A “MANAGE”ed Approach for 4R Nutrient Stewardship on Drained Land


01 Mar 2014

Project Description

Summary: Complex environmental, economic, and social demands placed upon agriculture mean 4R Nutrient Stewardship is now a vital approach to guide on-farm nutrient management. With the rapid dissemination of these stewardship ideas, there arises a critical need to evaluate and better understand their environmental and economic impacts. The overarching aim of this proposed work is to review and analyze the water quality and crop yield impacts of the 4R practices to better target practice implementation and optimize agronomic and environmental goals in three U.S. regions where artificial agricultural drainage is common. The specific assessable research objectives are to use information compiled from published literature to further develop MANAGE, an existing water quality database (Objective #1), and to perform a meta-analysis on the water quality and crop yield effects of the 4R practices in artificially drained agronomic systems in the Midwest, Southeast, and Mid-Atlantic United States (Objective #2). The combination of the Dr. Christianson’s previous post-doctoral literature review experience and Dr. Harmel’s leading efforts with the MANAGE database form an ideal foundation for this work. The broader long-term impacts of this study are aimed at improved targeting and increased implementation of appropriate 4R Nutrient Stewardship practices and a corresponding improvement in water quality.

I. Background

Changing global diets, intensified climate variability, and increasingly degraded land and water resources have created an urgent need to revisit agriculture’s approach towards sustainability. This mounting complexity now requires producers to undertake new and redefined roles as integrated landscape managers, directors of natural capital, and ecosystem service suppliers, beyond their more overt responsibilities as providers of food, fiber, and fuel. With society demanding that farmers now balance multiple environmental and agronomic objectives, it is critical to provide comprehensive and useful information to producers and industry stakeholders on the impacts of recommended on-farm management practices.

In most agronomic systems, nutrient additions are required to sustain the viability of soil resources. The 4R Nutrient Stewardship approach to fertilizer management is an integrated strategy developed to foster achievement of agricultural production goals while minimizing negative associated environmental, economic, and social effects. Simply put, this approach advises the application of “the right source of nutrient, at the right rate, at the right time, and in the right place” (Pagani et al., 2013). Despite the simplicity of this concept, accurate implementation of the 4Rs requires site-specific knowledge of any given field’s biophysical and social constraints in tandem with associated economic and production goals.

In addition to the 4Rs framework, maintained and improved artificial agricultural drainage networks will be required in many areas of the United States to tackle the production needs associated with growing population pressure and changing diets (Figure 1). Unfortunately, the intersection of agricultural drainage and nutrient mobility in the environment has led to multi-scale water quality concerns (Thomas et al., 1995; Kleinman et al., 2007; David et al., 2010). Variation in soil type, weather, climate, drainage system, and management practices, among other factors, affect drainage nutrient losses (Skaggs and van Schilfgaarde, 1999). This means individual nutrient management practices will have differing effectiveness and differing compatibility with farm management and profitability goals in any given location.

While studies of the agronomic and environmental impacts of improved nutrient management practices have been conducted, there is a need to assemble and further analyze these previous works to develop a more comprehensive understanding. In particular, an applied synthesis of water quality and crop yield effects of the 4Rs in artificially drained agronomic systems would enrich knowledge across industry, academia, and agencies. Ultimately, such improved understanding could facilitate enhanced agricultural crop production, increased on-farm profitability, and improved water quality. To this end, this proposed work aims to better identify and define the consequences of the 4Rs nutrient strategy in the face of the 21st century’s complexity.
a. Overview of approach

The overarching goal of this work is to review published literature to develop both a comprehensive assemblage of and statistical analysis on the water quality and economic impacts of the 4R practices in artificially drained agronomic systems. Specifically, the objectives are to use information compiled from published literature to further develop MANAGE, an existing water quality database (Objective #1), and to perform a meta-analysis on the water quality and crop yield effects of the 4R practices across three U.S. regions where artificial agricultural drainage is common (Objective #2). The impact of selected 4R strategies upon dissolved, particulate, and total nitrogen (N) and phosphorus (P) transport in drainage systems in the Midwest, Southeast, and Mid-Atlantic regions will be investigated (Figure 2). This work will allow comprehensive evaluation of these practices’ impact upon environmental and economic outcomes (RFP Basic Requirements 1 and 3), and the detailed compilation of studies across regions will allow further analysis of 4R impacts across sites and cropping systems (RFP Basic Requirement 4).

