A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

EMPIRICAL MODELS FOR TROPHIC STATE IN SOUTHEASTERN U.S. LAKES AND RESERVOIRS1

ABSTRACT: A cross-sectional data set of 80 lakes and reservoirs in nine southeastern states was examined to specify and parameterize trophic state relationships. The relationships fitted are based on measurements of several limnological variables taken over the course of a growing season or year in each of the lakes. The trophic state models relate phosphorus and nitrogen loading to inlake phosphorus and nitrogen concentrations, which in turn are related to maximum chlorophyll level, Secchi disk depth, dominant algal species, and hypolimnetic dissolved oxygen status. Due to the empirical nature of the study, causal conclusions are limited; rather, the models are most useful for prediction of average growing season conditions related to trophic state.     

AN EXAMINATION OF LAND USE - NUTRIENT EXPORT RELATIONSHIPS1

ABSTRACT: Lake and watershed management strategies and recent environmental legislation dictate that nonpoht nutrient sources associated with storm water runoff must be assessed. Accordingly, a nutrient flu assessment for phosphorus and nitrogen is conducted through an extensive literature review of nutrient export studies. These studies are reevaluated. The nutrient export coefficients are screened according to sampling design criteria and compiled according to land use. The ecological mechanisms within each land use influencing the magnitude of nutrient flux are also discussed     

The MANAGE database: nutrient load and site characteristic updates and runoff concentration data

The "Measured Annual Nutrient loads from AGricultural Environments" (MANAGE) database was developed to be a readily accessible, easily queried database of site characteristic and field-scale nutrient export data. The original version of MANAGE, which drew heavily from an early 1980s compilation of nutrient export data, created an electronic database with nutrient load data and corresponding site characteristics from 40 studies on agricultural (cultivated and pasture/range) land uses. In the current update, N and P load data from 15 additional studies of agricultural runoff were included along with N and P concentration data for all 55 studies. The database now contains 1677 watershed years of data for various agricultural land uses (703 for pasture/rangeland; 333 for corn; 291 for various crop rotations; 177 for wheat/oats; and 4-33 yr for barley, citrus, vegetables, sorghum, soybeans, cotton, fallow, and peanuts). Across all land uses, annual runoff loads averaged 14.2 kg ha(-1) for total N and 2.2 kg ha(-1) for total P. On average, these losses represented 10 to 25% of applied fertilizer N and 4 to 9% of applied fertilizer P. Although such statistics produce interesting generalities across a wide range of land use, management, and climatic conditions, regional crop-specific analyses should be conducted to guide regulatory and programmatic decisions. With this update, MANAGE contains data from a vast majority of published peer-reviewed N and P export studies on homogeneous agricultural land uses in the USA under natural rainfall-runoff conditions and thus provides necessary data for modeling and decision-making related to agricultural runoff. The current version can be downloaded at http://www.ars.usda.gov/spa/manage-nutrient.     

A Bayesian approach to retransformation bias in transformed regression

Ecological data analysis often involves fitting linear or nonlinear equations to data after transforming either the response variable, the right side of the equation, or both, so that the standard suite of regression assumptions are more closely met. However, inference is usually done in the natural metric and it is well known that retransforming back to the original metric provides a biased estimator for the mean of the response variable. For the normal linear model, fit under a log-transformation, correction factors are available to reduce this bias, but these factors may not be generally applicable to all model forms or other transformations. We demonstrate that this problem is handled in a straightforward manner using a Bayesian approach, which is general for linear and nonlinear models and other transformations and model error structures. The Bayesian framework provides a predictive distribution for the response variable so that inference can be made at the mean, or over the entire distribution to incorporate the predictive uncertainty.     

TECHNIQUES FOR DETECTING TRENDS IN LAKE WATER QUALITY1

ABSTRACT: With the advent of standards and criteria for water quality variables, there has been an increasing concern about the changes of these variables over time. Thus, sound statistical methods for determining the presence or absence of trends are needed. A Trend Detection Method is presented that provides: 1) Hypothesis Formulation - statement of the problem to be tested, 2) Data Preparation - selection of water quality variable and data, 3) Data Analysis - exploratory data analysis techniques, and 4) Statistical Tests - tests for detecting trends. The method is utilized in a stepwise fashion and is presented in a nonstatistical manner to allow use by those not well versed in statistical theory. While the emphasis herein is on lakes, the method may be adopted easily to other water bodies.     

LAND COVER AS A FRAMEWORK FOR ASSESSING RISK OF WATER POLLUTION1

ABSTRACT: A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land‐cover types. We used simulations to estimate the land‐cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at between 20 percent and 30 percent nonforest cover, there is a 10 percent or greater chance of N or P nutrient loads being equivalent to the median values of predominantly agricultural or urban watersheds. The methods apply to environmental management for assessing the risk to increased nonpoint nutrient pollution. Interpretation of the risk measures are discussed relative to their application for a single watershed and across a region comprised of several watersheds.     

Modeling excessive nutrient loading in the environment

Models addressing excessive nutrient loading in the environment originated over 50 years ago with the simple nutrient concentration thresholds proposed by Sawyer (1947. Fertilization of lakes by agricultural and urban drainage. New Engl. Water Works Assoc. 61, 109-127). Since then, models have improved due to progress in modeling techniques and technology as well as enhancements in scientific knowledge. Several of these advances are examined here. Among the recent approaches in modeling techniques we review are error propagation, model confirmation, generalized sensitivity analysis, and Bayesian analysis. In the scientific arena and process characterization, we focus on advances in surface water modeling, discussing enhanced modeling of organic carbon, improved hydrodynamics, and refined characterization of sediment diagenesis. We conclude with some observations on future needs and anticipated developments.     

Metabolism of DDT in Different Tissues of Young Rats

The bioconcentration and distribution pattern of p,p′-DDT 1,1,1-1trichloro-2,2-bis(2-chlorophenyl-4-chlorophenyl)-ethane] and its main metabolites (p,p′-DDD [1,1-dichloro-2,2-bis (4-chlorophenyl) ethane] and p,p′-DDE [1,1-dichloro-2,2-bis (4-chlorophenyl) in adipose tissue, liver, brain, kidney, thymus, and testis were examined in young rats after 10 days of intraperitoneal injection of 50 and 100 mg of p,p′-DDT/kg of body weight. Analyses were performed by high-resolution gas chromatography. p,p′-DDT was found to be accumulated in a dose-dependent manner with the highest concentration in adipose tissue. However, in brain, the accumulation of pesticide was low and remained unchanged at the higher dose. This difference may relate to the protective role of the blood-brain barrier, which limits the access of the xenobiotic in the cerebral compartment, and to the differential tissue lipid composition. Although tissues concentration of p,p′-DDE and p,p′-DDD correlated positively to total p,p′-DDT levels, the active role in detoxification of pollutants may explain why p,p′-DDD is more abundant in liver than in the rest of organs. On the contrary, in brain, the concentration of p,p′-DDE is higher than that of p,p′-DDD, suggesting that the metabolism of the parent insecticide proceeds via more than one pathway.