The buffering of phosphorus (P) in the landscape delays management outcomes for water quality. If stored in labile form (readily exchangeable and bioavailable), P may readily pollute waters. We studied labile P and its intensity for >600 soils and sediments across seven study locations in the United States. Stocks of labile P were large enough to sustain high P losses for decades, indicating the transport‐limited regime typical of legacy P. Sediments were commonly more P‐sorptive than nearby soils. Soils in the top 5 cm had 1.3–3.0 times more labile P than soils at 5–15 cm. Stratification in soil test P and total P was, however, less consistent. As P exchange via sorption processes follows the difference in intensities between soil/sediment surface and solution, we built a model for the equilibrium phosphate concentration at net zero sorption (EPC₀) as a function of labile P (quantity) and buffer capacity. Despite widely varying properties across sites, the model generalized well for all soils and sediments: EPC₀ increased sharply with more labile P and to greater degree when buffer capacity was low or sorption sites were likely more saturated. This quantity–intensity–capacity relationship is central to the P transport models we rely on today. Our data inform the improvement of such P models, which will be necessary to predict the impacts of legacy P. Further, this work reaffirms the position of labile P as a key focus for environmental P management—a view Dr. Sharpley developed in the 1980s with fewer data and resources.

Mung beans (Vigna radiata (L.) Wilczek) are only inoculated in some production systems, but there is a current lack of knowledge on the best inoculants to use for effective nitrogen fixation (nodulation) and plant yields. The objectives of the present study were to determine if the dual inoculation of Arbuscular Mycorrhizal Fungi (F) and Bradyrhizobium (R) provides greater (a) mung bean yield and quality (b) nitrogen fixation for mung bean and residual soil nitrogen for the following crop, and (c) determine if these effects are consistent across various environments. Field trials were conducted in Blacksburg, VA (sandy clay loam), and Eastern Shore, VA (sandy loam), over the summers of 2020 and 2021. There were 5 treatments replicated 5 times for each variety at each site; R, F, R + F, high nitrogen (N) (100 kg ha⁻¹), and a control, for a total of 25 plots per site. Mung beans grown in Blacksburg in 2020 and 2021 averaged 53.8% more seeds per pod than mung beans grown at the Eastern Shore. Overall yield components (seeds per pod, pods per plant) are heavily influenced by soil type. Dual inoculation significantly increased grain yield (+33%) compared to a synthetic N fertilizer application, but did not significantly increase grain yield compared to the control (+22%). Dual inoculation may increase the grain yields of mung beans compared to synthetic fertilizer regime, but does not show evidence of improving N fixation.

As United States farmers adapt soybean (Glycine max) production methods from oilseed to vegetable (edamame), key management practices will need to be considered. The key objective of this study was to determine the optimal nitrogen (N) rate and N application timing for edamame in the mid-Atlantic coastal plain system. The study was conducted for three years in Painter, VA, USA on sandy loam soils. A factorial arrangement of four N rates was applied with two application timing strategies: at-planting, and split application. Leaf tissue samples were collected and analyzed at R1. At harvest, the Normalized Difference Vegetation Index (NDVI) was measured, whole pods were mechanically collected, and yield was recorded. Additionally, pod and bean physical and chemical quality were assessed. Nitrogen fertilization significantly increased pod yield in two out of three years. R1 leaf N and sulfur (S) concentrations correlated to the yield, and R1 leaf and R6 whole-plant N concentrations correlated to the total N uptake. None of the tested parameters indicated that N fertilizer decreased yield or quality. In conclusion, we found that N fertilizer applied at planting may aid edamame yield and profit for sandy loam soils in the mid-Atlantic, USA.

The pursuit of sustainable phosphorus (P) management represents a long‐standing challenge in agricultural arenas, with far‐reaching implications for the environment and societal development. Few scholars are as synonymous with P science as Andrew Sharpley. Renowned over his 44‐year professional career for providing foundational insights into the fate and management of agricultural P, Sharpley also became the central figure in organizing responses to concerns over the contribution of non‐point source P pollution to eutrophication. As a global authority, Sharpley led teams that crafted scientific consensus for use by managers and policymakers in the face of complexity and uncertainty. His leadership offers lessons to those continuing in his footsteps and a model for all who desire to achieve scientific impact. This special collection of papers celebrates the perspectives, contributions, and legacy of Andrew Sharpley.

Methods for soil test phosphorus (STP) differ globally and even within countries. While soil P tests often correlate, the relationship is often specific to a region or study, making any conversion equation difficult to transfer between contexts. Agronomic recommendations, P transport models, syntheses, and other works lack a strong basis for converting between STP. We fulfil this need for converting between two common STP measurements – Olsen P and Mehlich-3 P – through models which account explicitly for soil properties. Hypothesizing that soil properties at the sample level govern how STP values relate, we built models using a combined dataset of ca. 900 soils across the conterminous US and Canada, spanning 10 soil orders (USDA), 3 to 89 % clay, and pH 4 to 9. Model complexity ranged from conventional ‘region-level’ regressions (no soil data) to models adapting to many facets of soil P chemistry, presenting users several viable options suitable for their data context. Depending on data availability, the user could convert between Olsen P and Mehlich-3 P with half the error or less of conventional ‘region-level’ regressions. This reduction in conversion error impacts agronomic recommendations, environmental risk assessments (e.g., P index), and calibration of P transport models (e.g., SWAT+). While it remains best to simply measure the STP of interest, the conversion models here should prove useful in many contexts where that is not feasible. We provide the models in ready-to-use formats, depending on the covariates available to the user and whether the user wants to apply the equations in a spreadsheet or within model code.