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Abstract National nutrient inventories provide surplus phosphorus (P) estimates derived from county‐scale mass balance calculations using P inputs from manure and fertilizer sales and P outputs from crop yield data. Although bioavailable P and surplus P are often correlated at the field scale, few studies have investigated the relationship between measured soil P concentrations of large‐scale soil testing programs and inventory‐based surplus P estimates. In this study, we assessed the relationship between national surplus P data from the NuGIS dataset and laboratory‐measured soil test phosphorus (STP) at the county scale for Arkansas, North Carolina, and Oklahoma. For optimal periods of surplus P aggregation, surplus P was positively correlated with STP based on both Pearson (Arkansas:r = 0.65, North Carolina:r = 0.45, Oklahoma:r = 0.52) and Spearman correlation coefficients (Arkansas:ρ = 0.57, North Carolina:ρ = 0.28, and Oklahoma:ρ = 0.66). Based on Pearson correlations, the optimal surplus P aggregation periods were 10, 30, and 4 years for AR, NC, and OK, respectively. On average, STP was more strongly correlated with surplus P than with individual P inventory components (fertilizer, manure, and crop removal), except in North Carolina. In Arkansas and North Carolina, manure P was positively correlated with STP, and fertilizer P was negatively correlated with STP. Altogether, results suggest that surplus P moderately correlates with STP concentrations, but aggregation period and location‐specific factors influence the strength of the relationship. 

Livestock are a critical part of our food systems, yet their abundance globally has been cited as a driver of many environmental and human health concerns. Issues such as soil, water, and air pollution, greenhouse gas emissions, aquifer depletion, antimicrobial resistance genes, and zoonotic disease outbreaks have all been linked to livestock operations. While many studies have examined these issues at depth at local scales, it has been difficult to complete studies at regional or national scales due to the dearth of livestock data, hindering pollution mitigation or response time for tracing and monitoring disease outbreaks. In the U.S. the National Agricultural Statistics Service completes a Census once every 5 years that includes livestock, but data are only available at the county level leaving little inference that can be made at such a coarse spatiotemporal scale. While other data exist through some regulated permitting programs, there are significant data gaps in where livestock are raised, how many livestock are on site at a given time, and how these livestock and, importantly, their waste emissions, are managed. In this perspective, we highlight the need for better livestock data, then discuss the accessibility and key limitations of currently available data. We then feature some recent work to improve livestock data availability through remote-sensing and machine learning, ending with our takeaways to address these data needs for the future of environmental and public health management. 

Today’s challenges with sustainability are driven by complexity, lack necessary information, resist straightforward solutions, span multiple scales, and encompass diverse or sometimes conflicting perspectives. To tackle these issues effectively, research organizations need tools that support and accelerate the integration of disciplinary knowledge across both natural and social sciences so that they can explore and execute workable solutions. Boundary objects are tools that can bring diverse perspectives together through a shared point of focus that is meaningful across different groups and perspectives, enhancing communication between them. Here, we introduce a framework to develop Triple Bottom Line Scenario Sites (TBL Sites) as “convergence” boundary objects and intervention testbeds to support a holistic approach to sustainability research within multidisciplinary and multi-institutional organizations. We describe four key criteria used to identify a potential TBL Site: (1) proximity to researchers, (2) a bounded geographic location encompassing a particular ecosystem, (3) an integrated stakeholder network, and (4) access to existing resources. We explain how TBL Sites may be used to assess research impacts on environmental, economic, and social sustainability goals. Finally, we provide examples of aquatic, agricultural, and urban TBL Sites used by the Science and Technologies for Phosphorus Sustainability (STEPS) Center, demonstrating how these boundary objects facilitate convergence across a large multidisciplinary research team to tackle sustainable phosphorus management.