4.4 Article

A Global Perspective on Phosphorus Management Decision Support in Agriculture: Lessons Learned and Future Directions

Journal

JOURNAL OF ENVIRONMENTAL QUALITY
Volume 48, Issue 5, Pages 1218-1233

Publisher

AMER SOC AGRONOMY
DOI: 10.2134/jeq2019.03.0107

Keywords

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Funding

  1. Agriculture and Food Research Initiative Competitive Grant from the USDA National Institute of Food and Agriculture [2012-67019-1929]
  2. USDA National Institute of Food and Agriculture [PEN04573, 1004449]
  3. Northern Ireland Department of Agriculture, Environment and Rural Affair, Evidence and Innovation Research Program [17/04/08]
  4. Swedish Farmers' Foundation for Agricultural Research [O-15-23-573]
  5. BONUS GO4BALTIC project - EU
  6. Academy of Finland [291705]
  7. BBSRC [BB/R005842/1] Funding Source: UKRI
  8. Academy of Finland (AKA) [291705, 291705] Funding Source: Academy of Finland (AKA)

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The evolution of phosphorus (P) management decision support tools (DSTs) and systems (DSS), in support of food and environmental security has been most strongly affected in developed regions by national strategies (i) to optimize levels of plant available P in agricultural soils, and (ii) to mitigate P runoff to water bodies. In the United States, Western Europe, and New Zealand, combinations of regulatory and voluntary strategies, sometimes backed by economic incentives, have often been driven by reactive legislation to protect water bodies. Farmer-specific DSSs, either based on modeling of P transfer source and transport mechanisms, or when coupled with farm-specific information or local knowledge, have typically guided best practices, education, and implementation, yet applying DSSs in data poor catchments and/or where user adoption is poor hampers the effectiveness of these systems. Recent developments focused on integrated digital mapping of hydrologically sensitive areas and critical source areas, sometimes using real-time data and weather forecasting, have rapidly advanced runoff modeling and education. Advances in technology related to monitoring, imaging, sensors, remote sensing, and analytical instrumentation will facilitate the development of DSSs that can predict heterogeneity over wider geographical areas. However, significant challenges remain in developing DSSs that incorporate big data in a format that is acceptable to users, and that adequately accounts for catchment variability, farming systems, and farmer behavior. Future efforts will undoubtedly focus on improving efficiency and conserving phosphate rock reserves in the face of future scarcity or prohibitive cost. Most importantly, the principles reviewed here are critical for sustainable agriculture.

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