Search for: All records

With diminishing availability of high-quality phosphate rock and increasing supply uncertainties, improving phosphorus (P) recovery, recycling, and waste reduction has become critical for sustaining agricultural production. We developed an integrated P cycling and soil dynamics model to quantify 7 circular strategies for reducing mineral P demand in the United States, using data for 91 major crops and 20 livestock types across 3,142 counties from 1866 to 2050. We show that soil residual P reuse has the largest potential to reduce mineral P demand in the United States. By 2023, total soil P stocks had accumulated to 99 Tg, equivalent to approximately 68% of mineral P inputs over 1866–2023. For 2024–2050, projections under various socioeconomic scenarios indicate that soil residual P reuse alone could potentially supply approximately 2.4 to 5.1 times projected US mineral P demand, with substantial residual P stocks accumulated in both cropland and pastureland soils. Recycling from sewage sludge and livestock and crop by-products could collectively offset an additional approximately 0.5 to 1.0 times mineral P demand, while food waste reduction could reduce requirements by approximately 0.3 times. Spatial analyses further highlight a mismatch between circular P availability and cropland P demand, with high mineral P avoidance potential concentrated in the South and West, but relatively low ratios of circular P supply to projected mineral P demand across most counties in the Midwest. These findings provide spatially explicit and decision-relevant insights into how circular P strategies can enhance the stability and resilience of US food systems under future resource constraints. 

Phosphorus (P) is essential for plant growth, but excessive and continuous application of P fertilizers and animal manure has led to the accumulation of legacy phosphorus (legacy-P) in soils. While legacy-P presents a potential resource to support future agricultural demands, limited understanding of its chemical forms across different soil types hinders its sustainable management. This study aimed to characterize the chemical nature and storage potential of legacy-P in three contrasting soil types: acidic, organic, and calcareous. Key soil properties—including pH, organic matter, total P, Mehlich-3 P, and concentrations of aluminum (Al), calcium (Ca), iron (Fe), and magnesium (Mg)—were evaluated alongside P fractionation using a modified Hedley method. Furthermore, the soil P saturation ratio (PSR) was calculated to evaluate the relative saturation of soil sorption sites with P. Results showed considerable variability in Mehlich-3 P across soil types, ranging from 7–62% of total P in acidic soils, 1–8% in organic soils, and 3–47% in calcareous soils. Acidic soils were dominated by humic/fulvic-bound P (> 42%), organic soils by recalcitrant residual P (> 62%), and calcareous soils by Ca/Mg-bound P (> 69%), highlighting the influence of soil chemistry on P stability. Despite considerable variation among soil types in P fractionations, PSR results suggested that Ca/Mg-associated minerals play a greater role in retaining legacy P in organic and calcareous soils than Al- and Fe-associated minerals. In acidic soils, both mineral groups contributed similarly to P retention. 

Nutrient runoff from agricultural activities in the watershed of Western Lake Erie (WLE) is a dominant driver of harmful algal blooms (HABs). While phosphorus (P) is a key factor causing these blooms and has been the focus for researchers and policymakers, the influence of nitrogen (N) on bloom dynamics has been overlooked. Total Kjeldahl N (TKN; organic N and ammonium N) has not been the focus of eutrophication research but was recently linked to bloom development in WLE. Here, monotonic and oscillatory statistical trend analyses were performed to interpret long-term (1982 to 2022) patterns of TKN in the Maumee River and were compared to algal biomass data as chlorophyll a. A predictive regression model used principal component analysis to estimate a chlorophyll-based index of HABs in WLE, and a systematic iterative process identified that TKN influences bloom dynamics along with soluble reactive phosphorus (SRP), total suspended solids (TSS) and flow. Although TKN loads exhibited a long-term decline, this decrease did not correspond to reduced HAB severity, reflecting the strong influence of flow-driven hydrologic variability on nutrient delivery and bloom response. The modeling results demonstrate that TKN, together with SRP, TSS, and flow, significantly contributes to predicting bloom magnitude. These findings highlight the need for dual-nutrient (N and P) management strategies and additional analyses of nutrient–hydrology interactions to improve HAB mitigation in WLE. 

Successfully tackling many urgent challenges in socio-economically critical domains, such as public health and sustainability, requires a deeper understanding of causal relationships and interactions among a diverse spectrum of spatio-temporally distributed entities. In these applications, the ability to leverage spatio-temporal data to obtain causally based situational awareness and to develop informed forecasts to provide resilience at different scales is critical. While the promise of a causally grounded approach to these challenges is apparent, the core data technologies needed to achieve these are in the early stages and lack a framework to help realize their potential. In this article, we argue that there is an urgent need for a novel paradigm of spatio-causal research built on computational advances in spatio-temporal data and model integration, causal learning and discovery, large scale data- and model-driven simulations, emulations, and forecasting, as well as spatio-temporal data-driven and model-centric operational recommendations, and effective causally driven visualization and explanation. We thus provide a vision, and a road map, for spatio-causal situation awareness, forecasting, and planning.