Nitrogen Losses: Meta-analyses on Fertilizer Management- Results and Recommendations.

Crops: Alfalfa Almonds Apples Barley Beans (dry) Canola Citrus Clover Corn for grain Corn for silage Cotton Cucumbers Green beans Hay Hazelnuts Hops Mustard Peanuts Pecans Potato Rice Rye Ryegrass Sorghum Soybeans Spinach Strawberries Sugar beets Sugarcane Sweet corn Tart cherry Tobacco Tomato Winter wheat Wheat
4R Practices: Metadata Project

Nitrogen Losses: Meta-analyses on Fertilizer Management- Results and Recommendations.

Lead Researcher:

Dr. Alison Eagle


Environmental Defense Fund

Start Date: 2014

End Date: 2015

Collaborating scientists and universities

  • Dr. Laura Christianson, University of Illinois
  • Dr. Rachel Cook, Southern Illinois University
  • Dr. R. Daren Harmel, USDA-ARS
  • Dr. Fernando Miguez, Iowa State University
  • Dr. Song Qian, University of Toledo
  • Dr. Dorivar Ruiz Diaz, Kansas State University
  • Dr. Cristie Preston, Nutrien, Ltd.

Project Summary

Growing population and consumer demand require that agriculture continue to increase productivity while managing environmental impacts. Efficient farm production and environmental management needs a well-informed and scientifically-based strategy. To do this, the ever- increasing volume of data from agricultural field research must be summarized, assessed, and interpreted. Meta-analysis of experimental data can be used to find overall or widespread benefits of management practices that may be difficult to fully understand with individual research projects, most of which are limited to particular climatic and soil conditions. Policy makers and producers would like to see broader application of practices that can have water or air quality benefits while maintaining or enhancing production. However, accurate scientific information is needed to know how to do this best, where it will work, and how it can be cost- effective.

This project will summarize the results of all five 4R Research Fund supported meta-analysis projects, and detail the databases generated, as well as the potential for linkages between them or with other databases. This summary will allow for a discussion on the implications of 4R nutrient management that go beyond that possible in single research papers or even in the individual meta-analysis projects. 

Project Goals:

  • Summarize the 4R Research Fund-supported meta- analyses, noting how the combined data and results can advise best practice 
  • Summarize the critical data gaps found by the 4R Research Fund-supported meta-analysis teams and provide recommendations for field researchers to aid future data synthesis efforts in making the most effective use of their data following initial publication. 

Project Results:

  • Alleviate challenges in meta-analysis by implementing the following in individual research projects:
  • use common meta-data protocols for consistent units and terminology;
  • clearly define treatments and controls;
  • provide complete, tabular, full-factorial response data for each year and location;
  • collect and report a minimum set of auxiliary data;
  • establish requirements for data curation and repositories in funding and publication cycles.

Annual Reports