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This dataset presents spatiotemporal dynamics of phosphorus (P) fertilizer management (application rate, timing, and method) at a 4km × 4 km resolution in agricultural land of the contiguous U.S. from 1850 to 2022. By harmonizing multiple data sources, we reconstructed the county-level crop-specific P fertilizer use history. We then spatialized and resampled P fertilizer use data to 4 km × 4 km gridded maps based on historical U.S. cropland distribution and crop type database developed by Ye et al. (2024). This dataset contains (1) P fertilizer total consumption and mean application rate at the national level (Tabular); (2) P fertilizer consumption of 11 crops at the state level (Tabular); (3) P fertilizer consumption of permanent pasture (Tabular); (4) P fertilizer consumption of non-farm at the state level (Tabular); (5) P fertilizer application rate of 11 crop types at the state level (Tabular); (6) P fertilizer application rate of 11 crop types at the county level (Tabular); (7) P fertilizer application timing ratio at the state level (Tabular); (8) P fertilizer application method ratio at the state level (Tabular); (9) Gridded maps of P fertilizer application rate based on state-level data; (10) and (11) Gridded maps of P fertilizer application rate based on county-level data; (12)-(20) Gridded maps of P fertilizer application rate for each crop. A detailed description of the data development processes, key findings, and uncertainties can be found in Cao, P., Yi, B., Bilotto, F., Gonzalez Fischer, C., Herrero, M., Lu, C.: Crop-specific Management History of Phosphorus fertilizer input (CMH-P) in the croplands of United States: Reconciliation of top-down and bottom-up data sources, is under review for the journal Earth System Science Data (ESSD). https://essd.copernicus.org/preprints/essd-2024-67/#discussion.  This work is supported by the Iowa Nutrient Research Center, the ISU College of Liberal Arts and Sciences Dean's Faculty Fellowship, and NSF CAREER grant (1945036). 

Abstract. Understanding and assessing the spatiotemporal patterns in crop-specific phosphorus (P) fertilizer management are crucial for enhancing crop yield and mitigating environmental problems. The existing P fertilizer dataset, derived from sales data, depicts an average application rate over total cropland at the county level but overlooks cross-crop variations. Conversely, the survey-based dataset offers crop-specific application details at the state level yet lacks inter-state variability. By reconciling these two datasets, we developed long-term gridded maps to characterize crop-specific P fertilizer application rates, timing, and methods across the contiguous US at a resolution of 4 km × 4 km from 1850 to 2022. We found that P fertilizer application rate over fertilized areas in the US increased from 0.9 g P m−2 yr−1 in 1940 to 1.9 g P m−2 yr−1 in 2022, with substantial variations among crops. However, approximately 40 % of cropland nationwide has remained unfertilized in the recent decade. The hotspots for P fertilizer use have shifted from the southeastern and eastern US to the Midwest and the Great Plains over the past century, reflecting changes in cropland area, crop choices, and P fertilizer use across different crops. Pre-planting (fall and spring) and broadcast application are prevalent among corn, soybean, and cotton in the Midwest and the Southeast, indicating a high P loss risk in these regions. In contrast, wheat and barley in the Great Plains receive the most intensive P fertilization at planting and via non-broadcast application. The P fertilizer management dataset developed in this study can advance our comprehension of agricultural P budgets and facilitate the refinement of best P fertilizer management practices to optimize crop yield and to reduce P loss. Datasets are available at https://doi.org/10.5281/zenodo.10700821 (Cao et al., 2024). 

Food production data — such as crop, livestock, aquaculture and fisheries statistics — are critical to achieving multiple sustainable development goals. However, the lack of reliable, regularly collected, accessible, usable and spatially disaggregated statistics limits an accurate picture of the state of food production in many countries and prevents the implementation of effective food system interventions. In this Review, we take stock of national and international food production data to understand its availability and limitations. Across databases, there is substantial global variation in data timeliness, granularity (both spatially and by food category) and transparency. Data scarcity challenges are most pronounced for livestock and aquatic food production. These challenges are largely concentrated in Central America, the Middle East and Africa owing to a combination of inconsistent census implementation and a global reliance on self-reporting. Because data scarcity is the result of technical, institutional and political obstacles, solutions must include technological and policy innovations. Fusing traditional and emerging data-gathering techniques with coordinated governance and dedicated long-term financing will be key to overcoming current obstacles to sustained, up-to-date and accurate food production data collection, foundational in promoting and monitoring progress towards healthier and more sustainable food systems worldwide. 

Agriculture’s global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture’s environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change–reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products.