- Agronomic: wheat
- Crop Production: fertilizers, nutrient cycling, nutrient management, water management
- Education and Training: on-farm/ranch research, participatory research
- Farm Business Management: budgets/cost and returns
- Soil Management: nutrient mineralization, organic matter, soil analysis, soil chemistry, soil microbiology, soil physics, soil quality/health
- Sustainable Communities: infrastructure analysis
Nitrogen (N) fertilizer is generally the largest input cost for farmers in the Northern Great Plains. Despite this fact, scientists, producers, and their advisors have failed to develop a system for determining areas of fields that are more or less susceptible to N loss. Moreover, warming temperatures are projected to increase the fraction of precipitation delivered as rain versus snow, which in turn could affect spatiotemporal variability in N loss processes such as leaching. Leaching losses alone can account for up to one-third of typical fertilizer rates in shallow and variable soils. Subfield-scale changes in surface (0-20 cm) soil water extractable N (WEN) during the winter months (September to April), henceforth overwinter N changes (ONCs), were spatially characterized based on high-resolution (5 cm) imagery of wheat in Central Montana. By restricting the period of inquiry to the months between September and April, contributions of N loss processes such as denitrification and crop uptake were minimized or eliminated. No fertilizers were applied during this time. Restricting the study area to a 0.4-ha subfield encompassing a strong gradient in thickness of fine-textured soil (zf; a major control on N leaching per Sigler et al. ), allowed for spatial estimates of overwinter leaching, given that mineralization (estimated by enzyme assays and in situ microbial activity) did not vary with zf in the current study. It is therefore suggested that differences in N leaching were largely responsible for the ONCs observed, while mineralization and denitrification were relatively unchanged across the study area. Spatially interpolated ONCs ranged from -9.4 kg ha-1 to +17.8 kg ha-1 and averaged 1.1 ± 3.1 kg ha-1 (± SD) following wheat during the 2019-2020 winter. Standard deviations of spatially interpolated 2019-2020 ONCs were not as large as observed single-year ONCs (6.9 and 8.1 kg ha-1), while observed single-year ONCs were greater than the year-to-year standard deviation (4.5 kg ha-1), suggesting ONC spatial variability is at least as large as ONC inter-annual variability in shallow and variable soils. ONC variability was driven by large fall WEN standard deviations (4.4 and 6.7 kg ha-1), with comparatively low standard deviations observed in spring WEN (1.8 and 3.7 kg ha-1). A negative relationship (p = 0.0278) between fall WEN and zf analyzed across years suggests that mitigating N loss overwinter is matter of optimizing crop uptake during the growing season. It was estimated that 14.5 ± 3.4 kg N ha-1 was left ‘stranded’ in the top 20 cm of the profile in fall 2019. Results indicate strong potential for spatially and temporally explicit management strategies (e.g., variable rate seeding and/or fertilizer application, split application) to optimize crop uptake, minimize residual soil N, and mitigate N loss overwinter. Climate warming trends identified in the current study are likely to disproportionately inflate year-to-year variability in ONC, given that warming should occur uniformly across small areas (0.4-ha) and surface soil temperatures do not vary with zf (p = 0.8232). It is also possible that warming trends will shorten the leaching season such that temporally explicit management strategies (e.g., split fertilizer application) will hold less potential for N loss mitigation in the future. In a warmer climate with more precipitation being delivered as rain versus snow, it may become more important for farmers to avoid high soil N concentrations when crop uptake is minimal or absent. However, this window is likely to shorten as air temperatures increase, freezing temperatures in mid-to-late spring become less frequent, and growing seasons lengthen. More work is needed to explore these complex feedbacks under field conditions.
1. Quantify subfield-scale variability in ONCs toward improved precision ag methods such as
variable rate fertilizer application.
2. Develop a model to predict ONCs and to notify farmers when large ONCs are likely to have
occurred in order to minimize economic and environmental injuries resulting from uninformed
fertilizer management decisions.
3. Demonstrate to farmers the economic and environmental benefits of soil testing and the
implications of changing precipitation and temperature patterns for N management practices.