ArticleScientific data2026
gTREND-Nitrogen - Long-term nitrogen mass balance data for the contiguous United States (1930-2017).
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A Community Dataset for Large-Scale River Nitrogen Modeling in the United States.Scientific data · 2026Article
- gTREND-Nitrogen - Long-term nitrogen mass balance data for the contiguous United States (1930-2017).Scientific data · 2026Article
- Legacy P and water quality perspective.Journal of environmental qualityArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Excess nitrogen (N) within the landscape can lead to environmental issues such as water pollution and downstream eutrophication. Quantification of landscape N fluxes can help identify areas of excess N and can improve our understanding of the sources, sinks, and transport of N within ecosystems. The gTREND-Nitrogen dataset provides a comprehensive, long-term (1930-2017) N mass balance for the contiguous United States at a spatial resolution of 250 meters. This dataset integrates county-scale estimates of N fluxes with gridded land use and population data to estimate grid-scale surface fluxes of N, including fertilizer, atmospheric deposition, manure inputs, biological N fixation, crop N uptake, and population-based human waste. The downscaled gTREND-Nitrogen data will allow for fine-scale insights into both historical and current N dynamics, addressing the limitations of previous datasets developed at coarser spatial scales. The data is openly available and will help to inform the development of effective policy and management strategies to mitigate the negative impacts of excess N and to promote sustainable nutrient management practices.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.