II. Approach: Activities and methods

a. Objectives

The major aim of this work is to review and analyze the water quality and yield impacts of the 4R practices in artificially drained agronomic systems in the Midwest, Southeast, and Mid-Atlantic United States. The two specific assessable objectives are to:
    1. Further develop the MANAGE database through addition of drainage studies focused on the 4R practices that contain water quality and crop yield data
    2. Perform a statistical meta-analysis of data assembled during the review to determine the response effect of 4R practices upon water quality and crop yield

b. Hypothesis

The extent of the water quality impact and economic benefit or penalty (as indicated by crop yield) precipitated by individual 4R Nutrient Stewardship strategies will vary by the specific practice (rate/ timing/ placement/ source), pollutant (N/P, dissolved/particulate), drainage type (surface/subsurface), and region (Midwest/ Southeast/ Mid-Atlantic).

c. Proposed activities

The Co-PI and project director, Laura Christianson, will review existing literature for relevant data pertaining to N and P drainage losses (loads and/or concentrations) and economic/yield impacts from studies evaluating one or more of the 4R practices conducted in the three regions of interest. First, studies already in the MANAGE database that report drainage water quality will be examined so that identifiers and names across the database are consistent. Then, additional peer-reviewed articles will be identified through engines such as Agricola and Google Scholar and through citation lists of other relevant studies. Articles of interest will be purchased, and citations for each will be managed using EndNote software.

A master database will be kept of all potential and sourced articles to aid in tracking (1) articles yet to be sourced/reviewed, (2) suitable articles having undergone review, (3) articles needing further review, and (4) articles having undergone review and deemed unsuitable. Each article classified as suitable and will be summarized in a supporting appendix document intended to accompany the final project outputs. It is possible some articles judged unsuitable may also be summarized in this synopsis to increase transparency as to why certain studies were excluded. Studies deemed suitable with sufficient N and P drainage transport load and/or concentration and yield data will be further entered into the MANAGE database (Microsoft Access) (Objective #1). If necessary, data will be extracted from published graphs and figures using Data Thief® software (Johnson and Curtis, 2001; Tonitto et al., 2006). Additionally, the project director will not hesitate to contact authors of relevant studies upon the possibility that additional pertinent data may be available.

The “Measured Annual Nutrient loads from AGricultural Environments” (MANAGE) database aims to “compil[e] measured annual nitrogen and phosphorus load data representing field-scale transport from agricultural land uses in the USA into a readily accessible, easily queried format” (Harmel et al., 2008). This free and easily accessible compilation of water quality information was developed by the United States Department of Agriculture, Agricultural Research Service, Grassland, Soil, and Water Research Laboratory in Temple, Texas, and is publically available (http://www.ars.usda.gov/Research/docs.htm?docid=11079). MANAGE currently includes over 1800 watershed years from 300 nutrient load database records with database categories including study location, tillage type, conservation practice, soil type/group, fertilizer application, nutrient loss, and citations (Harmel et al., 2006). This well-established database is an ideal platform for this proposed work to integrate water quality and yield information under the context of 4R practices.

While MANAGE does include conservation practices (i.e., waterways, terraces, filter strips, riparian buffers, and contour farming), it was not originally designed to be a depository of nutrient stewardship studies. Additionally, the primary focus of MANAGE is runoff nutrient losses, although several MANAGE records do contain drainage water quality information. These existing drainage records will be revisited in this proposed work, and new studies will be added based on the literature review and criteria described below (“II. c. i. Review framework”). The drainage loss studies will be incorporated as a standalone table(s) in MANAGE called “drainage load” and/or “drainage conc”. Drainage studies that currently are MANAGE records will be linked across the database for traceability. Existing database categories in MANAGE’s “ag load” and/or “ag conc” tabs will serve as the template for the new proposed drainage tabs. Note, if the funders of this RFP wish data compiled during this work be included in a different database of their choosing (i.e., a “4R project database” according to the RFP), this will also be done.

Once compiled, the data from suitable studies will be analyzed using meta-analysis techniques in MetaWin software (Johnson and Curtis, 2001; Tonitto et al., 2006) (Objective #2). Resulting graphs and figures will be generated using SigmaPlot software. See section “II. c. ii. Meta-analysis of results” below for detailed rationale for and about these statistical methods.

i. Review framework

MANAGE is based upon a robust selection process that has already withstood peer-review (Harmel et al., 2006; Harmel et al., 2008). Studies suitable for MANAGE inclusion must be:
    · Peer-reviewed
    · From study areas of at least 0.009 ha (0.022 ac)
    · Not be a rainfall simulation study
    · Include data from at least one year

Additionally, for this work, studies will need to be relevant to the 4R practices, have been conducted in the Midwest, Southeast or Mid-Atlantic, and have a drainage component. Irrigation-drainage systems more common in the western United States and drained pastoral systems will not be included. Following Tonitto et al. (2006), data will be selected from studies where “(1) the land use had a cropping history typical of the production system under study, and (2) land management reflected the best (or typical) practice for a given climate.”

