treatment data from six previously published articles, we compared P loads with P-Index values and ratings using the 12 southern P indices. When total measured P loads were regressed with P-Index rating values, moderate to very strong relationships (0.50 to 0.97) existed for five indices (Arkansas, Florida, Georgia, North Carolina, and South Carolina) and all but one index was directionally correct. Regressions with dissolved P were also moderate to very strong ( of 0.55 to 0.95) for the same five state P indices (Arkansas, Florida, Georgia, North Carolina, and South Carolina); directionality of the Alabama Index was negative. When total measured P loads were transformed to current NRCS 590 Standard ratings (Low [<2.2 kg P ha], Moderate, [2.2-5.5 kg P ha], and High [>5.5 kg P ha]) and these ratings were then compared to the southern-Index ratings, many of the P indices correctly identified Low losses (77%), but most did not correctly identify Moderate or High loss situations (14 and 31%, respectively). This study demonstrates that while many of the P indices were directionally correct relative to the measured water quality data, there is a large variability among southern P indices that may result in different P management strategies being employed under similar conditions.

Multivariate analysis of laser-induced breakdown spectroscopy spectra of soil samples.

Abstract Laser-induced breakdown spectroscopy (LIBS) is a rapid quantitative analytical technique that can be used to determine the elemental composition of numerous sample matrices, and it has been successfully applied in many types of samples. However, for chemically and physically complex soil samples, its quantitative analytical ability is controversial. Multivariate analytical techniques have great potential for analyzing the complex LIBS spectra. To demonstrate the feasibility of LIBS as an alternative technique to quantitatively analyze soil samples, the univariate and the partial least square (PLS) techniques are used to analyze the LIBS spectra of 12 soil samples and to build calibration models predicting Cu and Zn concentrations. The results show that PLS can significantly improve the analytical results compared with the univariate technique. The normalized root mean square error (NRMSE) and r2 of the univariate models are 16.60% and 0.71 in calibration and 18.80% and 0.62 in prediction for Cu and 18.97% and 0.62 in calibration and 22.81% and 0.45 in prediction for Zn. For the PLS models using the spectral range 300 to 350 nm, the NRMSE and r2 are 1.94% and 0.99 for both Cu and Zn in calibration and 7.90% and 0.94 for Cu and 8.14% and 0.94 for Zn in prediction, respectively. Compared with the univariate technique, PLS improves the NRMSE 87.53% and 87.78% in calibration and 44.47% and 53.44% in prediction for Cu and Zn, respectively. The results indicate that PLS can improve the quantitative analytical ability of LIBS for soil sample analysis.

Southern Phosphorus Indices, Water Quality Data, and Modeling (APEX, APLE, and TBET) Results: A Comparison

Phosphorus (P) Indices in the southern United States frequently produce different recommendations for similar conditions. We compared risk ratings from 12 southern states (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, and Texas) using data collected from benchmark sites in the South (Arkansas, Georgia, Mississippi, North Carolina, Oklahoma, and Texas). Phosphorus Index ratings were developed using both measured erosion losses from each benchmark site and Revised Universal Soil Loss Equation 2 predictions; mostly, there was no difference in P Index outcome. The derived loss ratings were then compared with measured P loads at the benchmark sites by using equivalent USDA-NRCS P Index ratings and three water quality models (Annual P Loss Estimator [APLE], Agricultural Policy Environmental eXtender [APEX], and Texas Best Management Practice Evaluation Tool [TBET]). Phosphorus indices were finally compared against each other using USDA-NRCS loss ratings model estimate correspondence with USDA-NRCS loss ratings. Correspondence was 61% for APEX, 48% for APLE, and 52% for TBET, with overall P index correspondence at 55%. Additive P Indices (Alabama and Texas) had the lowest USDA-NRCS loss rating correspondence (31%), while the multiplicative (Arkansas, Florida, Louisiana, Mississippi, South Carolina, and Tennessee) and component (Georgia, Kentucky, and North Carolina) indices had similar USDA-NRCS loss rating correspondence-60 and 64%, respectively. Analysis using Kendalls modified Tau suggested that correlations between measured and calculated P-loss ratings were similar or better for most P Indices than the models.

A study of cattle producer preferences for best management practices in an East Tennessee watershed

Best Management Practices (BMPs) contribute to a broader range of efforts to improve the environmental performance of the livestock sector and its impact on water quality. This research evaluates a survey of cattle producers in an East Tennessee watershed and parts of five surrounding watersheds, along with and the factors correlated with preferences for BMPs designed to reduce sediment, nutrient, and fecal coliform contamination of surface waters by limiting cattle access to streams. The objective of the survey was to gather behavioral information about producer interest in specific BMPs in an effort to supplement a long-term biophysical modeling project. Structures and BMPs analyzed include stream crossings, rotational grazing, pasture improvement, and cattle water tanks. The physical and economic constraints faced by producers and the incentives provided by state and federal programs influence the decision to adopt a set of practices or structures that impact pathogen loading into streams. There was a clear preference for a suite of BMPs that did not include stream crossings, reinforcing anecdotal evidence that the maintenance associated with frequent high flow events may reduce willingness to install stream crossings. Cattle producers were more willing to implement rotational grazing and pasture improvement BMPs, which were associated with cattle health and productivity. The extensive distribution of pastureland in the region analyzed, the relatively inexpensive costs of adopting practices supporting pasture improvement, and higher quality forage correlated with improved pastures suggest a win-win outcome for cattle owners and efforts to enhance water quality.