Meta-analysis constrained by data: Recommendations to improve relevance of nutrient management research

Five research teams identified parallel obstacles when concurrently attempting to conduct meta-analyses on the air and water quality impacts of on-farm 4R nutrient management practices. Across projects, system complexity and the lack of relevant data from cultivated and grassland agriculture field trials impeded the application of standard meta-analytical procedures. Because challenges were comparable across projects, the 4R Research Fund technical leadership tasked the researchers with recommending improvements in field research design, data collection, and reporting to enhance future agri-environmental data syntheses and meta-analyses. Here we outline statistical and analytical issues unique to meta-analysis and data synthesis in agriculture, discuss critical data and reporting gaps in the existing literature, and provide specific recommendations for researchers, funders, and journals. Key obstacles developed when field studies did not include complete descriptive or response data (per treatment and experiment year), measurement uncertainty, estimation error in treatment effects, or simultaneously measured nutrient losses and crop yield. Others did not report crop nutrient uptake or their apparent recovery efficiencies. To alleviate such challenges for subsequent research, we make the following recommendations: (i) use common meta-data protocols for consistent units and terminology; (ii) clearly define treatments and controls; (iii) provide complete, tabular, full-factorial response data for each year and location; (iv) collect and report a minimum set of auxiliary data; and (v) establish requirements for data curation and repositories in funding and publication cycles. Implementing these in future nutrient management research will facilitate more robust meta-analyses and other data synthesis efforts.