In keeping with MANAGE’s existing framework, data on dissolved, particulate and total N and P loads and/or concentrations will be sought. In terms of economics, yield impacts will be the primary metric, but studies reporting input and management costs, revenue, or profitability from artificially drained areas in the regions of interest will also be noted. Special effort will be given to evaluating the most applicable desired categories before beginning the review. As suggested in the RFP (“Projects including a task to add crop yield data to existing database …”), studies including drainage components currently reported in MANAGE will be revisited to attempt to incorporate yield data. However, this work does not endeavor to add yield information to all existing MANAGE database records. Special note will be made of any socio-economic factors mentioned in the studies under review (e.g., additional labor required, necessary off-farm/community infrastructure, consideration of affordable and accessible food).

Water quality and crop yield impacts will be compared across drainage types, crop types (e.g., corn, soybean, wheat), specific 4R practices, and regions. In this way, interactions between site conditions and cropping systems will be evaluated for the individual given 4R practices (RFP Basic Requirement #4). To support a manageable scope of work for this nine month proposed project period, the major 4R practices investigated for N and P will be limited to those listed in Table 1 with the regions defined as in Table 2. It is expected that of the 4Rs most applicable for N drainage water quality improvement, rate and timing will be most important, while for P, placement, timing and source will be primary (Table 1). The broad regional categories setting the spatial framework for sourcing of studies (Table 2) were slightly modified from Sugg (2007) estimates in Figure 1.

Table 1: Major 4R practices to be reviewed in this proposed work
· Rate: Comparison of multiple rates · Source: Inorganic versus manure
· Nitrification inhibitor · Placement: Use of banded inorganic P, incorporation
· Timing: split application, pre-plant, side-dress · Timing

Table 2: Regional categories investigated in this proposed work (modified from Sugg, 2007)
North Dakota
North Carolina
South Dakota2
South Carolina
1 Nebraska and New York from Sugg (2007) were excluded here
2 Additions to Sugg (2007)

It is expected relatively few studies will contain both economic (e.g., crop yield) and water quality data; thus, any applicable studies sufficing MANAGE’s bulleted criteria above will be included in the database even if not all database categories are reported (Objective #1). Note, studies must have both crop yield and water quality data to be included in the meta-analysis

Objective #2 of this proposed work is to perform a statistical meta-analysis of data assembled during the review to determine the response effect of 4R practices upon drainage water quality and crop yield. This meta-analysis will be used to ask the questions “How do the 4R practices affect N and P losses in artificial drainage water”, and (2) “How do the 4R practices effect crop yield and on-farm profitability in drained agronomic systems?” The treatment effect estimator here will be the ratio of the N/P load/concentration or yield of a treatment having undergone a 4R practice compared with that of a control treatment. It is crucial to define a consistent control across studies (Tonitto et al., 2006); the control here will be defined as a conventional agronomic system with a fertilized cash crop that is either surface or subsurface artificially drained. Only studies with both water quality data (N and/or P, loads and/or concentrations) and yield information for the treatment versus a control will be used for this meta-analysis; this means the selected meta-analysis studies will likely be fewer than the records entered into MANAGE.

True meta-analysis studies weight individual response ratios based upon the sample size and variance of each study. However, this sort of statistical information is often not reported for field-scale ecological or agricultural studies. In these cases, resampling procedures to develop unweighted meta-analysis statistics are the best approach, with bootstrapping a recommended resampling technique (Adams et al., 1997; Gurevitch and Hedges, 1999). Thus, a bootstrap procedure (5000 iterations) allowing development of 95% confidence intervals will be performed using MetaWin software for this unweighted meta-analysis. Following Johnson and Curtis (2001) and Tonitto et al. (2006), treatment means will be considered to be significantly different from one another if their 95% confidence intervals do not overlap, and will considered significantly different from zero if the 95% confidence interval does not overlap zero. Categorical variables (e.g., crop type, surface/subsurface drainage, region) will be used as subpopulations to investigate the impact of given 4R practices on water quality and yield. Publication-quality final graphs and figures will be generated for manuscripts and presentations in SigmaPlot software.